From ebrahimi_nia at yahoo.com  Sat Jun  1 06:52:43 2013
From: ebrahimi_nia at yahoo.com (Fatemeh Ebrahimi nia)
Date: Fri, 31 May 2013 21:52:43 -0700 (PDT)
Subject: [FieldTrip] loreta2fieldtrip function error
In-Reply-To: <1370015815.5183.YahooMailNeo@web122402.mail.ne1.yahoo.com>
References: <1369934092.15336.YahooMailNeo@web122405.mail.ne1.yahoo.com>
	<51A78CC1.6030906@berkeley.edu>
	<1370015815.5183.YahooMailNeo@web122402.mail.ne1.yahoo.com>
Message-ID: <1370062363.83888.YahooMailNeo@web122406.mail.ne1.yahoo.com>



Hi Dear all,
Can any one give me information about the output structure of "loreta2fieldtrip" function (What do the matrixes refer to?) or advise a reference to study about that please? 

Best,
Fatemeh



________________________________
 From: Ingrid Nieuwenhuis <inieuwenhuis at berkeley.edu>
To: fieldtrip at science.ru.nl 
Sent: Thursday, May 30, 2013 10:30 AM
Subject: Re: [FieldTrip] loreta2fieldtrip function error
 


Hi Fatemeh,

I had the same error recently when I did the same. I filed the bug,
    see http://bugzilla.fcdonders.nl/show_bug.cgi?id=2144

I did create a work around. In the LORETA program, you can export
    the source data as a text file. You can read that text file in with
    loreta2fieldtrip.m. It's a bit of a patch, but it worked for me. 

Hope this helps,
Ingrid


On 5/30/2013 10:14 AM, Fatemeh Ebrahimi nia wrote:

Hi dear all,
>
>
>I am analyzing EEG data. I have computed sLORETA (.slor) from ERP data. Now I want to read and convert LORETA source reconstruction into a
>MATLAB data structure using "loreta2fieldtrip" function, But I have gotten the bellow error.
>
>
>**** Error using fread
>
>Invalid precision.
>Error in loreta2fieldtrip (line 85)
>activity = fread(fid, [voxnumber Ntime], 'float = >single'); ***
>
>
>Can someone give me a help?
>
>
>
>Best regards,
>Fatemeh
>
>
>
>
>_______________________________________________
fieldtrip mailing list fieldtrip at donders.ru.nl http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

-- 
Ingrid Nieuwenhuis PhD
Postdoctoral Fellow
Sleep and Neuroimaging Laboratory
Department of Psychology
University of California, Berkeley
California 94720-1650
Tolman Hall, room 5305 
_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl
http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl
http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
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From politzerahless at gmail.com  Sat Jun  1 20:44:04 2013
From: politzerahless at gmail.com (Stephen Politzer-Ahles)
Date: Sat, 1 Jun 2013 13:44:04 -0500
Subject: [FieldTrip] Question about minimum norm estimate pipeline
Message-ID: <CAJT2k_-Qba_X4uqQeR54LFApDSe31xkWCkCAwO-DnR5=zXxWpQ@mail.gmail.com>

Hi Arjen,

Thanks for your message. I did align the mri to Talairach; as you can see
from http://i.imgur.com/26nyHYZ.png, the volume conduction model and
sourcespace are both expressed in the same coordinate system (i.e.,
everything's pointing in the same direction) but they're just not sitting
on top of one another. If anyone has any ideas on where that problem was
introduced (or how to re-align them now), I would greatly appreciate it.
Below I have some more details about how I processed that data, if it helps.

I'm trying to go through the data one step at a time and track where the
problem might have happened. When I compare the sourcespace before having
applied any transformation (i.e., the headshape from
<subject>-oct-6-src.fif) to the original mri (orig-nomask.mgz), they look
ok (I don't know how to plot them together, but see
http://i.imgur.com/LGW7YnJ.png and http://i.imgur.com/JUoTxc9.png -- things
at least look like they're on more or less the same plane). Then I
re-register the mri to CTF (
http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate#source_modelco-registration_of_the_source_space_to_the_sensor-based_head_coordinate_system);
after that, in mri_nom_ctf, the axes are all going in the right direction
but the whole head is tilted forward and the origin of the axes is no
longer at the anterior commisure (see http://i.imgur.com/CTZNOTk.png for
the realigned MRI).  Applying the transformation matrix T to the
sourcespace also seems to tilt it like that (http://i.imgur.com/bcNIpf3.png),
although as can be seen from the first image in this message it doesn't
quite line up with the volume conduction model in the end. As for the
volume conduction model, here is what it looks like at first (
http://i.imgur.com/ZX3m38b.png) and here is what it looks like after
applying the transformation matrix (http://i.imgur.com/vXa3Cnc.png).
Obviously the transformation matrix is doing something, but it's not
getting the sourcespace and volume conduction model lined up; since it's
the same transformation matrix, all I can guess is that there was some
pre-existing difference between the source mesh (the .fif file) and the
anatomical mri (orig-nomask.mgz), but I'm not sure when that came in.

Another minor issue: when I first compared the volume conduction model and
the sourcespace, they were expressed in different units even though I
followed the code in the tutorial. See http://i.imgur.com/orwgcTJ.png: the
sourcespace looks 10x smaller than the volume conduction model, which I
assume is because it is expressed in cm whereas the volume conduction model
is expressed in mm. To get the figure linked at the very beginning of this
message, I had to convert the units of the volume conduction model to cm,
even though that's not in the tutorial.

I notice that the tutorial on the wiki hasn't been edited since October
2012 (other than a few edits I made this month which were just correcting
typos in the prose). Is it possible that what's on the wiki is out of date?
(Also cc'ing Lilla on this.)

Thanks,
Steve



> Message: 1
> Date: Fri, 31 May 2013 08:11:23 +0200 (CEST)
> From: "Stolk, A." <a.stolk at fcdonders.ru.nl>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] Question about minimum norm estimate pipeline
> Message-ID:
>         <
1914237354.1292588.1369980683984.JavaMail.root at sculptor.zimbra.ru.nl>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Steve, A quick guess; did you correctly align your resliced mri to
Talairach space by indicating the commissures (
http://imaging.mrc-cbu.cam.ac.uk/imaging/FindingCommissures ) and, if I'm
correct, a point in the same place, e.g. between the hemispheres? This
should update the transformation matrix. Best regards, Arjen -----
Oorspronkelijk bericht -----
> > Van: "Stephen Politzer-Ahles" <politzerahless at gmail.com>
> > Aan: fieldtrip at science.ru.nl
> > Verzonden: Vrijdag 31 mei 2013 05:53:45
> > Onderwerp: [FieldTrip] Question about minimum norm estimate pipeline
> > Hello all,
> > I have not yet gotten a response to my question below, but in the
> > meantime I have another question about the minimum norm estimate
> > workflow--specifically, about the coordinate system for the
> > skull-stripped anatomy in the step described at
> >
http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate#preprocessing_of_the_anatomical_mrisave_to_disk
> > . I'm confused by the following bit of code:
> > % ensure that the skull-stripped anatomy is expressed in the same
> > coordinate system as the anatomy
> > seg.transform = mri_tal.transform;
> > In my data, mri_tal.coordsys is 'spm' (I presume this is the result of
> > re-aligning to Talairach in the previous step?) whereas seg.coordsys
> > is 'ctf' (as a result of re-aligning to CTF several steps earlier).
> > (But mri_tal also has a field mri_tal.transformorig, which seg does
> > not have.) So should I really be using the same transform for both, as
> > shown in the tutorial?
> > Apologies if this question is pretty basic; I'm just trying to
> > pinpoint where the mis-alignment described in my message below
> > occurred, so I want to make sure I understand each step of the
> > workflow correctly
> > Best,
> > Steve
> > > Message: 1
> > > Date: Sat, 25 May 2013 08:11:18 -0500
> > > From: Stephen Politzer-Ahles < politzerahless at gmail.com >
> > > To: fieldtrip at donders.ru.nl
> > > Subject: [FieldTrip] Sourcespace and volume conductor misaligned
> > > Message-ID:
> > > <CAJT2k_9-hd_sM=hp4P-CUu+=aduSOMyZV7XPG0= fFk0ouR0wzA at mail.gmail.com
> > > >
> > > Content-Type: text/plain; charset="utf-8"
> > >
> > > Hello all,
> > >
> > > I am going through the workflow at
> > > http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate . After
> > > making
> > > the volume conduction model using ft_prepare_headmodel(), I noticed
> > > that
> > > although the volume conduction model and sourcespace have the same
> > > orientation and overall size/shape (after I converted the volume
> > > conduction
> > > model to cm, which wasn't in the tutorial but my original model came
> > > out in
> > > mm), they don't quite line up, as you can see in this figure:
> > >
> > > http://i.imgur.com/mGEtLOa.png
> > >
> > > I did interactively re-align the data to CTF (twice--in step 2 of
> > > "Preprocessing of the anatomical MRI" and in step 4 of "Source
> > > model")
> > > using fiducials, and to Talairach (step 5 of "Preprocessing of the
> > > anatomical data"), so I'm not sure how it ended up this way. The
> > > code I've
> > > used at each step is basically the same as that in the tutorial.
> > >
> > > Is there any way to line up my volume conduction model and
> > > sourcespace now,
> > > without going back and re-running most of the workflow?
> > >
> > > Best,
> > > Steve
> > >
> > > --
> > > Stephen Politzer-Ahles
> > > University of Kansas
> > > Linguistics Department
> > > http://people.ku.edu/~sjpa/
> > On Sat, May 25, 2013 at 1:56 PM, < fieldtrip-request at science.ru.nl >
> > wrote:
> > >
> > > Send fieldtrip mailing list submissions to
> > > fieldtrip at science.ru.nl
> > >
> > > To subscribe or unsubscribe via the World Wide Web, visit
> > > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > > or, via email, send a message with subject or body 'help' to
> > > fieldtrip-request at science.ru.nl
> > >
> > > You can reach the person managing the list at
> > > fieldtrip-owner at science.ru.nl
> > >
> > > When replying, please edit your Subject line so it is more specific
> > > than "Re: Contents of fieldtrip digest..."
> > >
> > >
> > > Today's Topics:
> > >
> > > 1. Sourcespace and volume conductor misaligned
> > > (Stephen Politzer-Ahles)
> > > 2. Re: fieldtrip Digest, Vol 30, Issue 31 (Johanna Zumer)
> > >
> > >
> > > ----------------------------------------------------------------------
> > >
> > > Message: 1
> > > Date: Sat, 25 May 2013 08:11:18 -0500
> > > From: Stephen Politzer-Ahles < politzerahless at gmail.com >
> > > To: fieldtrip at donders.ru.nl
> > > Subject: [FieldTrip] Sourcespace and volume conductor misaligned
> > > Message-ID:
> > > <CAJT2k_9-hd_sM=hp4P-CUu+=aduSOMyZV7XPG0= fFk0ouR0wzA at mail.gmail.com
> > > >
> > > Content-Type: text/plain; charset="utf-8"
> > >
> > > Hello all,
> > >
> > > I am going through the workflow at
> > > http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate . After
> > > making
> > > the volume conduction model using ft_prepare_headmodel(), I noticed
> > > that
> > > although the volume conduction model and sourcespace have the same
> > > orientation and overall size/shape (after I converted the volume
> > > conduction
> > > model to cm, which wasn't in the tutorial but my original model came
> > > out in
> > > mm), they don't quite line up, as you can see in this figure:
> > >
> > > http://i.imgur.com/mGEtLOa.png
> > >
> > > I did interactively re-align the data to CTF (twice--in step 2 of
> > > "Preprocessing of the anatomical MRI" and in step 4 of "Source
> > > model")
> > > using fiducials, and to Talairach (step 5 of "Preprocessing of the
> > > anatomical data"), so I'm not sure how it ended up this way. The
> > > code I've
> > > used at each step is basically the same as that in the tutorial.
> > >
> > > Is there any way to line up my volume conduction model and
> > > sourcespace now,
> > > without going back and re-running most of the workflow?
> > >
> > > Best,
> > > Steve
> > >
> > > --
> > > Stephen Politzer-Ahles
> > > University of Kansas
> > > Linguistics Department
> > > http://people.ku.edu/~sjpa/
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From Lilla.Magyari at mpi.nl  Sat Jun  1 23:22:34 2013
From: Lilla.Magyari at mpi.nl (Lilla.Magyari at mpi.nl)
Date: Sat, 1 Jun 2013 23:22:34 +0200 (CEST)
Subject: [FieldTrip] Question about minimum norm estimate pipeline
In-Reply-To: <CAJT2k_-Qba_X4uqQeR54LFApDSe31xkWCkCAwO-DnR5=zXxWpQ@mail.gmail.com>
References: <CAJT2k_-Qba_X4uqQeR54LFApDSe31xkWCkCAwO-DnR5=zXxWpQ@mail.gmail.com>
Message-ID: <2765.87.78.47.204.1370121754.squirrel@87.78.47.204>

hi Steve,

yes, it is possible that the tutorial is slightly out of the date. I can
look at your problem and the tutorial around the end of the next week.
Thanks a lot for the detailed email!

Lilla



> Hi Arjen,
>
> Thanks for your message. I did align the mri to Talairach; as you can see
> from http://i.imgur.com/26nyHYZ.png, the volume conduction model and
> sourcespace are both expressed in the same coordinate system (i.e.,
> everything's pointing in the same direction) but they're just not sitting
> on top of one another. If anyone has any ideas on where that problem was
> introduced (or how to re-align them now), I would greatly appreciate it.
> Below I have some more details about how I processed that data, if it
> helps.
>
> I'm trying to go through the data one step at a time and track where the
> problem might have happened. When I compare the sourcespace before having
> applied any transformation (i.e., the headshape from
> <subject>-oct-6-src.fif) to the original mri (orig-nomask.mgz), they look
> ok (I don't know how to plot them together, but see
> http://i.imgur.com/LGW7YnJ.png and http://i.imgur.com/JUoTxc9.png --
> things
> at least look like they're on more or less the same plane). Then I
> re-register the mri to CTF (
> http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate#source_modelco-registration_of_the_source_space_to_the_sensor-based_head_coordinate_system);
> after that, in mri_nom_ctf, the axes are all going in the right direction
> but the whole head is tilted forward and the origin of the axes is no
> longer at the anterior commisure (see http://i.imgur.com/CTZNOTk.png for
> the realigned MRI).  Applying the transformation matrix T to the
> sourcespace also seems to tilt it like that
> (http://i.imgur.com/bcNIpf3.png),
> although as can be seen from the first image in this message it doesn't
> quite line up with the volume conduction model in the end. As for the
> volume conduction model, here is what it looks like at first (
> http://i.imgur.com/ZX3m38b.png) and here is what it looks like after
> applying the transformation matrix (http://i.imgur.com/vXa3Cnc.png).
> Obviously the transformation matrix is doing something, but it's not
> getting the sourcespace and volume conduction model lined up; since it's
> the same transformation matrix, all I can guess is that there was some
> pre-existing difference between the source mesh (the .fif file) and the
> anatomical mri (orig-nomask.mgz), but I'm not sure when that came in.
>
> Another minor issue: when I first compared the volume conduction model and
> the sourcespace, they were expressed in different units even though I
> followed the code in the tutorial. See http://i.imgur.com/orwgcTJ.png: the
> sourcespace looks 10x smaller than the volume conduction model, which I
> assume is because it is expressed in cm whereas the volume conduction
> model
> is expressed in mm. To get the figure linked at the very beginning of this
> message, I had to convert the units of the volume conduction model to cm,
> even though that's not in the tutorial.
>
> I notice that the tutorial on the wiki hasn't been edited since October
> 2012 (other than a few edits I made this month which were just correcting
> typos in the prose). Is it possible that what's on the wiki is out of
> date?
> (Also cc'ing Lilla on this.)
>
> Thanks,
> Steve
>
>
>
>> Message: 1
>> Date: Fri, 31 May 2013 08:11:23 +0200 (CEST)
>> From: "Stolk, A." <a.stolk at fcdonders.ru.nl>
>> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
>> Subject: Re: [FieldTrip] Question about minimum norm estimate pipeline
>> Message-ID:
>>         <
> 1914237354.1292588.1369980683984.JavaMail.root at sculptor.zimbra.ru.nl>
>> Content-Type: text/plain; charset="utf-8"
>>
>> Hi Steve, A quick guess; did you correctly align your resliced mri to
> Talairach space by indicating the commissures (
> http://imaging.mrc-cbu.cam.ac.uk/imaging/FindingCommissures ) and, if I'm
> correct, a point in the same place, e.g. between the hemispheres? This
> should update the transformation matrix. Best regards, Arjen -----
> Oorspronkelijk bericht -----
>> > Van: "Stephen Politzer-Ahles" <politzerahless at gmail.com>
>> > Aan: fieldtrip at science.ru.nl
>> > Verzonden: Vrijdag 31 mei 2013 05:53:45
>> > Onderwerp: [FieldTrip] Question about minimum norm estimate pipeline
>> > Hello all,
>> > I have not yet gotten a response to my question below, but in the
>> > meantime I have another question about the minimum norm estimate
>> > workflow--specifically, about the coordinate system for the
>> > skull-stripped anatomy in the step described at
>> >
> http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate#preprocessing_of_the_anatomical_mrisave_to_disk
>> > . I'm confused by the following bit of code:
>> > % ensure that the skull-stripped anatomy is expressed in the same
>> > coordinate system as the anatomy
>> > seg.transform = mri_tal.transform;
>> > In my data, mri_tal.coordsys is 'spm' (I presume this is the result of
>> > re-aligning to Talairach in the previous step?) whereas seg.coordsys
>> > is 'ctf' (as a result of re-aligning to CTF several steps earlier).
>> > (But mri_tal also has a field mri_tal.transformorig, which seg does
>> > not have.) So should I really be using the same transform for both, as
>> > shown in the tutorial?
>> > Apologies if this question is pretty basic; I'm just trying to
>> > pinpoint where the mis-alignment described in my message below
>> > occurred, so I want to make sure I understand each step of the
>> > workflow correctly
>> > Best,
>> > Steve
>> > > Message: 1
>> > > Date: Sat, 25 May 2013 08:11:18 -0500
>> > > From: Stephen Politzer-Ahles < politzerahless at gmail.com >
>> > > To: fieldtrip at donders.ru.nl
>> > > Subject: [FieldTrip] Sourcespace and volume conductor misaligned
>> > > Message-ID:
>> > > <CAJT2k_9-hd_sM=hp4P-CUu+=aduSOMyZV7XPG0= fFk0ouR0wzA at mail.gmail.com
>> > > >
>> > > Content-Type: text/plain; charset="utf-8"
>> > >
>> > > Hello all,
>> > >
>> > > I am going through the workflow at
>> > > http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate . After
>> > > making
>> > > the volume conduction model using ft_prepare_headmodel(), I noticed
>> > > that
>> > > although the volume conduction model and sourcespace have the same
>> > > orientation and overall size/shape (after I converted the volume
>> > > conduction
>> > > model to cm, which wasn't in the tutorial but my original model came
>> > > out in
>> > > mm), they don't quite line up, as you can see in this figure:
>> > >
>> > > http://i.imgur.com/mGEtLOa.png
>> > >
>> > > I did interactively re-align the data to CTF (twice--in step 2 of
>> > > "Preprocessing of the anatomical MRI" and in step 4 of "Source
>> > > model")
>> > > using fiducials, and to Talairach (step 5 of "Preprocessing of the
>> > > anatomical data"), so I'm not sure how it ended up this way. The
>> > > code I've
>> > > used at each step is basically the same as that in the tutorial.
>> > >
>> > > Is there any way to line up my volume conduction model and
>> > > sourcespace now,
>> > > without going back and re-running most of the workflow?
>> > >
>> > > Best,
>> > > Steve
>> > >
>> > > --
>> > > Stephen Politzer-Ahles
>> > > University of Kansas
>> > > Linguistics Department
>> > > http://people.ku.edu/~sjpa/
>> > On Sat, May 25, 2013 at 1:56 PM, < fieldtrip-request at science.ru.nl >
>> > wrote:
>> > >
>> > > Send fieldtrip mailing list submissions to
>> > > fieldtrip at science.ru.nl
>> > >
>> > > To subscribe or unsubscribe via the World Wide Web, visit
>> > > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> > > or, via email, send a message with subject or body 'help' to
>> > > fieldtrip-request at science.ru.nl
>> > >
>> > > You can reach the person managing the list at
>> > > fieldtrip-owner at science.ru.nl
>> > >
>> > > When replying, please edit your Subject line so it is more specific
>> > > than "Re: Contents of fieldtrip digest..."
>> > >
>> > >
>> > > Today's Topics:
>> > >
>> > > 1. Sourcespace and volume conductor misaligned
>> > > (Stephen Politzer-Ahles)
>> > > 2. Re: fieldtrip Digest, Vol 30, Issue 31 (Johanna Zumer)
>> > >
>> > >
>> > > ----------------------------------------------------------------------
>> > >
>> > > Message: 1
>> > > Date: Sat, 25 May 2013 08:11:18 -0500
>> > > From: Stephen Politzer-Ahles < politzerahless at gmail.com >
>> > > To: fieldtrip at donders.ru.nl
>> > > Subject: [FieldTrip] Sourcespace and volume conductor misaligned
>> > > Message-ID:
>> > > <CAJT2k_9-hd_sM=hp4P-CUu+=aduSOMyZV7XPG0= fFk0ouR0wzA at mail.gmail.com
>> > > >
>> > > Content-Type: text/plain; charset="utf-8"
>> > >
>> > > Hello all,
>> > >
>> > > I am going through the workflow at
>> > > http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate . After
>> > > making
>> > > the volume conduction model using ft_prepare_headmodel(), I noticed
>> > > that
>> > > although the volume conduction model and sourcespace have the same
>> > > orientation and overall size/shape (after I converted the volume
>> > > conduction
>> > > model to cm, which wasn't in the tutorial but my original model came
>> > > out in
>> > > mm), they don't quite line up, as you can see in this figure:
>> > >
>> > > http://i.imgur.com/mGEtLOa.png
>> > >
>> > > I did interactively re-align the data to CTF (twice--in step 2 of
>> > > "Preprocessing of the anatomical MRI" and in step 4 of "Source
>> > > model")
>> > > using fiducials, and to Talairach (step 5 of "Preprocessing of the
>> > > anatomical data"), so I'm not sure how it ended up this way. The
>> > > code I've
>> > > used at each step is basically the same as that in the tutorial.
>> > >
>> > > Is there any way to line up my volume conduction model and
>> > > sourcespace now,
>> > > without going back and re-running most of the workflow?
>> > >
>> > > Best,
>> > > Steve
>> > >
>> > > --
>> > > Stephen Politzer-Ahles
>> > > University of Kansas
>> > > Linguistics Department
>> > > http://people.ku.edu/~sjpa/
>




From frank.ye.mei at gmail.com  Sun Jun  2 03:58:29 2013
From: frank.ye.mei at gmail.com (Frank Mei)
Date: Sat, 1 Jun 2013 21:58:29 -0400
Subject: [FieldTrip] error when using ctf2grad (Lozano Soldevilla,
	D. (Diego))
Message-ID: <CAF0J_Mts3imCMYaVE8QppR=oT8j0h9ceLKm=ANtW6JNyAxoPcA@mail.gmail.com>

Hello Diego,

Thank you for the reply. I was using fieldtrip20120822.

I found the bug in the fieldtrip20120822 file -ft_read_header.m.
In line 446 of the file:

-------
if any(~cellfun(@isempty,strfind(coeftype, 'G1AR')))
-------

should be:

-------
if any(~cellfun(@isempty,strfind(coeftype, 'G3AR')))
-------


The bug is corrected in the latest version of fieldtrip, and it runs
correctly now.

Now, grad.balance has 'G1BR','G2BR','G3BR''G3AR' in it.

The ctf sytem I use is ctf151.

Regards,
Ye
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From vitoria.piai at gmail.com  Sun Jun  2 11:17:25 2013
From: vitoria.piai at gmail.com (=?ISO-8859-1?Q?Vit=F3ria_Magalh=E3es_Piai?=)
Date: Sun, 02 Jun 2013 11:17:25 +0200
Subject: [FieldTrip] how to use ft_stratify?
Message-ID: <51AB0DA5.10805@gmail.com>

Hi all,

I'm trying to use ft_stratify for the first time, but (it could be just 
me) I don't find the help info helpful enough :)
What I want to achieve in the end is TFRs of two conditions for which 
the histogram of the reaction time over trials for each condition is 
matched.

If I understood ft_stratify correctly (and I doubt that), I could use 
this function to select the trials for each condition such that the 
histograms of the RTs match. Then knowing which trials to keep, I run 
ft_freqanalysis on those specifically.
So question number 1, is that how I should proceed? 'Cause as far as I 
can tell, ft_stratify will not take a whole raw data structure: The help 
says "each input is a Nchan X Nobs matrix". So I have to go for the RTs 
then.

Assuming my approach is correct (ft_stratify on RTs of two conditions, 
then move on with only those trials), I've made a matrix Nchan x 
N_trials for each condition.
% input1 = 265 sensors x 95 RT_trials;
% input2 = 265 sensors x 100 RT_trials;

         cfgst = [];
         cfgst.method      = 'histogram';
         cfgst.equalbinavg = 'no';
         cfgst.numbin      = 4;
         cfgst.numiter     = 2000; % default
         [output,bin] = ft_stratify(cfgst, input1, input2);

I then get an error in line 127:
linearhisto = zeros(ncond, cfg.numbin.^nchan);
??? Error using ==> zeros
Maximum variable size allowed by the program is exceeded.

Apparently, zeros(2, 4^265) is something matlab doesn't want to calculate!
Am I doing something wrong here? Has anyone worked with this function 
before (with such a number of sensors)?

Any help is greatly appreciated!
Cheers, Vitória


From a.stolk at fcdonders.ru.nl  Sun Jun  2 11:46:03 2013
From: a.stolk at fcdonders.ru.nl (Stolk, A.)
Date: Sun, 2 Jun 2013 11:46:03 +0200 (CEST)
Subject: [FieldTrip] how to use ft_stratify?
In-Reply-To: <51AB0DA5.10805@gmail.com>
Message-ID: <1910615072.1312606.1370166363974.JavaMail.root@sculptor.zimbra.ru.nl>

Hi Vitoria,

There is a wikipage that may help you get started, and answer your questions:
http://fieldtrip.fcdonders.nl/example/stratify

Best wishes,
Arjen  

----- Oorspronkelijk bericht -----
> Van: "Vitória Magalhães Piai" <vitoria.piai at gmail.com>
> Aan: fieldtrip at donders.ru.nl
> Verzonden: Zondag 2 juni 2013 11:17:25
> Onderwerp: [FieldTrip] how to use ft_stratify?
> Hi all,
> 
> I'm trying to use ft_stratify for the first time, but (it could be
> just
> me) I don't find the help info helpful enough :)
> What I want to achieve in the end is TFRs of two conditions for which
> the histogram of the reaction time over trials for each condition is
> matched.
> 
> If I understood ft_stratify correctly (and I doubt that), I could use
> this function to select the trials for each condition such that the
> histograms of the RTs match. Then knowing which trials to keep, I run
> ft_freqanalysis on those specifically.
> So question number 1, is that how I should proceed? 'Cause as far as I
> can tell, ft_stratify will not take a whole raw data structure: The
> help
> says "each input is a Nchan X Nobs matrix". So I have to go for the
> RTs
> then.
> 
> Assuming my approach is correct (ft_stratify on RTs of two conditions,
> then move on with only those trials), I've made a matrix Nchan x
> N_trials for each condition.
> % input1 = 265 sensors x 95 RT_trials;
> % input2 = 265 sensors x 100 RT_trials;
> 
> cfgst = [];
> cfgst.method = 'histogram';
> cfgst.equalbinavg = 'no';
> cfgst.numbin = 4;
> cfgst.numiter = 2000; % default
> [output,bin] = ft_stratify(cfgst, input1, input2);
> 
> I then get an error in line 127:
> linearhisto = zeros(ncond, cfg.numbin.^nchan);
> ??? Error using ==> zeros
> Maximum variable size allowed by the program is exceeded.
> 
> Apparently, zeros(2, 4^265) is something matlab doesn't want to
> calculate!
> Am I doing something wrong here? Has anyone worked with this function
> before (with such a number of sensors)?
> 
> Any help is greatly appreciated!
> Cheers, Vitória
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip



From vitoria.piai at gmail.com  Sun Jun  2 17:09:34 2013
From: vitoria.piai at gmail.com (=?ISO-8859-1?Q?Vit=F3ria_Magalh=E3es_Piai?=)
Date: Sun, 02 Jun 2013 17:09:34 +0200
Subject: [FieldTrip] how to use ft_stratify?
In-Reply-To: <mailman.11.1370167205.25821.fieldtrip@science.ru.nl>
References: <mailman.11.1370167205.25821.fieldtrip@science.ru.nl>
Message-ID: <51AB602E.8020609@gmail.com>

Thanx, Arjen!
Shame on me, I should have known that there would be a wikipage on that :)

And for the sake of archiving, in case someone else ever bumps into this 
thread because they're making the same mistake as me when using this 
function, here's what I was doing wrong:
The input Nchan x N_trials for each condition, Nchan should be 1 'cause 
my data are the RTs
So:

% input1 = RT_trials_cond1' ; % size = 1 x 95
% input2 = RT_trials_cond2' ;  % size = 1 x 100
cfgst = [];
cfgst.method = 'histogram';
output = ft_stratify(cfgst, input1, input2);

Now it will run and it won't even complain they are of different sizes 
either!

Hope this will help anyone in the future making the same mistake!
Cheers, Vitória



On 6/2/2013 12:00 PM, fieldtrip-request at science.ru.nl wrote:
> Message: 2
> Date: Sun, 02 Jun 2013 11:17:25 +0200
> From: Vit?ria Magalh?es Piai<vitoria.piai at gmail.com>
> To:fieldtrip at donders.ru.nl
> Subject: [FieldTrip] how to use ft_stratify?
> Message-ID:<51AB0DA5.10805 at gmail.com>
> Content-Type: text/plain; charset=ISO-8859-1; format=flowed
>
> Hi all,
>
> I'm trying to use ft_stratify for the first time, but (it could be just
> me) I don't find the help info helpful enough:)
> What I want to achieve in the end is TFRs of two conditions for which
> the histogram of the reaction time over trials for each condition is
> matched.
>
> If I understood ft_stratify correctly (and I doubt that), I could use
> this function to select the trials for each condition such that the
> histograms of the RTs match. Then knowing which trials to keep, I run
> ft_freqanalysis on those specifically.
> So question number 1, is that how I should proceed? 'Cause as far as I
> can tell, ft_stratify will not take a whole raw data structure: The help
> says "each input is a Nchan X Nobs matrix". So I have to go for the RTs
> then.
>
> Assuming my approach is correct (ft_stratify on RTs of two conditions,
> then move on with only those trials), I've made a matrix Nchan x
> N_trials for each condition.
> % input1 = 265 sensors x 95 RT_trials;
> % input2 = 265 sensors x 100 RT_trials;
>
>           cfgst = [];
>           cfgst.method      = 'histogram';
>           cfgst.equalbinavg = 'no';
>           cfgst.numbin      = 4;
>           cfgst.numiter     = 2000; % default
>           [output,bin] = ft_stratify(cfgst, input1, input2);
>
> I then get an error in line 127:
> linearhisto = zeros(ncond, cfg.numbin.^nchan);
> ??? Error using ==> zeros
> Maximum variable size allowed by the program is exceeded.
>
> Apparently, zeros(2, 4^265) is something matlab doesn't want to calculate!
> Am I doing something wrong here? Has anyone worked with this function
> before (with such a number of sensors)?
>
> Any help is greatly appreciated!
> Cheers, Vit?ria
>
>
> ------------------------------
>
> Message: 3
> Date: Sun, 2 Jun 2013 11:46:03 +0200 (CEST)
> From: "Stolk, A."<a.stolk at fcdonders.ru.nl>
> To: FieldTrip discussion list<fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] how to use ft_stratify?
> Message-ID:
> 	<1910615072.1312606.1370166363974.JavaMail.root at sculptor.zimbra.ru.nl>
> Content-Type: text/plain; charset=utf-8
>
> Hi Vitoria,
>
> There is a wikipage that may help you get started, and answer your questions:
> http://fieldtrip.fcdonders.nl/example/stratify
>
> Best wishes,
> Arjen

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From d.stoffers at gmail.com  Mon Jun  3 10:12:17 2013
From: d.stoffers at gmail.com (Diederick Stoffers)
Date: Mon, 3 Jun 2013 10:12:17 +0200
Subject: [FieldTrip] Postdoc positions available at the Netherlands
	Institute for Neuroscience in Amsterdam
In-Reply-To: <21E5F1A0-241E-43B6-957B-18A7767A7B51@gmail.com>
References: <21E5F1A0-241E-43B6-957B-18A7767A7B51@gmail.com>
Message-ID: <8B956BE9-4168-4ED4-B0E9-47FE260EAEE4@gmail.com>

Dear all,

Please find attached a description of postdoc positions available at the Netherlands Institute for Neuroscience in Amsterdam, which I am posting on behalf of my group leader Eus van Someren (cc). 

Relevant keywords for these positions are sleep, emotion, arousal, high-density EEG, fMRI, TMS, insomnia, internet assessment, database, latent class and latent trait analysis. 

Cheers,

Diederick


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From d.stoffers at gmail.com  Mon Jun  3 10:20:20 2013
From: d.stoffers at gmail.com (Diederick Stoffers)
Date: Mon, 3 Jun 2013 10:20:20 +0200
Subject: [FieldTrip] Postdoc positions available at the Netherlands
	Institute for Neuroscience in Amsterdam
In-Reply-To: <8B956BE9-4168-4ED4-B0E9-47FE260EAEE4@gmail.com>
References: <21E5F1A0-241E-43B6-957B-18A7767A7B51@gmail.com>
	<8B956BE9-4168-4ED4-B0E9-47FE260EAEE4@gmail.com>
Message-ID: <6DACABEC-925B-4E71-A7A2-FB8C7B2A60D1@gmail.com>

Dear all,

Please find attached a description of postdoc positions available at the Netherlands Institute for Neuroscience in Amsterdam, which I am posting on behalf of my group leader Eus van Someren (cc). 

Relevant keywords for these positions are sleep, emotion, arousal, high-density EEG, fMRI, TMS, insomnia, internet assessment, database, latent class and latent trait analysis. 

Cheers,

Diederick

NB Apologies if you receive this message twice, the initial message was rejected by some servers because it exceeded maximum message size.


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From jm.horschig at donders.ru.nl  Mon Jun  3 10:59:49 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Mon, 03 Jun 2013 10:59:49 +0200
Subject: [FieldTrip] channel combination problems
In-Reply-To: <27E5CAD9145EEC41BB9B34C01716A1983046156B@UM-EXCDAG-A01.um.gwdg.de>
References: <27E5CAD9145EEC41BB9B34C01716A1983046156B@UM-EXCDAG-A01.um.gwdg.de>
Message-ID: <51AC5B05.2020409@donders.ru.nl>

Hi Thomas,

that is indeed a bug that we are currently working on, see also here:
http://bugzilla.fcdonders.nl/show_bug.cgi?id=2148

A workaround for the moment is to call this:

   coh.dimord = 'chancmb_freq';
   coh = ft_checkdata(coh, 'cmbrepresentation', 'full');


As you asked what the difference between the two is:
Connectivity measures are define between two signals, or channels. So, 
for example you compute coherence between channel1 and channel2. In 
FieldTrip there are two ways to represent this: Either by a 3D NxMxF 
matrix or by a 2D (NxM)xF matrix, where F denotes the frequency 
dimension and N and M are the in- or output channels (coherence is a 
symmetric measure, so N=M). In other words, we can either represent it 
as a three dimensional matrix, where the first dimension denotes the 
input and the second the output channels, or we represent it as a two 
dimensional matrix, where the first dimension denotes the relation 
between in- and output channels. The latter is what we call a 
channelcombination (chancmb). It can be channel1->channel2 (meaning, 
influence from channel1 to channel 2). The same in a three dimensional 
matrix would be channel1 for dimension 1 and channel 2 for dimension 2. 
The workaround above converts from one to the other convention. If your 
data is in 'cmbrepresentation;, you will have 'labelcmb' which is a 2D 
cell-matrix, and your data dimensions (dimord) will be 'chancmb_XXX', 
where a single dimension respective to labelcmb defines the channel 
combination. If your data is not in 'cmbrepresentation', you will have a 
1D 'label' field and your data dimension (dimord) will be 
'chan_chan_XXX', this a 2D channel combinations that explains the 
channel combination.

Btw, I am not aware that you can define cfg.labelcmb in any function, 
imho it is always cfg.channelcmb.

Best,
Jörn


On 5/31/2013 11:42 AM, Wunderle, Thomas wrote:
>
> Hi all,
>
> I'm new in fieldtrip and I try to get the cfg.channelcmb to work, 
> because I want to plot the connectivity between the channels of 
> different laminar electrodes,
>
> let's say the connectivity between channel 1:24 and 25:38
>
> I tried the following:
>
> cfg           = [];
>
> cfg.method    = 'mtmfft';
>
> cfg.taper     = 'dpss';
>
> cfg.output    = 'fourier';
>
> cfg.tapsmofrq = 1;
>
> freq          = ft_freqanalysis(cfg, data)
>
> The output is:
>
> >> freq
>
> freq =
>
>             label: {3x1 cell}
>
>            dimord: 'rpttap_chan_freq'
>
>             freq: [1x101 double]
>
>             fourierspctrm: [500x3x101 double]
>
>             cumsumcnt: [500x1 double]
>
>             cumtapcnt: [500x1 double]
>
>              cfg: [1x1 struct]
>
> I then run
>
> cfg = [];
>
> cfg.method = 'coh';
>
> cfg.channelcmb = {freq.label{1} freq.label{2};freq.label{2} 
> freq.label{1}};
>
> coh= ft_connectivityanalysis(cfg, freq);
>
> And the output here is:
>
> >> coh
>
> coh =
>
>        labelcmb: {2x2 cell}
>
>        dimord: 'chan_freq'
>
>        cohspctrm: [2x101 double]
>
>         freq: [1x101 double]
>
>         dof: 500
>
>         cfg: [1x1 struct]
>
> As you can seen, the output of dimord is 'chan_freq' so in the 
> subsequent call of ft_connectivityplot I get an error message:
>
> cfg           = [];
>
> cfg.parameter = 'cohspctrm';
>
> ft_connectivityplot(cfg, coh);
>
> ??? Error using ==> ft_connectivityplot at 99
>
> the data should have a dimord of chan_chan_freq or chancmb_freq
>
> If I use in ft_freqanalysis the cfg.method = 'powandcsd', 
> cfg.channelcmb seems to have no effect at all,
>
> the coherence is computed for all possible pairs.
>
> I also don't understand the difference between "cfg.channelcmb" and 
> "cfg.labelcmb"
>
> Can you help me in how I should correctly use the cannelcmb and 
> labelcmb options?
>
> Thanks for your help,
>
> Thomas
>
> -----
>
> Dr. Thomas Wunderle
>
> Ernst Strüngmann Institute (ESI) for Neuroscience 
> <http://www.ncbi.nlm.nih.gov/feed/rss.cgi?ChanKey=PubMedNews>
>
> in Cooperation with Max Planck Society 
> <http://www.ncbi.nlm.nih.gov/feed/rss.cgi?ChanKey=PubMedNews>
>
> Deutschordenstrasse 46
>
> 60528 Frankfurt am Main, Germany
>
> www.esi-frankfurt.de <http://www.esi-frankfurt.de/>
>
> thomas.wunderle at esi-frankfurt.de <mailto:thomas.wunderle at esi-frankfurt.de>
>
> Tel: +49 69 96769 519
>
> Fax: +49 69 96769 555
>
> Sitz der Gesellschaft: Frankfurt am Main
>
> Registergericht: Amtsgericht Frankfurt - HRB 84266
>
> Geschäftsführer: Prof. Dr. Pascal Fries
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands

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From jm.horschig at donders.ru.nl  Mon Jun  3 11:30:34 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Mon, 03 Jun 2013 11:30:34 +0200
Subject: [FieldTrip] some of the requested samples occur twice
In-Reply-To: <CALsWBNOxcuA=LCMONaGWObU4fdZ3+vskGGFcKdTZE4jGRoW47Q@mail.gmail.com>
References: <CALsWBNOxcuA=LCMONaGWObU4fdZ3+vskGGFcKdTZE4jGRoW47Q@mail.gmail.com>
Message-ID: <51AC623A.1080207@donders.ru.nl>

Hi Robin,

it's not a bug that ft_fetch_data is not allowing for overlap. The 
function needs to be generic and eventually allow for fetching data 
extending over several trial segments. However, what should be the way 
to fetch  data that occurs twice, i.e. at the end of one trial and the 
beginning of another? If you have data with overlapping samples, it is 
not straight forward to define data from one trial as to be fetched and 
ignore the other. Since preprocessing options like filters are applied 
per trial segment, data will differ between trial segments if it 
overlaps. As there are a multitude of possibilities to deal with this 
and none of them is perfect (imho neither of them can even be called 
good), we decided to not allow for that.

For your problem, however, imho you can define negative trial padding in 
the function call to ft_artifact_zvalue, which should effectively pad. 
Have you tried this rather than padding manually?

Best,
Jörn

On 5/31/2013 6:14 PM, Robin wrote:
> I have a problem in preprocessing where I am getting this error:
>
> """
> some of the requested samples occur twice in the data
>
> Error in ft_artifact_zvalue (line 262)
>        dat{trlop} = ft_fetch_data(data,        'header', hdr, 'begsample',
>        trl(trlop,1)-fltpadding, 'endsample', trl(trlop,2)+fltpadding,
>        'chanindx', sgnind, 'checkboundary', strcmp(cfg.continuous,'no
> Error in ft_artifact_muscle (line 158)
>      [tmpcfg, artifact] = ft_artifact_zvalue(tmpcfg, data);
> """
>
> I think this is because I am manually adding some extra padding to the
> trials so that the artifact filtering can use that padding (I am doing
> the artifact filtering on data in memory which is output from
> ft_denoise_pca). So in this case it is not a problem if consecutive
> trials overlap a bit.
>
> I would therefore like to disable this error and wondered what is the
> best way to do it. I am a bit confused because ft_artifact_zvalue
> calls ft_fetch data with a "checkboundary" option which looks like it
> might be what I want (and set correctly), but ft_fetch_data doesn't
> seem to use that option. Instead it has an allowoverlap option.
>
> So for now I will manually add the allowoverlap option to the call in
> ft_artifact_zvalue, but I wondered what checkboundary doesn't appear
> in ft_fetch_data or if this might be a bug.
>
> Cheers
>
> Robin
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands



From julian.keil at gmail.com  Mon Jun  3 17:14:08 2013
From: julian.keil at gmail.com (Julian Keil)
Date: Mon, 3 Jun 2013 17:14:08 +0200
Subject: [FieldTrip] Polhemus Patriot
Message-ID: <67D8C434-4D28-40C3-94A6-A95C86BD6B78@gmail.com>

Dear FieldTrip-Users,

I have a not really FieldTrip-related question, but maybe one of you can help me anyways.
In our lab, we have a Polhemus Patriot 3D tracking system to acquire electrode positions.
Unfortunately, the recordings are severely distorted in the Z-axis (up-down).
After contacting the Polhemus Support, I got the information, that this is due to metal in the surroundings of the source which distorts the magnetic field.
I tried to get as far away from any metal as possible in our lab (~1.5 m to the walls and floor) but to no avail.

Now to my question: Has anyone any experience dealing with this? I'm quite puzzled by this as I know plenty of labs use Polhemus trackers, and I'm not sure if our lab is especially metal prone or if I'm missing something.

Thanks a lot for any help.

Julian

********************
Dr. Julian Keil

AG Multisensorische Integration
Psychiatrische Universitätsklinik
der Charité im St. Hedwig-Krankenhaus
Große Hamburger Straße 5-11, Raum E 307
10115 Berlin

Telefon: +49-30-2311-1879
Fax:        +49-30-2311-2209 
http://psy-ccm.charite.de/forschung/bildgebung/ag_multisensorische_integration

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From inieuwenhuis at berkeley.edu  Mon Jun  3 17:52:14 2013
From: inieuwenhuis at berkeley.edu (Ingrid Nieuwenhuis)
Date: Mon, 03 Jun 2013 08:52:14 -0700
Subject: [FieldTrip] loreta2fieldtrip function error
In-Reply-To: <1370015815.5183.YahooMailNeo@web122402.mail.ne1.yahoo.com>
References: <1369934092.15336.YahooMailNeo@web122405.mail.ne1.yahoo.com>
	<51A78CC1.6030906@berkeley.edu>
	<1370015815.5183.YahooMailNeo@web122402.mail.ne1.yahoo.com>
Message-ID: <51ACBBAE.4070508@berkeley.edu>

Hi Fatameh,

- In the LORETA program, you go to main utilities > Format converter.
- There you select: input binary file (sLORETA)
- It does not matter which format for output you choose, I coded it 
robust, it'll figure it out. As it says, rows are time points, columns 
are the volume-gridpoints (called voxels)
- After using loreta2fieldtrip the data is in normal FieldTrip volume 
format, see here: http://fieldtrip.fcdonders.nl/reference/ft_datatype_volume

To get familiar with FieldTrip source plotting etc, see the tutorials, 
for instance: http://fieldtrip.fcdonders.nl/tutorial/plotting
- The following steps are:
1) create a template: template = ft_read_mri([cur_path_FT, 
'\external\spm8\templates\T1.nii']);
2) interpolate your volume on the MNI template: [interp_mean] = 
ft_sourceinterpolate(cfg, GA_mean, template);
3) plot it using ft_sourceplot

Hope it helps,
Ingrid

On 5/31/2013 8:56 AM, Fatemeh Ebrahimi nia wrote:
> Dear respondent,
>
> Thank you for your advices.
> I have used the function that you have updated. It works out. Can you 
> give me information about the output structure (What do the matrixes 
> refer to?) or advise a reference to study about that please?
>
> Best,
> Fatemeh
>
>
> ------------------------------------------------------------------------
> *From:* Ingrid Nieuwenhuis <inieuwenhuis at berkeley.edu>
> *To:* fieldtrip at science.ru.nl
> *Sent:* Thursday, May 30, 2013 10:30 AM
> *Subject:* Re: [FieldTrip] loreta2fieldtrip function error
>
> Hi Fatemeh,
>
> I had the same error recently when I did the same. I filed the bug, 
> see http://bugzilla.fcdonders.nl/show_bug.cgi?id=2144
>
> I did create a work around. In the LORETA program, you can export the 
> source data as a text file. You can read that text file in with 
> loreta2fieldtrip.m. It's a bit of a patch, but it worked for me.
>
> Hope this helps,
> Ingrid
>
> On 5/30/2013 10:14 AM, Fatemeh Ebrahimi nia wrote:
>> Hi dear all,
>>
>> I am analyzing EEG data. I have computed sLORETA (.slor) from ERP 
>> data. Now I want to read and convert LORETA source reconstruction into a
>> MATLAB data structure using "loreta2fieldtrip" function, But I have 
>> gotten the bellow error.
>>
>> **** Error using fread
>> Invalid precision.
>> Error in loreta2fieldtrip (line 85)
>> activity = fread(fid, [voxnumber Ntime], 'float = >single'); ***
>>
>> Can someone give me a help?
>>
>> Best regards,
>> Fatemeh
>>
>>
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl  <mailto:fieldtrip at donders.ru.nl>
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
> -- 
> Ingrid Nieuwenhuis PhD
> Postdoctoral Fellow
> Sleep and Neuroimaging Laboratory
> Department of Psychology
> University of California, Berkeley
> California 94720-1650
> Tolman Hall, room 5305
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl <mailto:fieldtrip at donders.ru.nl>
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

-- 
Ingrid Nieuwenhuis PhD
Postdoctoral Fellow
Sleep and Neuroimaging Laboratory
Department of Psychology
University of California, Berkeley
California 94720-1650
Tolman Hall, room 5305

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From smoratti at psi.ucm.es  Mon Jun  3 18:07:40 2013
From: smoratti at psi.ucm.es (smoratti at psi.ucm.es)
Date: Mon, 3 Jun 2013 18:07:40 +0200
Subject: [FieldTrip] Polhemus Patriot
In-Reply-To: <67D8C434-4D28-40C3-94A6-A95C86BD6B78@gmail.com>
References: <67D8C434-4D28-40C3-94A6-A95C86BD6B78@gmail.com>
Message-ID: <C92FAB98-3619-4953-9C1D-DFD3186EFD40@psi.ucm.es>

Dear Julian,

Maybe a stupid answer and probably you have taken care of this already, but does the chair have any metal? We use an IKEA wooden garden chair.

Best,

Stephan

________________________________________________________
Stephan Moratti, PhD

see also: http://web.me.com/smoratti/

Universidad Complutense de Madrid
Facultad de Psicología
Departamento de Psicología Básica I
Campus de Somosaguas
28223 Pozuelo de Alarcón (Madrid)
Spain

and

Center for Biomedical Technology
Laboratory for Cognitive and Computational Neuroscience
Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
Campus Montegancedo
28223 Pozuelo de Alarcón (Madrid)
Spain


email: smoratti at psi.ucm.es
Tel.:    +34 679219982

El 03/06/2013, a las 17:14, Julian Keil escribió:

> Dear FieldTrip-Users,
> 
> I have a not really FieldTrip-related question, but maybe one of you can help me anyways.
> In our lab, we have a Polhemus Patriot 3D tracking system to acquire electrode positions.
> Unfortunately, the recordings are severely distorted in the Z-axis (up-down).
> After contacting the Polhemus Support, I got the information, that this is due to metal in the surroundings of the source which distorts the magnetic field.
> I tried to get as far away from any metal as possible in our lab (~1.5 m to the walls and floor) but to no avail.
> 
> Now to my question: Has anyone any experience dealing with this? I'm quite puzzled by this as I know plenty of labs use Polhemus trackers, and I'm not sure if our lab is especially metal prone or if I'm missing something.
> 
> Thanks a lot for any help.
> 
> Julian
> 
> ********************
> Dr. Julian Keil
> 
> AG Multisensorische Integration
> Psychiatrische Universitätsklinik
> der Charité im St. Hedwig-Krankenhaus
> Große Hamburger Straße 5-11, Raum E 307
> 10115 Berlin
> 
> Telefon: +49-30-2311-1879
> Fax:        +49-30-2311-2209 
> http://psy-ccm.charite.de/forschung/bildgebung/ag_multisensorische_integration
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From sarang.dalal at uni-konstanz.de  Mon Jun  3 18:16:02 2013
From: sarang.dalal at uni-konstanz.de (Sarang S. Dalal)
Date: Mon, 3 Jun 2013 09:16:02 -0700
Subject: [FieldTrip] Polhemus Patriot
In-Reply-To: <mailman.159.1370275680.1298.fieldtrip@science.ru.nl>
References: <mailman.159.1370275680.1298.fieldtrip@science.ru.nl>
Message-ID: <27A129F9-9570-4D6B-BBF9-48080801F980@uni-konstanz.de>

Dear Julian,

At UCSF, we were unable to use a Polhemus (an older model, not sure which) in the shielded room of the MEG, so we performed the digitization just outside the room before moving the subject inside. Perhaps if you have a nicely shielded EEG booth you have the same problem...

Sarang


On Jun 3, 2013, at 9:08 AM, fieldtrip-request at science.ru.nl wrote:
> Date: Mon, 3 Jun 2013 17:14:08 +0200
> From: Julian Keil <julian.keil at gmail.com>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: [FieldTrip] Polhemus Patriot
> Message-ID: <67D8C434-4D28-40C3-94A6-A95C86BD6B78 at gmail.com>
> Content-Type: text/plain; charset="iso-8859-1"
> 
> Dear FieldTrip-Users,
> 
> I have a not really FieldTrip-related question, but maybe one of you can help me anyways.
> In our lab, we have a Polhemus Patriot 3D tracking system to acquire electrode positions.
> Unfortunately, the recordings are severely distorted in the Z-axis (up-down).
> After contacting the Polhemus Support, I got the information, that this is due to metal in the surroundings of the source which distorts the magnetic field.
> I tried to get as far away from any metal as possible in our lab (~1.5 m to the walls and floor) but to no avail.
> 
> Now to my question: Has anyone any experience dealing with this? I'm quite puzzled by this as I know plenty of labs use Polhemus trackers, and I'm not sure if our lab is especially metal prone or if I'm missing something.
> 
> Thanks a lot for any help.
> 
> Julian
> 
> ********************
> Dr. Julian Keil
> 
> AG Multisensorische Integration
> Psychiatrische Universit?tsklinik
> der Charit? im St. Hedwig-Krankenhaus
> Gro?e Hamburger Stra?e 5-11, Raum E 307
> 10115 Berlin
> 
> Telefon: +49-30-2311-1879
> Fax:        +49-30-2311-2209 
> http://psy-ccm.charite.de/forschung/bildgebung/ag_multisensorische_integration




From inieuwenhuis at berkeley.edu  Mon Jun  3 18:25:47 2013
From: inieuwenhuis at berkeley.edu (Ingrid Nieuwenhuis)
Date: Mon, 03 Jun 2013 09:25:47 -0700
Subject: [FieldTrip] format conversion
In-Reply-To: <1369986505.7865.YahooMailNeo@web192306.mail.sg3.yahoo.com>
References: <1369986505.7865.YahooMailNeo@web192306.mail.sg3.yahoo.com>
Message-ID: <51ACC38B.9080802@berkeley.edu>

Hi Bahar,

I've added more info on the FieldTrip wiki about this for you and other. 
See here:
http://fieldtrip.fcdonders.nl/integrating_with_loreta

Hope it helps,
Ingrid


On 5/31/2013 12:48 AM, Bahar Bahar wrote:
> Hi dear all,
>
> I have a technical question about format converter module via sLORETA 
> software (.slor file to .txt one). Can any one give me some 
> information about the conversion procedure (and the meaning of the 
> column and row of the output file)?
>
> Thanks,
> bahar
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

-- 
Ingrid Nieuwenhuis PhD
Postdoctoral Fellow
Sleep and Neuroimaging Laboratory
Department of Psychology
University of California, Berkeley
California 94720-1650
Tolman Hall, room 5305

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From andmib at gmail.com  Mon Jun  3 22:15:49 2013
From: andmib at gmail.com (Andrew Brooks)
Date: Mon, 3 Jun 2013 16:15:49 -0400
Subject: [FieldTrip] Private function problems
Message-ID: <CALJPz69S8R+n+vWMYsmqC_Rqo63FbfECL+UStC0HcjQA3m8w2w@mail.gmail.com>

Hello all,

I followed the instructions on properly adding FieldTrip to the Matlab path
file. However, I continue to run into errors involving private functions.
In this case, I get the error 'undefined function 'hom2six' for input
arguments of type 'double''.

Does anybody have a suggestion as to why this is occurring?

Thanks!
Andrew
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From d.lozanosoldevilla at fcdonders.ru.nl  Mon Jun  3 22:53:41 2013
From: d.lozanosoldevilla at fcdonders.ru.nl (Lozano Soldevilla, D. (Diego))
Date: Mon, 3 Jun 2013 22:53:41 +0200 (CEST)
Subject: [FieldTrip] Private function problems
In-Reply-To: <CALJPz69S8R+n+vWMYsmqC_Rqo63FbfECL+UStC0HcjQA3m8w2w@mail.gmail.com>
Message-ID: <481032685.1338448.1370292821035.JavaMail.root@sculptor.zimbra.ru.nl>

Hi Andrew, Did you type the following? >> restoredefaultpath >> addpath /fieldtripxxxx >> ft_defaults What's the ft_* function you invoke to get the error 'undefined function 'hom2six'? And what's the fieldtrip version you're using? best, Diego ----- Original Message -----
> From: "Andrew Brooks" <andmib at gmail.com>
> To: "FieldTrip discussion list" <fieldtrip at science.ru.nl>
> Sent: Monday, 3 June, 2013 10:15:49 PM
> Subject: [FieldTrip] Private function problems
> Hello all,
> I followed the instructions on properly adding FieldTrip to the Matlab
> path file. However, I continue to run into errors involving private
> functions. In this case, I get the error 'undefined function 'hom2six'
> for input arguments of type 'double''.
> Does anybody have a suggestion as to why this is occurring?
> Thanks!
> Andrew
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
-- PhD Student Neuronal Oscillations Group Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Trigon, room 0.83 Kapittelweg 29 Radboud University Nijmegen NL-6525 EN Nijmegen The Netherlands E-Mail: d.lozanosoldevilla at fcdonders.ru.nl Tel: +31-(0)24-36-66274 Web: http://www.neuosc.com/ 
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From 13681530640 at 139.com  Tue Jun  4 04:16:18 2013
From: 13681530640 at 139.com (WangJing)
Date: Tue, 4 Jun 2013 10:16:18 +0800 (CST)
Subject: [FieldTrip] Question about Head Model
References: <mailman.159.1370275680.1298.fieldtrip@science.ru.nl>
Message-ID: <2af951ad49e020a-0000c.Richmail.00026806626265132618@139.com>


HI everyone,


 


    When I build head model,I encount some questions.


    1.for two Functions ft_volumereslice and ft_volumerealign,which should be run firstly?


    2. when surfaces are created at the boarders of the different tissue-types by the ft_prepare_mesh function. how to determine the parameter cfg.numvertices?


    3.when I build the head model,using the following codes:


     cfg        = [];
     cfg.method ='dipoli';
     cfg.cond =[0.3300 0.004125 0.3300];
     vol        = ft_prepare_headmodel(cfg, bnd);


     


the error message is:


 


??? Error using ==> surface_nesting at 26
the compartment nesting cannot be determined


Error in ==> ft_headmodel_dipoli at 84
order = surface_nesting(vol.bnd, 'outsidefirst');


Error in ==> ft_prepare_headmodel at 226
      vol = ft_headmodel_dipoli(geometry,'conductivity',cfg.conductivity,'isolatedsource',cfg.isolatedsource);


Error in ==> Myheadmodel at 5
vol        = ft_prepare_headmodel(cfg, bnd);


 


   I don't know where is wrong.who can help me? Thank you!


 


Best Regards,


Jing Wang


 


 






 
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From sauer.mpih at googlemail.com  Tue Jun  4 11:42:13 2013
From: sauer.mpih at googlemail.com (Andreas Sauer)
Date: Tue, 4 Jun 2013 11:42:13 +0200
Subject: [FieldTrip] NaNs as output of ft_sourceanalysis (DICS)
Message-ID: <CAHLSopU-XWo6-t=MW78POK-6CvN1hRoFcc74aRxEuXZXhiSjUQ@mail.gmail.com>

Dear all,

I would like to analyze sources with the beamforming approach using the
DICS method. I followed the steps in the tutorial and everything works
well. However, the output of ft_sourceanalysis contains only NaNs.

I checked the TF data that I calculated in the step before but that looks
fine, so I assume the error happens somewhere during ft_sourceanalysis.

That's how I calculate the TFRs:

        cfg = [];
        cfg.toilim = [-0.5 -0.3]; % baseline activity
        eval(['dataPre =
ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
        cfg.toilim = [0.1 1.0]; % task-related activity
        eval(['dataPost =
ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);

        % Combine the two datasets...
        data = appenddata(cfg, dataPre, dataPost);
        trialdesign = [ones(1,length(dataPost.trial))
ones(1,length(dataPre.trial))*2];

        % ... and compute the CSD matrices...
        cfg = [];
        cfg.output     = 'powandcsd';
        cfg.channel    = Channel.meg;
        cfg.method     = 'mtmfft';
        cfg.taper      = 'dpss';
        cfg.foilim     = [75 75];
        cfg.tapsmofrq  = 15; % amount of spectral smoothing = +/- 15 Hz
        cfg.channelcmb = {Channel.meg Channel.meg};

        % ... for the baseline and task part separately...
        eval(['freqPre.Cond_',num2str(cond(j)), ' =
ft_freqanalysis(cfg,dataPre);']);
        eval(['freqPost.Cond_',num2str(cond(j)), ' =
ft_freqanalysis(cfg,dataPost);']);

        % ... and for the whole trial
        eval(['freqAll.Cond_',num2str(cond(j)), ' =
ft_freqanalysis(cfg,data);']);
        eval(['freqAll.Cond_',num2str(cond(j)), '.trialdesign =
trialdesign;']); % pre and post info

And that's how I calculate the sources:

        cfg               = [];
        cfg.frequency     = 75;
        cfg.method        = 'dics';
        cfg.grid          = grid; % Here it gives .pos, .inside, .outside
to the structure
        cfg.vol           = vol;
        cfg.dim           = template_grid.dim; % Here I give the dimension
of the template grid
        cfg.grad          = Cond_101.hdr.grad;
        cfg.lambda        = '5%';
        cfg.reducerank    = 'no';
        cfg.projectnoise  = 'yes';
        cfg.realfilter    = 'yes';
        cfg.keepfilter    = 'yes'; % the output saves the computed inverse
filter

        eval(['SourceAll = ft_sourceanalysis(cfg,
freqAll.Cond_',num2str(cond(k)),');'])

        % use the common filter here
        cfg.grid.filter = SourceAll.avg.filter;
        eval(['sourcePre_con = ft_sourceanalysis(cfg,
freqPre.Cond_',num2str(cond(k)),');'])
        eval(['sourcePost_con = ft_sourceanalysis(cfg,
freqPost.Cond_',num2str(cond(k)),');'])



I would really appreciate any help with that! Thanks a lot!

Best,

Andreas

-- 
Andreas Sauer
Max Planck Institute for Brain Research
Deutschordenstr. 46
60528 Frankfurt am Main
Germany

T: +49 69 96769 278
F: +49 69 96769 327
Email: andreas.sauer at brain.mpg.de
www.brain.mpg.de
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From sauer.mpih at googlemail.com  Tue Jun  4 11:52:24 2013
From: sauer.mpih at googlemail.com (Andreas Sauer)
Date: Tue, 4 Jun 2013 11:52:24 +0200
Subject: [FieldTrip] NaNs as outpout of ft_sourceanalysis (DICS)
Message-ID: <CAHLSopUvv47POq0cHQD8iZfYnOvp+oz6VyCLcW4CsNhjJAvBVw@mail.gmail.com>

Dear all,

I would like to analyze sources with the beamforming approach using the
DICS method. I followed the steps in the tutorial and everything works
well. However, the output of ft_sourceanalysis contains only NaNs.

I checked the TF data that I calculated in the step before but that looks
fine, so I assume the error happens somewhere during ft_sourceanalysis.

That's how I calculate the TFRs:

        cfg = [];
        cfg.toilim = [-0.5 -0.3]; % baseline activity
        eval(['dataPre =
ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
        cfg.toilim = [0.1 1.0]; % task-related activity
        eval(['dataPost =
ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);

        % Combine the two datasets...
        data = appenddata(cfg, dataPre, dataPost);
        trialdesign = [ones(1,length(dataPost.trial))
ones(1,length(dataPre.trial))*2];

        % ... and compute the CSD matrices...
        cfg = [];
        cfg.output     = 'powandcsd';
        cfg.channel    = Channel.meg;
        cfg.method     = 'mtmfft';
        cfg.taper      = 'dpss';
        cfg.foilim     = [75 75];
        cfg.tapsmofrq  = 15; % amount of spectral smoothing = +/- 15 Hz
        cfg.channelcmb = {Channel.meg Channel.meg};

        % ... for the baseline and task part separately...
        eval(['freqPre.Cond_',num2str(cond(j)), ' =
ft_freqanalysis(cfg,dataPre);']);
        eval(['freqPost.Cond_',num2str(cond(j)), ' =
ft_freqanalysis(cfg,dataPost);']);

        % ... and for the whole trial
        eval(['freqAll.Cond_',num2str(cond(j)), ' =
ft_freqanalysis(cfg,data);']);
        eval(['freqAll.Cond_',num2str(cond(j)), '.trialdesign =
trialdesign;']); % pre and post info

And that's how I calculate the sources:

        cfg               = [];
        cfg.frequency     = 75;
        cfg.method        = 'dics';
        cfg.grid          = grid; % Here it gives .pos, .inside, .outside
to the structure
        cfg.vol           = vol;
        cfg.dim           = template_grid.dim; % Here I give the dimension
of the template grid
        cfg.grad          = Cond_101.hdr.grad;
        cfg.lambda        = '5%';
        cfg.reducerank    = 'no';
        cfg.projectnoise  = 'yes';
        cfg.realfilter    = 'yes';
        cfg.keepfilter    = 'yes'; % the output saves the computed inverse
filter

        eval(['SourceAll = ft_sourceanalysis(cfg,
freqAll.Cond_',num2str(cond(k)),');'])

        % use the common filter here
        cfg.grid.filter = SourceAll.avg.filter;
        eval(['sourcePre_con = ft_sourceanalysis(cfg,
freqPre.Cond_',num2str(cond(k)),');'])
        eval(['sourcePost_con = ft_sourceanalysis(cfg,
freqPost.Cond_',num2str(cond(k)),');'])



I would really appreciate any help with that! Thanks a lot!

Best,

Andreas


-- 
Andreas Sauer
Max Planck Institute for Brain Research
Deutschordenstr. 46
60528 Frankfurt am Main
Germany

T: +49 69 96769 278
F: +49 69 96769 327
Email: andreas.sauer at brain.mpg.de <sauer.mpih at gmail.com>
www.brain.mpg.de
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From eelke.spaak at donders.ru.nl  Tue Jun  4 11:54:51 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Tue, 4 Jun 2013 11:54:51 +0200
Subject: [FieldTrip] NaNs as output of ft_sourceanalysis (DICS)
In-Reply-To: <CAHLSopU-XWo6-t=MW78POK-6CvN1hRoFcc74aRxEuXZXhiSjUQ@mail.gmail.com>
References: <CAHLSopU-XWo6-t=MW78POK-6CvN1hRoFcc74aRxEuXZXhiSjUQ@mail.gmail.com>
Message-ID: <CABPNLUoRezPPHDCNMJqvw3T3-dOqnC32VP_ihdmDqqpXQF0aNQ@mail.gmail.com>

Dear Andreas,

How many NaNs do you get exactly and in which field? If it is some
NaNs in source.avg.pow, then it is quite normal: the estimates for
dipole locations which were flagged as outside the brain are always
NaN, as they are not scanned. The following should hold:

sum(isnan(source.avg.pow)) == numel(source.outside)
&&
sum(~isnan(source.avg.pow)) == numel(source.inside)

Best,
Eelke

On 4 June 2013 11:42, Andreas Sauer <sauer.mpih at googlemail.com> wrote:
> Dear all,
>
> I would like to analyze sources with the beamforming approach using the DICS
> method. I followed the steps in the tutorial and everything works well.
> However, the output of ft_sourceanalysis contains only NaNs.
>
> I checked the TF data that I calculated in the step before but that looks
> fine, so I assume the error happens somewhere during ft_sourceanalysis.
>
> That's how I calculate the TFRs:
>
>         cfg = [];
>         cfg.toilim = [-0.5 -0.3]; % baseline activity
>         eval(['dataPre =
> ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
>         cfg.toilim = [0.1 1.0]; % task-related activity
>         eval(['dataPost =
> ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
>
>         % Combine the two datasets...
>         data = appenddata(cfg, dataPre, dataPost);
>         trialdesign = [ones(1,length(dataPost.trial))
> ones(1,length(dataPre.trial))*2];
>
>         % ... and compute the CSD matrices...
>         cfg = [];
>         cfg.output     = 'powandcsd';
>         cfg.channel    = Channel.meg;
>         cfg.method     = 'mtmfft';
>         cfg.taper      = 'dpss';
>         cfg.foilim     = [75 75];
>         cfg.tapsmofrq  = 15; % amount of spectral smoothing = +/- 15 Hz
>         cfg.channelcmb = {Channel.meg Channel.meg};
>
>         % ... for the baseline and task part separately...
>         eval(['freqPre.Cond_',num2str(cond(j)), ' =
> ft_freqanalysis(cfg,dataPre);']);
>         eval(['freqPost.Cond_',num2str(cond(j)), ' =
> ft_freqanalysis(cfg,dataPost);']);
>
>         % ... and for the whole trial
>         eval(['freqAll.Cond_',num2str(cond(j)), ' =
> ft_freqanalysis(cfg,data);']);
>         eval(['freqAll.Cond_',num2str(cond(j)), '.trialdesign =
> trialdesign;']); % pre and post info
>
> And that's how I calculate the sources:
>
>         cfg               = [];
>         cfg.frequency     = 75;
>         cfg.method        = 'dics';
>         cfg.grid          = grid; % Here it gives .pos, .inside, .outside to
> the structure
>         cfg.vol           = vol;
>         cfg.dim           = template_grid.dim; % Here I give the dimension
> of the template grid
>         cfg.grad          = Cond_101.hdr.grad;
>         cfg.lambda        = '5%';
>         cfg.reducerank    = 'no';
>         cfg.projectnoise  = 'yes';
>         cfg.realfilter    = 'yes';
>         cfg.keepfilter    = 'yes'; % the output saves the computed inverse
> filter
>
>         eval(['SourceAll = ft_sourceanalysis(cfg,
> freqAll.Cond_',num2str(cond(k)),');'])
>
>         % use the common filter here
>         cfg.grid.filter = SourceAll.avg.filter;
>         eval(['sourcePre_con = ft_sourceanalysis(cfg,
> freqPre.Cond_',num2str(cond(k)),');'])
>         eval(['sourcePost_con = ft_sourceanalysis(cfg,
> freqPost.Cond_',num2str(cond(k)),');'])
>
>
>
> I would really appreciate any help with that! Thanks a lot!
>
> Best,
>
> Andreas
>
> --
> Andreas Sauer
> Max Planck Institute for Brain Research
> Deutschordenstr. 46
> 60528 Frankfurt am Main
> Germany
>
> T: +49 69 96769 278
> F: +49 69 96769 327
> Email: andreas.sauer at brain.mpg.de
> www.brain.mpg.de
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From jm.horschig at donders.ru.nl  Tue Jun  4 12:17:37 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Tue, 04 Jun 2013 12:17:37 +0200
Subject: [FieldTrip] NaNs as output of ft_sourceanalysis (DICS)
In-Reply-To: <CABPNLUoRezPPHDCNMJqvw3T3-dOqnC32VP_ihdmDqqpXQF0aNQ@mail.gmail.com>
References: <CAHLSopU-XWo6-t=MW78POK-6CvN1hRoFcc74aRxEuXZXhiSjUQ@mail.gmail.com>
	<CABPNLUoRezPPHDCNMJqvw3T3-dOqnC32VP_ihdmDqqpXQF0aNQ@mail.gmail.com>
Message-ID: <51ADBEC1.5060204@donders.ru.nl>

Hi Andreas,

could it be related to the fact that you redefine your trials and when 
estimating the frequency content, there is no exact 75Hz bin, thus 
ft_sourceanalysis cannot beam the frequency you specify? Since you cut 
out the pre- and poststimulus periods with different lengths, the 
frequency resolution will be strongly different, thus an estimate of 
75Hz will effectively be somewhere around 75Hz, but not exactly 75Hz. 
You could try to set 
cfg.frequency=freqAll.Cond_(yourNumberedCondition).freq instead of 
cfg.frequency=75. Note that in this case, sourceAll might have non-nans, 
but sourcePre and sourcePost will probably still have nans due to the 
resolution issue
If that's not the case, then I agree also with Eelke that more 
information is needed to help you, e.g. in which of the three source 
structures are nans? How many nans are there (try 
all(isnan(source.avg.pow(:))))?

Best,
Jörn

On 6/4/2013 11:54 AM, Eelke Spaak wrote:
> Dear Andreas,
>
> How many NaNs do you get exactly and in which field? If it is some
> NaNs in source.avg.pow, then it is quite normal: the estimates for
> dipole locations which were flagged as outside the brain are always
> NaN, as they are not scanned. The following should hold:
>
> sum(isnan(source.avg.pow)) == numel(source.outside)
> &&
> sum(~isnan(source.avg.pow)) == numel(source.inside)
>
> Best,
> Eelke
>
> On 4 June 2013 11:42, Andreas Sauer <sauer.mpih at googlemail.com> wrote:
>> Dear all,
>>
>> I would like to analyze sources with the beamforming approach using the DICS
>> method. I followed the steps in the tutorial and everything works well.
>> However, the output of ft_sourceanalysis contains only NaNs.
>>
>> I checked the TF data that I calculated in the step before but that looks
>> fine, so I assume the error happens somewhere during ft_sourceanalysis.
>>
>> That's how I calculate the TFRs:
>>
>>          cfg = [];
>>          cfg.toilim = [-0.5 -0.3]; % baseline activity
>>          eval(['dataPre =
>> ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
>>          cfg.toilim = [0.1 1.0]; % task-related activity
>>          eval(['dataPost =
>> ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
>>
>>          % Combine the two datasets...
>>          data = appenddata(cfg, dataPre, dataPost);
>>          trialdesign = [ones(1,length(dataPost.trial))
>> ones(1,length(dataPre.trial))*2];
>>
>>          % ... and compute the CSD matrices...
>>          cfg = [];
>>          cfg.output     = 'powandcsd';
>>          cfg.channel    = Channel.meg;
>>          cfg.method     = 'mtmfft';
>>          cfg.taper      = 'dpss';
>>          cfg.foilim     = [75 75];
>>          cfg.tapsmofrq  = 15; % amount of spectral smoothing = +/- 15 Hz
>>          cfg.channelcmb = {Channel.meg Channel.meg};
>>
>>          % ... for the baseline and task part separately...
>>          eval(['freqPre.Cond_',num2str(cond(j)), ' =
>> ft_freqanalysis(cfg,dataPre);']);
>>          eval(['freqPost.Cond_',num2str(cond(j)), ' =
>> ft_freqanalysis(cfg,dataPost);']);
>>
>>          % ... and for the whole trial
>>          eval(['freqAll.Cond_',num2str(cond(j)), ' =
>> ft_freqanalysis(cfg,data);']);
>>          eval(['freqAll.Cond_',num2str(cond(j)), '.trialdesign =
>> trialdesign;']); % pre and post info
>>
>> And that's how I calculate the sources:
>>
>>          cfg               = [];
>>          cfg.frequency     = 75;
>>          cfg.method        = 'dics';
>>          cfg.grid          = grid; % Here it gives .pos, .inside, .outside to
>> the structure
>>          cfg.vol           = vol;
>>          cfg.dim           = template_grid.dim; % Here I give the dimension
>> of the template grid
>>          cfg.grad          = Cond_101.hdr.grad;
>>          cfg.lambda        = '5%';
>>          cfg.reducerank    = 'no';
>>          cfg.projectnoise  = 'yes';
>>          cfg.realfilter    = 'yes';
>>          cfg.keepfilter    = 'yes'; % the output saves the computed inverse
>> filter
>>
>>          eval(['SourceAll = ft_sourceanalysis(cfg,
>> freqAll.Cond_',num2str(cond(k)),');'])
>>
>>          % use the common filter here
>>          cfg.grid.filter = SourceAll.avg.filter;
>>          eval(['sourcePre_con = ft_sourceanalysis(cfg,
>> freqPre.Cond_',num2str(cond(k)),');'])
>>          eval(['sourcePost_con = ft_sourceanalysis(cfg,
>> freqPost.Cond_',num2str(cond(k)),');'])
>>
>>
>>
>> I would really appreciate any help with that! Thanks a lot!
>>
>> Best,
>>
>> Andreas
>>
>> --
>> Andreas Sauer
>> Max Planck Institute for Brain Research
>> Deutschordenstr. 46
>> 60528 Frankfurt am Main
>> Germany
>>
>> T: +49 69 96769 278
>> F: +49 69 96769 327
>> Email: andreas.sauer at brain.mpg.de
>> www.brain.mpg.de
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands



From sauer.mpih at googlemail.com  Tue Jun  4 12:31:32 2013
From: sauer.mpih at googlemail.com (Andreas Sauer)
Date: Tue, 4 Jun 2013 12:31:32 +0200
Subject: [FieldTrip] NaNs as output of ft_sourceanalysis (DICS)
In-Reply-To: <CABPNLUoRezPPHDCNMJqvw3T3-dOqnC32VP_ihdmDqqpXQF0aNQ@mail.gmail.com>
References: <CAHLSopU-XWo6-t=MW78POK-6CvN1hRoFcc74aRxEuXZXhiSjUQ@mail.gmail.com>
	<CABPNLUoRezPPHDCNMJqvw3T3-dOqnC32VP_ihdmDqqpXQF0aNQ@mail.gmail.com>
Message-ID: <CAHLSopUkz1XxH+2VoLH9FYOE_97ouFDCxV8Qvy8fO2oP-vU6iw@mail.gmail.com>

Dear Eelke and Jörn,

thanks for the super quick responses! And sorry for the double post...

I tried Eelke's suggestion and that holds. So, I have only NaNs in the
fields for the dipole locations outside the brain.
However, if I continue and calculate the contrast between pre and post and
plot it I don't see any activation.

I will try your suggestion, Jörn, as well and see whether it has to do with
the re-definition.

Thanks again for your suggestions!

Best,

Andreas


2013/6/4 Eelke Spaak <eelke.spaak at donders.ru.nl>

> Dear Andreas,
>
> How many NaNs do you get exactly and in which field? If it is some
> NaNs in source.avg.pow, then it is quite normal: the estimates for
> dipole locations which were flagged as outside the brain are always
> NaN, as they are not scanned. The following should hold:
>
> sum(isnan(source.avg.pow)) == numel(source.outside)
> &&
> sum(~isnan(source.avg.pow)) == numel(source.inside)
>
> Best,
> Eelke
>
> On 4 June 2013 11:42, Andreas Sauer <sauer.mpih at googlemail.com> wrote:
> > Dear all,
> >
> > I would like to analyze sources with the beamforming approach using the
> DICS
> > method. I followed the steps in the tutorial and everything works well.
> > However, the output of ft_sourceanalysis contains only NaNs.
> >
> > I checked the TF data that I calculated in the step before but that looks
> > fine, so I assume the error happens somewhere during ft_sourceanalysis.
> >
> > That's how I calculate the TFRs:
> >
> >         cfg = [];
> >         cfg.toilim = [-0.5 -0.3]; % baseline activity
> >         eval(['dataPre =
> > ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
> >         cfg.toilim = [0.1 1.0]; % task-related activity
> >         eval(['dataPost =
> > ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
> >
> >         % Combine the two datasets...
> >         data = appenddata(cfg, dataPre, dataPost);
> >         trialdesign = [ones(1,length(dataPost.trial))
> > ones(1,length(dataPre.trial))*2];
> >
> >         % ... and compute the CSD matrices...
> >         cfg = [];
> >         cfg.output     = 'powandcsd';
> >         cfg.channel    = Channel.meg;
> >         cfg.method     = 'mtmfft';
> >         cfg.taper      = 'dpss';
> >         cfg.foilim     = [75 75];
> >         cfg.tapsmofrq  = 15; % amount of spectral smoothing = +/- 15 Hz
> >         cfg.channelcmb = {Channel.meg Channel.meg};
> >
> >         % ... for the baseline and task part separately...
> >         eval(['freqPre.Cond_',num2str(cond(j)), ' =
> > ft_freqanalysis(cfg,dataPre);']);
> >         eval(['freqPost.Cond_',num2str(cond(j)), ' =
> > ft_freqanalysis(cfg,dataPost);']);
> >
> >         % ... and for the whole trial
> >         eval(['freqAll.Cond_',num2str(cond(j)), ' =
> > ft_freqanalysis(cfg,data);']);
> >         eval(['freqAll.Cond_',num2str(cond(j)), '.trialdesign =
> > trialdesign;']); % pre and post info
> >
> > And that's how I calculate the sources:
> >
> >         cfg               = [];
> >         cfg.frequency     = 75;
> >         cfg.method        = 'dics';
> >         cfg.grid          = grid; % Here it gives .pos, .inside,
> .outside to
> > the structure
> >         cfg.vol           = vol;
> >         cfg.dim           = template_grid.dim; % Here I give the
> dimension
> > of the template grid
> >         cfg.grad          = Cond_101.hdr.grad;
> >         cfg.lambda        = '5%';
> >         cfg.reducerank    = 'no';
> >         cfg.projectnoise  = 'yes';
> >         cfg.realfilter    = 'yes';
> >         cfg.keepfilter    = 'yes'; % the output saves the computed
> inverse
> > filter
> >
> >         eval(['SourceAll = ft_sourceanalysis(cfg,
> > freqAll.Cond_',num2str(cond(k)),');'])
> >
> >         % use the common filter here
> >         cfg.grid.filter = SourceAll.avg.filter;
> >         eval(['sourcePre_con = ft_sourceanalysis(cfg,
> > freqPre.Cond_',num2str(cond(k)),');'])
> >         eval(['sourcePost_con = ft_sourceanalysis(cfg,
> > freqPost.Cond_',num2str(cond(k)),');'])
> >
> >
> >
> > I would really appreciate any help with that! Thanks a lot!
> >
> > Best,
> >
> > Andreas
> >
> > --
> > Andreas Sauer
> > Max Planck Institute for Brain Research
> > Deutschordenstr. 46
> > 60528 Frankfurt am Main
> > Germany
> >
> > T: +49 69 96769 278
> > F: +49 69 96769 327
> > Email: andreas.sauer at brain.mpg.de
> > www.brain.mpg.de
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
Dipl.-Psych. Andreas Sauer
Max Planck Institute for Brain Research
Deutschordenstraße 46
60528 Frankfurt am Main
Germany

T: +49 69 96769 278
F: +49 69 96769 327
Email: sauer.mpih at gmail.com
www.brain.mpg.de
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From r.cox at uva.nl  Tue Jun  4 14:31:06 2013
From: r.cox at uva.nl (Roy Cox)
Date: Tue, 4 Jun 2013 14:31:06 +0200
Subject: [FieldTrip] ft_freqstatistics & ft_clusterplot
Message-ID: <CABafTZd5GXvBG=Xa=252EGwEsQysX1zaCnn+iuRH575F6byo7Q@mail.gmail.com>

Dear all,

I recently joined your trip and I want to make use of fieldtrip's cluster
correction capabilities. But I can't seem to get it to work. Perhaps some
of you can clarify some things I can't figure out easily from the tutorials
or functions themselves.

A potentially important thing to know is that I performed all
single-subject tf analyes using custom scripts, and now I want to have
fieldtrip perform the overall statistics (8 subjects, 2 within-subj
conditions).

ft_freqstatistics works. However, I wonder: does it matter for the
statistics what latency and frequency range you choose and/or whether you
average across time/freq bins? I tried a number of variants, but the
command window output "found [] positive/negative clusters in observed
data" is always identical. Which confuses me.

is it possible to call ft_freqstatistics and neither average over time nor
frequency bins? or am I supposed to average across at least one to end up
with less-dimensional data for ft_clusterplot?

regardless of how I call ft_freqstatistics, ft_clusterplot crashes like
this:

 Assignment has more non-singleton rhs dimensions than non-singleton
subscripts

Error in ==> ft_clusterplot at 179
    sigposCLM(:,:,iPos) = (posCLM == sigpos(iPos));

here, my posCLM is a 126(chan)x35(freqs)x301(time) array, which indeed does
not fit the left-hand side.

If anyone has any ideas/suggestions I'd be happy to hear them.

Roy

-- 
Roy Cox, M.Sc. | Brain & Cognition Group | Department of Psychology |
University of Amsterdam | Weesperplein 4 | 1018 XA Amsterdam | the
Netherlands | room 3.21 | phone: +31 20 525 6847 | email: r.cox at uva.nl
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From andmib at gmail.com  Tue Jun  4 17:01:43 2013
From: andmib at gmail.com (Andrew Brooks)
Date: Tue, 4 Jun 2013 11:01:43 -0400
Subject: [FieldTrip] Private function problems
In-Reply-To: <481032685.1338448.1370292821035.JavaMail.root@sculptor.zimbra.ru.nl>
References: <CALJPz69S8R+n+vWMYsmqC_Rqo63FbfECL+UStC0HcjQA3m8w2w@mail.gmail.com>
	<481032685.1338448.1370292821035.JavaMail.root@sculptor.zimbra.ru.nl>
Message-ID: <CALJPz69LZ_35=Z6YR5E6yRymDcZ3bBjaOpXOMyz3+CTWDjDNcw@mail.gmail.com>

Hello Diego,

I am using the example pipeline script from an earlier version of FieldTrip
(ft_omri_pipeline_nuisance). The exact code that is throwing the
error: curSixDof = hom2six(M).

I did run the three lines of code to reset the default paths, add
fieldtrip, and then ran ft_defaults. The version of FieldTrip I am using is
20130602.

Thanks,
Andrew






On Mon, Jun 3, 2013 at 4:53 PM, Lozano Soldevilla, D. (Diego) <
d.lozanosoldevilla at fcdonders.ru.nl> wrote:

> Hi Andrew,
>
> Did you type the following?
>
> >> restoredefaultpath
> >> addpath /fieldtripxxxx
> >> ft_defaults
>
> What's the ft_* function you invoke to get the error 'undefined function
> 'hom2six'? And what's the fieldtrip version you're using?
>
> best,
>
> Diego
>
> ------------------------------
>
> *From: *"Andrew Brooks" <andmib at gmail.com>
> *To: *"FieldTrip discussion list" <fieldtrip at science.ru.nl>
> *Sent: *Monday, 3 June, 2013 10:15:49 PM
> *Subject: *[FieldTrip] Private function problems
>
>
> Hello all,
>
> I followed the instructions on properly adding FieldTrip to the Matlab
> path file. However, I continue to run into errors involving private
> functions. In this case, I get the error 'undefined function 'hom2six' for
> input arguments of type 'double''.
>
> Does anybody have a suggestion as to why this is occurring?
>
> Thanks!
> Andrew
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
>
> --
> PhD Student
> Neuronal Oscillations Group
> Donders Institute for Brain, Cognition and Behaviour
> Centre for Cognitive Neuroimaging
> Trigon, room 0.83
> Kapittelweg 29
> Radboud University Nijmegen
> NL-6525 EN Nijmegen
> The Netherlands
> E-Mail: d.lozanosoldevilla at fcdonders.ru.nl
> Tel:     +31-(0)24-36-66274
> Web:   http://www.neuosc.com/
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From frank.ye.mei at gmail.com  Tue Jun  4 22:47:08 2013
From: frank.ye.mei at gmail.com (Frank Mei)
Date: Tue, 4 Jun 2013 16:47:08 -0400
Subject: [FieldTrip] How to set a small window when doing source
	localization?
Message-ID: <CAF0J_Mu4csTxGVM=3UQajwDQFbM3igEyjLUUMwvW9GBVcZpW7w@mail.gmail.com>

Hello all,

I want to be more precise in time, when doing source localization. So I
tried to set a small cfg.toilim, before the 'ft_redefinetrial'.   But if it
is set smaller than 0.3(corresponding to 300ms), an error will pop up.

How to solve that problem?

thanks ahead,
Ye Mei
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From d.lozanosoldevilla at fcdonders.ru.nl  Wed Jun  5 15:39:14 2013
From: d.lozanosoldevilla at fcdonders.ru.nl (Lozano Soldevilla, D. (Diego))
Date: Wed, 5 Jun 2013 15:39:14 +0200 (CEST)
Subject: [FieldTrip] Private function problems
In-Reply-To: <CALJPz69LZ_35=Z6YR5E6yRymDcZ3bBjaOpXOMyz3+CTWDjDNcw@mail.gmail.com>
Message-ID: <2127428772.1387542.1370439554352.JavaMail.root@sculptor.zimbra.ru.nl>

Hi Andrew, Could you please check inside your matlab path there's the realtime/mri directory where ft_omri_pipeline_nuisance.m function is located? Mine looks like this: '/home/electromag/dieloz/matlab/ fieldtrip-dev/realtime/online_mri/ ' If it's there, you shouldn't have the private folder problem. Otherwise, add from the command window and tell me. best, Diego ----- Original Message -----
> From: "Andrew Brooks" <andmib at gmail.com>
> To: "Diego Lozano" <diego.lozanosoldevilla at fcdonders.ru.nl>,
> "FieldTrip discussion list" <fieldtrip at science.ru.nl>
> Sent: Tuesday, 4 June, 2013 5:01:43 PM
> Subject: Re: [FieldTrip] Private function problems
> Hello Diego,
> I am using the example pipeline script from an earlier version of
> FieldTrip (ft_omri_pipeline_nuisance). The exact code that is throwing
> the error: curSixDof = hom2six(M).
> I did run the three lines of code to reset the default paths, add
> fieldtrip, and then ran ft_defaults. The version of FieldTrip I am
> using is 20130602.
> Thanks,
> Andrew
> On Mon, Jun 3, 2013 at 4:53 PM, Lozano Soldevilla, D. (Diego) <
> d.lozanosoldevilla at fcdonders.ru.nl > wrote:
> > Hi Andrew,
> > Did you type the following?
> > >> restoredefaultpath
> > >> addpath /fieldtripxxxx
> > >> ft_defaults
> > What's the ft_* function you invoke to get the error 'undefined
> > function 'hom2six'? And what's the fieldtrip version you're using?
> > best,
> > Diego
> > > From: "Andrew Brooks" < andmib at gmail.com >
> > > To: "FieldTrip discussion list" < fieldtrip at science.ru.nl >
> > > Sent: Monday, 3 June, 2013 10:15:49 PM
> > > Subject: [FieldTrip] Private function problems
> > > Hello all,
> > > I followed the instructions on properly adding FieldTrip to the
> > > Matlab
> > > path file. However, I continue to run into errors involving
> > > private
> > > functions. In this case, I get the error 'undefined function
> > > 'hom2six'
> > > for input arguments of type 'double''.
> > > Does anybody have a suggestion as to why this is occurring?
> > > Thanks!
> > > Andrew
> > > _______________________________________________
> > > fieldtrip mailing list
> > > fieldtrip at donders.ru.nl
> > > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > --
> > PhD Student
> > Neuronal Oscillations Group
> > Donders Institute for Brain, Cognition and Behaviour
> > Centre for Cognitive Neuroimaging
> > Trigon, room 0.83
> > Kapittelweg 29
> > Radboud University Nijmegen
> > NL-6525 EN Nijmegen
> > The Netherlands
> > E-Mail: d.lozanosoldevilla at fcdonders.ru.nl
> > Tel: +31-(0)24-36-66274
> > Web: http://www.neuosc.com/
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
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From elizabeth.bock at mcgill.ca  Wed Jun  5 17:53:36 2013
From: elizabeth.bock at mcgill.ca (Elizabeth Anne Bock, Ms)
Date: Wed, 5 Jun 2013 15:53:36 +0000
Subject: [FieldTrip] Polhemus Patriot
In-Reply-To: <67D8C434-4D28-40C3-94A6-A95C86BD6B78@gmail.com>
References: <67D8C434-4D28-40C3-94A6-A95C86BD6B78@gmail.com>
Message-ID: <86D86365C4E767468A79EB52DFBFB46F051E242F@exmbx2010-8.campus.MCGILL.CA>

Hi Julian,
We have experienced this problem as well.  We solved it using the following guidelines:

No metal near the polhemus or any of the receivers/transmitters - you will need to move the setup around the room to find the perfect spot.
Use a wooden or plastic chair
Use plastic or cloth glasses/holder to attach the receiver to the subject

My system is sensitive to the proximity of the transmitter and the receiver.  I use two receivers, #1 is the stylus and #2 is secured to plastic glasses that the subject wears.  The transmitter is taped to the back of the chair.  If #2 and the transmitter are too close to each other (i.e. a short person or child), then the measurement are inaccurate.  You would have to experiment with different distances that give good results.

Hope this helps!
Beth


------------------------------------------------------------------------------------------

Elizabeth Bock / MEG System Engineer

McConnell Brain Imaging Centre / Montreal Neurological Institute

McGill University / 3801 University St. / Montreal, QC H3A 2B4


Office: 514.398.3706

MEG Lab: 514.398.6056

Mobile: 514.718.6342

________________________________
From: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl] on behalf of Julian Keil [julian.keil at gmail.com]
Sent: Monday, June 03, 2013 11:14 AM
To: FieldTrip discussion list
Subject: [FieldTrip] Polhemus Patriot

Dear FieldTrip-Users,

I have a not really FieldTrip-related question, but maybe one of you can help me anyways.
In our lab, we have a Polhemus Patriot 3D tracking system to acquire electrode positions.
Unfortunately, the recordings are severely distorted in the Z-axis (up-down).
After contacting the Polhemus Support, I got the information, that this is due to metal in the surroundings of the source which distorts the magnetic field.
I tried to get as far away from any metal as possible in our lab (~1.5 m to the walls and floor) but to no avail.

Now to my question: Has anyone any experience dealing with this? I'm quite puzzled by this as I know plenty of labs use Polhemus trackers, and I'm not sure if our lab is especially metal prone or if I'm missing something.

Thanks a lot for any help.

Julian

********************
Dr. Julian Keil

AG Multisensorische Integration
Psychiatrische Universitätsklinik
der Charité im St. Hedwig-Krankenhaus
Große Hamburger Straße 5-11, Raum E 307
10115 Berlin

Telefon: +49-30-2311-1879
Fax:        +49-30-2311-2209
http://psy-ccm.charite.de/forschung/bildgebung/ag_multisensorische_integration

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From julian.keil at gmail.com  Wed Jun  5 18:02:55 2013
From: julian.keil at gmail.com (Julian Keil)
Date: Wed, 5 Jun 2013 18:02:55 +0200
Subject: [FieldTrip] Polhemus Patriot
In-Reply-To: <86D86365C4E767468A79EB52DFBFB46F051E242F@exmbx2010-8.campus.MCGILL.CA>
References: <67D8C434-4D28-40C3-94A6-A95C86BD6B78@gmail.com>
	<86D86365C4E767468A79EB52DFBFB46F051E242F@exmbx2010-8.campus.MCGILL.CA>
Message-ID: <CC0BDDFC-CF83-47BE-8B49-C18B3D1EC701@gmail.com>

Dear all,

thank you very much for your input.
I'll have to experiment a bit more with the distance to the walls (which probably contain metal) and the chair.
Thank you also for the idea with the second sensor, I hadn't tried this before.

Best,

Julian

Am 05.06.2013 um 17:53 schrieb Elizabeth Anne Bock, Ms:

> Hi Julian,
> We have experienced this problem as well.  We solved it using the following guidelines:
> 
> No metal near the polhemus or any of the receivers/transmitters - you will need to move the setup around the room to find the perfect spot.
> Use a wooden or plastic chair
> Use plastic or cloth glasses/holder to attach the receiver to the subject
> 
> My system is sensitive to the proximity of the transmitter and the receiver.  I use two receivers, #1 is the stylus and #2 is secured to plastic glasses that the subject wears.  The transmitter is taped to the back of the chair.  If #2 and the transmitter are too close to each other (i.e. a short person or child), then the measurement are inaccurate.  You would have to experiment with different distances that give good results.
> 
> Hope this helps!
> Beth
> 
> ------------------------------------------------------------------------------------------
> Elizabeth Bock / MEG System Engineer
> McConnell Brain Imaging Centre / Montreal Neurological Institute
> McGill University / 3801 University St. / Montreal, QC H3A 2B4
> 
> Office: 514.398.3706 
> MEG Lab: 514.398.6056
> Mobile: 514.718.6342
> From: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl] on behalf of Julian Keil [julian.keil at gmail.com]
> Sent: Monday, June 03, 2013 11:14 AM
> To: FieldTrip discussion list
> Subject: [FieldTrip] Polhemus Patriot
> 
> Dear FieldTrip-Users,
> 
> I have a not really FieldTrip-related question, but maybe one of you can help me anyways.
> In our lab, we have a Polhemus Patriot 3D tracking system to acquire electrode positions.
> Unfortunately, the recordings are severely distorted in the Z-axis (up-down).
> After contacting the Polhemus Support, I got the information, that this is due to metal in the surroundings of the source which distorts the magnetic field.
> I tried to get as far away from any metal as possible in our lab (~1.5 m to the walls and floor) but to no avail.
> 
> Now to my question: Has anyone any experience dealing with this? I'm quite puzzled by this as I know plenty of labs use Polhemus trackers, and I'm not sure if our lab is especially metal prone or if I'm missing something.
> 
> Thanks a lot for any help.
> 
> Julian
> 
> ********************
> Dr. Julian Keil
> 
> AG Multisensorische Integration
> Psychiatrische Universitätsklinik
> der Charité im St. Hedwig-Krankenhaus
> Große Hamburger Straße 5-11, Raum E 307
> 10115 Berlin
> 
> Telefon: +49-30-2311-1879
> Fax:        +49-30-2311-2209 
> http://psy-ccm.charite.de/forschung/bildgebung/ag_multisensorische_integration
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From mje.mads at gmail.com  Thu Jun  6 09:16:01 2013
From: mje.mads at gmail.com (Mads Jensen)
Date: Thu, 06 Jun 2013 09:16:01 +0200
Subject: [FieldTrip] Extracting the time of a cluster
Message-ID: <51B03731.2080303@gmail.com>

Dear all,

I have made a statistics analysis on ERP data using 
ft_timelockstatistics and got a significant cluster I would like to know 
the time course of this cluster(i.e. when it starts and ends being 
significant) , is that possible?

I take to the cirange that is computed in the output for the cluster 
from ft_timelockstatistics be the upper and lower limit of the 
confidence interval, so the cluster.prop +/- the cirange gives the 
95%confidence intervals. Is that correct?

best wishes,
Mads


From jm.horschig at donders.ru.nl  Thu Jun  6 10:17:50 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Thu, 06 Jun 2013 10:17:50 +0200
Subject: [FieldTrip] Extracting the time of a cluster
In-Reply-To: <51B03731.2080303@gmail.com>
References: <51B03731.2080303@gmail.com>
Message-ID: <51B045AE.3010305@donders.ru.nl>

Hi Mads,

there is a stats.posclusterlabelmat and stats.negclusterlabelmat field, 
which contain the indices of all your clusters. You can use these 
indices and to index the period where your test shows some significant 
effect(e.g. for timelock.avg or timelock.time). See here for an example, 
which does not quite do what you want, but gets close
http://fieldtrip.fcdonders.nl/tutorial/cluster_permutation_timelock#plotting_the_results

And, yes, cirange defines the range of the confidence interval for that 
particular cluster, so pvalue - cirange gives the lower bound and pvalue 
+ cirange the upper bound. If your upper bound extends beyond the 
critical alpha-value, I would advise to use more randomizations.

Best,
Jörn

On 6/6/2013 9:16 AM, Mads Jensen wrote:
> Dear all,
>
> I have made a statistics analysis on ERP data using 
> ft_timelockstatistics and got a significant cluster I would like to 
> know the time course of this cluster(i.e. when it starts and ends 
> being significant) , is that possible?
>
> I take to the cirange that is computed in the output for the cluster 
> from ft_timelockstatistics be the upper and lower limit of the 
> confidence interval, so the cluster.prop +/- the cirange gives the 
> 95%confidence intervals. Is that correct?
>
> best wishes,
> Mads
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands



From mje.mads at gmail.com  Thu Jun  6 12:48:02 2013
From: mje.mads at gmail.com (Mads Jensen)
Date: Thu, 06 Jun 2013 12:48:02 +0200
Subject: [FieldTrip] Extracting the time of a cluster
In-Reply-To: <51B045AE.3010305@donders.ru.nl>
References: <51B03731.2080303@gmail.com> <51B045AE.3010305@donders.ru.nl>
Message-ID: <51B068E2.3010500@gmail.com>

Hi Jörn,

thanks for the swift and very useful reply.

best,
mads

On 06/06/13 10:17, "Jörn M. Horschig" wrote:
> Hi Mads,
>
> there is a stats.posclusterlabelmat and stats.negclusterlabelmat field,
> which contain the indices of all your clusters. You can use these
> indices and to index the period where your test shows some significant
> effect(e.g. for timelock.avg or timelock.time). See here for an example,
> which does not quite do what you want, but gets close
> http://fieldtrip.fcdonders.nl/tutorial/cluster_permutation_timelock#plotting_the_results
>
>
> And, yes, cirange defines the range of the confidence interval for that
> particular cluster, so pvalue - cirange gives the lower bound and pvalue
> + cirange the upper bound. If your upper bound extends beyond the
> critical alpha-value, I would advise to use more randomizations.
>
> Best,
> Jörn
>
> On 6/6/2013 9:16 AM, Mads Jensen wrote:
>> Dear all,
>>
>> I have made a statistics analysis on ERP data using
>> ft_timelockstatistics and got a significant cluster I would like to
>> know the time course of this cluster(i.e. when it starts and ends
>> being significant) , is that possible?
>>
>> I take to the cirange that is computed in the output for the cluster
>> from ft_timelockstatistics be the upper and lower limit of the
>> confidence interval, so the cluster.prop +/- the cirange gives the
>> 95%confidence intervals. Is that correct?
>>
>> best wishes,
>> Mads
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>


From antony.passaro at gmail.com  Thu Jun  6 15:59:22 2013
From: antony.passaro at gmail.com (Antony Passaro)
Date: Thu, 6 Jun 2013 09:59:22 -0400
Subject: [FieldTrip] Statistics for correlation across subjects using
	cluster analysis
Message-ID: <CAB8wAYRKGor5kv1KYB4z-z92AGyyFFgqTkpUgkZTYQVHefeVyw@mail.gmail.com>

Hi,

I came across an email in the mailing list archives from this time last
year when a user ( Ingrid ) was asking about using a statistical model with
a cluster analysis to correct for multiple comparisons based on performing
a correlation across trials (and/or subjects). Jan-mathijs replied saying
he had a copy of statfun_corr and statfun_glm but I don't see a copy of
either of those functions in the latest fieldtrip release. Would anyone be
so kind as to point my in the right directions to tackle this problem?

Thank you,
-Tony
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From andmib at gmail.com  Thu Jun  6 17:06:25 2013
From: andmib at gmail.com (Andrew Brooks)
Date: Thu, 6 Jun 2013 11:06:25 -0400
Subject: [FieldTrip] Private function problems
In-Reply-To: <2127428772.1387542.1370439554352.JavaMail.root@sculptor.zimbra.ru.nl>
References: <CALJPz69LZ_35=Z6YR5E6yRymDcZ3bBjaOpXOMyz3+CTWDjDNcw@mail.gmail.com>
	<2127428772.1387542.1370439554352.JavaMail.root@sculptor.zimbra.ru.nl>
Message-ID: <CALJPz68nhn6pRVcDaKSazaic76pw+OsZaowVtWsBmhkWora_kg@mail.gmail.com>

Diego,

Thank you, that was indeed the problem. I had moved the ft_omri_pipeline
script out of the /realtime/online_mri directory, which caused the problems.

Thanks,
Andrew


On Wed, Jun 5, 2013 at 9:39 AM, Lozano Soldevilla, D. (Diego) <
d.lozanosoldevilla at fcdonders.ru.nl> wrote:

> Hi Andrew,
>
> Could you please check inside your matlab path there's the realtime/mri
> directory where ft_omri_pipeline_nuisance.m function is located?
>
> Mine looks like this:
>
> '/home/electromag/dieloz/matlab/*fieldtrip-dev/realtime/online_mri/*'
>
> If it's there, you shouldn't have the private folder problem. Otherwise,
> add from the command window and tell me.
>
> best,
>
> Diego
>
> ------------------------------
>
> *From: *"Andrew Brooks" <andmib at gmail.com>
> *To: *"Diego Lozano" <diego.lozanosoldevilla at fcdonders.ru.nl>, "FieldTrip
> discussion list" <fieldtrip at science.ru.nl>
> *Sent: *Tuesday, 4 June, 2013 5:01:43 PM
> *Subject: *Re: [FieldTrip] Private function problems
>
>
> Hello Diego,
>
> I am using the example pipeline script from an earlier version of
> FieldTrip (ft_omri_pipeline_nuisance). The exact code that is throwing the
> error: curSixDof = hom2six(M).
>
> I did run the three lines of code to reset the default paths, add
> fieldtrip, and then ran ft_defaults. The version of FieldTrip I am using is
> 20130602.
>
> Thanks,
> Andrew
>
>
>
>
>
>
> On Mon, Jun 3, 2013 at 4:53 PM, Lozano Soldevilla, D. (Diego) <
> d.lozanosoldevilla at fcdonders.ru.nl> wrote:
>
>> Hi Andrew,
>>
>> Did you type the following?
>>
>> >> restoredefaultpath
>> >> addpath /fieldtripxxxx
>> >> ft_defaults
>>
>> What's the ft_* function you invoke to get the error 'undefined function
>> 'hom2six'? And what's the fieldtrip version you're using?
>>
>> best,
>>
>> Diego
>>
>> ------------------------------
>>
>> *From: *"Andrew Brooks" <andmib at gmail.com>
>> *To: *"FieldTrip discussion list" <fieldtrip at science.ru.nl>
>> *Sent: *Monday, 3 June, 2013 10:15:49 PM
>> *Subject: *[FieldTrip] Private function problems
>>
>>
>> Hello all,
>>
>> I followed the instructions on properly adding FieldTrip to the Matlab
>> path file. However, I continue to run into errors involving private
>> functions. In this case, I get the error 'undefined function 'hom2six' for
>> input arguments of type 'double''.
>>
>> Does anybody have a suggestion as to why this is occurring?
>>
>> Thanks!
>> Andrew
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>>
>>
>>
>> --
>> PhD Student
>> Neuronal Oscillations Group
>> Donders Institute for Brain, Cognition and Behaviour
>> Centre for Cognitive Neuroimaging
>> Trigon, room 0.83
>> Kapittelweg 29
>> Radboud University Nijmegen
>> NL-6525 EN Nijmegen
>> The Netherlands
>> E-Mail: d.lozanosoldevilla at fcdonders.ru.nl
>> Tel:     +31-(0)24-36-66274
>> Web:   http://www.neuosc.com/
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From jkamienk at gmail.com  Thu Jun  6 17:49:27 2013
From: jkamienk at gmail.com (Juan Kamienkowski)
Date: Thu, 6 Jun 2013 12:49:27 -0300
Subject: [FieldTrip] Oscillatory power normalization
In-Reply-To: <CAJB8axm9J3=ktKM16bVhjFiToBOcD1RrVbn+1xxD4HiiqP1_WA@mail.gmail.com>
References: <CAJB8axm9J3=ktKM16bVhjFiToBOcD1RrVbn+1xxD4HiiqP1_WA@mail.gmail.com>
Message-ID: <CAARjoQSOKzcBL8qF6LYLd4CYzCOfzOhYiSQbfwhVDBB16bu2dg@mail.gmail.com>

Hi everybody,

More than one year later we come up with the same questions. Does anybody
have suggestions on this topic?

Thanks a lot!

Best,

juan


On Fri, Mar 9, 2012 at 4:16 PM, Matt Mollison <matt.mollison at gmail.com>wrote:

> My questions essentially boil down to: what do people do for power
> normalization when assessing statistical differences?
>
> It gets more detailed below regarding examining event-related power
> changes relative to a baseline (within-subjects, comparing two conditions,
> stimulus onset = 0 ms). I didn't find much discussion of this on the list
> or the wiki. Any references for these issues would also be appreciated.
>
> (1) Does power data need to be baseline normalized for statistical tests
> comparing conditions? Normalization would put power on equal footing across
> all subjects, conditions, sensors, times, frequencies, etc., but it will
> surely affect power during the stimulus period in a particular way. If so,
> do the two (or more) conditions need to use the same baseline condition, or
> can each trial be normalized to its own pre-stim baseline period (a la
> ft_freqbaseline)? For either, it seems like you'd always need
> keeptrials='yes' in ft_freqanalysis. However, it does not seem to get
> normalized in the cluster_permutation_freq tutorial (within-subjects)---am
> I missing something?
>
> If we should normalize:
> (2) I've read a number of papers that Z-transform stimulus period power
> relative to pre-stim activity (subtract mean, divide by std) before doing
> statistics. I've also read a lot that don't mention baselines, or e.g. do a
> decibel [dB] transform. ft_freqbaseline does not have a Z-transform option.
> There is ft_preproc_standardize, but this seems to operate at a lower level
> than is usually recommended. Z-transforming seems like a good option, but
> how can I use it in the FT pipeline for within-subjects analyses
> (especially with keeptrials='no')? Alternatively, when should one use
> 'absolute', 'relative', or 'relchange'?
>
> Regarding choosing the baseline period:
> (3) It seems that the baseline period needs to precede stimulus onset by a
> sufficient amount of time so that the stimulus period doesn't bleed into
> the baseline; this time would be specific to both the frequency and either
> wavelet width or taper window length. For example, at 4 Hz with wavelet
> width=6 or a taper with 6 cycles per time window (t_ftimwin) the
> wavelet/window would be 1500 ms long, and the end of the baseline must
> precede stimulus onset by at least half this to keep them separate. At
> lower frequencies this could get quite unruly (e.g., 1 Hz would require
> ending 3000 ms before stimulus). Is this correct? Maybe that's why it's
> better to have a single separate baseline condition. Anyway, the
> timefrequencyanalysis tutorial seems to disregard this separation of
> baseline and stimulus activity (as have many papers I've read), so maybe
> I'm wrong about this being necessary.
>
> Thanks for your time,
> Matt Mollison
>
> --
> Univ. of Colorado at Boulder
> Dept. of Psychology and Neuroscience
> matthew.mollison at colorado.edu
> http://psych.colorado.edu/~mollison/
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
Juan E Kamienkowski
Laboratorio de Neurociencia Integrativa
Departamento de Fisica, FCEN-UBA
Ciudad Universitaria, Pabellon I
(1428) Buenos Aires, Argentina
Phone: (54-11) 4576 3300 (282)
Fax: (54-11) 4576 3357
http://www.neurociencia.df.uba.ar/
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From S.J.Johnston at swansea.ac.uk  Fri Jun  7 11:23:20 2013
From: S.J.Johnston at swansea.ac.uk (Steve Johnston)
Date: Fri, 7 Jun 2013 10:23:20 +0100
Subject: [FieldTrip] Bad channel correction problems and ICA
Message-ID: <55D211F2-5D76-43EE-B41A-EA05C8FFCE6F@swansea.ac.uk>

Dear fters

I've just started using ft and, although being able to run through a test run of eye movement data just fine, I'm now getting into the more detailed stuff and I'm hitting a snag that I hope you can help me with.

Specifically I'm struggling to get any real ICA results after using ft_channelrepair but not if I go through without it. 

Data was recorded on a biosemi 128 system and the trials are just eye movements that I want to identify via ICA (simple test). 

If I just run through the procedure of importing data, set markers, remove gross artifacts (keeping all channels, including 3 bad ones) and then run the ICA - I get lovely eye movement components appearing. However, now I want to do it 'properly' and replace the bad channels. Currently I do the following … (sorry, for completeness I included everything to be on the safe side).

%%
% Standard cfg for import
 
cfg                         = [];
cfg.trialdef.prestim        = .2;
cfg.trialdef.poststim       = 2;
cfg.trialdef.eventtype      = 'STATUS';
 
%%
%Load each dataset and examine for channels that are bad - starting with EOG Localiser.
 
cfg.dataset                 = [subjectdata.dir filesep subjectdata.artifactfile];
cfg.trialdef.eventvalue     = markers.artifact;
cfg                         = ft_definetrial(cfg);
 
cfg.demean                  = 'yes';
data                        = ft_preprocessing(cfg);
 
% After the above, run ChannelRepair after identifying bad channels.
%%
% Channel Replace - get nearest neighbours
cfg                      = [];
cfg.method               = 'distance'
cfg.layout               = 'biosemi128.lay';
cfg.neighbourdist        = 0.13;
[neighbours]             = ft_prepare_neighbours(cfg,data)
 
%% Interpolate and put into new data structure
cfg                      = [];
cfg.badchannel           = replace_channels;
cfg.layout               = 'biosemi128.lay';
cfg.method               = 'nearest';
cfg.neighbours           = neighbours;
cfg.neighbourdist        = 0.13;
artifact_cleandata       = ft_channelrepair(cfg,data)

% Visualise data for and mark uncorrectable artifacts.
cfg.viewmode                = 'vertical';
cfg.continuous              = 'yes';
cfg.blocksize               = 12;
cfg                         = ft_databrowser(cfg,artifact_cleandata)
 
%%
% Do artifact rejection (also redefine settings lost during re-cfg in artefact rejection) 
cfg.trialdef.prestim        = .2;
cfg.trialdef.poststim       = 2;
cfg.trialdef.eventtype      = 'STATUS';
cfg.artifact.reject         = 'complete';
cfg.channel                 = 'EEG';
cfg                         = ft_rejectartifact(cfg, artifact_cleandata);
trialdata                   = ft_preprocessing(cfg, artifact_cleandata);
 
%%
cfg                         = [];
comp                        = ft_componentanalysis(cfg, trialdata); 
cfg                         = [];
cfg.component               = [1:20]
cfg.layout                  = 'biosemi128.lay'
cfg.comment                 = 'no'
ft_topoplotIC(cfg,comp)

So, the big question is - why do I get nothing after doing the channel repair. I've been through it several times and that seems to be the step where everything goes wrong. I've looked at the data post re-interpolation and it looks good - for now I'm assuming I've missed something.

Thanks for any help

Steve 
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From jm.horschig at donders.ru.nl  Fri Jun  7 11:47:11 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Fri, 07 Jun 2013 11:47:11 +0200
Subject: [FieldTrip] Bad channel correction problems and ICA
In-Reply-To: <55D211F2-5D76-43EE-B41A-EA05C8FFCE6F@swansea.ac.uk>
References: <55D211F2-5D76-43EE-B41A-EA05C8FFCE6F@swansea.ac.uk>
Message-ID: <51B1AC1F.1010008@donders.ru.nl>

Hi Steve,

I'm not quite sure what you mean with getting nothing (nothing like, 
empty? or an error?) or not getting real ICA results (real in contrast 
to complex?). My hunge is that you need to take the rank of your data 
into account. Interpolating missing channels is done by combining 
already existing information, i.e. channels, to reconstruct a 
time-course at another spatial location, i.e. another channel. Since you 
do not add any new information by this (it's just a linear combination 
of your existing data matrix), you can leave that step out prior to 
doing ICA. Otherwise, you can set something like ica_cfg.XXXica.pca = 
rank(data.trial{1}), then afaik ft_componentanalysis will perform a PCA 
and essentially identify that the interpolated channels are a linear 
combination of other channels (ICA is then done of the PCA components). 
Both methods are equivalent, so you might as well just drop the 
interpolation and remove bad channels completely.

Best,
Jörn


On 6/7/2013 11:23 AM, Steve Johnston wrote:
> Dear fters
>
> I've just started using ft and, although being able to run through a 
> test run of eye movement data just fine, I'm now getting into the more 
> detailed stuff and I'm hitting a snag that I hope you can help me with.
>
> Specifically I'm struggling to get any real ICA results after using 
> ft_channelrepair but not if I go through without it.
>
> Data was recorded on a biosemi 128 system and the trials are just eye 
> movements that I want to identify via ICA (simple test).
>
> If I just run through the procedure of importing data, set markers, 
> remove gross artifacts (keeping all channels, including 3 bad ones) 
> and then run the ICA - I get lovely eye movement components appearing. 
> However, now I want to do it 'properly' and replace the bad channels. 
> Currently I do the following ... (sorry, for completeness I included 
> everything to be on the safe side).
>
> %%
> % Standard cfg for import
>
> cfg                         = [];
> cfg.trialdef.prestim       = .2;
> cfg.trialdef.poststim       = 2;
> cfg.trialdef.eventtype     = 'STATUS';
>
> %%
> %Load each dataset and examine for channels that are bad - starting 
> with EOG Localiser.
>
> cfg.dataset                 = [subjectdata.dir filesep 
> subjectdata.artifactfile];
> cfg.trialdef.eventvalue     = markers.artifact;
> cfg                         = ft_definetrial(cfg);
>
> cfg.demean                 = 'yes';
> data                       = ft_preprocessing(cfg);
>
> % After the above, run ChannelRepair after identifying bad channels.
> %%
> % Channel Replace - get nearest neighbours
> cfg                      = [];
> cfg.method               = 'distance'
> cfg.layout               = 'biosemi128.lay';
> cfg.neighbourdist        = 0.13;
> [neighbours]             = ft_prepare_neighbours(cfg,data)
>
> %% Interpolate and put into new data structure
> cfg                      = [];
> cfg.badchannel           = replace_channels;
> cfg.layout               = 'biosemi128.lay';
> cfg.method               = 'nearest';
> cfg.neighbours           = neighbours;
> cfg.neighbourdist        = 0.13;
> artifact_cleandata       = ft_channelrepair(cfg,data)
>
> % Visualise data for and mark uncorrectable artifacts.
> cfg.viewmode                = 'vertical';
> cfg.continuous              = 'yes';
> cfg.blocksize               = 12;
> cfg                         = ft_databrowser(cfg,artifact_cleandata)
>
> %%
> % Do artifact rejection (also redefine settings lost during re-cfg in 
> artefact rejection)
> cfg.trialdef.prestim        = .2;
> cfg.trialdef.poststim       = 2;
> cfg.trialdef.eventtype      = 'STATUS';
> cfg.artifact.reject         = 'complete';
> cfg.channel                 = 'EEG';
> cfg                         = ft_rejectartifact(cfg, artifact_cleandata);
> trialdata                   = ft_preprocessing(cfg, artifact_cleandata);
>
> %%
> cfg                         = [];
> comp                        = ft_componentanalysis(cfg, trialdata);
> cfg                         = [];
> cfg.component               = [1:20]
> cfg.layout                  = 'biosemi128.lay'
> cfg.comment                 = 'no'
> ft_topoplotIC(cfg,comp)
>
> So, the big question is - why do I get nothing after doing the channel 
> repair. I've been through it several times and that seems to be the 
> step where everything goes wrong. I've looked at the data post 
> re-interpolation and it looks good - for now I'm assuming I've missed 
> something.
>
> Thanks for any help
>
> Steve
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands

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From S.J.Johnston at swansea.ac.uk  Fri Jun  7 11:59:10 2013
From: S.J.Johnston at swansea.ac.uk (Steve Johnston)
Date: Fri, 7 Jun 2013 10:59:10 +0100
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 15
In-Reply-To: <mailman.405.1370598433.1298.fieldtrip@science.ru.nl>
References: <mailman.405.1370598433.1298.fieldtrip@science.ru.nl>
Message-ID: <49AE80C3-1CA6-402B-8819-3140FCFF7DC3@swansea.ac.uk>

Thanks, and sorry, that was a pretty poor description of the results by me. Yes, I am getting a result, but the error/warning is 

'Warning: Matrix is close to singular or badly scaled.
Results may be inaccurate. RCOND = 1.376132e-17. '

I figured that matrix singularity may have been the problem, although I hadn't appreciated that replacing only three channels could lead to it -  I was expecting that to result from more channel replacements or using a lot of electrodes to interpolate with.

Thanks a lot for the help, will try as you suggest

Steve



> 
> 
> ----------------------------------------------------------------------
> 
> Message: 1
> Date: Fri, 7 Jun 2013 10:23:20 +0100
> From: Steve Johnston <S.J.Johnston at swansea.ac.uk>
> To: "fieldtrip at science.ru.nl" <fieldtrip at science.ru.nl>
> Subject: [FieldTrip] Bad channel correction problems and ICA
> Message-ID: <55D211F2-5D76-43EE-B41A-EA05C8FFCE6F at swansea.ac.uk>
> Content-Type: text/plain; charset="windows-1252"
> 
> Dear fters
> 
> I've just started using ft and, although being able to run through a test run of eye movement data just fine, I'm now getting into the more detailed stuff and I'm hitting a snag that I hope you can help me with.
> 
> Specifically I'm struggling to get any real ICA results after using ft_channelrepair but not if I go through without it. 
> 
> Data was recorded on a biosemi 128 system and the trials are just eye movements that I want to identify via ICA (simple test). 
> 
> If I just run through the procedure of importing data, set markers, remove gross artifacts (keeping all channels, including 3 bad ones) and then run the ICA - I get lovely eye movement components appearing. However, now I want to do it 'properly' and replace the bad channels. Currently I do the following ? (sorry, for completeness I included everything to be on the safe side).
> 
> %%
> % Standard cfg for import
> 
> cfg                         = [];
> cfg.trialdef.prestim        = .2;
> cfg.trialdef.poststim       = 2;
> cfg.trialdef.eventtype      = 'STATUS';
> 
> %%
> %Load each dataset and examine for channels that are bad - starting with EOG Localiser.
> 
> cfg.dataset                 = [subjectdata.dir filesep subjectdata.artifactfile];
> cfg.trialdef.eventvalue     = markers.artifact;
> cfg                         = ft_definetrial(cfg);
> 
> cfg.demean                  = 'yes';
> data                        = ft_preprocessing(cfg);
> 
> % After the above, run ChannelRepair after identifying bad channels.
> %%
> % Channel Replace - get nearest neighbours
> cfg                      = [];
> cfg.method               = 'distance'
> cfg.layout               = 'biosemi128.lay';
> cfg.neighbourdist        = 0.13;
> [neighbours]             = ft_prepare_neighbours(cfg,data)
> 
> %% Interpolate and put into new data structure
> cfg                      = [];
> cfg.badchannel           = replace_channels;
> cfg.layout               = 'biosemi128.lay';
> cfg.method               = 'nearest';
> cfg.neighbours           = neighbours;
> cfg.neighbourdist        = 0.13;
> artifact_cleandata       = ft_channelrepair(cfg,data)
> 
> % Visualise data for and mark uncorrectable artifacts.
> cfg.viewmode                = 'vertical';
> cfg.continuous              = 'yes';
> cfg.blocksize               = 12;
> cfg                         = ft_databrowser(cfg,artifact_cleandata)
> 
> %%
> % Do artifact rejection (also redefine settings lost during re-cfg in artefact rejection) 
> cfg.trialdef.prestim        = .2;
> cfg.trialdef.poststim       = 2;
> cfg.trialdef.eventtype      = 'STATUS';
> cfg.artifact.reject         = 'complete';
> cfg.channel                 = 'EEG';
> cfg                         = ft_rejectartifact(cfg, artifact_cleandata);
> trialdata                   = ft_preprocessing(cfg, artifact_cleandata);
> 
> %%
> cfg                         = [];
> comp                        = ft_componentanalysis(cfg, trialdata); 
> cfg                         = [];
> cfg.component               = [1:20]
> cfg.layout                  = 'biosemi128.lay'
> cfg.comment                 = 'no'
> ft_topoplotIC(cfg,comp)
> 
> So, the big question is - why do I get nothing after doing the channel repair. I've been through it several times and that seems to be the step where everything goes wrong. I've looked at the data post re-interpolation and it looks good - for now I'm assuming I've missed something.
> 
> Thanks for any help
> 
> Steve 
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> 
> ------------------------------
> 
> Message: 2
> Date: Fri, 07 Jun 2013 11:47:11 +0200
> From: "J?rn M. Horschig" <jm.horschig at donders.ru.nl>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] Bad channel correction problems and ICA
> Message-ID: <51B1AC1F.1010008 at donders.ru.nl>
> Content-Type: text/plain; charset="iso-8859-1"; Format="flowed"
> 
> Hi Steve,
> 
> I'm not quite sure what you mean with getting nothing (nothing like, 
> empty? or an error?) or not getting real ICA results (real in contrast 
> to complex?). My hunge is that you need to take the rank of your data 
> into account. Interpolating missing channels is done by combining 
> already existing information, i.e. channels, to reconstruct a 
> time-course at another spatial location, i.e. another channel. Since you 
> do not add any new information by this (it's just a linear combination 
> of your existing data matrix), you can leave that step out prior to 
> doing ICA. Otherwise, you can set something like ica_cfg.XXXica.pca = 
> rank(data.trial{1}), then afaik ft_componentanalysis will perform a PCA 
> and essentially identify that the interpolated channels are a linear 
> combination of other channels (ICA is then done of the PCA components). 
> Both methods are equivalent, so you might as well just drop the 
> interpolation and remove bad channels completely.
> 
> Best,
> J?rn
> 
> 
> On 6/7/2013 11:23 AM, Steve Johnston wrote:
>> Dear fters
>> 
>> I've just started using ft and, although being able to run through a 
>> test run of eye movement data just fine, I'm now getting into the more 
>> detailed stuff and I'm hitting a snag that I hope you can help me with.
>> 
>> Specifically I'm struggling to get any real ICA results after using 
>> ft_channelrepair but not if I go through without it.
>> 
>> Data was recorded on a biosemi 128 system and the trials are just eye 
>> movements that I want to identify via ICA (simple test).
>> 
>> If I just run through the procedure of importing data, set markers, 
>> remove gross artifacts (keeping all channels, including 3 bad ones) 
>> and then run the ICA - I get lovely eye movement components appearing. 
>> However, now I want to do it 'properly' and replace the bad channels. 
>> Currently I do the following ... (sorry, for completeness I included 
>> everything to be on the safe side).
>> 
>> %%
>> % Standard cfg for import
>> 
>> cfg                         = [];
>> cfg.trialdef.prestim       = .2;
>> cfg.trialdef.poststim       = 2;
>> cfg.trialdef.eventtype     = 'STATUS';
>> 
>> %%
>> %Load each dataset and examine for channels that are bad - starting 
>> with EOG Localiser.
>> 
>> cfg.dataset                 = [subjectdata.dir filesep 
>> subjectdata.artifactfile];
>> cfg.trialdef.eventvalue     = markers.artifact;
>> cfg                         = ft_definetrial(cfg);
>> 
>> cfg.demean                 = 'yes';
>> data                       = ft_preprocessing(cfg);
>> 
>> % After the above, run ChannelRepair after identifying bad channels.
>> %%
>> % Channel Replace - get nearest neighbours
>> cfg                      = [];
>> cfg.method               = 'distance'
>> cfg.layout               = 'biosemi128.lay';
>> cfg.neighbourdist        = 0.13;
>> [neighbours]             = ft_prepare_neighbours(cfg,data)
>> 
>> %% Interpolate and put into new data structure
>> cfg                      = [];
>> cfg.badchannel           = replace_channels;
>> cfg.layout               = 'biosemi128.lay';
>> cfg.method               = 'nearest';
>> cfg.neighbours           = neighbours;
>> cfg.neighbourdist        = 0.13;
>> artifact_cleandata       = ft_channelrepair(cfg,data)
>> 
>> % Visualise data for and mark uncorrectable artifacts.
>> cfg.viewmode                = 'vertical';
>> cfg.continuous              = 'yes';
>> cfg.blocksize               = 12;
>> cfg                         = ft_databrowser(cfg,artifact_cleandata)
>> 
>> %%
>> % Do artifact rejection (also redefine settings lost during re-cfg in 
>> artefact rejection)
>> cfg.trialdef.prestim        = .2;
>> cfg.trialdef.poststim       = 2;
>> cfg.trialdef.eventtype      = 'STATUS';
>> cfg.artifact.reject         = 'complete';
>> cfg.channel                 = 'EEG';
>> cfg                         = ft_rejectartifact(cfg, artifact_cleandata);
>> trialdata                   = ft_preprocessing(cfg, artifact_cleandata);
>> 
>> %%
>> cfg                         = [];
>> comp                        = ft_componentanalysis(cfg, trialdata);
>> cfg                         = [];
>> cfg.component               = [1:20]
>> cfg.layout                  = 'biosemi128.lay'
>> cfg.comment                 = 'no'
>> ft_topoplotIC(cfg,comp)
>> 
>> So, the big question is - why do I get nothing after doing the channel 
>> repair. I've been through it several times and that seems to be the 
>> step where everything goes wrong. I've looked at the data post 
>> re-interpolation and it looks good - for now I'm assuming I've missed 
>> something.
>> 
>> Thanks for any help
>> 
>> Steve
>> 
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> 
> -- 
> J?rn M. Horschig
> PhD Student
> Donders Institute for Brain, Cognition and Behaviour
> Centre for Cognitive Neuroimaging
> Radboud University Nijmegen
> Neuronal Oscillations Group
> FieldTrip Development Team
> 
> P.O. Box 9101
> NL-6500 HB Nijmegen
> The Netherlands
> 
> Contact:
> E-Mail: jm.horschig at donders.ru.nl
> Tel:    +31-(0)24-36-68493
> Web: http://www.ru.nl/donders
> 
> Visiting address:
> Trigon, room 2.30
> Kapittelweg 29
> NL-6525 EN Nijmegen
> The Netherlands
> 
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> 
> ------------------------------
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> End of fieldtrip Digest, Vol 31, Issue 15
> *****************************************




From robince at gmail.com  Fri Jun  7 17:03:21 2013
From: robince at gmail.com (Robin)
Date: Fri, 7 Jun 2013 16:03:21 +0100
Subject: [FieldTrip] some of the requested samples occur twice
In-Reply-To: <51AC623A.1080207@donders.ru.nl>
References: <CALsWBNOxcuA=LCMONaGWObU4fdZ3+vskGGFcKdTZE4jGRoW47Q@mail.gmail.com>
	<51AC623A.1080207@donders.ru.nl>
Message-ID: <CALsWBNOe7BiBuBcHGeLOSAf0diPUzGdLg0E+M3wq9MnZ21t6FA@mail.gmail.com>

Hi Jörn,

Thanks.

I am already using negative trlpadding.

In this case I am trying to do the artifact detection on in memory trial
data, because I want to do it after denoise_pca. I am not sure if this is
correct but it seemed to me that denoise_pca is to correct physical
aquisition artifacts so it would be better to do it before trying to
identify biological artifacts that are a part of the recorded signal.

The code I am using is below. If you could point out how to add padding for
the ft*artifact* section so that it can work on in memory data it would be
great.

Thanks,

Robin

%% Automatic artifact rejection
% for each run
run_data = cell(1,length(sub.blocks));
trl_idx = 0;
for ri=1:length(sub.blocks)
    % extra data to allow padding in artifact detection
    filterpad = 0.2;
    prestim = 0.5;
    poststim = 0.6;
    % extract trials
    cfg = [];
    cfg.dataset = fullfile(sub.megDataPath, num2str(sub.blocks(ri)), 'c,rfDC');
    cfg.trialdef.eventtype  = 'TRIGGER';
    cfg.trialdef.eventvalue = 192;
    cfg.trialdef.prestim    = prestim + filterpad;
    cfg.trialdef.poststim   = poststim + filterpad;
    cfg.trialfun = 'ft_trialfun_general';
    cfg.continuous = 'yes';

    cfg = ft_definetrial(cfg);
    % overwrite unnecessary constant eventvalue
    % with trial number within this block
    cfg.trl(:,4) = (1:size(cfg.trl,1)) + trl_idx;
    trl_idx = trl_idx + size(cfg.trl,1);

    % remove jump artifact trials
    trlidx = ismember(cfg.trl(:,4), good_trials);
    cfg.trl = cfg.trl(trlidx, :);

    % load
    cfg.detrend = 'yes';
    % long padding for line noise removal
    cfg.dftfilter = 'yes';
    cfg.padding = 10;
    run_raw = ft_preprocessing(cfg);

    % apply denoise_pca
    cfg = [];
    if isfield(sub,'posthoc_badchannels')
        remove_chans = sub.posthoc_badchannels;
    else
        remove_chans = {};
    end
    cfg.channel = ft_channelselection([{'all'} remove_chans],
good_meg_channels);
    cfg.trials = find(ismember(run_raw.trialinfo, good_trials));
    run_clean = ft_denoise_pca(cfg, run_raw);

    % artifact detection
    cfg = [];
    cfg.continuous = 'no'; % some trials are excluded
    cfg.trl = run_clean.sampleinfo;
    cfg.artfctdef.muscle.trlpadding = -filterpad;
    cfg.artfctdef.muscle.cutoff     = 20;
    [cfg, artifact] = ft_artifact_muscle(cfg, run_clean);

    cfg.artfctdef.eog.trlpadding = -filterpad;
    cfg.artfctdef.eog.channel    = {'A150' 'A124'};
    cfg.artfctdef.eog.cutoff     = 5;
    [cfg, artifact] = ft_artifact_eog(cfg, run_clean);

    % reject artifacts
    cfg.artfctdef.reject = 'complete';
    run_artfree = ft_rejectartifact(cfg, run_clean);

    % reduce to the original window
    cfg = [];
    cfg.toilim = [-prestim poststim];
    run_artfree = ft_redefinetrial(cfg, run_artfree);

    run_data{ri} = run_artfree;end

On Mon, Jun 3, 2013 at 10:30 AM, "Jörn M. Horschig" <
jm.horschig at donders.ru.nl> wrote:

Hi Robin,
>
> it's not a bug that ft_fetch_data is not allowing for overlap. The
> function needs to be generic and eventually allow for fetching data
> extending over several trial segments. However, what should be the way to
> fetch  data that occurs twice, i.e. at the end of one trial and the
> beginning of another? If you have data with overlapping samples, it is not
> straight forward to define data from one trial as to be fetched and ignore
> the other. Since preprocessing options like filters are applied per trial
> segment, data will differ between trial segments if it overlaps. As there
> are a multitude of possibilities to deal with this and none of them is
> perfect (imho neither of them can even be called good), we decided to not
> allow for that.
>
> For your problem, however, imho you can define negative trial padding in
> the function call to ft_artifact_zvalue, which should effectively pad. Have
> you tried this rather than padding manually?
>
> Best,
> Jörn
>
>
> On 5/31/2013 6:14 PM, Robin wrote:
>
>> I have a problem in preprocessing where I am getting this error:
>>
>> """
>> some of the requested samples occur twice in the data
>>
>> Error in ft_artifact_zvalue (line 262)
>>        dat{trlop} = ft_fetch_data(data,        'header', hdr, 'begsample',
>>        trl(trlop,1)-fltpadding, 'endsample', trl(trlop,2)+fltpadding,
>>        'chanindx', sgnind, 'checkboundary', strcmp(cfg.continuous,'no
>> Error in ft_artifact_muscle (line 158)
>>      [tmpcfg, artifact] = ft_artifact_zvalue(tmpcfg, data);
>> """
>>
>> I think this is because I am manually adding some extra padding to the
>> trials so that the artifact filtering can use that padding (I am doing
>> the artifact filtering on data in memory which is output from
>> ft_denoise_pca). So in this case it is not a problem if consecutive
>> trials overlap a bit.
>>
>> I would therefore like to disable this error and wondered what is the
>> best way to do it. I am a bit confused because ft_artifact_zvalue
>> calls ft_fetch data with a "checkboundary" option which looks like it
>> might be what I want (and set correctly), but ft_fetch_data doesn't
>> seem to use that option. Instead it has an allowoverlap option.
>>
>> So for now I will manually add the allowoverlap option to the call in
>> ft_artifact_zvalue, but I wondered what checkboundary doesn't appear
>> in ft_fetch_data or if this might be a bug.
>>
>> Cheers
>>
>> Robin
>> ______________________________**_________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/**mailman/listinfo/fieldtrip<http://mailman.science.ru.nl/mailman/listinfo/fieldtrip>
>>
>
>
> --
> Jörn M. Horschig
> PhD Student
> Donders Institute for Brain, Cognition and Behaviour
> Centre for Cognitive Neuroimaging
> Radboud University Nijmegen
> Neuronal Oscillations Group
> FieldTrip Development Team
>
> P.O. Box 9101
> NL-6500 HB Nijmegen
> The Netherlands
>
> Contact:
> E-Mail: jm.horschig at donders.ru.nl
> Tel:    +31-(0)24-36-68493
> Web: http://www.ru.nl/donders
>
> Visiting address:
> Trigon, room 2.30
> Kapittelweg 29
> NL-6525 EN Nijmegen
> The Netherlands
>
> ______________________________**_________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/**mailman/listinfo/fieldtrip<http://mailman.science.ru.nl/mailman/listinfo/fieldtrip>
>
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From jkamienk at gmail.com  Fri Jun  7 19:02:22 2013
From: jkamienk at gmail.com (Juan Kamienkowski)
Date: Fri, 7 Jun 2013 14:02:22 -0300
Subject: [FieldTrip] Cluster-based permutation tests on single channel
Message-ID: <CAARjoQQ-HQ7ML+2krPKvVePZo_ckfZQ8iy=4M4P7M2bvVCr_bA@mail.gmail.com>

Hi,

I wanted to perform a Cluster-based permutation tests on time-frequency
data, on a single channel (one Independent Component). But the
ft_freqstatistics() function ask me for the "neighbours" field in the "cfg"
structure, although I set the cfg.minnbchan to 0. Is there a way to run
this analysis in a single channel?

Thanks a lot in advance!

Best,

Juan

-- 
Juan E Kamienkowski
Laboratorio de Neurociencia Integrativa
Departamento de Fisica, FCEN-UBA
Ciudad Universitaria, Pabellon I
(1428) Buenos Aires, Argentina
Phone: (54-11) 4576 3300 (282)
Fax: (54-11) 4576 3357
http://www.neurociencia.df.uba.ar/
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From Don.Rojas at ucdenver.edu  Fri Jun  7 23:37:10 2013
From: Don.Rojas at ucdenver.edu (Rojas, Don)
Date: Fri, 7 Jun 2013 15:37:10 -0600
Subject: [FieldTrip] Cluster-based permutation tests on single channel
In-Reply-To: <CAARjoQQ-HQ7ML+2krPKvVePZo_ckfZQ8iy=4M4P7M2bvVCr_bA@mail.gmail.com>
References: <CAARjoQQ-HQ7ML+2krPKvVePZo_ckfZQ8iy=4M4P7M2bvVCr_bA@mail.gmail.com>
Message-ID: <E59258AC-98B2-40CB-8986-D047C55F2BB2@ucdenver.edu>

Juan,

The neighbours field is for defining adjacent channels for multi-channel multiple comparison correction. I'm not sure if you've gotten a response on this yet, but you simply set the cfg.neighbours field to be empty in your call to ft_freqstatistics for using cluster based corrections within time-frequency space for single channels.

cfg.neighbours = [];

Best,

Don

On Jun 7, 2013, at 11:02 AM, Juan Kamienkowski <jkamienk at gmail.com<mailto:jkamienk at gmail.com>> wrote:

Hi,

I wanted to perform a Cluster-based permutation tests on time-frequency data, on a single channel (one Independent Component). But the ft_freqstatistics() function ask me for the "neighbours" field in the "cfg" structure, although I set the cfg.minnbchan to 0. Is there a way to run this analysis in a single channel?

Thanks a lot in advance!

Best,

Juan

--
Juan E Kamienkowski
Laboratorio de Neurociencia Integrativa
Departamento de Fisica, FCEN-UBA
Ciudad Universitaria, Pabellon I
(1428) Buenos Aires, Argentina
Phone: (54-11) 4576 3300 (282)
Fax: (54-11) 4576 3357
http://www.neurociencia.df.uba.ar/
_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
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From Don.Rojas at ucdenver.edu  Fri Jun  7 23:37:10 2013
From: Don.Rojas at ucdenver.edu (Rojas, Don)
Date: Fri, 7 Jun 2013 15:37:10 -0600
Subject: [FieldTrip] Cluster-based permutation tests on single channel
In-Reply-To: <CAARjoQQ-HQ7ML+2krPKvVePZo_ckfZQ8iy=4M4P7M2bvVCr_bA@mail.gmail.com>
References: <CAARjoQQ-HQ7ML+2krPKvVePZo_ckfZQ8iy=4M4P7M2bvVCr_bA@mail.gmail.com>
Message-ID: <E59258AC-98B2-40CB-8986-D047C55F2BB2@ucdenver.edu>

Juan,

The neighbours field is for defining adjacent channels for multi-channel multiple comparison correction. I'm not sure if you've gotten a response on this yet, but you simply set the cfg.neighbours field to be empty in your call to ft_freqstatistics for using cluster based corrections within time-frequency space for single channels.

cfg.neighbours = [];

Best,

Don

On Jun 7, 2013, at 11:02 AM, Juan Kamienkowski <jkamienk at gmail.com<mailto:jkamienk at gmail.com>> wrote:

Hi,

I wanted to perform a Cluster-based permutation tests on time-frequency data, on a single channel (one Independent Component). But the ft_freqstatistics() function ask me for the "neighbours" field in the "cfg" structure, although I set the cfg.minnbchan to 0. Is there a way to run this analysis in a single channel?

Thanks a lot in advance!

Best,

Juan

--
Juan E Kamienkowski
Laboratorio de Neurociencia Integrativa
Departamento de Fisica, FCEN-UBA
Ciudad Universitaria, Pabellon I
(1428) Buenos Aires, Argentina
Phone: (54-11) 4576 3300 (282)
Fax: (54-11) 4576 3357
http://www.neurociencia.df.uba.ar/
_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From haristz at gmail.com  Sat Jun  8 00:25:03 2013
From: haristz at gmail.com (Charidimos Tzagarakis)
Date: Fri, 7 Jun 2013 17:25:03 -0500
Subject: [FieldTrip] Using ft_rejectcomponent after PCA reduction
Message-ID: <CAFN2X+fGYE6maW7X6_eyGrbt7+wvWggv4xXvu6PhebXPgSpq5A@mail.gmail.com>

Dear Fieldtripverse,
I have been experimenting with using ICA for artifact correction and have
the following question:
Because of the relatively large number of channels vs samples I have, I use
the option to first reduce the dimensionality of the data with PCA (I have
248 MEG channels and I select, say 100 components, using the <for
cfg.method="runica"> cfg.numcomponent=100 and cfg.runica.pca=100 in the
call to ft_componentanalysis ).
So the "topo" matrix in the component output structure has dimensions
248x100 and the unmixing matrix has dimensions 100x248. I then use
something like "data = ft_rejectcomponent(cfg, comp,data)" to say reject 2
components cfg.component=[30 40] that contain ECG signal. Note: data here
is the original data I fed in the ft_componentanalysis function.
This is all pretty straightforward and as described in the Fieldtrip
tutorial (minus the PCA part) . I am however a bit worried by the
message:"removing 2 components
keeping 246 components" I get in the end. Should it not be "removing 2
components
keeping 98 components"? When I look in the code for ft_rejectcomponent, I
can see that if "hasdata" is True the message is calculated based on the
number of channels : fprintf('keeping %d components\n',
nchans-length(cfg.component));
On the other hand (as far as I can tell, not being an ICA expert) the
actual calculation for the removal of the desired components seems to
correctly use the components selected for removal :
  mixing = comp.topo(selcomp,:);
  unmixing = comp.unmixing(:,selcomp);
  tra = eye(length(selcomp)) - mixing(:, cfg.component)*unmixing(cfg.
component, :);
(I do note the comment under that snippet!:
 %I am not sure about this, but it gives comparable results to the ~hasdata
case
  %when comp contains non-orthogonal (=ica) topographies, and contains a
complete decomposition)

Further down the function code there are however more operations (eg remove
unused channels, remove unused components ) where I am less able to follow
things to make sure it is robust to non-square mixing and unmixing
matrices.

In summary, I wanted to ask if it is OK to use ft_rejectcomponent in this
way (ie without decomposing to the full number of ICA's and then using it
on the original data).
With Thanks and Best Wishes,
Haris

Charidimos [Haris] Tzagarakis MD, PhD, MRCPsych
University of Minnesota Dept of Neuroscience and Brain Sciences Center
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From mengtongxiao at gmail.com  Sun Jun  9 03:31:56 2013
From: mengtongxiao at gmail.com (=?GB2312?B?s8LRqQ==?=)
Date: Sun, 9 Jun 2013 09:31:56 +0800
Subject: [FieldTrip] what is the MNI-template be use to constructed
	sourcemodel , MNI125 or colin27?
Message-ID: <CADiddyX5sgXN2qhoVPCmDsm9sbjSCkUGp=sv6PKBy1UBF_+arw@mail.gmail.com>

Dear all
I use the model ( fieldtrip/template/sourcemodel )  doing source
reconstruction with beamformer .
I want to know  the template is matching  MNI125 or colin27 .

thanks.
best ,
xiao
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From nomeserio at gmail.com  Mon Jun 10 10:29:21 2013
From: nomeserio at gmail.com (Michele Barsotti)
Date: Mon, 10 Jun 2013 10:29:21 +0200
Subject: [FieldTrip] Downloading FieldTrip
Message-ID: <CAGZjeH4vNQBHOYe7kp6jQXjtcnRD=Wvic99OkjARq57h=hm1Vg@mail.gmail.com>

Dear FieldTrip users and staff,

  I'm dealing with the download of fieldtrip but everytime I try a download
error occurs with this message:
"...fieldtrip-aaaammgg.zip could not be saved, because the source file
could not be read. Try again later, or contact the server administrator."

Can someone help me?

Thank in advance

-- 
        -Michele-
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From joramvandriel at gmail.com  Mon Jun 10 16:09:25 2013
From: joramvandriel at gmail.com (Joram van Driel)
Date: Mon, 10 Jun 2013 16:09:25 +0200
Subject: [FieldTrip] BEM for MEG data
Message-ID: <CAKk__WVoQL5s4NwxPFpLJm7WRgFzwX1CxQk4k4WtRToormTEhA@mail.gmail.com>

Dear Fieldtrip users and developers,

I've been struggling quite some time now with the following problem.

We want to do source localization of MEG data from an experiment with 10
subjects. We collected MRIs using a Phillips scanner (UvA), and MEG data
using the Neuromag Elekta scanner (VUmc).

Using Neuromag software in Linux (seglab, xfit), I've created BEM forward
models based on coregistered MRIs (coregistration also done using the
Neuromag package), which result in .fif files (extension *bem-sol.fif).

Using these models we want to continue computing the leadfields and doing
source reconstruction in Matlab. For the latter, we have our own customized
codes; to get the leadfield, we need some step in between. I'm trying to
use fieldtrip functions for this but I get stuck. Here's what I do:

- Import the bem fif files using the mne toolbox (function:
mne_read_bem_surfaces).
- Attach the imported boundary data to a vol structure as follows:

[bem] = mne_read_bem_surfaces(bemfilz(subno).name);
vol                 = [];
vol.bnd.pnt         = bem.rr;
vol.bnd.tri         = double(bem.tris);
vol.unit            = 'mm';
vol.cfg.sourceunits = 'mm';
vol.type            = 'bemcp';
vol.cfg.numvertices = bem.np;

- Import the sensor locations using ft_read_sens and convert to mm using
ft_convert_units.
- Check whether the resulting structures are OK for leadfield computation
using ft_prepare_vol_sens. This results in an error "Unsupported volume
conductor model for MEG".

I also tried ft_read_vol, but for Neuromag this needs the meg-pd toolbox
which doesn't run on Windows (the Linux we use for the Neuromag software,
in turn, is a virtual machine and doesn't have Matlab).

Is there a way around this? Using BEM models for MEG data should in
principle be possible, but not using Fieldtrip?

Any suggestions would be much appreciated!
Thanks in advance,

Joram


-- 
Joram van Driel, MSc.
PhD student at the University of Amsterdam
Department of Psychology, Brain & Cognition
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From aaron.schurger at gmail.com  Mon Jun 10 18:11:23 2013
From: aaron.schurger at gmail.com (Aaron Schurger)
Date: Mon, 10 Jun 2013 18:11:23 +0200
Subject: [FieldTrip] What are the units output by ft_freqanalysis_tfr?
Message-ID: <CALeeyAQiEs-GM+40MU-O4QJQq29iO4XaK97_6utb2dLjpCqW_Q@mail.gmail.com>

Hi,
I am preparing figures for a paper, one of which is a time-frequency
plot of the output from ft_freqanalysis (using the tfr method). The
units of the data going in were on the order of 10e-11 or smaller (MEG
data), but the units on the color (power) axis of the plot are on the
order of 10e-1. Are the units normalized by default when you use
ft_freqanalysis? If not then what are the units? The help on these
functions was short on this kind of detail.
Thanks!
Aaron Schurger

--
Aaron Schurger, PhD
Post-doctoral researcher
INSERM U992 / NeuroSpin
CEA - Saclay, France
+33-1-69-08-66-47
aaron.schurger at gmail.com
http://www.unicog.org


From ivan.skelin at uleth.ca  Tue Jun 11 03:57:55 2013
From: ivan.skelin at uleth.ca (Skelin, Ivan)
Date: Mon, 10 Jun 2013 18:57:55 -0700
Subject: [FieldTrip] ncs file downsampling and further processing
Message-ID: <CA+pymnfq-RTSQuP_LQvZLGACQPetbdWeaT_zY81_cwA+hKATPw@mail.gmail.com>

Hi,

I am recording from the anesthetized rats using the two NeuroNexus silicone
probes with 8 tetrodes (32 channels) each and Neuralynx Cheetah system at
32556 Hz sampling frequency. I choose to analyze the .ncs files from 1/4 of
the channels or 1 channel per tetrode. Since the recordings took about 150
mins, the .ncs files are too bulky (0.5 GB) for the standard procedure that
the FieldTrip recommends for discontinuous data recorded using Neuralynx
system. More precisely, when I preprocess the channels separately and
subsequently run the ft_read_neuralynx_interp on them, I get the "out of
memory" error message (even when running it on only two .ncs files at the
time).

My question is if I can first downsample all the .csc files that I want to
analyze using the ft_spikedownsample, before I run the ft_read_neuralynx_interp
on them?



Thank you very much,

Ivan


-- 
Ivan Skelin, MD, PhD
Postdoctoral Fellow
Polaris Brain Dynamics Research Group
Canadian Centre for Behavioural Neuroscience
The University of Lethbridge
4401 University Dr W
Lethbridge, AB, T1K 3M4
Canada
http://lethbridgebraindynamics.com
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From explena at gmail.com  Tue Jun 11 09:48:34 2013
From: explena at gmail.com (Shen-Mou Hsu)
Date: Tue, 11 Jun 2013 15:48:34 +0800
Subject: [FieldTrip] ROC_based permutation test
Message-ID: <CAFg6g2eKEb-EmYa=BkWTwUVx20+oP92rs6u06w9m+Ehz5ni8qg@mail.gmail.com>

Dear all,

I was trying to perform signle-trial ROC-based permutation tests using the
statfun_roc. However I encountered two questions and wondered if anyone
could kindly shed some light on the issues. First, is it necessary to
perform baseline normalization for each trial before the tests? Second, an
error message returned stating "Error using roc. Too many input arguments.
Error using ft_statistics_montecarlo (line 223) could not determine the
parametric critical value for clustering", after running the following
script:

load (['t_RF_EpoRejDePow']); load (['t_RN_EpoRejDePow']);

cfg = [];
cfg.channel     = 'MEG';
cfg.latency     = [-0.35 0.55];
cfg.frequency   = [8 12];
cfg.parameter   = 'powspctrm';
cfg.method      = 'montecarlo';
cfg.statistic   = 'roc';
cfg.alpha       = 0.025;
cfg.tail = 0;
cfg.correctm    = 'cluster';
cfg.clusteralpha = 0.05;
% cfg.correcttail = 'prob';
cfg.clustertail = 0;
cfg.numrandomization = 1000;
cfg.minnbchan        = 2;
cfg_neighb.method    = 'distance';
cfg.neighbours       = ft_prepare_neighbours(cfg_neighb, t_RN_EpoRejDePow);
cfg.logtransform = 'yes';

design = [1*ones(1,size(t_RF_EpoRejDePow.powspctrm,1))
2*ones(1,size(t_RN_EpoRejDePow.powspctrm,1))]; % the first dimension of
these variable is the trial number.
cfg.design  = design;

P_ROC_t_RFvsRN = ft_freqstatistics(cfg,t_RF_EpoRejDePow,t_RN_EpoRejDePow);


Any help is greatly appreciated.

Best regards,

Shen-Mou Hsu
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From eelke.spaak at donders.ru.nl  Tue Jun 11 09:58:58 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Tue, 11 Jun 2013 09:58:58 +0200
Subject: [FieldTrip] What are the units output by ft_freqanalysis_tfr?
In-Reply-To: <CALeeyAQiEs-GM+40MU-O4QJQq29iO4XaK97_6utb2dLjpCqW_Q@mail.gmail.com>
References: <CALeeyAQiEs-GM+40MU-O4QJQq29iO4XaK97_6utb2dLjpCqW_Q@mail.gmail.com>
Message-ID: <CABPNLUrhOFUV30iN8SWGEbR_613nYXVa6=gFaE8toDB+rNwTwA@mail.gmail.com>

Hi Aaron,

How are you plotting the data? If you are using
ft_single/multi/topoplotTFR, did you use baseline correction
(cfg.baseline = 'yes' or [begin end])? If you use cfg.baselinetype =
'relative' or cfg.baselinetype = 'relchange', data plotted will
typically be on the order of 10e-1. It represents ratio vs baseline
('relative') or relative change vs baseline ('relchange').

If you did not specify baseline correction, then there is something
else going on. In any case, ft_freqanalysis does not explicitly
transform/normalize units; it does not care about them.

Best,
Eelke

On 10 June 2013 18:11, Aaron Schurger <aaron.schurger at gmail.com> wrote:
> Hi,
> I am preparing figures for a paper, one of which is a time-frequency
> plot of the output from ft_freqanalysis (using the tfr method). The
> units of the data going in were on the order of 10e-11 or smaller (MEG
> data), but the units on the color (power) axis of the plot are on the
> order of 10e-1. Are the units normalized by default when you use
> ft_freqanalysis? If not then what are the units? The help on these
> functions was short on this kind of detail.
> Thanks!
> Aaron Schurger
>
> --
> Aaron Schurger, PhD
> Post-doctoral researcher
> INSERM U992 / NeuroSpin
> CEA - Saclay, France
> +33-1-69-08-66-47
> aaron.schurger at gmail.com
> http://www.unicog.org
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From eelke.spaak at donders.ru.nl  Tue Jun 11 10:18:09 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Tue, 11 Jun 2013 10:18:09 +0200
Subject: [FieldTrip] ROC_based permutation test
In-Reply-To: <CAFg6g2eKEb-EmYa=BkWTwUVx20+oP92rs6u06w9m+Ehz5ni8qg@mail.gmail.com>
References: <CAFg6g2eKEb-EmYa=BkWTwUVx20+oP92rs6u06w9m+Ehz5ni8qg@mail.gmail.com>
Message-ID: <CABPNLUpB9DHCQCszf7WuujVgKT4g9Dp3GPNd19-O65b160y8NQ@mail.gmail.com>

Dear Shen-Mou Hsu,

With regards to your first question, I do not know the answer, so
someone else might help you there.

In response to your second question, regarding the error "could not
determine the parametric critical value for clustering", this is
caused by the value of cfg.clusterthreshold used. The default value
there is 'parametric', meaning that the statistics routine will ask
your 'statfun' to compute a parametric threshold for considering a
(time/frequency/channel)-voxel a cluster-member candidate. This can be
done by e.g. depsamplesT or indepsamplesT, as it is possible to
analytically compute a T value corresponding to p < 0.05. However, in
the case of the ROC statistic, no such parametric estimate can be
computed (or perhaps it can be in some way, I don't know, but at least
I know the FT implementation does not).

Fortunately, the statistics routines also allow you to use a
nonparametric threshold for cluster-member candidates, based on the
generated distribution of the test statistic under the null
hypothesis. To use this, simply specify cfg.clusterthreshold =
'nonparametric_individual' or cfg.clusterthreshold =
'nonparametric_common'. The difference between the two is that the
former computes a threshold per voxel, and the latter uses the same
threshold for all voxels. Which one is appropriate for you I don't
know. (Good reasons for using 'nonparametric_individual' might be a
strong variation of your test statistic with frequency. I know for a
fact this is the case with certain quantifications of phase-amplitude
coupling; these show much higher values in the low frequencies even
when computed on noise.)

Hope this helps.

Best,
Eelke

On 11 June 2013 09:48, Shen-Mou Hsu <explena at gmail.com> wrote:
> Dear all,
>
> I was trying to perform signle-trial ROC-based permutation tests using the
> statfun_roc. However I encountered two questions and wondered if anyone
> could kindly shed some light on the issues. First, is it necessary to
> perform baseline normalization for each trial before the tests? Second, an
> error message returned stating "Error using roc. Too many input arguments.
> Error using ft_statistics_montecarlo (line 223) could not determine the
> parametric critical value for clustering", after running the following
> script:
>
> load (['t_RF_EpoRejDePow']); load (['t_RN_EpoRejDePow']);
>
> cfg = [];
> cfg.channel     = 'MEG';
> cfg.latency     = [-0.35 0.55];
> cfg.frequency   = [8 12];
> cfg.parameter   = 'powspctrm';
> cfg.method      = 'montecarlo';
> cfg.statistic   = 'roc';
> cfg.alpha       = 0.025;
> cfg.tail = 0;
> cfg.correctm    = 'cluster';
> cfg.clusteralpha = 0.05;
> % cfg.correcttail = 'prob';
> cfg.clustertail = 0;
> cfg.numrandomization = 1000;
> cfg.minnbchan        = 2;
> cfg_neighb.method    = 'distance';
> cfg.neighbours       = ft_prepare_neighbours(cfg_neighb, t_RN_EpoRejDePow);
> cfg.logtransform = 'yes';
>
> design = [1*ones(1,size(t_RF_EpoRejDePow.powspctrm,1))
> 2*ones(1,size(t_RN_EpoRejDePow.powspctrm,1))]; % the first dimension of
> these variable is the trial number.
> cfg.design  = design;
>
> P_ROC_t_RFvsRN = ft_freqstatistics(cfg,t_RF_EpoRejDePow,t_RN_EpoRejDePow);
>
>
> Any help is greatly appreciated.
>
> Best regards,
>
> Shen-Mou Hsu
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From aaron.schurger at gmail.com  Tue Jun 11 11:00:03 2013
From: aaron.schurger at gmail.com (Aaron Schurger)
Date: Tue, 11 Jun 2013 11:00:03 +0200
Subject: [FieldTrip] What are the units output by ft_freqanalysis_tfr?
In-Reply-To: <CABPNLUrhOFUV30iN8SWGEbR_613nYXVa6=gFaE8toDB+rNwTwA@mail.gmail.com>
References: <CALeeyAQiEs-GM+40MU-O4QJQq29iO4XaK97_6utb2dLjpCqW_Q@mail.gmail.com>
	<CABPNLUrhOFUV30iN8SWGEbR_613nYXVa6=gFaE8toDB+rNwTwA@mail.gmail.com>
Message-ID: <CALeeyAS=CgYuqCh0cve-euKptDk2AGNyS8vLXZtQ987244zAaQ@mail.gmail.com>

Hi, Eelke,
Thanks for your reply. I think that might explain it. When I step
through my code, I see that the units are as expected for MEG in the
output from ft_freqanalysis, so it must be something after that stage
that is changing.
Thanks for the tip!
Best wishes,
Aaron

On Tue, Jun 11, 2013 at 9:58 AM, Eelke Spaak <eelke.spaak at donders.ru.nl> wrote:
> Hi Aaron,
>
> How are you plotting the data? If you are using
> ft_single/multi/topoplotTFR, did you use baseline correction
> (cfg.baseline = 'yes' or [begin end])? If you use cfg.baselinetype =
> 'relative' or cfg.baselinetype = 'relchange', data plotted will
> typically be on the order of 10e-1. It represents ratio vs baseline
> ('relative') or relative change vs baseline ('relchange').
>
> If you did not specify baseline correction, then there is something
> else going on. In any case, ft_freqanalysis does not explicitly
> transform/normalize units; it does not care about them.
>
> Best,
> Eelke
>
> On 10 June 2013 18:11, Aaron Schurger <aaron.schurger at gmail.com> wrote:
>> Hi,
>> I am preparing figures for a paper, one of which is a time-frequency
>> plot of the output from ft_freqanalysis (using the tfr method). The
>> units of the data going in were on the order of 10e-11 or smaller (MEG
>> data), but the units on the color (power) axis of the plot are on the
>> order of 10e-1. Are the units normalized by default when you use
>> ft_freqanalysis? If not then what are the units? The help on these
>> functions was short on this kind of detail.
>> Thanks!
>> Aaron Schurger
>>
>> --
>> Aaron Schurger, PhD
>> Post-doctoral researcher
>> INSERM U992 / NeuroSpin
>> CEA - Saclay, France
>> +33-1-69-08-66-47
>> aaron.schurger at gmail.com
>> http://www.unicog.org
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip



-- 
Aaron Schurger, PhD
Post-doctoral researcher
INSERM U992 / NeuroSpin
CEA - Saclay, France
+33-1-69-08-66-47
aaron.schurger at gmail.com
http://www.unicog.org


From nicolai at mersebak.dk  Wed Jun 12 15:44:00 2013
From: nicolai at mersebak.dk (Nicolai Mersebak)
Date: Wed, 12 Jun 2013 15:44:00 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
Message-ID: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>

Dear all,

I have a question concerning the usage of ft_sourcegrandaverage and
ft_sourcestatistics.

After using ft_sourceanalysis (method: MNE), I get spatio-temporal source
reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897
time points.

Now I would like to use the cluster-based permutation test on my source
reconstructed data. However it seems like ft_sourcegrandaverage and
ft_sourcestatistics
don't support source level time courses. E.g when I am using
ft_sourcegrandaverage
I am getting the following error:

Error in ft_sourcegrandaverage (line 158)
  dat(:,i) = tmp(:);

Looking into the code:

  for i=1:Nsubject

    tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter,
varargin{i}));

    dat(:,i) = tmp(:);

    tmp = getsubfield(varargin{i}, 'inside');

    inside(tmp,i) = 1;

  end

I see that "tmp" are getting the structure [N_sources x timepoints] from
source.avg.pow for one subject, where "dat" requires the structure
[N_sources x 1].

I seached the mailing list for similar issues and found this thread:

http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html

Since I am interested in using the temporal dimension in my statistics, I
would like to know if it is still not possible to use spatio-temporal
source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?

Or if any have succeeded in using the cluster-based permutation test on
source level also including the temporal dimension ?

Alternative I was thinking that I might could use ft_timelockstatistics,
where I substituted the channels with sources, e.g instead of having 64
channels, I would now have 4050 "channels".
If so I need to calculate a label structure and an appropriate neighbor
structure, which I guess is possible as I have all the 3D coordinates for
each source, e.g in leadfield.pos ?
I know this is a work around solution, but have anyone tried or have any
experience using such an approach ?

Best,

Nicolai
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From johanna.zumer at donders.ru.nl  Wed Jun 12 16:03:16 2013
From: johanna.zumer at donders.ru.nl (Johanna Zumer)
Date: Wed, 12 Jun 2013 16:03:16 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
 reconstruction data (MNE)
In-Reply-To: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
Message-ID: <CAL4kA6dpzj6xWWs0kXOeQ60WKVixowZtF6N4Kse0ubeoA=4vLQ@mail.gmail.com>

Dear Nicolai,

Good timing, I have just last week filed a 'bug' for this code modification
request:  http://bugzilla.fcdonders.nl/show_bug.cgi?id=2185
You may add yourself to the CC list if you wish to receive updates on the
bug progress.

I would be interested to hear if anyone else has thoughts on your
suggestion to 'hack' it as a timelock structure with channels.

Best,
Johanna


2013/6/12 Nicolai Mersebak <nicolai at mersebak.dk>

> Dear all,
>
> I have a question concerning the usage of ft_sourcegrandaverage and
> ft_sourcestatistics.
>
> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source
> reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897
> time points.
>
> Now I would like to use the cluster-based permutation test on my source
> reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics
> don't support source level time courses. E.g when I am using ft_sourcegrandaverage
> I am getting the following error:
>
> Error in ft_sourcegrandaverage (line 158)
>   dat(:,i) = tmp(:);
>
> Looking into the code:
>
>   for i=1:Nsubject
>
>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter,
> varargin{i}));
>
>     dat(:,i) = tmp(:);
>
>     tmp = getsubfield(varargin{i}, 'inside');
>
>     inside(tmp,i) = 1;
>
>   end
>
> I see that "tmp" are getting the structure [N_sources x timepoints] from
> source.avg.pow for one subject, where "dat" requires the structure
> [N_sources x 1].
>
> I seached the mailing list for similar issues and found this thread:
>
> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>
> Since I am interested in using the temporal dimension in my statistics, I
> would like to know if it is still not possible to use spatio-temporal
> source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
>
> Or if any have succeeded in using the cluster-based permutation test on
> source level also including the temporal dimension ?
>
> Alternative I was thinking that I might could use ft_timelockstatistics,
> where I substituted the channels with sources, e.g instead of having 64
> channels, I would now have 4050 "channels".
> If so I need to calculate a label structure and an appropriate neighbor
> structure, which I guess is possible as I have all the 3D coordinates for
> each source, e.g in leadfield.pos ?
> I know this is a work around solution, but have anyone tried or have any
> experience using such an approach ?
>
> Best,
>
> Nicolai
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From jm.horschig at donders.ru.nl  Wed Jun 12 16:20:29 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Wed, 12 Jun 2013 16:20:29 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
 reconstruction data (MNE)
In-Reply-To: <CAL4kA6dpzj6xWWs0kXOeQ60WKVixowZtF6N4Kse0ubeoA=4vLQ@mail.gmail.com>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
	<CAL4kA6dpzj6xWWs0kXOeQ60WKVixowZtF6N4Kse0ubeoA=4vLQ@mail.gmail.com>
Message-ID: <51B883AD.8020707@donders.ru.nl>

Heyho,

it might be a good way, at least I am doing it that way :) But think 
about defining neighbouring voxels beforehands (easily doable for a 
decent programmer, hard for a not-so-experienced programmer). In the 
upcoming months/years there will be something changing on the 
source-front anyway, so maybe it is best to use the temporary solution 
with ft_timelockXXX until then. Note that my personal opinion does not 
necessarily reflect the opinion of the core dev team ;)

Best,
Jörn

On 6/12/2013 4:03 PM, Johanna Zumer wrote:
> Dear Nicolai,
>
> Good timing, I have just last week filed a 'bug' for this code 
> modification request: http://bugzilla.fcdonders.nl/show_bug.cgi?id=2185
> You may add yourself to the CC list if you wish to receive updates on 
> the bug progress.
>
> I would be interested to hear if anyone else has thoughts on your 
> suggestion to 'hack' it as a timelock structure with channels.
>
> Best,
> Johanna
>
>
> 2013/6/12 Nicolai Mersebak <nicolai at mersebak.dk 
> <mailto:nicolai at mersebak.dk>>
>
>     Dear all,
>
>     I have a question concerning the usage of ft_sourcegrandaverage
>     and ft_sourcestatistics.
>
>     After using ft_sourceanalysis (method: MNE), I get spatio-temporal
>     source reconstructed data in source.avg.pow (4050 x 897): 4050
>     sources and 897 time points.
>
>     Now I would like to use the cluster-based permutation test on my
>     source reconstructed data. However it seems like
>     ft_sourcegrandaverage and ft_sourcestatistics don't support source
>     level time courses. E.g when I am using ft_sourcegrandaverage I am
>     getting the following error:
>
>     Error in ft_sourcegrandaverage (line 158)
>       dat(:,i) = tmp(:);
>
>     Looking into the code:
>
>     for i=1:Nsubject
>
>       tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter,
>     varargin{i}));
>
>       dat(:,i) = tmp(:);
>
>       tmp = getsubfield(varargin{i}, 'inside');
>
>       inside(tmp,i) = 1;
>
>     end
>
>
>     I see that "tmp" are getting the structure [N_sources x
>     timepoints] from source.avg.pow for one subject, where "dat"
>     requires the structure [N_sources x 1].
>
>     I seached the mailing list for similar issues and found this thread:
>
>     http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>
>     Since I am interested in using the temporal dimension in my
>     statistics, I would like to know if it is still not possible to
>     use spatio-temporal source reconstructed data in
>     ft_sourcestatistics and ft_sourcegrandaverage ?
>
>     Or if any have succeeded in using the cluster-based permutation
>     test on source level also including the temporal dimension ?
>
>     Alternative I was thinking that I might could use
>     ft_timelockstatistics, where I substituted the channels with
>     sources, e.g instead of having 64 channels, I would now have 4050
>     "channels".
>     If so I need to calculate a label structure and an appropriate
>     neighbor structure, which I guess is possible as I have all the 3D
>     coordinates for each source, e.g in leadfield.pos ?
>     I know this is a work around solution, but have anyone tried or
>     have any experience using such an approach ?
>
>     Best,
>
>     Nicolai
>
>
>     _______________________________________________
>     fieldtrip mailing list
>     fieldtrip at donders.ru.nl <mailto:fieldtrip at donders.ru.nl>
>     http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands

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From smoratti at psi.ucm.es  Wed Jun 12 17:44:59 2013
From: smoratti at psi.ucm.es (smoratti at psi.ucm.es)
Date: Wed, 12 Jun 2013 17:44:59 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
In-Reply-To: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
Message-ID: <05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>

Dear Nicolai,

Indeed I have used ft_timelockstatistics for minimum norm source data. The trick is to put the source level data into a ERF structure. Determining the neighbors of a source surface with vertices is not trivial. However I used tess_vertconn.m from the BrainStorm toolbox to get the connectivity matrix that tells you who is a neighbor. This you can feed into timelockstats.

Hope that helps,

Stephan

________________________________________________________
Stephan Moratti, PhD

see also: http://web.me.com/smoratti/

Universidad Complutense de Madrid
Facultad de Psicología
Departamento de Psicología Básica I
Campus de Somosaguas
28223 Pozuelo de Alarcón (Madrid)
Spain

and

Center for Biomedical Technology
Laboratory for Cognitive and Computational Neuroscience
Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
Campus Montegancedo
28223 Pozuelo de Alarcón (Madrid)
Spain


email: smoratti at psi.ucm.es
Tel.:    +34 679219982

El 12/06/2013, a las 15:44, Nicolai Mersebak escribió:

> Dear all,
> 
> I have a question concerning the usage of ft_sourcegrandaverage and ft_sourcestatistics. 
> 
> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897 time points. 
> 
> Now I would like to use the cluster-based permutation test on my source reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics don't support source level time courses. E.g when I am using ft_sourcegrandaverage I am getting the following error:
> 
> Error in ft_sourcegrandaverage (line 158)
>   dat(:,i) = tmp(:);
> 
> Looking into the code:
> 
>   for i=1:Nsubject
>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter, varargin{i}));
>     dat(:,i) = tmp(:);
>     tmp = getsubfield(varargin{i}, 'inside');
>     inside(tmp,i) = 1;
>   end
> 
> I see that "tmp" are getting the structure [N_sources x timepoints] from source.avg.pow for one subject, where "dat" requires the structure [N_sources x 1]. 
> 
> I seached the mailing list for similar issues and found this thread:
> 
> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
> 
> Since I am interested in using the temporal dimension in my statistics, I would like to know if it is still not possible to use spatio-temporal source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
> 
> Or if any have succeeded in using the cluster-based permutation test on source level also including the temporal dimension ? 
> 
> Alternative I was thinking that I might could use ft_timelockstatistics, where I substituted the channels with sources, e.g instead of having 64 channels, I would now have 4050 "channels". 
> If so I need to calculate a label structure and an appropriate neighbor structure, which I guess is possible as I have all the 3D coordinates for each source, e.g in leadfield.pos ?
> I know this is a work around solution, but have anyone tried or have any experience using such an approach ? 
> 
> Best,
> 
> Nicolai
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From jan.schoffelen at donders.ru.nl  Wed Jun 12 18:00:46 2013
From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen)
Date: Wed, 12 Jun 2013 18:00:46 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
In-Reply-To: <05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
	<05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>
Message-ID: <683ABC6E-9FC6-420A-9DCF-E54D6FC6A27E@donders.ru.nl>

An alternative would be to interpolate the cortical sheet to a 3D grid (where the grid is defined for each subject based on a warped template grid defined in a standard space), and then do clustering using a regular 3D spatial neighbourhood structure. The rationale being that two vertices on the sheet may appear as disconnected  (e.g. being on two sides of a sulcus) whereas, given the poor spatial resolution, they belong to the same spatial blob.

Best,
Jan-Mathijs

On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:

> Dear Nicolai,
> 
> Indeed I have used ft_timelockstatistics for minimum norm source data. The trick is to put the source level data into a ERF structure. Determining the neighbors of a source surface with vertices is not trivial. However I used tess_vertconn.m from the BrainStorm toolbox to get the connectivity matrix that tells you who is a neighbor. This you can feed into timelockstats.
> 
> Hope that helps,
> 
> Stephan
> 
> ________________________________________________________
> Stephan Moratti, PhD
> 
> see also: http://web.me.com/smoratti/
> 
> Universidad Complutense de Madrid
> Facultad de Psicología
> Departamento de Psicología Básica I
> Campus de Somosaguas
> 28223 Pozuelo de Alarcón (Madrid)
> Spain
> 
> and
> 
> Center for Biomedical Technology
> Laboratory for Cognitive and Computational Neuroscience
> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
> Campus Montegancedo
> 28223 Pozuelo de Alarcón (Madrid)
> Spain
> 
> 
> email: smoratti at psi.ucm.es
> Tel.:    +34 679219982
> 
> El 12/06/2013, a las 15:44, Nicolai Mersebak escribió:
> 
>> Dear all,
>> 
>> I have a question concerning the usage of ft_sourcegrandaverage and ft_sourcestatistics. 
>> 
>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897 time points. 
>> 
>> Now I would like to use the cluster-based permutation test on my source reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics don't support source level time courses. E.g when I am using ft_sourcegrandaverage I am getting the following error:
>> 
>> Error in ft_sourcegrandaverage (line 158)
>>   dat(:,i) = tmp(:);
>> 
>> Looking into the code:
>> 
>>   for i=1:Nsubject
>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter, varargin{i}));
>>     dat(:,i) = tmp(:);
>>     tmp = getsubfield(varargin{i}, 'inside');
>>     inside(tmp,i) = 1;
>>   end
>> 
>> I see that "tmp" are getting the structure [N_sources x timepoints] from source.avg.pow for one subject, where "dat" requires the structure [N_sources x 1]. 
>> 
>> I seached the mailing list for similar issues and found this thread:
>> 
>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>> 
>> Since I am interested in using the temporal dimension in my statistics, I would like to know if it is still not possible to use spatio-temporal source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
>> 
>> Or if any have succeeded in using the cluster-based permutation test on source level also including the temporal dimension ? 
>> 
>> Alternative I was thinking that I might could use ft_timelockstatistics, where I substituted the channels with sources, e.g instead of having 64 channels, I would now have 4050 "channels". 
>> If so I need to calculate a label structure and an appropriate neighbor structure, which I guess is possible as I have all the 3D coordinates for each source, e.g in leadfield.pos ?
>> I know this is a work around solution, but have anyone tried or have any experience using such an approach ? 
>> 
>> Best,
>> 
>> Nicolai
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

Jan-Mathijs Schoffelen, MD PhD 

Donders Institute for Brain, Cognition and Behaviour, 
Centre for Cognitive Neuroimaging,
Radboud University Nijmegen, The Netherlands

Max Planck Institute for Psycholinguistics,
Nijmegen, The Netherlands

J.Schoffelen at donders.ru.nl
Telephone: +31-24-3614793

http://www.hettaligebrein.nl

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From smoratti at psi.ucm.es  Wed Jun 12 18:58:40 2013
From: smoratti at psi.ucm.es (smoratti at psi.ucm.es)
Date: Wed, 12 Jun 2013 18:58:40 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
In-Reply-To: <683ABC6E-9FC6-420A-9DCF-E54D6FC6A27E@donders.ru.nl>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
	<05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>
	<683ABC6E-9FC6-420A-9DCF-E54D6FC6A27E@donders.ru.nl>
Message-ID: <8D369E00-7FF3-4CC7-8B91-A55AD9ECE385@psi.ucm.es>


I think Jan.Mathijs alternative suggestion is quite attractive. With the neighbors on a cortical sheet I also had the problems that sometimes the vertices do not have the same distance and then clustering may be biased to smaller or bigger clusters as the number of neighbors does not guarantee same cluster sizes. With the interpolation onto a 3D grid, you won't have that problem.

best,

Stephan


________________________________________________________
Stephan Moratti, PhD

see also: http://web.me.com/smoratti/

Universidad Complutense de Madrid
Facultad de Psicología
Departamento de Psicología Básica I
Campus de Somosaguas
28223 Pozuelo de Alarcón (Madrid)
Spain

and

Center for Biomedical Technology
Laboratory for Cognitive and Computational Neuroscience
Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
Campus Montegancedo
28223 Pozuelo de Alarcón (Madrid)
Spain


email: smoratti at psi.ucm.es
Tel.:    +34 679219982

El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribió:

> An alternative would be to interpolate the cortical sheet to a 3D grid (where the grid is defined for each subject based on a warped template grid defined in a standard space), and then do clustering using a regular 3D spatial neighbourhood structure. The rationale being that two vertices on the sheet may appear as disconnected  (e.g. being on two sides of a sulcus) whereas, given the poor spatial resolution, they belong to the same spatial blob.
> 
> Best,
> Jan-Mathijs
> 
> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
> 
>> Dear Nicolai,
>> 
>> Indeed I have used ft_timelockstatistics for minimum norm source data. The trick is to put the source level data into a ERF structure. Determining the neighbors of a source surface with vertices is not trivial. However I used tess_vertconn.m from the BrainStorm toolbox to get the connectivity matrix that tells you who is a neighbor. This you can feed into timelockstats.
>> 
>> Hope that helps,
>> 
>> Stephan
>> 
>> ________________________________________________________
>> Stephan Moratti, PhD
>> 
>> see also: http://web.me.com/smoratti/
>> 
>> Universidad Complutense de Madrid
>> Facultad de Psicología
>> Departamento de Psicología Básica I
>> Campus de Somosaguas
>> 28223 Pozuelo de Alarcón (Madrid)
>> Spain
>> 
>> and
>> 
>> Center for Biomedical Technology
>> Laboratory for Cognitive and Computational Neuroscience
>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>> Campus Montegancedo
>> 28223 Pozuelo de Alarcón (Madrid)
>> Spain
>> 
>> 
>> email: smoratti at psi.ucm.es
>> Tel.:    +34 679219982
>> 
>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribió:
>> 
>>> Dear all,
>>> 
>>> I have a question concerning the usage of ft_sourcegrandaverage and ft_sourcestatistics. 
>>> 
>>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897 time points. 
>>> 
>>> Now I would like to use the cluster-based permutation test on my source reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics don't support source level time courses. E.g when I am using ft_sourcegrandaverage I am getting the following error:
>>> 
>>> Error in ft_sourcegrandaverage (line 158)
>>>   dat(:,i) = tmp(:);
>>> 
>>> Looking into the code:
>>> 
>>>   for i=1:Nsubject
>>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter, varargin{i}));
>>>     dat(:,i) = tmp(:);
>>>     tmp = getsubfield(varargin{i}, 'inside');
>>>     inside(tmp,i) = 1;
>>>   end
>>> 
>>> I see that "tmp" are getting the structure [N_sources x timepoints] from source.avg.pow for one subject, where "dat" requires the structure [N_sources x 1]. 
>>> 
>>> I seached the mailing list for similar issues and found this thread:
>>> 
>>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>>> 
>>> Since I am interested in using the temporal dimension in my statistics, I would like to know if it is still not possible to use spatio-temporal source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
>>> 
>>> Or if any have succeeded in using the cluster-based permutation test on source level also including the temporal dimension ? 
>>> 
>>> Alternative I was thinking that I might could use ft_timelockstatistics, where I substituted the channels with sources, e.g instead of having 64 channels, I would now have 4050 "channels". 
>>> If so I need to calculate a label structure and an appropriate neighbor structure, which I guess is possible as I have all the 3D coordinates for each source, e.g in leadfield.pos ?
>>> I know this is a work around solution, but have anyone tried or have any experience using such an approach ? 
>>> 
>>> Best,
>>> 
>>> Nicolai
>>> 
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> Jan-Mathijs Schoffelen, MD PhD 
> 
> Donders Institute for Brain, Cognition and Behaviour, 
> Centre for Cognitive Neuroimaging,
> Radboud University Nijmegen, The Netherlands
> 
> Max Planck Institute for Psycholinguistics,
> Nijmegen, The Netherlands
> 
> J.Schoffelen at donders.ru.nl
> Telephone: +31-24-3614793
> 
> http://www.hettaligebrein.nl
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From mengtongxiao at gmail.com  Thu Jun 13 10:10:14 2013
From: mengtongxiao at gmail.com (=?GB2312?B?s8LRqQ==?=)
Date: Thu, 13 Jun 2013 16:10:14 +0800
Subject: [FieldTrip] PDC
Message-ID: <CADiddyUvconnj1o5n+=RYKyDE0LsFsH7_Eg0re0+a5D-2oz9Xw@mail.gmail.com>

Dear  all

I want to use compute  PDC,
I want to  Konw   when I got the chan*chan*freq，
Dose the information flow from row (chan) to column(chan)?

best,
xiao

   
   
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From jan.schoffelen at donders.ru.nl  Thu Jun 13 10:20:48 2013
From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen)
Date: Thu, 13 Jun 2013 10:20:48 +0200
Subject: [FieldTrip] PDC
In-Reply-To: <CADiddyUvconnj1o5n+=RYKyDE0LsFsH7_Eg0re0+a5D-2oz9Xw@mail.gmail.com>
References: <CADiddyUvconnj1o5n+=RYKyDE0LsFsH7_Eg0re0+a5D-2oz9Xw@mail.gmail.com>
Message-ID: <756060F3-17D2-420B-B55F-FFE7671B067B@donders.ru.nl>

Hi Xiao,

this would be from row to column.

Best,
Jan-Mathijs

On Jun 13, 2013, at 10:10 AM, 陈雪 wrote:

> Dear  all
> 
> I want to use compute  PDC,
> I want to  Konw   when I got the chan*chan*freq，
> Dose the information flow from row (chan) to column(chan)?
> 
> best,
> xiao 
> 	
> 	
> 	
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

Jan-Mathijs Schoffelen, MD PhD 

Donders Institute for Brain, Cognition and Behaviour, 
Centre for Cognitive Neuroimaging,
Radboud University Nijmegen, The Netherlands

Max Planck Institute for Psycholinguistics,
Nijmegen, The Netherlands

J.Schoffelen at donders.ru.nl
Telephone: +31-24-3614793

http://www.hettaligebrein.nl

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From explena at gmail.com  Thu Jun 13 11:15:11 2013
From: explena at gmail.com (Shen-Mou Hsu)
Date: Thu, 13 Jun 2013 17:15:11 +0800
Subject: [FieldTrip] ROC_based permutation test
In-Reply-To: <CABPNLUpB9DHCQCszf7WuujVgKT4g9Dp3GPNd19-O65b160y8NQ@mail.gmail.com>
References: <CAFg6g2eKEb-EmYa=BkWTwUVx20+oP92rs6u06w9m+Ehz5ni8qg@mail.gmail.com>
	<CABPNLUpB9DHCQCszf7WuujVgKT4g9Dp3GPNd19-O65b160y8NQ@mail.gmail.com>
Message-ID: <CAFg6g2ewK2N54R0coEbShh1AxUrCkcL6gAgnEskEA5_sAa=h-A@mail.gmail.com>

Dear Eelke,

Many thanks for your helpful and detailed answers. I think that there is an
error in the documentation about the configuration option for performing
ROC analysis. The correct one should be cfg.statistic = 'ft_statfun_roc'.
Otherwise, it will call the matlab built-in ROC function.

Meanwhile, just to clarify my concept about the ROC_based permutation
tests. In the initial stage, does the test calculate whether for every
sample, the area under ROC curve is significant from 0.5. In this sense,
should I specify cfg.clusteralpha = 0.5?

Best regards,

Shen-Mou Hsu


On Tue, Jun 11, 2013 at 4:18 PM, Eelke Spaak <eelke.spaak at donders.ru.nl>wrote:

> Dear Shen-Mou Hsu,
>
> With regards to your first question, I do not know the answer, so
> someone else might help you there.
>
> In response to your second question, regarding the error "could not
> determine the parametric critical value for clustering", this is
> caused by the value of cfg.clusterthreshold used. The default value
> there is 'parametric', meaning that the statistics routine will ask
> your 'statfun' to compute a parametric threshold for considering a
> (time/frequency/channel)-voxel a cluster-member candidate. This can be
> done by e.g. depsamplesT or indepsamplesT, as it is possible to
> analytically compute a T value corresponding to p < 0.05. However, in
> the case of the ROC statistic, no such parametric estimate can be
> computed (or perhaps it can be in some way, I don't know, but at least
> I know the FT implementation does not).
>
> Fortunately, the statistics routines also allow you to use a
> nonparametric threshold for cluster-member candidates, based on the
> generated distribution of the test statistic under the null
> hypothesis. To use this, simply specify cfg.clusterthreshold =
> 'nonparametric_individual' or cfg.clusterthreshold =
> 'nonparametric_common'. The difference between the two is that the
> former computes a threshold per voxel, and the latter uses the same
> threshold for all voxels. Which one is appropriate for you I don't
> know. (Good reasons for using 'nonparametric_individual' might be a
> strong variation of your test statistic with frequency. I know for a
> fact this is the case with certain quantifications of phase-amplitude
> coupling; these show much higher values in the low frequencies even
> when computed on noise.)
>
> Hope this helps.
>
> Best,
> Eelke
>
> On 11 June 2013 09:48, Shen-Mou Hsu <explena at gmail.com> wrote:
> > Dear all,
> >
> > I was trying to perform signle-trial ROC-based permutation tests using
> the
> > statfun_roc. However I encountered two questions and wondered if anyone
> > could kindly shed some light on the issues. First, is it necessary to
> > perform baseline normalization for each trial before the tests? Second,
> an
> > error message returned stating "Error using roc. Too many input
> arguments.
> > Error using ft_statistics_montecarlo (line 223) could not determine the
> > parametric critical value for clustering", after running the following
> > script:
> >
> > load (['t_RF_EpoRejDePow']); load (['t_RN_EpoRejDePow']);
> >
> > cfg = [];
> > cfg.channel     = 'MEG';
> > cfg.latency     = [-0.35 0.55];
> > cfg.frequency   = [8 12];
> > cfg.parameter   = 'powspctrm';
> > cfg.method      = 'montecarlo';
> > cfg.statistic   = 'roc';
> > cfg.alpha       = 0.025;
> > cfg.tail = 0;
> > cfg.correctm    = 'cluster';
> > cfg.clusteralpha = 0.05;
> > % cfg.correcttail = 'prob';
> > cfg.clustertail = 0;
> > cfg.numrandomization = 1000;
> > cfg.minnbchan        = 2;
> > cfg_neighb.method    = 'distance';
> > cfg.neighbours       = ft_prepare_neighbours(cfg_neighb,
> t_RN_EpoRejDePow);
> > cfg.logtransform = 'yes';
> >
> > design = [1*ones(1,size(t_RF_EpoRejDePow.powspctrm,1))
> > 2*ones(1,size(t_RN_EpoRejDePow.powspctrm,1))]; % the first dimension of
> > these variable is the trial number.
> > cfg.design  = design;
> >
> > P_ROC_t_RFvsRN =
> ft_freqstatistics(cfg,t_RF_EpoRejDePow,t_RN_EpoRejDePow);
> >
> >
> > Any help is greatly appreciated.
> >
> > Best regards,
> >
> > Shen-Mou Hsu
> >
> >
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From nicolai at mersebak.dk  Thu Jun 13 12:04:34 2013
From: nicolai at mersebak.dk (Nicolai Mersebak)
Date: Thu, 13 Jun 2013 12:04:34 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
In-Reply-To: <8D369E00-7FF3-4CC7-8B91-A55AD9ECE385@psi.ucm.es>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
	<05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>
	<683ABC6E-9FC6-420A-9DCF-E54D6FC6A27E@donders.ru.nl>
	<8D369E00-7FF3-4CC7-8B91-A55AD9ECE385@psi.ucm.es>
Message-ID: <6F3697BB-194F-422F-A1BF-EBBB132F805B@mersebak.dk>

Thanks to all of you for your comments and ideas - they are very helpful! 

I ( off course :) ) have some follow up questions. 

I have created an ERP structure for my MNE source, so the only think which I need and that is not straight forward is the neighbour structure. 

I am using the standard bem template (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model and use the following code to get a grid for all subjects as I don't have any subject specific information regarding the anatomy. 

cfg = [];
cfg.grid.xgrid  = -100:10:100;
cfg.grid.ygrid  = -100:10:100;
cfg.grid.zgrid  = -100:10:100;
cfg.grid.tight  = 'yes';
cfg.grid.unit   = hdm.unit; % unit: mm
cfg.vol        = hdm;
grid  = ft_prepare_sourcemodel(cfg);


@Jan-Mathijs and Stephan: I guess making a subject specific grid based on a warped template requires anatomic information for each subject, e.g. a MRI image like this tutorial shows:
http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B

The final grid output in the tutorial - does it have this 3D grid which can be used as a neighbour structure ? 

I am not sure how to go from my cortical sheet [vertices x coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
 
A second thing I would like to know is, if any of you have tried to use an atlas (e.g ALL template atlas) where the regions now are channels in the permutation test? Going from source points to atlas regions can be done through ft_sourcestatistics, but I am still interested in keeping the temporal dimension. The reason to use atlas regions instead of source points is to decrease the computation time. 

Best,

Nicolai


Den 12/06/2013 kl. 18.58 skrev "smoratti at psi.ucm.es" <smoratti at psi.ucm.es>:

> 
> I think Jan.Mathijs alternative suggestion is quite attractive. With the neighbors on a cortical sheet I also had the problems that sometimes the vertices do not have the same distance and then clustering may be biased to smaller or bigger clusters as the number of neighbors does not guarantee same cluster sizes. With the interpolation onto a 3D grid, you won't have that problem.
> 
> best,
> 
> Stephan
> 
> 
> ________________________________________________________
> Stephan Moratti, PhD
> 
> see also: http://web.me.com/smoratti/
> 
> Universidad Complutense de Madrid
> Facultad de Psicología
> Departamento de Psicología Básica I
> Campus de Somosaguas
> 28223 Pozuelo de Alarcón (Madrid)
> Spain
> 
> and
> 
> Center for Biomedical Technology
> Laboratory for Cognitive and Computational Neuroscience
> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
> Campus Montegancedo
> 28223 Pozuelo de Alarcón (Madrid)
> Spain
> 
> 
> email: smoratti at psi.ucm.es
> Tel.:    +34 679219982
> 
> El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribió:
> 
>> An alternative would be to interpolate the cortical sheet to a 3D grid (where the grid is defined for each subject based on a warped template grid defined in a standard space), and then do clustering using a regular 3D spatial neighbourhood structure. The rationale being that two vertices on the sheet may appear as disconnected  (e.g. being on two sides of a sulcus) whereas, given the poor spatial resolution, they belong to the same spatial blob.
>> 
>> Best,
>> Jan-Mathijs
>> 
>> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
>> 
>>> Dear Nicolai,
>>> 
>>> Indeed I have used ft_timelockstatistics for minimum norm source data. The trick is to put the source level data into a ERF structure. Determining the neighbors of a source surface with vertices is not trivial. However I used tess_vertconn.m from the BrainStorm toolbox to get the connectivity matrix that tells you who is a neighbor. This you can feed into timelockstats.
>>> 
>>> Hope that helps,
>>> 
>>> Stephan
>>> 
>>> ________________________________________________________
>>> Stephan Moratti, PhD
>>> 
>>> see also: http://web.me.com/smoratti/
>>> 
>>> Universidad Complutense de Madrid
>>> Facultad de Psicología
>>> Departamento de Psicología Básica I
>>> Campus de Somosaguas
>>> 28223 Pozuelo de Alarcón (Madrid)
>>> Spain
>>> 
>>> and
>>> 
>>> Center for Biomedical Technology
>>> Laboratory for Cognitive and Computational Neuroscience
>>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>>> Campus Montegancedo
>>> 28223 Pozuelo de Alarcón (Madrid)
>>> Spain
>>> 
>>> 
>>> email: smoratti at psi.ucm.es
>>> Tel.:    +34 679219982
>>> 
>>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribió:
>>> 
>>>> Dear all,
>>>> 
>>>> I have a question concerning the usage of ft_sourcegrandaverage and ft_sourcestatistics. 
>>>> 
>>>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897 time points. 
>>>> 
>>>> Now I would like to use the cluster-based permutation test on my source reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics don't support source level time courses. E.g when I am using ft_sourcegrandaverage I am getting the following error:
>>>> 
>>>> Error in ft_sourcegrandaverage (line 158)
>>>>   dat(:,i) = tmp(:);
>>>> 
>>>> Looking into the code:
>>>> 
>>>>   for i=1:Nsubject
>>>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter, varargin{i}));
>>>>     dat(:,i) = tmp(:);
>>>>     tmp = getsubfield(varargin{i}, 'inside');
>>>>     inside(tmp,i) = 1;
>>>>   end
>>>> 
>>>> I see that "tmp" are getting the structure [N_sources x timepoints] from source.avg.pow for one subject, where "dat" requires the structure [N_sources x 1]. 
>>>> 
>>>> I seached the mailing list for similar issues and found this thread:
>>>> 
>>>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>>>> 
>>>> Since I am interested in using the temporal dimension in my statistics, I would like to know if it is still not possible to use spatio-temporal source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
>>>> 
>>>> Or if any have succeeded in using the cluster-based permutation test on source level also including the temporal dimension ? 
>>>> 
>>>> Alternative I was thinking that I might could use ft_timelockstatistics, where I substituted the channels with sources, e.g instead of having 64 channels, I would now have 4050 "channels". 
>>>> If so I need to calculate a label structure and an appropriate neighbor structure, which I guess is possible as I have all the 3D coordinates for each source, e.g in leadfield.pos ?
>>>> I know this is a work around solution, but have anyone tried or have any experience using such an approach ? 
>>>> 
>>>> Best,
>>>> 
>>>> Nicolai
>>>> 
>>>> _______________________________________________
>>>> fieldtrip mailing list
>>>> fieldtrip at donders.ru.nl
>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>> 
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> 
>> Jan-Mathijs Schoffelen, MD PhD 
>> 
>> Donders Institute for Brain, Cognition and Behaviour, 
>> Centre for Cognitive Neuroimaging,
>> Radboud University Nijmegen, The Netherlands
>> 
>> Max Planck Institute for Psycholinguistics,
>> Nijmegen, The Netherlands
>> 
>> J.Schoffelen at donders.ru.nl
>> Telephone: +31-24-3614793
>> 
>> http://www.hettaligebrein.nl
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From smoratti at psi.ucm.es  Thu Jun 13 15:50:30 2013
From: smoratti at psi.ucm.es (smoratti at psi.ucm.es)
Date: Thu, 13 Jun 2013 15:50:30 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
In-Reply-To: <6F3697BB-194F-422F-A1BF-EBBB132F805B@mersebak.dk>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
	<05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>
	<683ABC6E-9FC6-420A-9DCF-E54D6FC6A27E@donders.ru.nl>
	<8D369E00-7FF3-4CC7-8B91-A55AD9ECE385@psi.ucm.es>
	<6F3697BB-194F-422F-A1BF-EBBB132F805B@mersebak.dk>
Message-ID: <4755A6E7-44B5-4E98-B536-A19F544ED284@psi.ucm.es>

Dear Nikolai,

In ft_sourceplot there is the possibility of projecting grid data to surface data. However, I am not sure if the other way round is implemented in field trip.

With respect to the other (maybe less accurate solution) of providing a neighbor matrix of the vertices of your brain surface:

if you do " channeigbststructmat = your_neighbor_matrix" in clusterstat.m should work.

Best,

Stephan



________________________________________________________
Stephan Moratti, PhD

see also: http://web.me.com/smoratti/

Universidad Complutense de Madrid
Facultad de Psicología
Departamento de Psicología Básica I
Campus de Somosaguas
28223 Pozuelo de Alarcón (Madrid)
Spain

and

Center for Biomedical Technology
Laboratory for Cognitive and Computational Neuroscience
Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
Campus Montegancedo
28223 Pozuelo de Alarcón (Madrid)
Spain


email: smoratti at psi.ucm.es
Tel.:    +34 679219982

El 13/06/2013, a las 12:04, Nicolai Mersebak escribió:

> Thanks to all of you for your comments and ideas - they are very helpful! 
> 
> I ( off course :) ) have some follow up questions. 
> 
> I have created an ERP structure for my MNE source, so the only think which I need and that is not straight forward is the neighbour structure. 
> 
> I am using the standard bem template (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model and use the following code to get a grid for all subjects as I don't have any subject specific information regarding the anatomy. 
> 
> cfg = [];
> cfg.grid.xgrid  = -100:10:100;
> cfg.grid.ygrid  = -100:10:100;
> cfg.grid.zgrid  = -100:10:100;
> cfg.grid.tight  = 'yes';
> cfg.grid.unit   = hdm.unit; % unit: mm
> cfg.vol        = hdm;
> grid  = ft_prepare_sourcemodel(cfg);
> 
> 
> @Jan-Mathijs and Stephan: I guess making a subject specific grid based on a warped template requires anatomic information for each subject, e.g. a MRI image like this tutorial shows:
> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
> 
> The final grid output in the tutorial - does it have this 3D grid which can be used as a neighbour structure ? 
> 
> I am not sure how to go from my cortical sheet [vertices x coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
>  
> A second thing I would like to know is, if any of you have tried to use an atlas (e.g ALL template atlas) where the regions now are channels in the permutation test? Going from source points to atlas regions can be done through ft_sourcestatistics, but I am still interested in keeping the temporal dimension. The reason to use atlas regions instead of source points is to decrease the computation time. 
> 
> Best,
> 
> Nicolai
> 
> 
> Den 12/06/2013 kl. 18.58 skrev "smoratti at psi.ucm.es" <smoratti at psi.ucm.es>:
> 
>> 
>> I think Jan.Mathijs alternative suggestion is quite attractive. With the neighbors on a cortical sheet I also had the problems that sometimes the vertices do not have the same distance and then clustering may be biased to smaller or bigger clusters as the number of neighbors does not guarantee same cluster sizes. With the interpolation onto a 3D grid, you won't have that problem.
>> 
>> best,
>> 
>> Stephan
>> 
>> 
>> ________________________________________________________
>> Stephan Moratti, PhD
>> 
>> see also: http://web.me.com/smoratti/
>> 
>> Universidad Complutense de Madrid
>> Facultad de Psicología
>> Departamento de Psicología Básica I
>> Campus de Somosaguas
>> 28223 Pozuelo de Alarcón (Madrid)
>> Spain
>> 
>> and
>> 
>> Center for Biomedical Technology
>> Laboratory for Cognitive and Computational Neuroscience
>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>> Campus Montegancedo
>> 28223 Pozuelo de Alarcón (Madrid)
>> Spain
>> 
>> 
>> email: smoratti at psi.ucm.es
>> Tel.:    +34 679219982
>> 
>> El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribió:
>> 
>>> An alternative would be to interpolate the cortical sheet to a 3D grid (where the grid is defined for each subject based on a warped template grid defined in a standard space), and then do clustering using a regular 3D spatial neighbourhood structure. The rationale being that two vertices on the sheet may appear as disconnected  (e.g. being on two sides of a sulcus) whereas, given the poor spatial resolution, they belong to the same spatial blob.
>>> 
>>> Best,
>>> Jan-Mathijs
>>> 
>>> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
>>> 
>>>> Dear Nicolai,
>>>> 
>>>> Indeed I have used ft_timelockstatistics for minimum norm source data. The trick is to put the source level data into a ERF structure. Determining the neighbors of a source surface with vertices is not trivial. However I used tess_vertconn.m from the BrainStorm toolbox to get the connectivity matrix that tells you who is a neighbor. This you can feed into timelockstats.
>>>> 
>>>> Hope that helps,
>>>> 
>>>> Stephan
>>>> 
>>>> ________________________________________________________
>>>> Stephan Moratti, PhD
>>>> 
>>>> see also: http://web.me.com/smoratti/
>>>> 
>>>> Universidad Complutense de Madrid
>>>> Facultad de Psicología
>>>> Departamento de Psicología Básica I
>>>> Campus de Somosaguas
>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>> Spain
>>>> 
>>>> and
>>>> 
>>>> Center for Biomedical Technology
>>>> Laboratory for Cognitive and Computational Neuroscience
>>>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>>>> Campus Montegancedo
>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>> Spain
>>>> 
>>>> 
>>>> email: smoratti at psi.ucm.es
>>>> Tel.:    +34 679219982
>>>> 
>>>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribió:
>>>> 
>>>>> Dear all,
>>>>> 
>>>>> I have a question concerning the usage of ft_sourcegrandaverage and ft_sourcestatistics. 
>>>>> 
>>>>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897 time points. 
>>>>> 
>>>>> Now I would like to use the cluster-based permutation test on my source reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics don't support source level time courses. E.g when I am using ft_sourcegrandaverage I am getting the following error:
>>>>> 
>>>>> Error in ft_sourcegrandaverage (line 158)
>>>>>   dat(:,i) = tmp(:);
>>>>> 
>>>>> Looking into the code:
>>>>> 
>>>>>   for i=1:Nsubject
>>>>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter, varargin{i}));
>>>>>     dat(:,i) = tmp(:);
>>>>>     tmp = getsubfield(varargin{i}, 'inside');
>>>>>     inside(tmp,i) = 1;
>>>>>   end
>>>>> 
>>>>> I see that "tmp" are getting the structure [N_sources x timepoints] from source.avg.pow for one subject, where "dat" requires the structure [N_sources x 1]. 
>>>>> 
>>>>> I seached the mailing list for similar issues and found this thread:
>>>>> 
>>>>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>>>>> 
>>>>> Since I am interested in using the temporal dimension in my statistics, I would like to know if it is still not possible to use spatio-temporal source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
>>>>> 
>>>>> Or if any have succeeded in using the cluster-based permutation test on source level also including the temporal dimension ? 
>>>>> 
>>>>> Alternative I was thinking that I might could use ft_timelockstatistics, where I substituted the channels with sources, e.g instead of having 64 channels, I would now have 4050 "channels". 
>>>>> If so I need to calculate a label structure and an appropriate neighbor structure, which I guess is possible as I have all the 3D coordinates for each source, e.g in leadfield.pos ?
>>>>> I know this is a work around solution, but have anyone tried or have any experience using such an approach ? 
>>>>> 
>>>>> Best,
>>>>> 
>>>>> Nicolai
>>>>> 
>>>>> _______________________________________________
>>>>> fieldtrip mailing list
>>>>> fieldtrip at donders.ru.nl
>>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>> 
>>>> _______________________________________________
>>>> fieldtrip mailing list
>>>> fieldtrip at donders.ru.nl
>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>> 
>>> Jan-Mathijs Schoffelen, MD PhD 
>>> 
>>> Donders Institute for Brain, Cognition and Behaviour, 
>>> Centre for Cognitive Neuroimaging,
>>> Radboud University Nijmegen, The Netherlands
>>> 
>>> Max Planck Institute for Psycholinguistics,
>>> Nijmegen, The Netherlands
>>> 
>>> J.Schoffelen at donders.ru.nl
>>> Telephone: +31-24-3614793
>>> 
>>> http://www.hettaligebrein.nl
>>> 
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From jan.schoffelen at donders.ru.nl  Thu Jun 13 15:58:47 2013
From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen)
Date: Thu, 13 Jun 2013 15:58:47 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
In-Reply-To: <4755A6E7-44B5-4E98-B536-A19F544ED284@psi.ucm.es>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
	<05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>
	<683ABC6E-9FC6-420A-9DCF-E54D6FC6A27E@donders.ru.nl>
	<8D369E00-7FF3-4CC7-8B91-A55AD9ECE385@psi.ucm.es>
	<6F3697BB-194F-422F-A1BF-EBBB132F805B@mersebak.dk>
	<4755A6E7-44B5-4E98-B536-A19F544ED284@psi.ucm.es>
Message-ID: <944F6EF6-C03A-46F4-BFF4-3D9EC324E602@donders.ru.nl>

Hi all,

ft_sourceinterpolate can interpolate from between arbitrary point clouds, so also between a set of points defined on the cortical sheet, and a more or less regular 3D grid.

JM

On Jun 13, 2013, at 3:50 PM, smoratti at psi.ucm.es wrote:

> Dear Nikolai,
> 
> In ft_sourceplot there is the possibility of projecting grid data to surface data. However, I am not sure if the other way round is implemented in field trip.
> 
> With respect to the other (maybe less accurate solution) of providing a neighbor matrix of the vertices of your brain surface:
> 
> if you do " channeigbststructmat = your_neighbor_matrix" in clusterstat.m should work.
> 
> Best,
> 
> Stephan
> 
> 
> 
> ________________________________________________________
> Stephan Moratti, PhD
> 
> see also: http://web.me.com/smoratti/
> 
> Universidad Complutense de Madrid
> Facultad de Psicología
> Departamento de Psicología Básica I
> Campus de Somosaguas
> 28223 Pozuelo de Alarcón (Madrid)
> Spain
> 
> and
> 
> Center for Biomedical Technology
> Laboratory for Cognitive and Computational Neuroscience
> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
> Campus Montegancedo
> 28223 Pozuelo de Alarcón (Madrid)
> Spain
> 
> 
> email: smoratti at psi.ucm.es
> Tel.:    +34 679219982
> 
> El 13/06/2013, a las 12:04, Nicolai Mersebak escribió:
> 
>> Thanks to all of you for your comments and ideas - they are very helpful! 
>> 
>> I ( off course :) ) have some follow up questions. 
>> 
>> I have created an ERP structure for my MNE source, so the only think which I need and that is not straight forward is the neighbour structure. 
>> 
>> I am using the standard bem template (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model and use the following code to get a grid for all subjects as I don't have any subject specific information regarding the anatomy. 
>> 
>> cfg = [];
>> cfg.grid.xgrid  = -100:10:100;
>> cfg.grid.ygrid  = -100:10:100;
>> cfg.grid.zgrid  = -100:10:100;
>> cfg.grid.tight  = 'yes';
>> cfg.grid.unit   = hdm.unit; % unit: mm
>> cfg.vol        = hdm;
>> grid  = ft_prepare_sourcemodel(cfg);
>> 
>> 
>> @Jan-Mathijs and Stephan: I guess making a subject specific grid based on a warped template requires anatomic information for each subject, e.g. a MRI image like this tutorial shows:
>> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
>> 
>> The final grid output in the tutorial - does it have this 3D grid which can be used as a neighbour structure ? 
>> 
>> I am not sure how to go from my cortical sheet [vertices x coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
>>  
>> A second thing I would like to know is, if any of you have tried to use an atlas (e.g ALL template atlas) where the regions now are channels in the permutation test? Going from source points to atlas regions can be done through ft_sourcestatistics, but I am still interested in keeping the temporal dimension. The reason to use atlas regions instead of source points is to decrease the computation time. 
>> 
>> Best,
>> 
>> Nicolai
>> 
>> 
>> Den 12/06/2013 kl. 18.58 skrev "smoratti at psi.ucm.es" <smoratti at psi.ucm.es>:
>> 
>>> 
>>> I think Jan.Mathijs alternative suggestion is quite attractive. With the neighbors on a cortical sheet I also had the problems that sometimes the vertices do not have the same distance and then clustering may be biased to smaller or bigger clusters as the number of neighbors does not guarantee same cluster sizes. With the interpolation onto a 3D grid, you won't have that problem.
>>> 
>>> best,
>>> 
>>> Stephan
>>> 
>>> 
>>> ________________________________________________________
>>> Stephan Moratti, PhD
>>> 
>>> see also: http://web.me.com/smoratti/
>>> 
>>> Universidad Complutense de Madrid
>>> Facultad de Psicología
>>> Departamento de Psicología Básica I
>>> Campus de Somosaguas
>>> 28223 Pozuelo de Alarcón (Madrid)
>>> Spain
>>> 
>>> and
>>> 
>>> Center for Biomedical Technology
>>> Laboratory for Cognitive and Computational Neuroscience
>>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>>> Campus Montegancedo
>>> 28223 Pozuelo de Alarcón (Madrid)
>>> Spain
>>> 
>>> 
>>> email: smoratti at psi.ucm.es
>>> Tel.:    +34 679219982
>>> 
>>> El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribió:
>>> 
>>>> An alternative would be to interpolate the cortical sheet to a 3D grid (where the grid is defined for each subject based on a warped template grid defined in a standard space), and then do clustering using a regular 3D spatial neighbourhood structure. The rationale being that two vertices on the sheet may appear as disconnected  (e.g. being on two sides of a sulcus) whereas, given the poor spatial resolution, they belong to the same spatial blob.
>>>> 
>>>> Best,
>>>> Jan-Mathijs
>>>> 
>>>> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
>>>> 
>>>>> Dear Nicolai,
>>>>> 
>>>>> Indeed I have used ft_timelockstatistics for minimum norm source data. The trick is to put the source level data into a ERF structure. Determining the neighbors of a source surface with vertices is not trivial. However I used tess_vertconn.m from the BrainStorm toolbox to get the connectivity matrix that tells you who is a neighbor. This you can feed into timelockstats.
>>>>> 
>>>>> Hope that helps,
>>>>> 
>>>>> Stephan
>>>>> 
>>>>> ________________________________________________________
>>>>> Stephan Moratti, PhD
>>>>> 
>>>>> see also: http://web.me.com/smoratti/
>>>>> 
>>>>> Universidad Complutense de Madrid
>>>>> Facultad de Psicología
>>>>> Departamento de Psicología Básica I
>>>>> Campus de Somosaguas
>>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>>> Spain
>>>>> 
>>>>> and
>>>>> 
>>>>> Center for Biomedical Technology
>>>>> Laboratory for Cognitive and Computational Neuroscience
>>>>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>>>>> Campus Montegancedo
>>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>>> Spain
>>>>> 
>>>>> 
>>>>> email: smoratti at psi.ucm.es
>>>>> Tel.:    +34 679219982
>>>>> 
>>>>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribió:
>>>>> 
>>>>>> Dear all,
>>>>>> 
>>>>>> I have a question concerning the usage of ft_sourcegrandaverage and ft_sourcestatistics. 
>>>>>> 
>>>>>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897 time points. 
>>>>>> 
>>>>>> Now I would like to use the cluster-based permutation test on my source reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics don't support source level time courses. E.g when I am using ft_sourcegrandaverage I am getting the following error:
>>>>>> 
>>>>>> Error in ft_sourcegrandaverage (line 158)
>>>>>>   dat(:,i) = tmp(:);
>>>>>> 
>>>>>> Looking into the code:
>>>>>> 
>>>>>>   for i=1:Nsubject
>>>>>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter, varargin{i}));
>>>>>>     dat(:,i) = tmp(:);
>>>>>>     tmp = getsubfield(varargin{i}, 'inside');
>>>>>>     inside(tmp,i) = 1;
>>>>>>   end
>>>>>> 
>>>>>> I see that "tmp" are getting the structure [N_sources x timepoints] from source.avg.pow for one subject, where "dat" requires the structure [N_sources x 1]. 
>>>>>> 
>>>>>> I seached the mailing list for similar issues and found this thread:
>>>>>> 
>>>>>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>>>>>> 
>>>>>> Since I am interested in using the temporal dimension in my statistics, I would like to know if it is still not possible to use spatio-temporal source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
>>>>>> 
>>>>>> Or if any have succeeded in using the cluster-based permutation test on source level also including the temporal dimension ? 
>>>>>> 
>>>>>> Alternative I was thinking that I might could use ft_timelockstatistics, where I substituted the channels with sources, e.g instead of having 64 channels, I would now have 4050 "channels". 
>>>>>> If so I need to calculate a label structure and an appropriate neighbor structure, which I guess is possible as I have all the 3D coordinates for each source, e.g in leadfield.pos ?
>>>>>> I know this is a work around solution, but have anyone tried or have any experience using such an approach ? 
>>>>>> 
>>>>>> Best,
>>>>>> 
>>>>>> Nicolai
>>>>>> 
>>>>>> _______________________________________________
>>>>>> fieldtrip mailing list
>>>>>> fieldtrip at donders.ru.nl
>>>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>> 
>>>>> _______________________________________________
>>>>> fieldtrip mailing list
>>>>> fieldtrip at donders.ru.nl
>>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>> 
>>>> Jan-Mathijs Schoffelen, MD PhD 
>>>> 
>>>> Donders Institute for Brain, Cognition and Behaviour, 
>>>> Centre for Cognitive Neuroimaging,
>>>> Radboud University Nijmegen, The Netherlands
>>>> 
>>>> Max Planck Institute for Psycholinguistics,
>>>> Nijmegen, The Netherlands
>>>> 
>>>> J.Schoffelen at donders.ru.nl
>>>> Telephone: +31-24-3614793
>>>> 
>>>> http://www.hettaligebrein.nl
>>>> 
>>>> _______________________________________________
>>>> fieldtrip mailing list
>>>> fieldtrip at donders.ru.nl
>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>> 
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

Jan-Mathijs Schoffelen, MD PhD 

Donders Institute for Brain, Cognition and Behaviour, 
Centre for Cognitive Neuroimaging,
Radboud University Nijmegen, The Netherlands

Max Planck Institute for Psycholinguistics,
Nijmegen, The Netherlands

J.Schoffelen at donders.ru.nl
Telephone: +31-24-3614793

http://www.hettaligebrein.nl

-------------- next part --------------
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From jan.schoffelen at donders.ru.nl  Thu Jun 13 16:12:26 2013
From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen)
Date: Thu, 13 Jun 2013 16:12:26 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
In-Reply-To: <944F6EF6-C03A-46F4-BFF4-3D9EC324E602@donders.ru.nl>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
	<05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>
	<683ABC6E-9FC6-420A-9DCF-E54D6FC6A27E@donders.ru.nl>
	<8D369E00-7FF3-4CC7-8B91-A55AD9ECE385@psi.ucm.es>
	<6F3697BB-194F-422F-A1BF-EBBB132F805B@mersebak.dk>
	<4755A6E7-44B5-4E98-B536-A19F544ED284@psi.ucm.es>
	<944F6EF6-C03A-46F4-BFF4-3D9EC324E602@donders.ru.nl>
Message-ID: <C58208AA-1DC3-40CD-9E55-F1B3ADD3CCD4@donders.ru.nl>

Hi all,

As a follow up to my previous message: it is intended in the future to remove the functionality in ft_sourceplot, doing the interpolation on the fly when cfg.method='surface' but when the input contains data defined on a 3D grid, and to request the user to go through ft_sourceinterpolate before visualization. Stay tuned...

JM

On Jun 13, 2013, at 3:58 PM, jan-mathijs schoffelen wrote:

> Hi all,
> 
> ft_sourceinterpolate can interpolate from between arbitrary point clouds, so also between a set of points defined on the cortical sheet, and a more or less regular 3D grid.
> 
> JM
> 
> On Jun 13, 2013, at 3:50 PM, smoratti at psi.ucm.es wrote:
> 
>> Dear Nikolai,
>> 
>> In ft_sourceplot there is the possibility of projecting grid data to surface data. However, I am not sure if the other way round is implemented in field trip.
>> 
>> With respect to the other (maybe less accurate solution) of providing a neighbor matrix of the vertices of your brain surface:
>> 
>> if you do " channeigbststructmat = your_neighbor_matrix" in clusterstat.m should work.
>> 
>> Best,
>> 
>> Stephan
>> 
>> 
>> 
>> ________________________________________________________
>> Stephan Moratti, PhD
>> 
>> see also: http://web.me.com/smoratti/
>> 
>> Universidad Complutense de Madrid
>> Facultad de Psicología
>> Departamento de Psicología Básica I
>> Campus de Somosaguas
>> 28223 Pozuelo de Alarcón (Madrid)
>> Spain
>> 
>> and
>> 
>> Center for Biomedical Technology
>> Laboratory for Cognitive and Computational Neuroscience
>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>> Campus Montegancedo
>> 28223 Pozuelo de Alarcón (Madrid)
>> Spain
>> 
>> 
>> email: smoratti at psi.ucm.es
>> Tel.:    +34 679219982
>> 
>> El 13/06/2013, a las 12:04, Nicolai Mersebak escribió:
>> 
>>> Thanks to all of you for your comments and ideas - they are very helpful! 
>>> 
>>> I ( off course :) ) have some follow up questions. 
>>> 
>>> I have created an ERP structure for my MNE source, so the only think which I need and that is not straight forward is the neighbour structure. 
>>> 
>>> I am using the standard bem template (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model and use the following code to get a grid for all subjects as I don't have any subject specific information regarding the anatomy. 
>>> 
>>> cfg = [];
>>> cfg.grid.xgrid  = -100:10:100;
>>> cfg.grid.ygrid  = -100:10:100;
>>> cfg.grid.zgrid  = -100:10:100;
>>> cfg.grid.tight  = 'yes';
>>> cfg.grid.unit   = hdm.unit; % unit: mm
>>> cfg.vol        = hdm;
>>> grid  = ft_prepare_sourcemodel(cfg);
>>> 
>>> 
>>> @Jan-Mathijs and Stephan: I guess making a subject specific grid based on a warped template requires anatomic information for each subject, e.g. a MRI image like this tutorial shows:
>>> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
>>> 
>>> The final grid output in the tutorial - does it have this 3D grid which can be used as a neighbour structure ? 
>>> 
>>> I am not sure how to go from my cortical sheet [vertices x coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
>>>  
>>> A second thing I would like to know is, if any of you have tried to use an atlas (e.g ALL template atlas) where the regions now are channels in the permutation test? Going from source points to atlas regions can be done through ft_sourcestatistics, but I am still interested in keeping the temporal dimension. The reason to use atlas regions instead of source points is to decrease the computation time. 
>>> 
>>> Best,
>>> 
>>> Nicolai
>>> 
>>> 
>>> Den 12/06/2013 kl. 18.58 skrev "smoratti at psi.ucm.es" <smoratti at psi.ucm.es>:
>>> 
>>>> 
>>>> I think Jan.Mathijs alternative suggestion is quite attractive. With the neighbors on a cortical sheet I also had the problems that sometimes the vertices do not have the same distance and then clustering may be biased to smaller or bigger clusters as the number of neighbors does not guarantee same cluster sizes. With the interpolation onto a 3D grid, you won't have that problem.
>>>> 
>>>> best,
>>>> 
>>>> Stephan
>>>> 
>>>> 
>>>> ________________________________________________________
>>>> Stephan Moratti, PhD
>>>> 
>>>> see also: http://web.me.com/smoratti/
>>>> 
>>>> Universidad Complutense de Madrid
>>>> Facultad de Psicología
>>>> Departamento de Psicología Básica I
>>>> Campus de Somosaguas
>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>> Spain
>>>> 
>>>> and
>>>> 
>>>> Center for Biomedical Technology
>>>> Laboratory for Cognitive and Computational Neuroscience
>>>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>>>> Campus Montegancedo
>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>> Spain
>>>> 
>>>> 
>>>> email: smoratti at psi.ucm.es
>>>> Tel.:    +34 679219982
>>>> 
>>>> El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribió:
>>>> 
>>>>> An alternative would be to interpolate the cortical sheet to a 3D grid (where the grid is defined for each subject based on a warped template grid defined in a standard space), and then do clustering using a regular 3D spatial neighbourhood structure. The rationale being that two vertices on the sheet may appear as disconnected  (e.g. being on two sides of a sulcus) whereas, given the poor spatial resolution, they belong to the same spatial blob.
>>>>> 
>>>>> Best,
>>>>> Jan-Mathijs
>>>>> 
>>>>> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
>>>>> 
>>>>>> Dear Nicolai,
>>>>>> 
>>>>>> Indeed I have used ft_timelockstatistics for minimum norm source data. The trick is to put the source level data into a ERF structure. Determining the neighbors of a source surface with vertices is not trivial. However I used tess_vertconn.m from the BrainStorm toolbox to get the connectivity matrix that tells you who is a neighbor. This you can feed into timelockstats.
>>>>>> 
>>>>>> Hope that helps,
>>>>>> 
>>>>>> Stephan
>>>>>> 
>>>>>> ________________________________________________________
>>>>>> Stephan Moratti, PhD
>>>>>> 
>>>>>> see also: http://web.me.com/smoratti/
>>>>>> 
>>>>>> Universidad Complutense de Madrid
>>>>>> Facultad de Psicología
>>>>>> Departamento de Psicología Básica I
>>>>>> Campus de Somosaguas
>>>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>>>> Spain
>>>>>> 
>>>>>> and
>>>>>> 
>>>>>> Center for Biomedical Technology
>>>>>> Laboratory for Cognitive and Computational Neuroscience
>>>>>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>>>>>> Campus Montegancedo
>>>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>>>> Spain
>>>>>> 
>>>>>> 
>>>>>> email: smoratti at psi.ucm.es
>>>>>> Tel.:    +34 679219982
>>>>>> 
>>>>>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribió:
>>>>>> 
>>>>>>> Dear all,
>>>>>>> 
>>>>>>> I have a question concerning the usage of ft_sourcegrandaverage and ft_sourcestatistics. 
>>>>>>> 
>>>>>>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897 time points. 
>>>>>>> 
>>>>>>> Now I would like to use the cluster-based permutation test on my source reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics don't support source level time courses. E.g when I am using ft_sourcegrandaverage I am getting the following error:
>>>>>>> 
>>>>>>> Error in ft_sourcegrandaverage (line 158)
>>>>>>>   dat(:,i) = tmp(:);
>>>>>>> 
>>>>>>> Looking into the code:
>>>>>>> 
>>>>>>>   for i=1:Nsubject
>>>>>>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter, varargin{i}));
>>>>>>>     dat(:,i) = tmp(:);
>>>>>>>     tmp = getsubfield(varargin{i}, 'inside');
>>>>>>>     inside(tmp,i) = 1;
>>>>>>>   end
>>>>>>> 
>>>>>>> I see that "tmp" are getting the structure [N_sources x timepoints] from source.avg.pow for one subject, where "dat" requires the structure [N_sources x 1]. 
>>>>>>> 
>>>>>>> I seached the mailing list for similar issues and found this thread:
>>>>>>> 
>>>>>>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>>>>>>> 
>>>>>>> Since I am interested in using the temporal dimension in my statistics, I would like to know if it is still not possible to use spatio-temporal source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
>>>>>>> 
>>>>>>> Or if any have succeeded in using the cluster-based permutation test on source level also including the temporal dimension ? 
>>>>>>> 
>>>>>>> Alternative I was thinking that I might could use ft_timelockstatistics, where I substituted the channels with sources, e.g instead of having 64 channels, I would now have 4050 "channels". 
>>>>>>> If so I need to calculate a label structure and an appropriate neighbor structure, which I guess is possible as I have all the 3D coordinates for each source, e.g in leadfield.pos ?
>>>>>>> I know this is a work around solution, but have anyone tried or have any experience using such an approach ? 
>>>>>>> 
>>>>>>> Best,
>>>>>>> 
>>>>>>> Nicolai
>>>>>>> 
>>>>>>> _______________________________________________
>>>>>>> fieldtrip mailing list
>>>>>>> fieldtrip at donders.ru.nl
>>>>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>>> 
>>>>>> _______________________________________________
>>>>>> fieldtrip mailing list
>>>>>> fieldtrip at donders.ru.nl
>>>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>> 
>>>>> Jan-Mathijs Schoffelen, MD PhD 
>>>>> 
>>>>> Donders Institute for Brain, Cognition and Behaviour, 
>>>>> Centre for Cognitive Neuroimaging,
>>>>> Radboud University Nijmegen, The Netherlands
>>>>> 
>>>>> Max Planck Institute for Psycholinguistics,
>>>>> Nijmegen, The Netherlands
>>>>> 
>>>>> J.Schoffelen at donders.ru.nl
>>>>> Telephone: +31-24-3614793
>>>>> 
>>>>> http://www.hettaligebrein.nl
>>>>> 
>>>>> _______________________________________________
>>>>> fieldtrip mailing list
>>>>> fieldtrip at donders.ru.nl
>>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>> 
>>>> _______________________________________________
>>>> fieldtrip mailing list
>>>> fieldtrip at donders.ru.nl
>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>> 
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> Jan-Mathijs Schoffelen, MD PhD 
> 
> Donders Institute for Brain, Cognition and Behaviour, 
> Centre for Cognitive Neuroimaging,
> Radboud University Nijmegen, The Netherlands
> 
> Max Planck Institute for Psycholinguistics,
> Nijmegen, The Netherlands
> 
> J.Schoffelen at donders.ru.nl
> Telephone: +31-24-3614793
> 
> http://www.hettaligebrein.nl
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

Jan-Mathijs Schoffelen, MD PhD 

Donders Institute for Brain, Cognition and Behaviour, 
Centre for Cognitive Neuroimaging,
Radboud University Nijmegen, The Netherlands

Max Planck Institute for Psycholinguistics,
Nijmegen, The Netherlands

J.Schoffelen at donders.ru.nl
Telephone: +31-24-3614793

http://www.hettaligebrein.nl

-------------- next part --------------
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From gopalar.ccf at gmail.com  Fri Jun 14 17:37:54 2013
From: gopalar.ccf at gmail.com (Raghavan Gopalakrishnan)
Date: Fri, 14 Jun 2013 11:37:54 -0400
Subject: [FieldTrip] Butter command
Message-ID: <CAHz=SkUHMvCSLf+uZ=rJiEOvxJJGCJAiPq0RHtc0G34u7ToZhA@mail.gmail.com>

I noticed that 'butter' command in the fieldtrip toolbox
'/fieldtrip-20130609/external/signal/butter.m'
is interfering with the 'butter' command in the Matlab signal processing
toolbox. Can the name be changed?
There are probably more commands in fieldtrip that has same names as
regular matlab commands.
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From eelke.spaak at donders.ru.nl  Fri Jun 14 20:56:17 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Fri, 14 Jun 2013 20:56:17 +0200
Subject: [FieldTrip] Butter command
In-Reply-To: <CAHz=SkUHMvCSLf+uZ=rJiEOvxJJGCJAiPq0RHtc0G34u7ToZhA@mail.gmail.com>
References: <CAHz=SkUHMvCSLf+uZ=rJiEOvxJJGCJAiPq0RHtc0G34u7ToZhA@mail.gmail.com>
Message-ID: <CABPNLUo2=TjM0dqE41syJLtqAcmTEN2mAYsMmA045SGNabvRnQ@mail.gmail.com>

Dear Raghavan,

The /external/signal/ functions are meant as drop-in replacements for
functions in the MATLAB Signal Processing Toolbox, so they should
behave exactly the same as the functions they are shadowing. They are
included in the FieldTrip release for people who do not have Signal
Processing Toolbox licenses, or who would prefer not to use those
licenses just for tapering or filter coefficient functions.

Best,
Eelke

On 14 June 2013 17:37, Raghavan Gopalakrishnan <gopalar.ccf at gmail.com> wrote:
>
> I noticed that 'butter' command in the fieldtrip toolbox
> '/fieldtrip-20130609/external/signal/butter.m'
> is interfering with the 'butter' command in the Matlab signal processing
> toolbox. Can the name be changed?
> There are probably more commands in fieldtrip that has same names as regular
> matlab commands.
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From karenschuil at gmail.com  Mon Jun 17 13:56:09 2013
From: karenschuil at gmail.com (Karen Schuil)
Date: Mon, 17 Jun 2013 13:56:09 +0200
Subject: [FieldTrip] ERP average Brain Vision is different from ERP average
	FieldTrip
Message-ID: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>

Dear Fieldtrip Users,

I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision Analyser
are different from the ERPS of FieldTrip. It seems that in Fieldtrip a slow
negative drift is added and peaks are more/less pronounced than in BVA
(attached is a picture of the two different plots).

An expert FieldTrip User and I could not find a solution for this problem.
I hope one of you has a suggestion for this problem.

The individual trial data was exported from BVA (version 2.02.5859) with
the following settings:
File extension: .seg
Write header file: yes
Write marker file: yes
Format: BINARY
Orientation: MULTIPLEXED
Line Delimiter: CRLF (PC style)
Binary format: 16-Bit signed integer format
Set resolution manually: no
Individually optimized resolution for each channel: yes
Convert to big-endian order: no
Export all channels: no
Export the following channels:
AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5
CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5
FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5
P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8
Created Using Component Version 2.0.2.5827

We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
tried a version from 2011).

The scripts we used are read_analyzer_data and timelockanalysis. This is
the code we used for calling the scripts:
% read data into fieldtrip
cfg = [];

cfg.inputfile = 'pp10_A';
cfg.triggercode = 'S 20';
cfg.triggertype = 'Stimulus';
cfg.prestim = 1.2;
cfg.poststim = 1.7;

pp10_l = read_analyzer_data(cfg);

% check: compute ERP
%
cfg = [];
pp10_ERP = timelockanalysis(cfg, pp10_l);

%plot ERP

cfg = [];
cfg.layout = 'elec1010.lay';
cfg.xlim = [-0.15 1.7];
cfg.ylim = [-12.25 12.25];
% cfg.baseline = 'yes';
% cfg.baselinetype = 'absolute';
cfg.showlabels = 'yes';
cfg.interactive = 'yes';

multiplotER(cfg, pp10_ERP);


I hope you can help!

Kind regards,
Karen
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From j.herring at fcdonders.ru.nl  Mon Jun 17 14:23:13 2013
From: j.herring at fcdonders.ru.nl (Herring, J.D. (Jim))
Date: Mon, 17 Jun 2013 14:23:13 +0200 (CEST)
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
	average	FieldTrip
In-Reply-To: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
References: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
Message-ID: <001901ce6b55$6fcf4590$4f6dd0b0$@herring@fcdonders.ru.nl>

Dear Karen,

 

Comparing the BVA and Fieldtrip images it seems that the trials in BVA
have been filtered using at least a high-pass filter. I can see from the
BVA image that you have applied filters prior to averaging your trials.
>From the Fieldtrip code you've posted I cannot see any filtering applied.
If you could find out what filters were applied to the trials in BVA and
apply the same filters to the trials in FieldTrip using ft_preprocessing
your results will most likely be the same.

 

Best,

 

Jim

 

From: fieldtrip-bounces at science.ru.nl
[mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of Karen Schuil
Sent: maandag 17 juni 2013 13:56
To: fieldtrip at science.ru.nl
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
average FieldTrip

 

Dear Fieldtrip Users,

 

I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision Analyser
are different from the ERPS of FieldTrip. It seems that in Fieldtrip a
slow negative drift is added and peaks are more/less pronounced than in
BVA (attached is a picture of the two different plots). 

 

An expert FieldTrip User and I could not find a solution for this problem.
I hope one of you has a suggestion for this problem.

 

The individual trial data was exported from BVA (version 2.02.5859) with
the following settings:

File extension: .seg
Write header file: yes
Write marker file: yes
Format: BINARY
Orientation: MULTIPLEXED
Line Delimiter: CRLF (PC style)
Binary format: 16-Bit signed integer format
Set resolution manually: no
Individually optimized resolution for each channel: yes
Convert to big-endian order: no
Export all channels: no
Export the following channels:
AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5 
CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5 
FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5 
P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8

Created Using Component Version 2.0.2.5827

 

We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
tried a version from 2011).

 

The scripts we used are read_analyzer_data and timelockanalysis. This is
the code we used for calling the scripts:

% read data into fieldtrip

cfg = [];

 

cfg.inputfile = 'pp10_A';

cfg.triggercode = 'S 20';

cfg.triggertype = 'Stimulus';

cfg.prestim = 1.2;

cfg.poststim = 1.7;

 

pp10_l = read_analyzer_data(cfg);

 

% check: compute ERP

% 

cfg = [];

pp10_ERP = timelockanalysis(cfg, pp10_l);

 

%plot ERP

 

cfg = [];

cfg.layout = 'elec1010.lay';

cfg.xlim = [-0.15 1.7];

cfg.ylim = [-12.25 12.25];

% cfg.baseline = 'yes';

% cfg.baselinetype = 'absolute';

cfg.showlabels = 'yes';

cfg.interactive = 'yes';

 

multiplotER(cfg, pp10_ERP);

 

 

I hope you can help! 

 

Kind regards,

Karen

 

 

 

 

 

 

 

 

 

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From aaron.schurger at gmail.com  Mon Jun 17 14:25:25 2013
From: aaron.schurger at gmail.com (Aaron Schurger)
Date: Mon, 17 Jun 2013 14:25:25 +0200
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
 average FieldTrip
In-Reply-To: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
References: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
Message-ID: <CALeeyASM1BMtZu5GUUQfDocnPq+S=bdJyUrx0AYhB2_ON95ODA@mail.gmail.com>

To me it really looks like BVA is applying a high-pass filter at some
stage. When you export the data, the high-pass filter has probably
already been applied. It is typical in EEG (though not a good idea in
my opinion) to apply a high-pass filter with a cutoff at around 0.05
or 0.1 Hz. There should be a setting somewhere in BVA to turn off the
high-pass filter. Anyway, that's my guess just from looking at the
figure you attached.
Cheers,
Aaron

On Mon, Jun 17, 2013 at 1:56 PM, Karen Schuil <karenschuil at gmail.com> wrote:
> Dear Fieldtrip Users,
>
> I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision Analyser
> are different from the ERPS of FieldTrip. It seems that in Fieldtrip a slow
> negative drift is added and peaks are more/less pronounced than in BVA
> (attached is a picture of the two different plots).
>
> An expert FieldTrip User and I could not find a solution for this problem. I
> hope one of you has a suggestion for this problem.
>
> The individual trial data was exported from BVA (version 2.02.5859) with the
> following settings:
> File extension: .seg
> Write header file: yes
> Write marker file: yes
> Format: BINARY
> Orientation: MULTIPLEXED
> Line Delimiter: CRLF (PC style)
> Binary format: 16-Bit signed integer format
> Set resolution manually: no
> Individually optimized resolution for each channel: yes
> Convert to big-endian order: no
> Export all channels: no
> Export the following channels:
> AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5
> CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5
> FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5
> P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8
> Created Using Component Version 2.0.2.5827
>
> We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
> tried a version from 2011).
>
> The scripts we used are read_analyzer_data and timelockanalysis. This is the
> code we used for calling the scripts:
> % read data into fieldtrip
> cfg = [];
>
> cfg.inputfile = 'pp10_A';
> cfg.triggercode = 'S 20';
> cfg.triggertype = 'Stimulus';
> cfg.prestim = 1.2;
> cfg.poststim = 1.7;
>
> pp10_l = read_analyzer_data(cfg);
>
> % check: compute ERP
> %
> cfg = [];
> pp10_ERP = timelockanalysis(cfg, pp10_l);
>
> %plot ERP
>
> cfg = [];
> cfg.layout = 'elec1010.lay';
> cfg.xlim = [-0.15 1.7];
> cfg.ylim = [-12.25 12.25];
> % cfg.baseline = 'yes';
> % cfg.baselinetype = 'absolute';
> cfg.showlabels = 'yes';
> cfg.interactive = 'yes';
>
> multiplotER(cfg, pp10_ERP);
>
>
> I hope you can help!
>
> Kind regards,
> Karen
>
>
>
>
>
>
>
>
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip



-- 
Aaron Schurger, PhD
Post-doctoral researcher
INSERM U992 / NeuroSpin
CEA - Saclay, France
+33-1-69-08-66-47
aaron.schurger at gmail.com
http://www.unicog.org


From r.vandermeij at donders.ru.nl  Mon Jun 17 14:48:18 2013
From: r.vandermeij at donders.ru.nl (Roemer van der Meij)
Date: Mon, 17 Jun 2013 14:48:18 +0200
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
 average FieldTrip
In-Reply-To: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
References: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
Message-ID: <CA+WpQ345PZtMY27cMXWTsJNantCXJUd_E5ZUi86gFUNUpGREeg@mail.gmail.com>

Hi Karen,

In case the data wasn't exported with the filtering applied in BVA (see
email Jim) then that looks like a probable cause.
In case the data was exported with the filterings, I noticed in the BVA
part of the attached image that it says AF7 - ref, where I see no such
thing in your exported channel list (and thus not in the fieldtrip image).
What the AF7 - ref is referring to I don't know, it seems like a uncommon
place in the pipeline to do rereferencing, but maybe I'm missing something
obvious. Nevertheless, it might lead you somewhere.

All the best,
Roemer


On Mon, Jun 17, 2013 at 1:56 PM, Karen Schuil <karenschuil at gmail.com> wrote:

> Dear Fieldtrip Users,
>
> I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision Analyser
> are different from the ERPS of FieldTrip. It seems that in Fieldtrip a slow
> negative drift is added and peaks are more/less pronounced than in BVA
> (attached is a picture of the two different plots).
>
> An expert FieldTrip User and I could not find a solution for this problem.
> I hope one of you has a suggestion for this problem.
>
> The individual trial data was exported from BVA (version 2.02.5859) with
> the following settings:
> File extension: .seg
> Write header file: yes
> Write marker file: yes
> Format: BINARY
> Orientation: MULTIPLEXED
> Line Delimiter: CRLF (PC style)
> Binary format: 16-Bit signed integer format
> Set resolution manually: no
> Individually optimized resolution for each channel: yes
> Convert to big-endian order: no
> Export all channels: no
> Export the following channels:
> AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5
> CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5
> FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5
> P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8
> Created Using Component Version 2.0.2.5827
>
>  We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
> tried a version from 2011).
>
> The scripts we used are read_analyzer_data and timelockanalysis. This is
> the code we used for calling the scripts:
> % read data into fieldtrip
> cfg = [];
>
> cfg.inputfile = 'pp10_A';
> cfg.triggercode = 'S 20';
> cfg.triggertype = 'Stimulus';
> cfg.prestim = 1.2;
> cfg.poststim = 1.7;
>
> pp10_l = read_analyzer_data(cfg);
>
> % check: compute ERP
> %
> cfg = [];
> pp10_ERP = timelockanalysis(cfg, pp10_l);
>
> %plot ERP
>
> cfg = [];
> cfg.layout = 'elec1010.lay';
> cfg.xlim = [-0.15 1.7];
> cfg.ylim = [-12.25 12.25];
> % cfg.baseline = 'yes';
> % cfg.baselinetype = 'absolute';
> cfg.showlabels = 'yes';
> cfg.interactive = 'yes';
>
> multiplotER(cfg, pp10_ERP);
>
>
> I hope you can help!
>
> Kind regards,
> Karen
>
>
>
>
>
>
>
>
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
Roemer van der Meij M.Sc.
PhD Candidate
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognition
P.O. Box 9104
6500 HE Nijmegen
The Netherlands
Tel: +31(0)24 3655932
E-mail: r.vandermeij at donders.ru.nl
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From t.grent-tjong at donders.ru.nl  Mon Jun 17 14:55:43 2013
From: t.grent-tjong at donders.ru.nl (Tineke Grent-'t-Jong)
Date: Mon, 17 Jun 2013 14:55:43 +0200
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 32
References: <mailman.55.1371470195.980.fieldtrip@science.ru.nl>
Message-ID: <5819595A0394409287071472F2D6352A@socrates>

Hi Karen,

To me it looks like the only thing you need to do is subtract the baseline, 
like you have done in BVA (specifying the same window with cfg.baseline = 
[xmin xmax], not 'yes'). The average ERP that you are plotting in BVA has 
already been baselined, but the single trials that go into the 
ft_timelockanalysis function are not, hence the need for baselining later, 
like in your case at the level of plotting.

Hope this helps,

Tineke


----- Original Message ----- 
From: <fieldtrip-request at science.ru.nl>
To: <fieldtrip at science.ru.nl>
Sent: Monday, June 17, 2013 1:56 PM
Subject: fieldtrip Digest, Vol 31, Issue 32


> Send fieldtrip mailing list submissions to
> fieldtrip at science.ru.nl
>
> To subscribe or unsubscribe via the World Wide Web, visit
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> or, via email, send a message with subject or body 'help' to
> fieldtrip-request at science.ru.nl
>
> You can reach the person managing the list at
> fieldtrip-owner at science.ru.nl
>
> When replying, please edit your Subject line so it is more specific
> than "Re: Contents of fieldtrip digest..."
>


--------------------------------------------------------------------------------


> Today's Topics:
>
>   1. ERP average Brain Vision is different from ERP average
>      FieldTrip (Karen Schuil)
>


--------------------------------------------------------------------------------


> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip 



From aaron.schurger at gmail.com  Mon Jun 17 15:08:25 2013
From: aaron.schurger at gmail.com (Aaron Schurger)
Date: Mon, 17 Jun 2013 15:08:25 +0200
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 32
In-Reply-To: <5819595A0394409287071472F2D6352A@socrates>
References: <mailman.55.1371470195.980.fieldtrip@science.ru.nl>
	<5819595A0394409287071472F2D6352A@socrates>
Message-ID: <CALeeyASpsHCvVHZ_dYVt-aJt6F7vsuzLvb4wsmsDeYWCYJDphQ@mail.gmail.com>

Hi, Karen, Tineke,
To me it looks like more than just a baseline shift. It looks like
either linear de-trending or high-pass filtering was applied to the
BVA data. I don't see how a baseline shift could get rid of the low
frequency component that is clearly visible in the FT plot, but not
the BVA plot.
Cheers,
Aaron

On Mon, Jun 17, 2013 at 2:55 PM, Tineke Grent-'t-Jong
<t.grent-tjong at donders.ru.nl> wrote:
> Hi Karen,
>
> To me it looks like the only thing you need to do is subtract the baseline,
> like you have done in BVA (specifying the same window with cfg.baseline =
> [xmin xmax], not 'yes'). The average ERP that you are plotting in BVA has
> already been baselined, but the single trials that go into the
> ft_timelockanalysis function are not, hence the need for baselining later,
> like in your case at the level of plotting.
>
> Hope this helps,
>
> Tineke
>
>
> ----- Original Message ----- From: <fieldtrip-request at science.ru.nl>
> To: <fieldtrip at science.ru.nl>
> Sent: Monday, June 17, 2013 1:56 PM
> Subject: fieldtrip Digest, Vol 31, Issue 32
>
>
>> Send fieldtrip mailing list submissions to
>> fieldtrip at science.ru.nl
>>
>> To subscribe or unsubscribe via the World Wide Web, visit
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> or, via email, send a message with subject or body 'help' to
>> fieldtrip-request at science.ru.nl
>>
>> You can reach the person managing the list at
>> fieldtrip-owner at science.ru.nl
>>
>> When replying, please edit your Subject line so it is more specific
>> than "Re: Contents of fieldtrip digest..."
>>
>
>
> --------------------------------------------------------------------------------
>
>
>> Today's Topics:
>>
>>   1. ERP average Brain Vision is different from ERP average
>>      FieldTrip (Karen Schuil)
>>
>
>
> --------------------------------------------------------------------------------
>
>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip



-- 
Aaron Schurger, PhD
Post-doctoral researcher
INSERM U992 / NeuroSpin
CEA - Saclay, France
+33-1-69-08-66-47
aaron.schurger at gmail.com
http://www.unicog.org


From schuil at fsw.eur.nl  Mon Jun 17 15:22:22 2013
From: schuil at fsw.eur.nl (Karen Schuil)
Date: Mon, 17 Jun 2013 15:22:22 +0200
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
 average FieldTrip
In-Reply-To: <CALeeyASM1BMtZu5GUUQfDocnPq+S=bdJyUrx0AYhB2_ON95ODA@mail.gmail.com>
References: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
	<CALeeyASM1BMtZu5GUUQfDocnPq+S=bdJyUrx0AYhB2_ON95ODA@mail.gmail.com>
Message-ID: <CAGnbK6gqEqLBXuATfXHzh2M7ofohp_z7=i8x=WQtX4RxPEMx6A@mail.gmail.com>

Dear Jim, Aaron, Roemer and Tineke,

Thanks for your quick response and suggestions! The whole preprocessing
(including the filters) was done in BVA. After segmentatation of the
conditions, we exported the data to Fieldtrip. The only steps we did in
Fieldtrip was averaging, creating and plotting an ERP. Therefore it can't
be the filters, right? Unless, the averaging step in BVA applies filters as
well.

The ref in AF7-ref is added by BVA and refers to the channels being linked
to the mastoids.

We have also tried it with subtracting a baseline, but this unfortunately
did not help.

Do you have any other suggestions?

Cheers, Karen




On Mon, Jun 17, 2013 at 2:25 PM, Aaron Schurger <aaron.schurger at gmail.com>wrote:

> To me it really looks like BVA is applying a high-pass filter at some
> stage. When you export the data, the high-pass filter has probably
> already been applied. It is typical in EEG (though not a good idea in
> my opinion) to apply a high-pass filter with a cutoff at around 0.05
> or 0.1 Hz. There should be a setting somewhere in BVA to turn off the
> high-pass filter. Anyway, that's my guess just from looking at the
> figure you attached.
> Cheers,
> Aaron
>
> On Mon, Jun 17, 2013 at 1:56 PM, Karen Schuil <karenschuil at gmail.com>
> wrote:
> > Dear Fieldtrip Users,
> >
> > I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision Analyser
> > are different from the ERPS of FieldTrip. It seems that in Fieldtrip a
> slow
> > negative drift is added and peaks are more/less pronounced than in BVA
> > (attached is a picture of the two different plots).
> >
> > An expert FieldTrip User and I could not find a solution for this
> problem. I
> > hope one of you has a suggestion for this problem.
> >
> > The individual trial data was exported from BVA (version 2.02.5859) with
> the
> > following settings:
> > File extension: .seg
> > Write header file: yes
> > Write marker file: yes
> > Format: BINARY
> > Orientation: MULTIPLEXED
> > Line Delimiter: CRLF (PC style)
> > Binary format: 16-Bit signed integer format
> > Set resolution manually: no
> > Individually optimized resolution for each channel: yes
> > Convert to big-endian order: no
> > Export all channels: no
> > Export the following channels:
> > AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5
> > CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5
> > FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5
> > P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8
> > Created Using Component Version 2.0.2.5827
> >
> > We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
> > tried a version from 2011).
> >
> > The scripts we used are read_analyzer_data and timelockanalysis. This is
> the
> > code we used for calling the scripts:
> > % read data into fieldtrip
> > cfg = [];
> >
> > cfg.inputfile = 'pp10_A';
> > cfg.triggercode = 'S 20';
> > cfg.triggertype = 'Stimulus';
> > cfg.prestim = 1.2;
> > cfg.poststim = 1.7;
> >
> > pp10_l = read_analyzer_data(cfg);
> >
> > % check: compute ERP
> > %
> > cfg = [];
> > pp10_ERP = timelockanalysis(cfg, pp10_l);
> >
> > %plot ERP
> >
> > cfg = [];
> > cfg.layout = 'elec1010.lay';
> > cfg.xlim = [-0.15 1.7];
> > cfg.ylim = [-12.25 12.25];
> > % cfg.baseline = 'yes';
> > % cfg.baselinetype = 'absolute';
> > cfg.showlabels = 'yes';
> > cfg.interactive = 'yes';
> >
> > multiplotER(cfg, pp10_ERP);
> >
> >
> > I hope you can help!
> >
> > Kind regards,
> > Karen
> >
> >
> >
> >
> >
> >
> >
> >
> >
> >
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
> --
> Aaron Schurger, PhD
> Post-doctoral researcher
> INSERM U992 / NeuroSpin
> CEA - Saclay, France
> +33-1-69-08-66-47
> aaron.schurger at gmail.com
> http://www.unicog.org
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
-------------------
Karen Schuil
PhD student

Erasmus University Rotterdam
Institute of Psychology, T 13-09
Burgemeester Oudlaan 50
P.O. Box 1738
3000 DR Rotterdam
The Netherlands
Phone: +31 (0) 10 408 2293
Email:  schuil at fsw.eur.nl
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From t.grent-tjong at donders.ru.nl  Mon Jun 17 15:39:30 2013
From: t.grent-tjong at donders.ru.nl (Tineke Grent-'t-Jong)
Date: Mon, 17 Jun 2013 15:39:30 +0200
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 32
References: <mailman.55.1371470195.980.fieldtrip@science.ru.nl><5819595A0394409287071472F2D6352A@socrates>
	<CALeeyASpsHCvVHZ_dYVt-aJt6F7vsuzLvb4wsmsDeYWCYJDphQ@mail.gmail.com>
Message-ID: <0840040570ED4FE896ED4FAE33DE1355@socrates>

Hi Karen,

Aaron is right that it could be an effect of de-trending or high-pass 
filtering. You could try running the ft_timelockanalyis step again with 
option cfg.removemean = 'no' ('yes' is the default option!). If this
solves the problem then it indeed was some kind of de-trending problem.

Cheers,
Tineke



----- Original Message ----- 
From: "Aaron Schurger" <aaron.schurger at gmail.com>
To: "Tineke Grent-'t-Jong" <t.grent-tjong at donders.ru.nl>; "FieldTrip 
discussion list" <fieldtrip at science.ru.nl>
Sent: Monday, June 17, 2013 3:08 PM
Subject: Re: [FieldTrip] fieldtrip Digest, Vol 31, Issue 32


> Hi, Karen, Tineke,
> To me it looks like more than just a baseline shift. It looks like
> either linear de-trending or high-pass filtering was applied to the
> BVA data. I don't see how a baseline shift could get rid of the low
> frequency component that is clearly visible in the FT plot, but not
> the BVA plot.
> Cheers,
> Aaron
>
> On Mon, Jun 17, 2013 at 2:55 PM, Tineke Grent-'t-Jong
> <t.grent-tjong at donders.ru.nl> wrote:
>> Hi Karen,
>>
>> To me it looks like the only thing you need to do is subtract the 
>> baseline,
>> like you have done in BVA (specifying the same window with cfg.baseline =
>> [xmin xmax], not 'yes'). The average ERP that you are plotting in BVA has
>> already been baselined, but the single trials that go into the
>> ft_timelockanalysis function are not, hence the need for baselining 
>> later,
>> like in your case at the level of plotting.
>>
>> Hope this helps,
>>
>> Tineke
>>
>>
>> ----- Original Message ----- From: <fieldtrip-request at science.ru.nl>
>> To: <fieldtrip at science.ru.nl>
>> Sent: Monday, June 17, 2013 1:56 PM
>> Subject: fieldtrip Digest, Vol 31, Issue 32
>>
>>
>>> Send fieldtrip mailing list submissions to
>>> fieldtrip at science.ru.nl
>>>
>>> To subscribe or unsubscribe via the World Wide Web, visit
>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>> or, via email, send a message with subject or body 'help' to
>>> fieldtrip-request at science.ru.nl
>>>
>>> You can reach the person managing the list at
>>> fieldtrip-owner at science.ru.nl
>>>
>>> When replying, please edit your Subject line so it is more specific
>>> than "Re: Contents of fieldtrip digest..."
>>>
>>
>>
>> --------------------------------------------------------------------------------
>>
>>
>>> Today's Topics:
>>>
>>>   1. ERP average Brain Vision is different from ERP average
>>>      FieldTrip (Karen Schuil)
>>>
>>
>>
>> --------------------------------------------------------------------------------
>>
>>
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
> -- 
> Aaron Schurger, PhD
> Post-doctoral researcher
> INSERM U992 / NeuroSpin
> CEA - Saclay, France
> +33-1-69-08-66-47
> aaron.schurger at gmail.com
> http://www.unicog.org
> 



From berryv.dberg at gmail.com  Mon Jun 17 15:40:14 2013
From: berryv.dberg at gmail.com (berry van den berg)
Date: Mon, 17 Jun 2013 09:40:14 -0400
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
 average FieldTrip
In-Reply-To: <CAGnbK6gqEqLBXuATfXHzh2M7ofohp_z7=i8x=WQtX4RxPEMx6A@mail.gmail.com>
References: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
	<CALeeyASM1BMtZu5GUUQfDocnPq+S=bdJyUrx0AYhB2_ON95ODA@mail.gmail.com>
	<CAGnbK6gqEqLBXuATfXHzh2M7ofohp_z7=i8x=WQtX4RxPEMx6A@mail.gmail.com>
Message-ID: <CAL-qV4JzQmdy=-JNvpm1HwEEvVuLrjQ02sAzjdDffbCV+Ys0ew@mail.gmail.com>

I dont know BVA but it looks like the ERPs are a bit more different (for
example at timepoint 100ms) then I would expect just based on high pass
filtering.... Suggesting that there is different data going into averaging.
Maybe brain vision just detects trials with artifacts and does not throw
out the trials until the averaging step (similar to ERPlab). Can you check
the number of trials?

Cheers,

Berry van den Berg



On 17 June 2013 09:22, Karen Schuil <schuil at fsw.eur.nl> wrote:

> Dear Jim, Aaron, Roemer and Tineke,
>
> Thanks for your quick response and suggestions! The whole preprocessing
> (including the filters) was done in BVA. After segmentatation of the
> conditions, we exported the data to Fieldtrip. The only steps we did in
> Fieldtrip was averaging, creating and plotting an ERP. Therefore it can't
> be the filters, right? Unless, the averaging step in BVA applies filters as
> well.
>
> The ref in AF7-ref is added by BVA and refers to the channels being linked
> to the mastoids.
>
> We have also tried it with subtracting a baseline, but this unfortunately
> did not help.
>
> Do you have any other suggestions?
>
> Cheers, Karen
>
>
>
>
> On Mon, Jun 17, 2013 at 2:25 PM, Aaron Schurger <aaron.schurger at gmail.com>wrote:
>
>> To me it really looks like BVA is applying a high-pass filter at some
>> stage. When you export the data, the high-pass filter has probably
>> already been applied. It is typical in EEG (though not a good idea in
>> my opinion) to apply a high-pass filter with a cutoff at around 0.05
>> or 0.1 Hz. There should be a setting somewhere in BVA to turn off the
>> high-pass filter. Anyway, that's my guess just from looking at the
>> figure you attached.
>> Cheers,
>> Aaron
>>
>> On Mon, Jun 17, 2013 at 1:56 PM, Karen Schuil <karenschuil at gmail.com>
>> wrote:
>> > Dear Fieldtrip Users,
>> >
>> > I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision
>> Analyser
>> > are different from the ERPS of FieldTrip. It seems that in Fieldtrip a
>> slow
>> > negative drift is added and peaks are more/less pronounced than in BVA
>> > (attached is a picture of the two different plots).
>> >
>> > An expert FieldTrip User and I could not find a solution for this
>> problem. I
>> > hope one of you has a suggestion for this problem.
>> >
>> > The individual trial data was exported from BVA (version 2.02.5859)
>> with the
>> > following settings:
>> > File extension: .seg
>> > Write header file: yes
>> > Write marker file: yes
>> > Format: BINARY
>> > Orientation: MULTIPLEXED
>> > Line Delimiter: CRLF (PC style)
>> > Binary format: 16-Bit signed integer format
>> > Set resolution manually: no
>> > Individually optimized resolution for each channel: yes
>> > Convert to big-endian order: no
>> > Export all channels: no
>> > Export the following channels:
>> > AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5
>> > CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5
>> > FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5
>> > P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8
>> > Created Using Component Version 2.0.2.5827
>> >
>> > We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
>> > tried a version from 2011).
>> >
>> > The scripts we used are read_analyzer_data and timelockanalysis. This
>> is the
>> > code we used for calling the scripts:
>> > % read data into fieldtrip
>> > cfg = [];
>> >
>> > cfg.inputfile = 'pp10_A';
>> > cfg.triggercode = 'S 20';
>> > cfg.triggertype = 'Stimulus';
>> > cfg.prestim = 1.2;
>> > cfg.poststim = 1.7;
>> >
>> > pp10_l = read_analyzer_data(cfg);
>> >
>> > % check: compute ERP
>> > %
>> > cfg = [];
>> > pp10_ERP = timelockanalysis(cfg, pp10_l);
>> >
>> > %plot ERP
>> >
>> > cfg = [];
>> > cfg.layout = 'elec1010.lay';
>> > cfg.xlim = [-0.15 1.7];
>> > cfg.ylim = [-12.25 12.25];
>> > % cfg.baseline = 'yes';
>> > % cfg.baselinetype = 'absolute';
>> > cfg.showlabels = 'yes';
>> > cfg.interactive = 'yes';
>> >
>> > multiplotER(cfg, pp10_ERP);
>> >
>> >
>> > I hope you can help!
>> >
>> > Kind regards,
>> > Karen
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> > _______________________________________________
>> > fieldtrip mailing list
>> > fieldtrip at donders.ru.nl
>> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>>
>>
>> --
>> Aaron Schurger, PhD
>> Post-doctoral researcher
>> INSERM U992 / NeuroSpin
>> CEA - Saclay, France
>> +33-1-69-08-66-47
>> aaron.schurger at gmail.com
>> http://www.unicog.org
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>
>
>
> --
> -------------------
> Karen Schuil
> PhD student
>
> Erasmus University Rotterdam
> Institute of Psychology, T 13-09
> Burgemeester Oudlaan 50
> P.O. Box 1738
> 3000 DR Rotterdam
> The Netherlands
> Phone: +31 (0) 10 408 2293
> Email:  schuil at fsw.eur.nl
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
Berry van den Berg
berryv.dberg at gmail.com
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From aaron.schurger at gmail.com  Mon Jun 17 15:44:05 2013
From: aaron.schurger at gmail.com (Aaron Schurger)
Date: Mon, 17 Jun 2013 15:44:05 +0200
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
 average FieldTrip
In-Reply-To: <CAGnbK6gqEqLBXuATfXHzh2M7ofohp_z7=i8x=WQtX4RxPEMx6A@mail.gmail.com>
References: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
	<CALeeyASM1BMtZu5GUUQfDocnPq+S=bdJyUrx0AYhB2_ON95ODA@mail.gmail.com>
	<CAGnbK6gqEqLBXuATfXHzh2M7ofohp_z7=i8x=WQtX4RxPEMx6A@mail.gmail.com>
Message-ID: <CALeeyASwKFoiJ-YL_q1Me+QvFTCtsFvyWpM5i3J4FjgiC8Tuww@mail.gmail.com>

Hi, Karen,
Yes, you're right - it would have to be the case that the averaging
step in BVA applies the filters. That would be where I would check. If
nothing there then it really is mysterious!
Aaron

On Mon, Jun 17, 2013 at 3:22 PM, Karen Schuil <schuil at fsw.eur.nl> wrote:
> Dear Jim, Aaron, Roemer and Tineke,
>
> Thanks for your quick response and suggestions! The whole preprocessing
> (including the filters) was done in BVA. After segmentatation of the
> conditions, we exported the data to Fieldtrip. The only steps we did in
> Fieldtrip was averaging, creating and plotting an ERP. Therefore it can't be
> the filters, right? Unless, the averaging step in BVA applies filters as
> well.
>
> The ref in AF7-ref is added by BVA and refers to the channels being linked
> to the mastoids.
>
> We have also tried it with subtracting a baseline, but this unfortunately
> did not help.
>
> Do you have any other suggestions?
>
> Cheers, Karen
>
>
>
>
> On Mon, Jun 17, 2013 at 2:25 PM, Aaron Schurger <aaron.schurger at gmail.com>
> wrote:
>>
>> To me it really looks like BVA is applying a high-pass filter at some
>> stage. When you export the data, the high-pass filter has probably
>> already been applied. It is typical in EEG (though not a good idea in
>> my opinion) to apply a high-pass filter with a cutoff at around 0.05
>> or 0.1 Hz. There should be a setting somewhere in BVA to turn off the
>> high-pass filter. Anyway, that's my guess just from looking at the
>> figure you attached.
>> Cheers,
>> Aaron
>>
>> On Mon, Jun 17, 2013 at 1:56 PM, Karen Schuil <karenschuil at gmail.com>
>> wrote:
>> > Dear Fieldtrip Users,
>> >
>> > I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision
>> > Analyser
>> > are different from the ERPS of FieldTrip. It seems that in Fieldtrip a
>> > slow
>> > negative drift is added and peaks are more/less pronounced than in BVA
>> > (attached is a picture of the two different plots).
>> >
>> > An expert FieldTrip User and I could not find a solution for this
>> > problem. I
>> > hope one of you has a suggestion for this problem.
>> >
>> > The individual trial data was exported from BVA (version 2.02.5859) with
>> > the
>> > following settings:
>> > File extension: .seg
>> > Write header file: yes
>> > Write marker file: yes
>> > Format: BINARY
>> > Orientation: MULTIPLEXED
>> > Line Delimiter: CRLF (PC style)
>> > Binary format: 16-Bit signed integer format
>> > Set resolution manually: no
>> > Individually optimized resolution for each channel: yes
>> > Convert to big-endian order: no
>> > Export all channels: no
>> > Export the following channels:
>> > AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5
>> > CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5
>> > FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5
>> > P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8
>> > Created Using Component Version 2.0.2.5827
>> >
>> > We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
>> > tried a version from 2011).
>> >
>> > The scripts we used are read_analyzer_data and timelockanalysis. This is
>> > the
>> > code we used for calling the scripts:
>> > % read data into fieldtrip
>> > cfg = [];
>> >
>> > cfg.inputfile = 'pp10_A';
>> > cfg.triggercode = 'S 20';
>> > cfg.triggertype = 'Stimulus';
>> > cfg.prestim = 1.2;
>> > cfg.poststim = 1.7;
>> >
>> > pp10_l = read_analyzer_data(cfg);
>> >
>> > % check: compute ERP
>> > %
>> > cfg = [];
>> > pp10_ERP = timelockanalysis(cfg, pp10_l);
>> >
>> > %plot ERP
>> >
>> > cfg = [];
>> > cfg.layout = 'elec1010.lay';
>> > cfg.xlim = [-0.15 1.7];
>> > cfg.ylim = [-12.25 12.25];
>> > % cfg.baseline = 'yes';
>> > % cfg.baselinetype = 'absolute';
>> > cfg.showlabels = 'yes';
>> > cfg.interactive = 'yes';
>> >
>> > multiplotER(cfg, pp10_ERP);
>> >
>> >
>> > I hope you can help!
>> >
>> > Kind regards,
>> > Karen
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> > _______________________________________________
>> > fieldtrip mailing list
>> > fieldtrip at donders.ru.nl
>> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>>
>>
>> --
>> Aaron Schurger, PhD
>> Post-doctoral researcher
>> INSERM U992 / NeuroSpin
>> CEA - Saclay, France
>> +33-1-69-08-66-47
>> aaron.schurger at gmail.com
>> http://www.unicog.org
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
>
> --
> -------------------
> Karen Schuil
> PhD student
>
> Erasmus University Rotterdam
> Institute of Psychology, T 13-09
> Burgemeester Oudlaan 50
> P.O. Box 1738
> 3000 DR Rotterdam
> The Netherlands
> Phone: +31 (0) 10 408 2293
> Email:  schuil at fsw.eur.nl
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip



-- 
Aaron Schurger, PhD
Post-doctoral researcher
INSERM U992 / NeuroSpin
CEA - Saclay, France
+33-1-69-08-66-47
aaron.schurger at gmail.com
http://www.unicog.org


From eelke.spaak at donders.ru.nl  Tue Jun 18 10:29:34 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Tue, 18 Jun 2013 10:29:34 +0200
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
 average FieldTrip
In-Reply-To: <CAGnbK6gqEqLBXuATfXHzh2M7ofohp_z7=i8x=WQtX4RxPEMx6A@mail.gmail.com>
References: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
	<CALeeyASM1BMtZu5GUUQfDocnPq+S=bdJyUrx0AYhB2_ON95ODA@mail.gmail.com>
	<CAGnbK6gqEqLBXuATfXHzh2M7ofohp_z7=i8x=WQtX4RxPEMx6A@mail.gmail.com>
Message-ID: <CABPNLUomcmtO7B9phMmV9-aGAfJqURGjyxt-RV0v+z_RS_p4aA@mail.gmail.com>

Dear Karen,

It seems likely (as the other responses also indicate) that
BrainVision Analyzer is doing something to the data that FieldTrip is
not; in other words, the FieldTrip ERP is probably more 'pure'.
Therefore, perhaps it might be worth asking around on the BVA mailing
list if the people there know what BVA is doing to the data prior to
computing and displaying the average?

It is easy to check whether FieldTrip is doing something unexpected to
the data, by computing and plotting the average yourself:

erp = mean(cat(3, pp10_l.trial{:}), 3);
chanind = strmatch('AF7', pp10_l.label);
plot(pp10_l.time{1}, erp(chanind,:));

This only works if all trials have identical time axes, but judging
from your script I think they do. It the above steps give a different
plot than the FT functions, something is possibly (/probably) wrong in
the FT code.

Best,
Eelke

On 17 June 2013 15:22, Karen Schuil <schuil at fsw.eur.nl> wrote:
> Dear Jim, Aaron, Roemer and Tineke,
>
> Thanks for your quick response and suggestions! The whole preprocessing
> (including the filters) was done in BVA. After segmentatation of the
> conditions, we exported the data to Fieldtrip. The only steps we did in
> Fieldtrip was averaging, creating and plotting an ERP. Therefore it can't be
> the filters, right? Unless, the averaging step in BVA applies filters as
> well.
>
> The ref in AF7-ref is added by BVA and refers to the channels being linked
> to the mastoids.
>
> We have also tried it with subtracting a baseline, but this unfortunately
> did not help.
>
> Do you have any other suggestions?
>
> Cheers, Karen
>
>
>
>
> On Mon, Jun 17, 2013 at 2:25 PM, Aaron Schurger <aaron.schurger at gmail.com>
> wrote:
>>
>> To me it really looks like BVA is applying a high-pass filter at some
>> stage. When you export the data, the high-pass filter has probably
>> already been applied. It is typical in EEG (though not a good idea in
>> my opinion) to apply a high-pass filter with a cutoff at around 0.05
>> or 0.1 Hz. There should be a setting somewhere in BVA to turn off the
>> high-pass filter. Anyway, that's my guess just from looking at the
>> figure you attached.
>> Cheers,
>> Aaron
>>
>> On Mon, Jun 17, 2013 at 1:56 PM, Karen Schuil <karenschuil at gmail.com>
>> wrote:
>> > Dear Fieldtrip Users,
>> >
>> > I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision
>> > Analyser
>> > are different from the ERPS of FieldTrip. It seems that in Fieldtrip a
>> > slow
>> > negative drift is added and peaks are more/less pronounced than in BVA
>> > (attached is a picture of the two different plots).
>> >
>> > An expert FieldTrip User and I could not find a solution for this
>> > problem. I
>> > hope one of you has a suggestion for this problem.
>> >
>> > The individual trial data was exported from BVA (version 2.02.5859) with
>> > the
>> > following settings:
>> > File extension: .seg
>> > Write header file: yes
>> > Write marker file: yes
>> > Format: BINARY
>> > Orientation: MULTIPLEXED
>> > Line Delimiter: CRLF (PC style)
>> > Binary format: 16-Bit signed integer format
>> > Set resolution manually: no
>> > Individually optimized resolution for each channel: yes
>> > Convert to big-endian order: no
>> > Export all channels: no
>> > Export the following channels:
>> > AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5
>> > CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5
>> > FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5
>> > P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8
>> > Created Using Component Version 2.0.2.5827
>> >
>> > We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
>> > tried a version from 2011).
>> >
>> > The scripts we used are read_analyzer_data and timelockanalysis. This is
>> > the
>> > code we used for calling the scripts:
>> > % read data into fieldtrip
>> > cfg = [];
>> >
>> > cfg.inputfile = 'pp10_A';
>> > cfg.triggercode = 'S 20';
>> > cfg.triggertype = 'Stimulus';
>> > cfg.prestim = 1.2;
>> > cfg.poststim = 1.7;
>> >
>> > pp10_l = read_analyzer_data(cfg);
>> >
>> > % check: compute ERP
>> > %
>> > cfg = [];
>> > pp10_ERP = timelockanalysis(cfg, pp10_l);
>> >
>> > %plot ERP
>> >
>> > cfg = [];
>> > cfg.layout = 'elec1010.lay';
>> > cfg.xlim = [-0.15 1.7];
>> > cfg.ylim = [-12.25 12.25];
>> > % cfg.baseline = 'yes';
>> > % cfg.baselinetype = 'absolute';
>> > cfg.showlabels = 'yes';
>> > cfg.interactive = 'yes';
>> >
>> > multiplotER(cfg, pp10_ERP);
>> >
>> >
>> > I hope you can help!
>> >
>> > Kind regards,
>> > Karen
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> > _______________________________________________
>> > fieldtrip mailing list
>> > fieldtrip at donders.ru.nl
>> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>>
>>
>> --
>> Aaron Schurger, PhD
>> Post-doctoral researcher
>> INSERM U992 / NeuroSpin
>> CEA - Saclay, France
>> +33-1-69-08-66-47
>> aaron.schurger at gmail.com
>> http://www.unicog.org
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
>
> --
> -------------------
> Karen Schuil
> PhD student
>
> Erasmus University Rotterdam
> Institute of Psychology, T 13-09
> Burgemeester Oudlaan 50
> P.O. Box 1738
> 3000 DR Rotterdam
> The Netherlands
> Phone: +31 (0) 10 408 2293
> Email:  schuil at fsw.eur.nl
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From mje.mads at gmail.com  Tue Jun 18 10:44:01 2013
From: mje.mads at gmail.com (Mads Jensen)
Date: Tue, 18 Jun 2013 10:44:01 +0200
Subject: [FieldTrip] select trial by previous trigger code
Message-ID: <51C01DD1.5070005@gmail.com>

Hi all,

I would like to know if it is possible select a trail based on the 
previous trigger code?

I got a dataset (MEG, neuromeg) where sometimes the subject just press a 
button and sometimes a cue is shown and they then press the button, the 
button presses are coded "1" and the cue "2". So, what I would like is 
to datasets one with trials where there has been no cue and one dataset 
where the trials that have cue is. Is that possible to do automatically 
or do I have to do a "by hand"?

best wishes,
mads


From s.vanpelt at fcdonders.ru.nl  Tue Jun 18 11:11:06 2013
From: s.vanpelt at fcdonders.ru.nl (Stan van Pelt)
Date: Tue, 18 Jun 2013 11:11:06 +0200 (CEST)
Subject: [FieldTrip] select trial by previous trigger code
References: <51C01DD1.5070005@gmail.com> 
Message-ID: <03cc01ce6c03$c403fb20$4c0bf160$@vanpelt@fcdonders.ru.nl>

Dear Mads,

It is not possible to do this automatically. However, by writing your own
'trialfun', you should be able to program this in a relative
straightforward manner. You can enter this trialfun-name in the
cfg.trialfun configuration option when subsequently calling
ft_definetrial.
See
http://fieldtrip.fcdonders.nl/example/making_your_own_trialfun_for_conditi
onal_trial_definition

Best,
Stan

Stan van Pelt, PhD
Donders Institute for Brain, Cognition and Behaviour Centre for Cognition
Montessorilaan 3, B.01.19
6525 HR Nijmegen
tel: 024-3616288


-----Original Message-----
From: fieldtrip-bounces at science.ru.nl
[mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of Mads Jensen
Sent: dinsdag 18 juni 2013 10:44
To: FieldTrip discussion list
Subject: [FieldTrip] select trial by previous trigger code

Hi all,

I would like to know if it is possible select a trail based on the
previous trigger code?

I got a dataset (MEG, neuromeg) where sometimes the subject just press a
button and sometimes a cue is shown and they then press the button, the
button presses are coded "1" and the cue "2". So, what I would like is to
datasets one with trials where there has been no cue and one dataset where
the trials that have cue is. Is that possible to do automatically or do I
have to do a "by hand"?

best wishes,
mads
_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl
http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From jm.horschig at donders.ru.nl  Tue Jun 18 11:11:50 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Tue, 18 Jun 2013 11:11:50 +0200
Subject: [FieldTrip] select trial by previous trigger code
In-Reply-To: <51C01DD1.5070005@gmail.com>
References: <51C01DD1.5070005@gmail.com>
Message-ID: <51C02456.2000800@donders.ru.nl>

Hi Mads,

such things are possible if you write your own trial function. 
Basically, you need to read in the events (i.e. trigger values) and then 
make a selection based on that, see also here:
http://fieldtrip.fcdonders.nl/example/making_your_own_trialfun_for_conditional_trial_definition?s[]=trialfun
http://fieldtrip.fcdonders.nl/faq/what_is_the_relation_between_events_such_as_triggers_and_trials?s[]=trialfun

Hope that helps!
Best,
Jörn

On 6/18/2013 10:44 AM, Mads Jensen wrote:
> Hi all,
>
> I would like to know if it is possible select a trail based on the 
> previous trigger code?
>
> I got a dataset (MEG, neuromeg) where sometimes the subject just press 
> a button and sometimes a cue is shown and they then press the button, 
> the button presses are coded "1" and the cue "2". So, what I would 
> like is to datasets one with trials where there has been no cue and 
> one dataset where the trials that have cue is. Is that possible to do 
> automatically or do I have to do a "by hand"?
>
> best wishes,
> mads
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands



From yuvharpaz at gmail.com  Tue Jun 18 14:58:15 2013
From: yuvharpaz at gmail.com (Yuval Harpaz)
Date: Tue, 18 Jun 2013 15:58:15 +0300
Subject: [FieldTrip] fixed dipole orientation for MNE
Message-ID: <CAGQZS_m+RSW6LDOmbYc9MDtwf1dUM==a4c3Nc9BRA5WYneTp6w@mail.gmail.com>

Dear group
I would like to ask again (
http://mailman.science.ru.nl/pipermail/fieldtrip/2011-February/003456.html)
about head model with fixed dipole orientation (obtained from freesurfer),
as I saw no reply to the previous message.

I understand that there is no civilized way, currently, to tell MNE or
beamforming to use fixed orientation, or am I wrong?

applying 'sam' I managed to set dipole orinetation by making a dip.mom
field in addition to dip.pos and by
gain = lf;
instead of the existing
gain = lf * UnitMDip';
note that here lf is a vector (no 3 columns).

However this is patchy and not thorough. So can you please tell me if there
is a way to do it with regular ft functions?
thank you
Yuval




Dr .Harpaz

BIU MEG lab <http://faculty.biu.ac.il/~goldsa/index.html>
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From eelke.spaak at donders.ru.nl  Tue Jun 18 15:16:41 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Tue, 18 Jun 2013 15:16:41 +0200
Subject: [FieldTrip] fixed dipole orientation for MNE
In-Reply-To: <CAGQZS_m+RSW6LDOmbYc9MDtwf1dUM==a4c3Nc9BRA5WYneTp6w@mail.gmail.com>
References: <CAGQZS_m+RSW6LDOmbYc9MDtwf1dUM==a4c3Nc9BRA5WYneTp6w@mail.gmail.com>
Message-ID: <CABPNLUpqBxHFfrw=9mvesB2RXirhnyQH_-Mt5+icKA5HMcrkXQ@mail.gmail.com>

Dear Yuval,

The LCMV and DICS beamforming implementations in FieldTrip support
cfg.<method>.fixedori = 'yes', where <method> is either 'lcmv' or
'dics'. This will compute a filter which constrains each dipole to
point in the strongest orientation. For SAM I think this is not
implemented, and for MNE I have no clue.

Does this answer your question? Or are you lookling for another type
of fixed orientation, maybe based on anatomy or so?

Best,
Eelke

On 18 June 2013 14:58, Yuval Harpaz <yuvharpaz at gmail.com> wrote:
> Dear group
> I would like to ask again
> (http://mailman.science.ru.nl/pipermail/fieldtrip/2011-February/003456.html)
> about head model with fixed dipole orientation (obtained from freesurfer),
> as I saw no reply to the previous message.
>
> I understand that there is no civilized way, currently, to tell MNE or
> beamforming to use fixed orientation, or am I wrong?
>
> applying 'sam' I managed to set dipole orinetation by making a dip.mom field
> in addition to dip.pos and by
> gain = lf;
> instead of the existing
> gain = lf * UnitMDip';
> note that here lf is a vector (no 3 columns).
>
> However this is patchy and not thorough. So can you please tell me if there
> is a way to do it with regular ft functions?
> thank you
> Yuval
>
>
>
>
> Dr .Harpaz
>
> BIU MEG lab
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From yuvharpaz at gmail.com  Tue Jun 18 19:01:40 2013
From: yuvharpaz at gmail.com (Yuval Harpaz)
Date: Tue, 18 Jun 2013 20:01:40 +0300
Subject: [FieldTrip] fixed dipole orientation for MNE
In-Reply-To: <CABPNLUpqBxHFfrw=9mvesB2RXirhnyQH_-Mt5+icKA5HMcrkXQ@mail.gmail.com>
References: <CAGQZS_m+RSW6LDOmbYc9MDtwf1dUM==a4c3Nc9BRA5WYneTp6w@mail.gmail.com>
	<CABPNLUpqBxHFfrw=9mvesB2RXirhnyQH_-Mt5+icKA5HMcrkXQ@mail.gmail.com>
Message-ID: <CAGQZS_=G15YJw-Cc+aQrHhwSXq9pXC8P5qrCpbU8LAkqkMCBUg@mail.gmail.com>

Well, it uses fixed orientation but it calculates the orientation based on
the signal, not on the anatomy. I am trying to reduce leakage problems by
limiting orientation according to structure. you CAN specify dip.mom but
this is really buggy.
thanks


On 18 June 2013 16:16, Eelke Spaak <eelke.spaak at donders.ru.nl> wrote:

> Dear Yuval,
>
> The LCMV and DICS beamforming implementations in FieldTrip support
> cfg.<method>.fixedori = 'yes', where <method> is either 'lcmv' or
> 'dics'. This will compute a filter which constrains each dipole to
> point in the strongest orientation. For SAM I think this is not
> implemented, and for MNE I have no clue.
>
> Does this answer your question? Or are you lookling for another type
> of fixed orientation, maybe based on anatomy or so?
>
> Best,
> Eelke
>
> On 18 June 2013 14:58, Yuval Harpaz <yuvharpaz at gmail.com> wrote:
> > Dear group
> > I would like to ask again
> > (
> http://mailman.science.ru.nl/pipermail/fieldtrip/2011-February/003456.html
> )
> > about head model with fixed dipole orientation (obtained from
> freesurfer),
> > as I saw no reply to the previous message.
> >
> > I understand that there is no civilized way, currently, to tell MNE or
> > beamforming to use fixed orientation, or am I wrong?
> >
> > applying 'sam' I managed to set dipole orinetation by making a dip.mom
> field
> > in addition to dip.pos and by
> > gain = lf;
> > instead of the existing
> > gain = lf * UnitMDip';
> > note that here lf is a vector (no 3 columns).
> >
> > However this is patchy and not thorough. So can you please tell me if
> there
> > is a way to do it with regular ft functions?
> > thank you
> > Yuval
> >
> >
> >
> >
> > Dr .Harpaz
> >
> > BIU MEG lab
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
Yuval




Dr .Harpaz

BIU MEG lab <http://faculty.biu.ac.il/~goldsa/index.html>
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From mje.mads at gmail.com  Tue Jun 18 23:52:02 2013
From: mje.mads at gmail.com (Mads Jensen)
Date: Tue, 18 Jun 2013 23:52:02 +0200
Subject: [FieldTrip] select trial by previous trigger code
In-Reply-To: <51C02456.2000800@donders.ru.nl>
References: <51C01DD1.5070005@gmail.com> <51C02456.2000800@donders.ru.nl>
Message-ID: <51C0D682.7070008@gmail.com>

HI Jörn & Stan,

Thanks for your replies and advises. It worked.

thanks, best
mads



On 06/18/2013 11:11 AM, "Jörn M. Horschig" wrote:
> Hi Mads,
>
> such things are possible if you write your own trial function.
> Basically, you need to read in the events (i.e. trigger values) and then
> make a selection based on that, see also here:
> http://fieldtrip.fcdonders.nl/example/making_your_own_trialfun_for_conditional_trial_definition?s[]=trialfun
>
> http://fieldtrip.fcdonders.nl/faq/what_is_the_relation_between_events_such_as_triggers_and_trials?s[]=trialfun
>
>
> Hope that helps!
> Best,
> Jörn
>
> On 6/18/2013 10:44 AM, Mads Jensen wrote:
>> Hi all,
>>
>> I would like to know if it is possible select a trail based on the
>> previous trigger code?
>>
>> I got a dataset (MEG, neuromeg) where sometimes the subject just press
>> a button and sometimes a cue is shown and they then press the button,
>> the button presses are coded "1" and the cue "2". So, what I would
>> like is to datasets one with trials where there has been no cue and
>> one dataset where the trials that have cue is. Is that possible to do
>> automatically or do I have to do a "by hand"?
>>
>> best wishes,
>> mads
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>


From marco.porta88 at gmail.com  Wed Jun 19 16:41:47 2013
From: marco.porta88 at gmail.com (Marco Porta)
Date: Wed, 19 Jun 2013 16:41:47 +0200
Subject: [FieldTrip] statistics on non-event-related fields
Message-ID: <CAP6m0dHxFfYpYHFqeSMf83drbHD8TxU=9LqO8eAr8K0QC4mdNw@mail.gmail.com>

Dear Fieldtrip experts,
I have a question regarding the statistics. How can I statistics on non
event-related fields in a between-trials.
Thanks,

Marco
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From eelke.spaak at donders.ru.nl  Wed Jun 19 16:50:48 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Wed, 19 Jun 2013 16:50:48 +0200
Subject: [FieldTrip] statistics on non-event-related fields
In-Reply-To: <CAP6m0dHxFfYpYHFqeSMf83drbHD8TxU=9LqO8eAr8K0QC4mdNw@mail.gmail.com>
References: <CAP6m0dHxFfYpYHFqeSMf83drbHD8TxU=9LqO8eAr8K0QC4mdNw@mail.gmail.com>
Message-ID: <CABPNLUp6KKoApdcKEXJ2EFY29=JoXPJD+utHZ+jpcR3x0pW2=g@mail.gmail.com>

Dear Marco,

What do you mean exactly with "non event-related fields"? I presume
there is some structure in your data that you want to consider as the
independent variable of interest, right? Some more information on what
you want to do would help us to help you.

Best,
Eelke

On 19 June 2013 16:41, Marco Porta <marco.porta88 at gmail.com> wrote:
> Dear Fieldtrip experts,
> I have a question regarding the statistics. How can I statistics on non
> event-related fields in a between-trials.
> Thanks,
>
> Marco
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From jdien07 at mac.com  Thu Jun 20 02:35:35 2013
From: jdien07 at mac.com (Joseph Dien)
Date: Wed, 19 Jun 2013 20:35:35 -0400
Subject: [FieldTrip] ft_dipolefitting options no longer working
Message-ID: <C1AE459D-6A06-4743-ABD1-CAE20510BD28@mac.com>

Hi,
    it looks like changes have been made to ft_dipolefitting that have resulted in the following options no longer working:

        cfg.grid.xgrid  = 'auto';
        cfg.grid.ygrid  = 'auto';
        cfg.grid.zgrid  = 'auto';

The header of the ft_dipolefitting file as of the 20130619 release says:

% This function depends on FT_PREPARE_DIPOLE_GRID which has the following options:
% cfg.grid.xgrid (default set in FT_PREPARE_DIPOLE_GRID: cfg.grid.xgrid = 'auto'), documented
% cfg.grid.ygrid (default set in FT_PREPARE_DIPOLE_GRID: cfg.grid.ygrid = 'auto'), documented
% cfg.grid.zgrid (default set in FT_PREPARE_DIPOLE_GRID: cfg.grid.zgrid = 'auto'), documented

but a Find Files search indicates that FT_PREPARE_DIPOLE_GRID no longer exists.

I don't have copies of FieldTrip older than Feb 2013 so I can't check directly but I know that my function call used to work and no longer does.

Can someone help me find a fix for this?

Any help appreciated!

Joe

--------------------------------------------------------------------------------

Joseph Dien,
Senior Research Scientist
University of Maryland 

E-mail: jdien07 at mac.com
Phone: 301-226-8848
Fax: 301-226-8811
http://joedien.com//











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From jdien07 at mac.com  Thu Jun 20 04:41:49 2013
From: jdien07 at mac.com (Joseph Dien)
Date: Wed, 19 Jun 2013 22:41:49 -0400
Subject: [FieldTrip] ft_dipolefitting options no longer working
In-Reply-To: <C1AE459D-6A06-4743-ABD1-CAE20510BD28@mac.com>
References: <C1AE459D-6A06-4743-ABD1-CAE20510BD28@mac.com>
Message-ID: <B8CFEB76-33B2-474E-856C-4ABE53E5290C@mac.com>

Okay, I got this sorted out.  I was able to use ft_prepare_sourcemodel to set up the config variable.
The header info of ft_dipolefitting should get updated though.

Cheers!

Joe

On Jun 19, 2013, at 8:35 PM, Joseph Dien <jdien07 at mac.com> wrote:

> Hi,
>     it looks like changes have been made to ft_dipolefitting that have resulted in the following options no longer working:
> 
>         cfg.grid.xgrid  = 'auto';
>         cfg.grid.ygrid  = 'auto';
>         cfg.grid.zgrid  = 'auto';
> 
> The header of the ft_dipolefitting file as of the 20130619 release says:
> 
> % This function depends on FT_PREPARE_DIPOLE_GRID which has the following options:
> % cfg.grid.xgrid (default set in FT_PREPARE_DIPOLE_GRID: cfg.grid.xgrid = 'auto'), documented
> % cfg.grid.ygrid (default set in FT_PREPARE_DIPOLE_GRID: cfg.grid.ygrid = 'auto'), documented
> % cfg.grid.zgrid (default set in FT_PREPARE_DIPOLE_GRID: cfg.grid.zgrid = 'auto'), documented
> 
> but a Find Files search indicates that FT_PREPARE_DIPOLE_GRID no longer exists.
> 
> I don't have copies of FieldTrip older than Feb 2013 so I can't check directly but I know that my function call used to work and no longer does.
> 
> Can someone help me find a fix for this?
> 
> Any help appreciated!
> 
> Joe
> 
> --------------------------------------------------------------------------------
> 
> Joseph Dien,
> Senior Research Scientist
> University of Maryland 
> 
> E-mail: jdien07 at mac.com
> Phone: 301-226-8848
> Fax: 301-226-8811
> http://joedien.com//
> 
> 
> 
> 
> 
> 
> 
> 
> 
> 
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


--------------------------------------------------------------------------------

Joseph Dien,
Senior Research Scientist
University of Maryland 

E-mail: jdien07 at mac.com
Phone: 301-226-8848
Fax: 301-226-8811
http://joedien.com//











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From marco.porta88 at gmail.com  Thu Jun 20 14:48:18 2013
From: marco.porta88 at gmail.com (Marco Porta)
Date: Thu, 20 Jun 2013 14:48:18 +0200
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 37
In-Reply-To: <mailman.1.1371722418.14241.fieldtrip@science.ru.nl>
References: <mailman.1.1371722418.14241.fieldtrip@science.ru.nl>
Message-ID: <CAP6m0dGkRm0uo+zweS10nmv6Oj-c-_gmFapqNRDyg9TL3SVE+A@mail.gmail.com>

Dear Users and Eelke,
I have spontaneous LFP data recorded intracranially. I'm interested in
studying phase correlation between sensors and assess such correlation
within single subjects studies. Is it possible to study statistical
significance in such correlation study or should i implement my own
statistic?
Thanks,

Marco



Dear Marco,
>
> What do you mean exactly with "non event-related fields"? I presume
> there is some structure in your data that you want to consider as the
> independent variable of interest, right? Some more information on what
> you want to do would help us to help you.
>
> Best,
> Eelke
>
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From marco.porta88 at gmail.com  Fri Jun 21 14:26:12 2013
From: marco.porta88 at gmail.com (Marco Porta)
Date: Fri, 21 Jun 2013 14:26:12 +0200
Subject: [FieldTrip] statistics on non-event-related fields
Message-ID: <CAP6m0dGJTG=i9dFLsOhL4o9+wp_TXZfMYOa2917ik2TGu-dJeg@mail.gmail.com>

Dear Users and Eelke,
I have spontaneous LFP data recorded intracranially. I'm interested in studying
phase correlation between sensors and assess such correlation within single
subjects studies. Is it possible to study statistical significance in such
correlation study or should i implement my own statistic?
Thanks,

Marco



> Dear Marco,
>
> What do you mean exactly with "non event-related fields"? I presume
> there is some structure in your data that you want to consider as the
> independent variable of interest, right? Some more information on what
> you want to do would help us to help you.
>
> Best,
> Eelke
>
>
>
>
> Dear Fieldtrip experts,
> I have a question regarding the statistics. How can I statistics on non
> event-related fields in a between-trials.
> Thanks,
> Marco
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From politzerahless at gmail.com  Fri Jun 21 20:42:32 2013
From: politzerahless at gmail.com (Stephen Politzer-Ahles)
Date: Fri, 21 Jun 2013 13:42:32 -0500
Subject: [FieldTrip] Using fsaverage in the minimum norm pipeline?
Message-ID: <CAJT2k_8-nPkauRD0ciptFjPJtqbXTXv-0Xnj5GNw1aJ2LR6LJA@mail.gmail.com>

Hello everyone,

I am working through the minimum norm pipeline (
http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate) on functional
data for multiple participants; for all but one of these participants I
also have anatomical MRI. For the one participant for whom I couldn't get
an MRI, I was hoping to use the freesurfer average surface (fsaverage), but
I'm having some difficulty getting volume conduction models and
sourcespaces from this brain aligned to CTF.

Basically, I'm able to read in the data and create a sourcespace and volume
conduction model using the code below. These models seem to be aligned to
MNI (see the axes on http://i.imgur.com/g0DPs8A.png). To to re-align them
to CTF, what I tried to do was manually do ft_volumerealign on the original
anatomical MRI, and then apply that transformation matrix (which I assume
specifies the transformation from MNI to CTF) to the sourcespace and volume
conductor (in the third and fourth blocks of code below). But the resulting
sourcespace and volume conductor are clearly not aligned to CTF (see the
axes on http://i.imgur.com/MAjyDkL.png), so I assume I am doing something
wrong with the transformation matrix. I admit I do not fully understand how
the transformation matrix is supposed to work, so if anyone has any
feedback I would greatly appreciate it.

Thank you!
Steve


% Read the source space
bnd  =
ft_read_headshape('/tools/freesurfer/subjects/fsaverage/bem/fsaverage-oct-6-src.fif',
'format', 'mne_source');
sourcespace = ft_convert_units(bnd, 'mm');

% Read in the anatomical MRI, segment, and make volume conduction model
fsaverage = ft_read_mri('orig.mgz');
cfg           = [];
cfg.coordsys  = 'spm';
cfg.output    = {'skullstrip' 'brain'};
seg = ft_volumesegment( cfg, fsaverage);
cfg = []
cfg.method = 'singleshell';
cfg.tissue = 'brain';
vol = ft_prepare_headmodel( cfg, seg );

% Get a transformation matrix from MNI to CTF
cfg = [];
cfg.method = 'interactive';
seg_ctf = ft_volumerealign(cfg2, seg); % manually identify NAS, LAP, and RAP
T = seg_ctf.transform;

% Transform the sourcespace and vol
sourcespace_trans = ft_transform_geometry( T, sourcespace );
vol_trans = vol;
vol_trans.bnd = ft_transform_geometry( T, vol_trans.bnd );

% Plot the un-transformed vol and sourcespace (aligned to MNI)
figure;hold on;
ft_plot_vol(vol, 'facecolor', 'none');alpha 0.5;
ft_plot_mesh(sourcespace, 'edgecolor', 'none'); camlight

% Plot the transformed vol and sourcespace
figure;hold on;
ft_plot_vol(vol_trans, 'facecolor', 'none');alpha 0.5;
ft_plot_mesh(sourcespace_trans, 'edgecolor', 'none'); camlight



--
Stephen Politzer-Ahles
University of Kansas
Linguistics Department
http://people.ku.edu/~sjpa/
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From polomacnenad at gmail.com  Sat Jun 22 13:34:56 2013
From: polomacnenad at gmail.com (Nenad Polomac)
Date: Sat, 22 Jun 2013 13:34:56 +0200
Subject: [FieldTrip] padding of segmented data
Message-ID: <CAEk4EpFoOvobO+Ay2GQgx9k4h3g1wZAOoHoZ-t8u-qSodoYN5A@mail.gmail.com>

Dear all,

In my pipeline I need two times to filter data with ft_preprocessing. Is it
somehow possible to pad trials after segmentation? I need this in order to
avoid filter artifacts during the second filtering.

Thank you in advance!

Nenad
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From caspervanheck at gmail.com  Sat Jun 22 14:32:45 2013
From: caspervanheck at gmail.com (Casper van Heck)
Date: Sat, 22 Jun 2013 14:32:45 +0200
Subject: [FieldTrip] padding of segmented data
In-Reply-To: <CAEk4EpFoOvobO+Ay2GQgx9k4h3g1wZAOoHoZ-t8u-qSodoYN5A@mail.gmail.com>
References: <CAEk4EpFoOvobO+Ay2GQgx9k4h3g1wZAOoHoZ-t8u-qSodoYN5A@mail.gmail.com>
Message-ID: <CAJ7RtREwKrgNVCko=XkrjofHJduL64iEU0mESovdcrXqsm7M0A@mail.gmail.com>

Dear Nenad,

I think the option cfg.padding only works for that iteration of
ft_preprocessing, but what you can do, is select larger segments initially,
and then run ft_preprocessing again with smaller segments.

While you can set ft_preprocessing to apply multiple different filters in
one go (like a low-pass, a high-pass, and a DFT-filter, for example), using
a similar filter multiple times (like a high-pass filter at 4Hz, and
another at 8Hz) is usually not required, or recommended. If you do multiple
analyses on the same data (which, for example, require different filters)
you could find it useful to create multiple smaller pipelines with their
own ft_preprocessing. Debugging complex analyses can be a lot easier that
way:)

Hope this helps,

Casper


On Sat, Jun 22, 2013 at 1:34 PM, Nenad Polomac <polomacnenad at gmail.com>wrote:

> Dear all,
>
> In my pipeline I need two times to filter data with ft_preprocessing. Is
> it somehow possible to pad trials after segmentation? I need this in order
> to avoid filter artifacts during the second filtering.
>
> Thank you in advance!
>
> Nenad
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From mbj0310 at gmail.com  Mon Jun 24 06:27:47 2013
From: mbj0310 at gmail.com (Beom Jun Min)
Date: Mon, 24 Jun 2013 13:27:47 +0900
Subject: [FieldTrip] Decreased baseline level after using ICA in ERP data
Message-ID: <CA+v9jvKJnKAfsQDwoDhNVSPAKCmpOpwut8vdmFXa1akp_1WDGA@mail.gmail.com>

Dear all,

I have ERP data and now I am dealing with ICA to remove muscle and eye
artifacts.
However, I found that after ft_rejectcomponent, the baseline level of the
segmented epoch decreased. (The baselinewindow is [-0.2 0].)
The baseline level decreased even though I rejected only one component.

My script is shown below.

*%% Removing the Artifacts*
*cfg = [];
*
*cfg.component = [ ]; % to be removed component(s)*
*post_ICA_temp6 = ft_rejectcomponent(cfg, comp_detrand, data_raw);*
*
*
*%% timelocking*
*
*
*cfg = [];*
*timelock_temp6 = ft_timelockanalysis(cfg, post_ICA_temp6);*
*
*
*%% Plot*
*
*
*figure;*
*cfg = [];*
*cfg.layout = lay;*
*cfg.interactive = 'yes';*
*cfg.channel = ['all', {'-EKG', '-EMG'}];*
*ft_multiplotER(cfg, timelock_temp6)*

Is there something that I missed?

Thanks.

BJ

-- 
BeomJun Min, M.D.

Department of Medical System Engineering (DMSE)
Gwangju Institute of Science and Technology (GIST)
261 Cheomdan-gwagiro(Oryong-dong), Buk-gu, Gwangju
500-712, Republic of Korea (South)
Phone: +82-62-715-3266 / Fax: +82-62-715-3244
E-mail: mbj0310 at gmail.com, http://bmssa.gist.ac.kr
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From d.lozanosoldevilla at fcdonders.ru.nl  Mon Jun 24 10:25:24 2013
From: d.lozanosoldevilla at fcdonders.ru.nl (Lozano Soldevilla, D. (Diego))
Date: Mon, 24 Jun 2013 10:25:24 +0200 (CEST)
Subject: [FieldTrip] Decreased baseline level after using ICA in ERP data
In-Reply-To: <CA+v9jvKJnKAfsQDwoDhNVSPAKCmpOpwut8vdmFXa1akp_1WDGA@mail.gmail.com>
Message-ID: <831995030.1708865.1372062324986.JavaMail.root@sculptor.zimbra.ru.nl>

Dear Beom Jun, I see multiple scenarios why this baseline activity decrease could happen. First of all, how the component you're rejecting look like (i.e. "blink component")? Do you see this activity decrease after the baseline period? The "quality" of the ICA decomposition, how well your artifact/component of interest has been isolated by algorithm in time (i.e. blink time courses) and space (marked frontal topography), will determine the activity that later on you'll reject/select. If your decomposition is not well suited, the rejection of a particular IC activity might have "extra" activity you don't want to reject (effect of interest), might be the algorithm is not able to isolate the components of interests (i.e. artifacts) or a combination of both. To evaluate the quality of your ICA decomposition you might have a look here ( http://www.ncbi.nlm.nih.gov/pubmed/19162199 ). Basically, the authors find that the ICA decomposition improves significantly " increased by removing the mean EEG at each channel for each epoch of data rather than the mean EEG in a prestimulus baseline" . In addition (see here: http://sccn.ucsd.edu/pipermail/eeglablist/2012/004925.html ), high-pass filtering above ~1hz improve the results. It's very important to feed ICA as much relevant data as you can use. The more the data, the better the decomposition. There's a rule of thumb that says that for a reliable IC decomposition 20 time points per channel 2 is needed (see here for a reference http://www.ncbi.nlm.nih.gov/pubmed/16904745 ) I hope that helps, Diego ----- Original Message -----
> From: "Beom Jun Min" <mbj0310 at gmail.com>
> To: "FieldTrip discussion list" <fieldtrip at science.ru.nl>
> Sent: Monday, 24 June, 2013 6:27:47 AM
> Subject: [FieldTrip] Decreased baseline level after using ICA in ERP
> data
> Dear all,
> I have ERP data and now I am dealing with ICA to remove muscle and eye
> artifacts.
> However, I found that after ft_rejectcomponent, the baseline level of
> the segmented epoch decreased. (The baselinewindow is [-0.2 0].)
> The baseline level decreased even though I rejected only one
> component.
> My script is shown below.
> %% Removing the Artifacts
> cfg = [];
> cfg.component = [ ]; % to be removed component(s)
> post_ICA_temp6 = ft_rejectcomponent(cfg, comp_detrand, data_raw);
> %% timelocking
> cfg = [];
> timelock_temp6 = ft_timelockanalysis(cfg, post_ICA_temp6);
> %% Plot
> figure;
> cfg = [];
> cfg.layout = lay;
> cfg.interactive = 'yes';
> cfg.channel = ['all', {'-EKG', '-EMG'}];
> ft_multiplotER(cfg, timelock_temp6)
> Is there something that I missed?
> Thanks.
> BJ
> --
> BeomJun Min, M.D.
> Department of Medical System Engineering (DMSE)
> Gwangju Institute of Science and Technology (GIST)
> 261 Cheomdan-gwagiro(Oryong-dong), Buk-gu, Gwangju
> 500-712, Republic of Korea (South)
> Phone: +82-62-715-3266 / Fax: +82-62-715-3244
> E-mail: mbj0310 at gmail.com , http://bmssa.gist.ac.kr
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
-- PhD Student Neuronal Oscillations Group Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen NL-6525 EN Nijmegen The Netherlands http://www.ru.nl/people/donders/lozano-soldevilla-d/
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From jm.horschig at donders.ru.nl  Mon Jun 24 10:43:11 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Mon, 24 Jun 2013 10:43:11 +0200
Subject: [FieldTrip] padding of segmented data
In-Reply-To: <CAJ7RtREwKrgNVCko=XkrjofHJduL64iEU0mESovdcrXqsm7M0A@mail.gmail.com>
References: <CAEk4EpFoOvobO+Ay2GQgx9k4h3g1wZAOoHoZ-t8u-qSodoYN5A@mail.gmail.com>
	<CAJ7RtREwKrgNVCko=XkrjofHJduL64iEU0mESovdcrXqsm7M0A@mail.gmail.com>
Message-ID: <51C8069F.5070707@donders.ru.nl>

Hi Nenad,

what Casper said is not quite true. You can pad segmented trials, but 
you are limited in how to pad. There are different ways of padding, and 
what Casper was referring to is true data padding. Once you segmented 
your trials you cannot get back to your recorded data and attach more 
data to it. This is because filtering artifacts at edges etc would 
result in discontinuities and the like. However, there are other ways to 
achieve what you want. The most elegant way in my opinion is what Casper 
already suggested. Just for completeness, you can still pad using 
zero-padding (i.e. adding a bunch of 0s in the beginning and at the end 
of your trials). Other ways are mean-padding (pad with the mean value), 
or edge-padding (using the first/last value to padding). However, with 
all these methods you mostly also add a discontinuity, but you 
explicitly ask for that in this case :) The most elegant solution here 
might be to use mirror-padding, which is recently implemented.
See here:
http://fieldtrip.fcdonders.nl/reference/ft_preprocessing
and here:
http://fieldtrip.fcdonders.nl/reference/ft_preproc_padding

Best,
Jörn

On 6/22/2013 2:32 PM, Casper van Heck wrote:
> Dear Nenad,
>
> I think the option cfg.padding only works for that iteration of 
> ft_preprocessing, but what you can do, is select larger segments 
> initially, and then run ft_preprocessing again with smaller segments.
>
> While you can set ft_preprocessing to apply multiple different filters 
> in one go (like a low-pass, a high-pass, and a DFT-filter, for 
> example), using a similar filter multiple times (like a high-pass 
> filter at 4Hz, and another at 8Hz) is usually not required, or 
> recommended. If you do multiple analyses on the same data (which, for 
> example, require different filters) you could find it useful to create 
> multiple smaller pipelines with their own ft_preprocessing. Debugging 
> complex analyses can be a lot easier that way:)
>
> Hope this helps,
>
> Casper
>
>
> On Sat, Jun 22, 2013 at 1:34 PM, Nenad Polomac <polomacnenad at gmail.com 
> <mailto:polomacnenad at gmail.com>> wrote:
>
>     Dear all,
>
>     In my pipeline I need two times to filter data with
>     ft_preprocessing. Is it somehow possible to pad trials
>     after segmentation? I need this in order to avoid filter artifacts
>     during the second filtering.
>
>     Thank you in advance!
>
>     Nenad
>
>     _______________________________________________
>     fieldtrip mailing list
>     fieldtrip at donders.ru.nl <mailto:fieldtrip at donders.ru.nl>
>     http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands

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From polomacnenad at gmail.com  Mon Jun 24 11:02:18 2013
From: polomacnenad at gmail.com (Nenad Polomac)
Date: Mon, 24 Jun 2013 11:02:18 +0200
Subject: [FieldTrip] padding of segmented data
Message-ID: <CAEk4EpHDCCqhQvGRLShGfFU98Q2ccCsy1D=CRbadOzJf6G3ReA@mail.gmail.com>

Hi Jörn and Casper,

Thank you very for your answers
I will use Jörns suggestion. I wasn't aware that you upgraded
ft_preprocessing.
All the best!

Nenad

On 24 June 2013 10:44, <fieldtrip-request at science.ru.nl> wrote:

> Send fieldtrip mailing list submissions to
>         fieldtrip at science.ru.nl
>
> To subscribe or unsubscribe via the World Wide Web, visit
>         http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> or, via email, send a message with subject or body 'help' to
>         fieldtrip-request at science.ru.nl
>
> You can reach the person managing the list at
>         fieldtrip-owner at science.ru.nl
>
> When replying, please edit your Subject line so it is more specific
> than "Re: Contents of fieldtrip digest..."
>
>
> Today's Topics:
>
>    1. Decreased baseline level after using ICA in ERP data
>       (Beom Jun Min)
>    2. Re: Decreased baseline level after using ICA in ERP data
>       (Lozano Soldevilla, D. (Diego))
>    3. Re: padding of segmented data (J?rn M. Horschig)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Mon, 24 Jun 2013 13:27:47 +0900
> From: Beom Jun Min <mbj0310 at gmail.com>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: [FieldTrip] Decreased baseline level after using ICA in ERP
>         data
> Message-ID:
>         <
> CA+v9jvKJnKAfsQDwoDhNVSPAKCmpOpwut8vdmFXa1akp_1WDGA at mail.gmail.com>
> Content-Type: text/plain; charset="iso-8859-1"
>
> Dear all,
>
> I have ERP data and now I am dealing with ICA to remove muscle and eye
> artifacts.
> However, I found that after ft_rejectcomponent, the baseline level of the
> segmented epoch decreased. (The baselinewindow is [-0.2 0].)
> The baseline level decreased even though I rejected only one component.
>
> My script is shown below.
>
> *%% Removing the Artifacts*
> *cfg = [];
> *
> *cfg.component = [ ]; % to be removed component(s)*
> *post_ICA_temp6 = ft_rejectcomponent(cfg, comp_detrand, data_raw);*
> *
> *
> *%% timelocking*
> *
> *
> *cfg = [];*
> *timelock_temp6 = ft_timelockanalysis(cfg, post_ICA_temp6);*
> *
> *
> *%% Plot*
> *
> *
> *figure;*
> *cfg = [];*
> *cfg.layout = lay;*
> *cfg.interactive = 'yes';*
> *cfg.channel = ['all', {'-EKG', '-EMG'}];*
> *ft_multiplotER(cfg, timelock_temp6)*
>
> Is there something that I missed?
>
> Thanks.
>
> BJ
>
> --
> BeomJun Min, M.D.
>
> Department of Medical System Engineering (DMSE)
> Gwangju Institute of Science and Technology (GIST)
> 261 Cheomdan-gwagiro(Oryong-dong), Buk-gu, Gwangju
> 500-712, Republic of Korea (South)
> Phone: +82-62-715-3266 / Fax: +82-62-715-3244
> E-mail: mbj0310 at gmail.com, http://bmssa.gist.ac.kr
> -------------- next part --------------
> An HTML attachment was scrubbed...
> URL: <
> http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20130624/02dd2d57/attachment-0001.html
> >
>
> ------------------------------
>
> Message: 2
> Date: Mon, 24 Jun 2013 10:25:24 +0200 (CEST)
> From: "Lozano Soldevilla, D. (Diego)"
>         <d.lozanosoldevilla at fcdonders.ru.nl>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] Decreased baseline level after using ICA in
>         ERP data
> Message-ID:
>         <
> 831995030.1708865.1372062324986.JavaMail.root at sculptor.zimbra.ru.nl>
> Content-Type: text/plain; charset="utf-8"
>
> Dear Beom Jun, I see multiple scenarios why this baseline activity
> decrease could happen. First of all, how the component you're rejecting
> look like (i.e. "blink component")? Do you see this activity decrease after
> the baseline period? The "quality" of the ICA decomposition, how well your
> artifact/component of interest has been isolated by algorithm in time (i.e.
> blink time courses) and space (marked frontal topography), will determine
> the activity that later on you'll reject/select. If your decomposition is
> not well suited, the rejection of a particular IC activity might have
> "extra" activity you don't want to reject (effect of interest), might be
> the algorithm is not able to isolate the components of interests (i.e.
> artifacts) or a combination of both. To evaluate the quality of your ICA
> decomposition you might have a look here (
> http://www.ncbi.nlm.nih.gov/pubmed/19162199 ). Basically, the authors
> find that the ICA decomposition improves significantly " increased by
> removing the mean EEG at each channel for each epoch of data rather than
> the mean EEG in a prestimulus baseline" . In addition (see here:
> http://sccn.ucsd.edu/pipermail/eeglablist/2012/004925.html ), high-pass
> filtering above ~1hz improve the results. It's very important to feed ICA
> as much relevant data as you can use. The more the data, the better the
> decomposition. There's a rule of thumb that says that for a reliable IC
> decomposition 20 time points per channel 2 is needed (see here for a
> reference http://www.ncbi.nlm.nih.gov/pubmed/16904745 ) I hope that
> helps, Diego ----- Original Message -----
> > From: "Beom Jun Min" <mbj0310 at gmail.com>
> > To: "FieldTrip discussion list" <fieldtrip at science.ru.nl>
> > Sent: Monday, 24 June, 2013 6:27:47 AM
> > Subject: [FieldTrip] Decreased baseline level after using ICA in ERP
> > data
> > Dear all,
> > I have ERP data and now I am dealing with ICA to remove muscle and eye
> > artifacts.
> > However, I found that after ft_rejectcomponent, the baseline level of
> > the segmented epoch decreased. (The baselinewindow is [-0.2 0].)
> > The baseline level decreased even though I rejected only one
> > component.
> > My script is shown below.
> > %% Removing the Artifacts
> > cfg = [];
> > cfg.component = [ ]; % to be removed component(s)
> > post_ICA_temp6 = ft_rejectcomponent(cfg, comp_detrand, data_raw);
> > %% timelocking
> > cfg = [];
> > timelock_temp6 = ft_timelockanalysis(cfg, post_ICA_temp6);
> > %% Plot
> > figure;
> > cfg = [];
> > cfg.layout = lay;
> > cfg.interactive = 'yes';
> > cfg.channel = ['all', {'-EKG', '-EMG'}];
> > ft_multiplotER(cfg, timelock_temp6)
> > Is there something that I missed?
> > Thanks.
> > BJ
> > --
> > BeomJun Min, M.D.
> > Department of Medical System Engineering (DMSE)
> > Gwangju Institute of Science and Technology (GIST)
> > 261 Cheomdan-gwagiro(Oryong-dong), Buk-gu, Gwangju
> > 500-712, Republic of Korea (South)
> > Phone: +82-62-715-3266 / Fax: +82-62-715-3244
> > E-mail: mbj0310 at gmail.com , http://bmssa.gist.ac.kr
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> -- PhD Student Neuronal Oscillations Group Donders Institute for Brain,
> Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud
> University Nijmegen NL-6525 EN Nijmegen The Netherlands
> http://www.ru.nl/people/donders/lozano-soldevilla-d/
> -------------- next part --------------
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> URL: <
> http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20130624/ea1393f7/attachment-0001.html
> >
>
> ------------------------------
>
> Message: 3
> Date: Mon, 24 Jun 2013 10:43:11 +0200
> From: "J?rn M. Horschig" <jm.horschig at donders.ru.nl>
> To: fieldtrip at science.ru.nl
> Subject: Re: [FieldTrip] padding of segmented data
> Message-ID: <51C8069F.5070707 at donders.ru.nl>
> Content-Type: text/plain; charset="iso-8859-1"; Format="flowed"
>
> Hi Nenad,
>
> what Casper said is not quite true. You can pad segmented trials, but
> you are limited in how to pad. There are different ways of padding, and
> what Casper was referring to is true data padding. Once you segmented
> your trials you cannot get back to your recorded data and attach more
> data to it. This is because filtering artifacts at edges etc would
> result in discontinuities and the like. However, there are other ways to
> achieve what you want. The most elegant way in my opinion is what Casper
> already suggested. Just for completeness, you can still pad using
> zero-padding (i.e. adding a bunch of 0s in the beginning and at the end
> of your trials). Other ways are mean-padding (pad with the mean value),
> or edge-padding (using the first/last value to padding). However, with
> all these methods you mostly also add a discontinuity, but you
> explicitly ask for that in this case :) The most elegant solution here
> might be to use mirror-padding, which is recently implemented.
> See here:
> http://fieldtrip.fcdonders.nl/reference/ft_preprocessing
> and here:
> http://fieldtrip.fcdonders.nl/reference/ft_preproc_padding
>
> Best,
> J?rn
>
> On 6/22/2013 2:32 PM, Casper van Heck wrote:
> > Dear Nenad,
> >
> > I think the option cfg.padding only works for that iteration of
> > ft_preprocessing, but what you can do, is select larger segments
> > initially, and then run ft_preprocessing again with smaller segments.
> >
> > While you can set ft_preprocessing to apply multiple different filters
> > in one go (like a low-pass, a high-pass, and a DFT-filter, for
> > example), using a similar filter multiple times (like a high-pass
> > filter at 4Hz, and another at 8Hz) is usually not required, or
> > recommended. If you do multiple analyses on the same data (which, for
> > example, require different filters) you could find it useful to create
> > multiple smaller pipelines with their own ft_preprocessing. Debugging
> > complex analyses can be a lot easier that way:)
> >
> > Hope this helps,
> >
> > Casper
> >
> >
> > On Sat, Jun 22, 2013 at 1:34 PM, Nenad Polomac <polomacnenad at gmail.com
> > <mailto:polomacnenad at gmail.com>> wrote:
> >
> >     Dear all,
> >
> >     In my pipeline I need two times to filter data with
> >     ft_preprocessing. Is it somehow possible to pad trials
> >     after segmentation? I need this in order to avoid filter artifacts
> >     during the second filtering.
> >
> >     Thank you in advance!
> >
> >     Nenad
> >
> >     _______________________________________________
> >     fieldtrip mailing list
> >     fieldtrip at donders.ru.nl <mailto:fieldtrip at donders.ru.nl>
> >     http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >
> >
> >
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
> --
> J?rn M. Horschig
> PhD Student
> Donders Institute for Brain, Cognition and Behaviour
> Centre for Cognitive Neuroimaging
> Radboud University Nijmegen
> Neuronal Oscillations Group
> FieldTrip Development Team
>
> P.O. Box 9101
> NL-6500 HB Nijmegen
> The Netherlands
>
> Contact:
> E-Mail: jm.horschig at donders.ru.nl
> Tel:    +31-(0)24-36-68493
> Web: http://www.ru.nl/donders
>
> Visiting address:
> Trigon, room 2.30
> Kapittelweg 29
> NL-6525 EN Nijmegen
> The Netherlands
>
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>
> ------------------------------
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
> End of fieldtrip Digest, Vol 31, Issue 41
> *****************************************
>
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From eelke.spaak at donders.ru.nl  Mon Jun 24 11:31:35 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Mon, 24 Jun 2013 11:31:35 +0200
Subject: [FieldTrip] statistics on non-event-related fields
In-Reply-To: <CAP6m0dGJTG=i9dFLsOhL4o9+wp_TXZfMYOa2917ik2TGu-dJeg@mail.gmail.com>
References: <CAP6m0dGJTG=i9dFLsOhL4o9+wp_TXZfMYOa2917ik2TGu-dJeg@mail.gmail.com>
Message-ID: <CABPNLUrej3zMr7F7JW1Uvbz5ogdyFORFGhKuWVqr0a2pYN=NcA@mail.gmail.com>

Dear Marco,

The FieldTrip statistics routines support permutation of condition
labels among units of observation. I guess in your data you don't
really have 'units of observation', i.e. you have continuous data of
one (or several) subjects. In that case I would recommend taking care
of the statistics outside of FieldTrip, for instance by using a
randomisation approach based on shifting time series of different
channels by different, random, amounts. The coupling values obtained
by these shifted time series can serve as a distribution under the
null hypothesis of no coupling. The usual cluster machinery can then
be applied (i.e. combining above-(nonparametric)threshold
time-frequency-channel voxels into cluster candidates, compute cluster
statistics per randomization, and compare the observed cluster
statistic to the randomization distribution). You would also need to
write this yourself, but it should not be very difficult. The
mex-files bwlabel and spm_bwlabel (distributed with FieldTrip) are
very useful; they give index labels to connected clusters in a binary
matrix.

Note, however, that there is an important caveat with the approach I
describe here. The time shifting per channel also destroys the
between-channel structure in your data that is due to electric volume
conduction. So even if you find significant connectivity by this
approach, although the connectivity would be 'real' in a sense, it
still might not be meaningful if you do not account for this volume
conduction. This is something to think about apart from the
statistics.

Hope this helps.
Best,
Eelke

On 21 June 2013 14:26, Marco Porta <marco.porta88 at gmail.com> wrote:
> Dear Users and Eelke,
> I have spontaneous LFP data recorded intracranially. I'm interested in
> studying phase correlation between sensors and assess such correlation
> within single subjects studies. Is it possible to study statistical
> significance in such correlation study or should i implement my own
> statistic?
> Thanks,
>
> Marco
>
>
>
>> Dear Marco,
>>
>> What do you mean exactly with "non event-related fields"? I presume
>> there is some structure in your data that you want to consider as the
>> independent variable of interest, right? Some more information on what
>> you want to do would help us to help you.
>>
>> Best,
>> Eelke
>>
>>
>>
>>
>> Dear Fieldtrip experts,
>> I have a question regarding the statistics. How can I statistics on non
>> event-related fields in a between-trials.
>> Thanks,
>> Marco
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From nomeserio at gmail.com  Mon Jun 24 14:43:06 2013
From: nomeserio at gmail.com (Michele Barsotti)
Date: Mon, 24 Jun 2013 14:43:06 +0200
Subject: [FieldTrip] Loading Data into a fieldtrip structure
Message-ID: <CAGZjeH68Aq61DQBgPvVhOj2=f2ndrtWDuxFn58TKb8An4BUm7g@mail.gmail.com>

Dear FieldTrip Users,
  I'm working with eeglab since 2 years and now I would like to use also
fieldtrip. I've got many dataset in .mat format organized as [channels x
dataframe]. For each dataset I've got the channel location in a .ced file
format.
Can anyone help me to import these dataset into a fieldtrip data structure?

The channels (rows of the variable contained in the .mat file) are
organized like that:
1- time
2:17 - eeg channels
18:end - possible triggers

thank you in advance

cheers

-- 
        -Michele-
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From d.lozanosoldevilla at fcdonders.ru.nl  Mon Jun 24 14:55:18 2013
From: d.lozanosoldevilla at fcdonders.ru.nl (Diego Lozano Soldevilla)
Date: Mon, 24 Jun 2013 14:55:18 +0200
Subject: [FieldTrip] Loading Data into a fieldtrip structure
In-Reply-To: <CAGZjeH68Aq61DQBgPvVhOj2=f2ndrtWDuxFn58TKb8An4BUm7g@mail.gmail.com>
References: <CAGZjeH68Aq61DQBgPvVhOj2=f2ndrtWDuxFn58TKb8An4BUm7g@mail.gmail.com>
Message-ID: <CAEVBUjgj4FBxO-oGC5AcaS2h4V-2L=9DaGq1zbcB7a6B0CVz-A@mail.gmail.com>

Dear Michele,

You might have a look to the following FAQ:
http://fieldtrip.fcdonders.nl/faq/how_can_i_import_my_own_dataformat?s[]=import&s[]=data

I'm not sure about the state of the art of the eeglab2fieldtrip.m function
but it might help you out as well. To know more about the fieldtrip data
type field structures you need to have to work in Fieldtrip, the
ft_datatype* functions will be important for you, i.e.:

ft_datatype_freq
ft_datatype_raw
ft_datatype_sens
ft_datatype_timelock

I hope that helps

Diego






On 24 June 2013 14:43, Michele Barsotti <nomeserio at gmail.com> wrote:

> Dear FieldTrip Users,
>   I'm working with eeglab since 2 years and now I would like to use also
> fieldtrip. I've got many dataset in .mat format organized as [channels x
> dataframe]. For each dataset I've got the channel location in a .ced file
> format.
> Can anyone help me to import these dataset into a fieldtrip data structure?
>
> The channels (rows of the variable contained in the .mat file) are
> organized like that:
> 1- time
> 2:17 - eeg channels
> 18:end - possible triggers
>
> thank you in advance
>
> cheers
>
> --
>         -Michele-
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From david.schubring at uni-konstanz.de  Mon Jun 24 16:34:46 2013
From: david.schubring at uni-konstanz.de (David Schubring)
Date: Mon, 24 Jun 2013 16:34:46 +0200
Subject: [FieldTrip]  Matlab 2012/2013
In-Reply-To: <CAEVBUjgj4FBxO-oGC5AcaS2h4V-2L=9DaGq1zbcB7a6B0CVz-A@mail.gmail.com>
References: <CAGZjeH68Aq61DQBgPvVhOj2=f2ndrtWDuxFn58TKb8An4BUm7g@mail.gmail.com>
	<CAEVBUjgj4FBxO-oGC5AcaS2h4V-2L=9DaGq1zbcB7a6B0CVz-A@mail.gmail.com>
Message-ID: <51C85906.2090204@uni-konstanz.de>

Dear FieldTrip Users,

I was wondering if the incompatibility issues with fieldtrip and the 
latest MATLAB 2013a version still exist (and if so, which bugs exactly 
occur)?

(Some of our Matlab 2012a/b installations stopped working, maybe due to 
the latest java-update, and only the 2013 version still works.)

Thanks in advance and best regards,
David Schubring


From politzerahless at gmail.com  Mon Jun 24 17:19:59 2013
From: politzerahless at gmail.com (Stephen Politzer-Ahles)
Date: Mon, 24 Jun 2013 10:19:59 -0500
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 27
In-Reply-To: <mailman.200.1371117940.1243.fieldtrip@science.ru.nl>
References: <mailman.200.1371117940.1243.fieldtrip@science.ru.nl>
Message-ID: <CAJT2k_-XpQZ0diLY+pYtyOmD0R1s_0rKKRNSzfT2Ac9iuWPEbA@mail.gmail.com>

Hi everyone,

I recently tried
http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_spaceand
noticed some inconsistencies between the example code and the results;
I updated the code on the wiki but I wanted to send a message to the list
to double-check whether my changes are ok. Firstly, I had to add a call to
ft_convert_units, because otherwise the vol was expressed in mm and the
grid in cm, causing the grid to be much smaller than the volume conductor
(see http://i.imgur.com/gzct9Dm.png). Is this change ok?

The result I get is still not quite consistent with the examples shown on
that page, though; in my result, the grid is a cube (
http://i.imgur.com/NSgCFpg.png), whereas in the example the grid is
brain-shaped. I used the same Fieldtrip brain template and the same code
from the example (except for the change above), so I'm not sure if the
difference is due to different plot settings, a change in the Fieldtrip
code since this example was made, or a change in the sample brain included
in Fieldtrip since the example was made.

Best,
Steve


On Thu, Jun 13, 2013 at 5:05 AM, <fieldtrip-request at science.ru.nl> wrote:
>
> Send fieldtrip mailing list submissions to
>         fieldtrip at science.ru.nl
>
> To subscribe or unsubscribe via the World Wide Web, visit
>         http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> or, via email, send a message with subject or body 'help' to
>         fieldtrip-request at science.ru.nl
>
> You can reach the person managing the list at
>         fieldtrip-owner at science.ru.nl
>
> When replying, please edit your Subject line so it is more specific
> than "Re: Contents of fieldtrip digest..."
>
>
> Today's Topics:
>
>    1. Re: Source statistics on spatio-temporal source
>       reconstruction data (MNE) (Nicolai Mersebak)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Thu, 13 Jun 2013 12:04:34 +0200
> From: Nicolai Mersebak <nicolai at mersebak.dk>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] Source statistics on spatio-temporal source
>         reconstruction data (MNE)
> Message-ID: <6F3697BB-194F-422F-A1BF-EBBB132F805B at mersebak.dk>
> Content-Type: text/plain; charset="iso-8859-1"
>
> Thanks to all of you for your comments and ideas - they are very helpful!
>
> I ( off course :) ) have some follow up questions.
>
> I have created an ERP structure for my MNE source, so the only think
which I need and that is not straight forward is the neighbour structure.
>
> I am using the standard bem template
(fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model
and use the following code to get a grid for all subjects as I don't have
any subject specific information regarding the anatomy.
>
> cfg = [];
> cfg.grid.xgrid  = -100:10:100;
> cfg.grid.ygrid  = -100:10:100;
> cfg.grid.zgrid  = -100:10:100;
> cfg.grid.tight  = 'yes';
> cfg.grid.unit   = hdm.unit; % unit: mm
> cfg.vol        = hdm;
> grid  = ft_prepare_sourcemodel(cfg);
>
>
> @Jan-Mathijs and Stephan: I guess making a subject specific grid based on
a warped template requires anatomic information for each subject, e.g. a
MRI image like this tutorial shows:
>
http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
>
> The final grid output in the tutorial - does it have this 3D grid which
can be used as a neighbour structure ?
>
> I am not sure how to go from my cortical sheet [vertices x
coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
>
> A second thing I would like to know is, if any of you have tried to use
an atlas (e.g ALL template atlas) where the regions now are channels in the
permutation test? Going from source points to atlas regions can be done
through ft_sourcestatistics, but I am still interested in keeping the
temporal dimension. The reason to use atlas regions instead of source
points is to decrease the computation time.
>
> Best,
>
> Nicolai
>
>


On Thu, Jun 13, 2013 at 5:05 AM, <fieldtrip-request at science.ru.nl> wrote:

> Send fieldtrip mailing list submissions to
>         fieldtrip at science.ru.nl
>
> To subscribe or unsubscribe via the World Wide Web, visit
>         http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> or, via email, send a message with subject or body 'help' to
>         fieldtrip-request at science.ru.nl
>
> You can reach the person managing the list at
>         fieldtrip-owner at science.ru.nl
>
> When replying, please edit your Subject line so it is more specific
> than "Re: Contents of fieldtrip digest..."
>
>
> Today's Topics:
>
>    1. Re: Source statistics on spatio-temporal source
>       reconstruction data (MNE) (Nicolai Mersebak)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Thu, 13 Jun 2013 12:04:34 +0200
> From: Nicolai Mersebak <nicolai at mersebak.dk>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] Source statistics on spatio-temporal source
>         reconstruction data (MNE)
> Message-ID: <6F3697BB-194F-422F-A1BF-EBBB132F805B at mersebak.dk>
> Content-Type: text/plain; charset="iso-8859-1"
>
> Thanks to all of you for your comments and ideas - they are very helpful!
>
> I ( off course :) ) have some follow up questions.
>
> I have created an ERP structure for my MNE source, so the only think which
> I need and that is not straight forward is the neighbour structure.
>
> I am using the standard bem template
> (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model
> and use the following code to get a grid for all subjects as I don't have
> any subject specific information regarding the anatomy.
>
> cfg = [];
> cfg.grid.xgrid  = -100:10:100;
> cfg.grid.ygrid  = -100:10:100;
> cfg.grid.zgrid  = -100:10:100;
> cfg.grid.tight  = 'yes';
> cfg.grid.unit   = hdm.unit; % unit: mm
> cfg.vol        = hdm;
> grid  = ft_prepare_sourcemodel(cfg);
>
>
> @Jan-Mathijs and Stephan: I guess making a subject specific grid based on
> a warped template requires anatomic information for each subject, e.g. a
> MRI image like this tutorial shows:
>
> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
>
> The final grid output in the tutorial - does it have this 3D grid which
> can be used as a neighbour structure ?
>
> I am not sure how to go from my cortical sheet [vertices x
> coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
>
> A second thing I would like to know is, if any of you have tried to use an
> atlas (e.g ALL template atlas) where the regions now are channels in the
> permutation test? Going from source points to atlas regions can be done
> through ft_sourcestatistics, but I am still interested in keeping the
> temporal dimension. The reason to use atlas regions instead of source
> points is to decrease the computation time.
>
> Best,
>
> Nicolai
>
>
> Den 12/06/2013 kl. 18.58 skrev "smoratti at psi.ucm.es" <smoratti at psi.ucm.es
> >:
>
> >
> > I think Jan.Mathijs alternative suggestion is quite attractive. With the
> neighbors on a cortical sheet I also had the problems that sometimes the
> vertices do not have the same distance and then clustering may be biased to
> smaller or bigger clusters as the number of neighbors does not guarantee
> same cluster sizes. With the interpolation onto a 3D grid, you won't have
> that problem.
> >
> > best,
> >
> > Stephan
> >
> >
> > ________________________________________________________
> > Stephan Moratti, PhD
> >
> > see also: http://web.me.com/smoratti/
> >
> > Universidad Complutense de Madrid
> > Facultad de Psicolog?a
> > Departamento de Psicolog?a B?sica I
> > Campus de Somosaguas
> > 28223 Pozuelo de Alarc?n (Madrid)
> > Spain
> >
> > and
> >
> > Center for Biomedical Technology
> > Laboratory for Cognitive and Computational Neuroscience
> > Parque Cient?fico y Tecnol?gico de la Universidad Politecnica de Madrid
> > Campus Montegancedo
> > 28223 Pozuelo de Alarc?n (Madrid)
> > Spain
> >
> >
> > email: smoratti at psi.ucm.es
> > Tel.:    +34 679219982
> >
> > El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribi?:
> >
> >> An alternative would be to interpolate the cortical sheet to a 3D grid
> (where the grid is defined for each subject based on a warped template grid
> defined in a standard space), and then do clustering using a regular 3D
> spatial neighbourhood structure. The rationale being that two vertices on
> the sheet may appear as disconnected  (e.g. being on two sides of a sulcus)
> whereas, given the poor spatial resolution, they belong to the same spatial
> blob.
> >>
> >> Best,
> >> Jan-Mathijs
> >>
> >> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
> >>
> >>> Dear Nicolai,
> >>>
> >>> Indeed I have used ft_timelockstatistics for minimum norm source data.
> The trick is to put the source level data into a ERF structure. Determining
> the neighbors of a source surface with vertices is not trivial. However I
> used tess_vertconn.m from the BrainStorm toolbox to get the connectivity
> matrix that tells you who is a neighbor. This you can feed into
> timelockstats.
> >>>
> >>> Hope that helps,
> >>>
> >>> Stephan
> >>>
> >>> ________________________________________________________
> >>> Stephan Moratti, PhD
> >>>
> >>> see also: http://web.me.com/smoratti/
> >>>
> >>> Universidad Complutense de Madrid
> >>> Facultad de Psicolog?a
> >>> Departamento de Psicolog?a B?sica I
> >>> Campus de Somosaguas
> >>> 28223 Pozuelo de Alarc?n (Madrid)
> >>> Spain
> >>>
> >>> and
> >>>
> >>> Center for Biomedical Technology
> >>> Laboratory for Cognitive and Computational Neuroscience
> >>> Parque Cient?fico y Tecnol?gico de la Universidad Politecnica de Madrid
> >>> Campus Montegancedo
> >>> 28223 Pozuelo de Alarc?n (Madrid)
> >>> Spain
> >>>
> >>>
> >>> email: smoratti at psi.ucm.es
> >>> Tel.:    +34 679219982
> >>>
> >>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribi?:
> >>>
> >>>> Dear all,
> >>>>
> >>>> I have a question concerning the usage of ft_sourcegrandaverage and
> ft_sourcestatistics.
> >>>>
> >>>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal
> source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and
> 897 time points.
> >>>>
> >>>> Now I would like to use the cluster-based permutation test on my
> source reconstructed data. However it seems like ft_sourcegrandaverage and
> ft_sourcestatistics don't support source level time courses. E.g when I am
> using ft_sourcegrandaverage I am getting the following error:
> >>>>
> >>>> Error in ft_sourcegrandaverage (line 158)
> >>>>   dat(:,i) = tmp(:);
> >>>>
> >>>> Looking into the code:
> >>>>
> >>>>   for i=1:Nsubject
> >>>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter,
> varargin{i}));
> >>>>     dat(:,i) = tmp(:);
> >>>>     tmp = getsubfield(varargin{i}, 'inside');
> >>>>     inside(tmp,i) = 1;
> >>>>   end
> >>>>
> >>>> I see that "tmp" are getting the structure [N_sources x timepoints]
> from source.avg.pow for one subject, where "dat" requires the structure
> [N_sources x 1].
> >>>>
> >>>> I seached the mailing list for similar issues and found this thread:
> >>>>
> >>>>
> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
> >>>>
> >>>> Since I am interested in using the temporal dimension in my
> statistics, I would like to know if it is still not possible to use
> spatio-temporal source reconstructed data in ft_sourcestatistics and
> ft_sourcegrandaverage ?
> >>>>
> >>>> Or if any have succeeded in using the cluster-based permutation test
> on source level also including the temporal dimension ?
> >>>>
> >>>> Alternative I was thinking that I might could use
> ft_timelockstatistics, where I substituted the channels with sources, e.g
> instead of having 64 channels, I would now have 4050 "channels".
> >>>> If so I need to calculate a label structure and an appropriate
> neighbor structure, which I guess is possible as I have all the 3D
> coordinates for each source, e.g in leadfield.pos ?
> >>>> I know this is a work around solution, but have anyone tried or have
> any experience using such an approach ?
> >>>>
> >>>> Best,
> >>>>
> >>>> Nicolai
> >>>>
> >>>> _______________________________________________
> >>>> fieldtrip mailing list
> >>>> fieldtrip at donders.ru.nl
> >>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >>>
> >>> _______________________________________________
> >>> fieldtrip mailing list
> >>> fieldtrip at donders.ru.nl
> >>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >>
> >> Jan-Mathijs Schoffelen, MD PhD
> >>
> >> Donders Institute for Brain, Cognition and Behaviour,
> >> Centre for Cognitive Neuroimaging,
> >> Radboud University Nijmegen, The Netherlands
> >>
> >> Max Planck Institute for Psycholinguistics,
> >> Nijmegen, The Netherlands
> >>
> >> J.Schoffelen at donders.ru.nl
> >> Telephone: +31-24-3614793
> >>
> >> http://www.hettaligebrein.nl
> >>
> >> _______________________________________________
> >> fieldtrip mailing list
> >> fieldtrip at donders.ru.nl
> >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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> ------------------------------
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
> End of fieldtrip Digest, Vol 31, Issue 27
> *****************************************
>



-- 
Stephen Politzer-Ahles
University of Kansas
Linguistics Department
http://people.ku.edu/~sjpa/
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From a.stolk at fcdonders.ru.nl  Mon Jun 24 20:11:26 2013
From: a.stolk at fcdonders.ru.nl (Stolk, A.)
Date: Mon, 24 Jun 2013 20:11:26 +0200 (CEST)
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 27
In-Reply-To: <CAJT2k_-XpQZ0diLY+pYtyOmD0R1s_0rKKRNSzfT2Ac9iuWPEbA@mail.gmail.com>
Message-ID: <331233946.1725662.1372097486678.JavaMail.root@sculptor.zimbra.ru.nl>

Hi Steve, With respect to the cube vs. brain-shaped grid; this seems to be plotting-related? template_grid.inside in the snippet of code below selects only the grid points that have been determined as inside the brain, but with a negative inwardshift, hence it's also outside. ft_plot_mesh ( template_grid. pos ( template_grid. inside ,: ) ) ; % taken from the wiki Hopefully someone else has up-to-date knowledge to answer your question pertaining to the units (mm vs. cm) of the volume conductor and the source model. Best regards, Arjen ----- Oorspronkelijk bericht -----
> Van: "Stephen Politzer-Ahles" <politzerahless at gmail.com>
> Aan: fieldtrip at science.ru.nl
> Verzonden: Maandag 24 juni 2013 17:19:59
> Onderwerp: Re: [FieldTrip] fieldtrip Digest, Vol 31, Issue 27
> Hi everyone,
> I recently tried
> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space
> and noticed some inconsistencies between the example code and the
> results; I updated the code on the wiki but I wanted to send a message
> to the list to double-check whether my changes are ok. Firstly, I had
> to add a call to ft_convert_units, because otherwise the vol was
> expressed in mm and the grid in cm, causing the grid to be much
> smaller than the volume conductor (see http://i.imgur.com/gzct9Dm.png
> ). Is this change ok?
> The result I get is still not quite consistent with the examples shown
> on that page, though; in my result, the grid is a cube (
> http://i.imgur.com/NSgCFpg.png ), whereas in the example the grid is
> brain-shaped. I used the same Fieldtrip brain template and the same
> code from the example (except for the change above), so I'm not sure
> if the difference is due to different plot settings, a change in the
> Fieldtrip code since this example was made, or a change in the sample
> brain included in Fieldtrip since the example was made.
> Best,
> Steve
> On Thu, Jun 13, 2013 at 5:05 AM, < fieldtrip-request at science.ru.nl >
> wrote:
> >
> > Send fieldtrip mailing list submissions to
> > fieldtrip at science.ru.nl
> >
> > To subscribe or unsubscribe via the World Wide Web, visit
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > or, via email, send a message with subject or body 'help' to
> > fieldtrip-request at science.ru.nl
> >
> > You can reach the person managing the list at
> > fieldtrip-owner at science.ru.nl
> >
> > When replying, please edit your Subject line so it is more specific
> > than "Re: Contents of fieldtrip digest..."
> >
> >
> > Today's Topics:
> >
> > 1. Re: Source statistics on spatio-temporal source
> > reconstruction data (MNE) (Nicolai Mersebak)
> >
> >
> > ----------------------------------------------------------------------
> >
> > Message: 1
> > Date: Thu, 13 Jun 2013 12:04:34 +0200
> > From: Nicolai Mersebak < nicolai at mersebak.dk >
> > To: FieldTrip discussion list < fieldtrip at science.ru.nl >
> > Subject: Re: [FieldTrip] Source statistics on spatio-temporal source
> > reconstruction data (MNE)
> > Message-ID: < 6F3697BB-194F-422F-A1BF-EBBB132F805B at mersebak.dk >
> > Content-Type: text/plain; charset="iso-8859-1"
> >
> > Thanks to all of you for your comments and ideas - they are very
> > helpful!
> >
> > I ( off course :) ) have some follow up questions.
> >
> > I have created an ERP structure for my MNE source, so the only think
> > which I need and that is not straight forward is the neighbour
> > structure.
> >
> > I am using the standard bem template
> > (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head
> > model and use the following code to get a grid for all subjects as I
> > don't have any subject specific information regarding the anatomy.
> >
> > cfg = [];
> > cfg.grid.xgrid = -100:10:100;
> > cfg.grid.ygrid = -100:10:100;
> > cfg.grid.zgrid = -100:10:100;
> > cfg.grid.tight = 'yes';
> > cfg.grid.unit = hdm.unit; % unit: mm
> > cfg.vol = hdm;
> > grid = ft_prepare_sourcemodel(cfg);
> >
> >
> > @Jan-Mathijs and Stephan: I guess making a subject specific grid
> > based on a warped template requires anatomic information for each
> > subject, e.g. a MRI image like this tutorial shows:
> > http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
> >
> > The final grid output in the tutorial - does it have this 3D grid
> > which can be used as a neighbour structure ?
> >
> > I am not sure how to go from my cortical sheet [vertices x
> > coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour
> > structure ?
> >
> > A second thing I would like to know is, if any of you have tried to
> > use an atlas (e.g ALL template atlas) where the regions now are
> > channels in the permutation test? Going from source points to atlas
> > regions can be done through ft_sourcestatistics, but I am still
> > interested in keeping the temporal dimension. The reason to use
> > atlas regions instead of source points is to decrease the
> > computation time.
> >
> > Best,
> >
> > Nicolai
> >
> >
> On Thu, Jun 13, 2013 at 5:05 AM, < fieldtrip-request at science.ru.nl >
> wrote:
> > Send fieldtrip mailing list submissions to
> > fieldtrip at science.ru.nl
> > To subscribe or unsubscribe via the World Wide Web, visit
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > or, via email, send a message with subject or body 'help' to
> > fieldtrip-request at science.ru.nl
> > You can reach the person managing the list at
> > fieldtrip-owner at science.ru.nl
> > When replying, please edit your Subject line so it is more specific
> > than "Re: Contents of fieldtrip digest..."
> > Today's Topics:
> > 1. Re: Source statistics on spatio-temporal source
> > reconstruction data (MNE) (Nicolai Mersebak)
> > ----------------------------------------------------------------------
> > Message: 1
> > Date: Thu, 13 Jun 2013 12:04:34 +0200
> > From: Nicolai Mersebak < nicolai at mersebak.dk >
> > To: FieldTrip discussion list < fieldtrip at science.ru.nl >
> > Subject: Re: [FieldTrip] Source statistics on spatio-temporal source
> > reconstruction data (MNE)
> > Message-ID: < 6F3697BB-194F-422F-A1BF-EBBB132F805B at mersebak.dk >
> > Content-Type: text/plain; charset="iso-8859-1"
> > Thanks to all of you for your comments and ideas - they are very
> > helpful!
> > I ( off course :) ) have some follow up questions.
> > I have created an ERP structure for my MNE source, so the only think
> > which I need and that is not straight forward is the neighbour
> > structure.
> > I am using the standard bem template
> > (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head
> > model and use the following code to get a grid for all subjects as I
> > don't have any subject specific information regarding the anatomy.
> > cfg = [];
> > cfg.grid.xgrid = -100:10:100;
> > cfg.grid.ygrid = -100:10:100;
> > cfg.grid.zgrid = -100:10:100;
> > cfg.grid.tight = 'yes';
> > cfg.grid.unit = hdm.unit; % unit: mm
> > cfg.vol = hdm;
> > grid = ft_prepare_sourcemodel(cfg);
> > @Jan-Mathijs and Stephan: I guess making a subject specific grid
> > based
> > on a warped template requires anatomic information for each subject,
> > e.g. a MRI image like this tutorial shows:
> > http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
> > The final grid output in the tutorial - does it have this 3D grid
> > which can be used as a neighbour structure ?
> > I am not sure how to go from my cortical sheet [vertices x
> > coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour
> > structure ?
> > A second thing I would like to know is, if any of you have tried to
> > use an atlas (e.g ALL template atlas) where the regions now are
> > channels in the permutation test? Going from source points to atlas
> > regions can be done through ft_sourcestatistics, but I am still
> > interested in keeping the temporal dimension. The reason to use
> > atlas
> > regions instead of source points is to decrease the computation
> > time.
> > Best,
> > Nicolai
> > Den 12/06/2013 kl. 18.58 skrev " smoratti at psi.ucm.es " <
> > smoratti at psi.ucm.es >:
> > >
> > > I think Jan.Mathijs alternative suggestion is quite attractive.
> > > With
> > > the neighbors on a cortical sheet I also had the problems that
> > > sometimes the vertices do not have the same distance and then
> > > clustering may be biased to smaller or bigger clusters as the
> > > number
> > > of neighbors does not guarantee same cluster sizes. With the
> > > interpolation onto a 3D grid, you won't have that problem.
> > >
> > > best,
> > >
> > > Stephan
> > >
> > >
> > > ________________________________________________________
> > > Stephan Moratti, PhD
> > >
> > > see also: http://web.me.com/smoratti/
> > >
> > > Universidad Complutense de Madrid
> > > Facultad de Psicolog?a
> > > Departamento de Psicolog?a B?sica I
> > > Campus de Somosaguas
> > > 28223 Pozuelo de Alarc?n (Madrid)
> > > Spain
> > >
> > > and
> > >
> > > Center for Biomedical Technology
> > > Laboratory for Cognitive and Computational Neuroscience
> > > Parque Cient?fico y Tecnol?gico de la Universidad Politecnica de
> > > Madrid
> > > Campus Montegancedo
> > > 28223 Pozuelo de Alarc?n (Madrid)
> > > Spain
> > >
> > >
> > > email: smoratti at psi.ucm.es
> > > Tel.: +34 679219982
> > >
> > > El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribi?:
> > >
> > >> An alternative would be to interpolate the cortical sheet to a 3D
> > >> grid (where the grid is defined for each subject based on a
> > >> warped
> > >> template grid defined in a standard space), and then do
> > >> clustering
> > >> using a regular 3D spatial neighbourhood structure. The rationale
> > >> being that two vertices on the sheet may appear as disconnected
> > >> (e.g. being on two sides of a sulcus) whereas, given the poor
> > >> spatial resolution, they belong to the same spatial blob.
> > >>
> > >> Best,
> > >> Jan-Mathijs
> > >>
> > >> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
> > >>
> > >>> Dear Nicolai,
> > >>>
> > >>> Indeed I have used ft_timelockstatistics for minimum norm source
> > >>> data. The trick is to put the source level data into a ERF
> > >>> structure. Determining the neighbors of a source surface with
> > >>> vertices is not trivial. However I used tess_vertconn.m from the
> > >>> BrainStorm toolbox to get the connectivity matrix that tells you
> > >>> who is a neighbor. This you can feed into timelockstats.
> > >>>
> > >>> Hope that helps,
> > >>>
> > >>> Stephan
> > >>>
> > >>> ________________________________________________________
> > >>> Stephan Moratti, PhD
> > >>>
> > >>> see also: http://web.me.com/smoratti/
> > >>>
> > >>> Universidad Complutense de Madrid
> > >>> Facultad de Psicolog?a
> > >>> Departamento de Psicolog?a B?sica I
> > >>> Campus de Somosaguas
> > >>> 28223 Pozuelo de Alarc?n (Madrid)
> > >>> Spain
> > >>>
> > >>> and
> > >>>
> > >>> Center for Biomedical Technology
> > >>> Laboratory for Cognitive and Computational Neuroscience
> > >>> Parque Cient?fico y Tecnol?gico de la Universidad Politecnica de
> > >>> Madrid
> > >>> Campus Montegancedo
> > >>> 28223 Pozuelo de Alarc?n (Madrid)
> > >>> Spain
> > >>>
> > >>>
> > >>> email: smoratti at psi.ucm.es
> > >>> Tel.: +34 679219982
> > >>>
> > >>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribi?:
> > >>>
> > >>>> Dear all,
> > >>>>
> > >>>> I have a question concerning the usage of ft_sourcegrandaverage
> > >>>> and ft_sourcestatistics.
> > >>>>
> > >>>> After using ft_sourceanalysis (method: MNE), I get
> > >>>> spatio-temporal source reconstructed data in source.avg.pow
> > >>>> (4050
> > >>>> x 897): 4050 sources and 897 time points.
> > >>>>
> > >>>> Now I would like to use the cluster-based permutation test on
> > >>>> my
> > >>>> source reconstructed data. However it seems like
> > >>>> ft_sourcegrandaverage and ft_sourcestatistics don't support
> > >>>> source level time courses. E.g when I am using
> > >>>> ft_sourcegrandaverage I am getting the following error:
> > >>>>
> > >>>> Error in ft_sourcegrandaverage (line 158)
> > >>>> dat(:,i) = tmp(:);
> > >>>>
> > >>>> Looking into the code:
> > >>>>
> > >>>> for i=1:Nsubject
> > >>>> tmp = getsubfield(varargin{i},
> > >>>> parameterselection(cfg.parameter,
> > >>>> varargin{i}));
> > >>>> dat(:,i) = tmp(:);
> > >>>> tmp = getsubfield(varargin{i}, 'inside');
> > >>>> inside(tmp,i) = 1;
> > >>>> end
> > >>>>
> > >>>> I see that "tmp" are getting the structure [N_sources x
> > >>>> timepoints] from source.avg.pow for one subject, where "dat"
> > >>>> requires the structure [N_sources x 1].
> > >>>>
> > >>>> I seached the mailing list for similar issues and found this
> > >>>> thread:
> > >>>>
> > >>>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
> > >>>>
> > >>>> Since I am interested in using the temporal dimension in my
> > >>>> statistics, I would like to know if it is still not possible to
> > >>>> use spatio-temporal source reconstructed data in
> > >>>> ft_sourcestatistics and ft_sourcegrandaverage ?
> > >>>>
> > >>>> Or if any have succeeded in using the cluster-based permutation
> > >>>> test on source level also including the temporal dimension ?
> > >>>>
> > >>>> Alternative I was thinking that I might could use
> > >>>> ft_timelockstatistics, where I substituted the channels with
> > >>>> sources, e.g instead of having 64 channels, I would now have
> > >>>> 4050
> > >>>> "channels".
> > >>>> If so I need to calculate a label structure and an appropriate
> > >>>> neighbor structure, which I guess is possible as I have all the
> > >>>> 3D coordinates for each source, e.g in leadfield.pos ?
> > >>>> I know this is a work around solution, but have anyone tried or
> > >>>> have any experience using such an approach ?
> > >>>>
> > >>>> Best,
> > >>>>
> > >>>> Nicolai
> > >>>>
> > >>>> _______________________________________________
> > >>>> fieldtrip mailing list
> > >>>> fieldtrip at donders.ru.nl
> > >>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > >>>
> > >>> _______________________________________________
> > >>> fieldtrip mailing list
> > >>> fieldtrip at donders.ru.nl
> > >>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > >>
> > >> Jan-Mathijs Schoffelen, MD PhD
> > >>
> > >> Donders Institute for Brain, Cognition and Behaviour,
> > >> Centre for Cognitive Neuroimaging,
> > >> Radboud University Nijmegen, The Netherlands
> > >>
> > >> Max Planck Institute for Psycholinguistics,
> > >> Nijmegen, The Netherlands
> > >>
> > >> J.Schoffelen at donders.ru.nl
> > >> Telephone: +31-24-3614793
> > >>
> > >> http://www.hettaligebrein.nl
> > >>
> > >> _______________________________________________
> > >> fieldtrip mailing list
> > >> fieldtrip at donders.ru.nl
> > >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > >
> > > _______________________________________________
> > > fieldtrip mailing list
> > > fieldtrip at donders.ru.nl
> > > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
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> > >
> > ------------------------------
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > End of fieldtrip Digest, Vol 31, Issue 27
> > *****************************************
> --
> Stephen Politzer-Ahles
> University of Kansas
> Linguistics Department
> http://people.ku.edu/~sjpa/
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
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From politzerahless at gmail.com  Mon Jun 24 20:29:01 2013
From: politzerahless at gmail.com (Stephen Politzer-Ahles)
Date: Mon, 24 Jun 2013 13:29:01 -0500
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
Message-ID: <CAJT2k__aWw_68dy7K2MnGHkP2cEEyredBduU+VgoSVatx=_hYw@mail.gmail.com>

Hi Arjen,

Thanks, I also just tried that (after noticing that code in a later part of
the example) and can confirm that that change makes the plot come out like
the plot in the example. I updated the wiki accordingly.

Best,
Steve

> Message: 1
> Date: Mon, 24 Jun 2013 20:11:26 +0200 (CEST)
> From: "Stolk, A." <a.stolk at fcdonders.ru.nl>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] fieldtrip Digest, Vol 31, Issue 27
> Message-ID:
>         <
331233946.1725662.1372097486678.JavaMail.root at sculptor.zimbra.ru.nl>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Steve, With respect to the cube vs. brain-shaped grid; this seems to
be plotting-related? template_grid.inside in the snippet of code below
selects only the grid points that have been determined as inside the brain,
but with a negative inwardshift, hence it's also outside. ft_plot_mesh (
template_grid. pos ( template_grid. inside ,: ) ) ; % taken from the wiki
Hopefully someone else has up-to-date knowledge to answer your question
pertaining to the units (mm vs. cm) of the volume conductor and the source
model. Best regards, Arjen ----- Oorspronkelijk bericht -----
> > Van: "Stephen Politzer-Ahles" <politzerahless at gmail.com>
> > Aan: fieldtrip at science.ru.nl
> > Verzonden: Maandag 24 juni 2013 17:19:59
> > Onderwerp: Re: [FieldTrip] fieldtrip Digest, Vol 31, Issue 27
> > Hi everyone,
> > I recently tried
> >
http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space
> > and noticed some inconsistencies between the example code and the
> > results; I updated the code on the wiki but I wanted to send a message
> > to the list to double-check whether my changes are ok. Firstly, I had
> > to add a call to ft_convert_units, because otherwise the vol was
> > expressed in mm and the grid in cm, causing the grid to be much
> > smaller than the volume conductor (see http://i.imgur.com/gzct9Dm.png
> > ). Is this change ok?
> > The result I get is still not quite consistent with the examples shown
> > on that page, though; in my result, the grid is a cube (
> > http://i.imgur.com/NSgCFpg.png ), whereas in the example the grid is
> > brain-shaped. I used the same Fieldtrip brain template and the same
> > code from the example (except for the change above), so I'm not sure
> > if the difference is due to different plot settings, a change in the
> > Fieldtrip code since this example was made, or a change in the sample
> > brain included in Fieldtrip since the example was made.
> > Best,
> > Steve
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From joramvandriel at gmail.com  Tue Jun 25 09:17:27 2013
From: joramvandriel at gmail.com (Joram van Driel)
Date: Tue, 25 Jun 2013 09:17:27 +0200
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 27
In-Reply-To: <331233946.1725662.1372097486678.JavaMail.root@sculptor.zimbra.ru.nl>
References: <CAJT2k_-XpQZ0diLY+pYtyOmD0R1s_0rKKRNSzfT2Ac9iuWPEbA@mail.gmail.com>
	<331233946.1725662.1372097486678.JavaMail.root@sculptor.zimbra.ru.nl>
Message-ID: <CAKk__WW9+yaz6FwUSRQ-4SqSCy66-PbYsWxDkpe7TO=TvxH_mA@mail.gmail.com>

Hi Steve,
I had the same problem a while ago.

First of all, you need to take care of all the necessary ingredients to be
in cm before computing the volume conduction model and the leadfield
matrix, by using ft_convertunits.

Second, I also first had a brain-shaped grid, which was not a plot-related
problem; I noticed during the computation of the leadfield in the Matlab
command lines that it estimated 0 dipoles outside, and x-number of dipoles
inside the brain, which already made me suspicious. Check whether you get
this as well, then you know it's not a plotting problem.
In the end I managed to get a x inside and x outside number of dipoles, and
I think the difference was that I first used ft_prepare_singleshell (which
gave me the weird brain-shaped results with 0 dipoles outside), while I
think you should use ft_prepare_headmodel with cfg.method='singleshell'.
Maybe it doesn't matter at all, and the problem lies somewhere else, but
for me it worked and I got a nice cube-shaped grid in the end.

Hope this helps.
Best,
Joram


On Mon, Jun 24, 2013 at 8:11 PM, Stolk, A. <a.stolk at fcdonders.ru.nl> wrote:

> Hi Steve,
>
> With respect to the cube vs. brain-shaped grid; this seems to be
> plotting-related? template_grid.inside in the snippet of code below selects
> only the grid points that have been determined as inside the brain, but
> with a negative inwardshift, hence it's also outside.
>
> ft_plot_mesh(template_grid.pos(template_grid.inside,:)); % taken from the
> wiki
>
> Hopefully someone else has up-to-date knowledge to answer your question
> pertaining to the units (mm vs. cm) of the volume conductor and the source
> model.
>
> Best regards,
> Arjen
>
> ------------------------------
>
> *Van: *"Stephen Politzer-Ahles" <politzerahless at gmail.com>
> *Aan: *fieldtrip at science.ru.nl
> *Verzonden: *Maandag 24 juni 2013 17:19:59
> *Onderwerp: *Re: [FieldTrip] fieldtrip Digest, Vol 31, Issue 27
>
>
> Hi everyone,
>
> I recently tried
> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_spaceand noticed some inconsistencies between the example code and the results;
> I updated the code on the wiki but I wanted to send a message to the list
> to double-check whether my changes are ok. Firstly, I had to add a call to
> ft_convert_units, because otherwise the vol was expressed in mm and the
> grid in cm, causing the grid to be much smaller than the volume conductor
> (see http://i.imgur.com/gzct9Dm.png). Is this change ok?
>
> The result I get is still not quite consistent with the examples shown on
> that page, though; in my result, the grid is a cube (
> http://i.imgur.com/NSgCFpg.png), whereas in the example the grid is
> brain-shaped. I used the same Fieldtrip brain template and the same code
> from the example (except for the change above), so I'm not sure if the
> difference is due to different plot settings, a change in the Fieldtrip
> code since this example was made, or a change in the sample brain included
> in Fieldtrip since the example was made.
>
> Best,
> Steve
>
>
> On Thu, Jun 13, 2013 at 5:05 AM, <fieldtrip-request at science.ru.nl> wrote:
> >
> > Send fieldtrip mailing list submissions to
> >         fieldtrip at science.ru.nl
> >
> > To subscribe or unsubscribe via the World Wide Web, visit
> >         http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > or, via email, send a message with subject or body 'help' to
> >         fieldtrip-request at science.ru.nl
> >
> > You can reach the person managing the list at
> >         fieldtrip-owner at science.ru.nl
> >
> > When replying, please edit your Subject line so it is more specific
> > than "Re: Contents of fieldtrip digest..."
> >
> >
> > Today's Topics:
> >
> >    1. Re: Source statistics on spatio-temporal source
> >       reconstruction data (MNE) (Nicolai Mersebak)
> >
> >
> > ----------------------------------------------------------------------
> >
> > Message: 1
> > Date: Thu, 13 Jun 2013 12:04:34 +0200
> > From: Nicolai Mersebak <nicolai at mersebak.dk>
> > To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> > Subject: Re: [FieldTrip] Source statistics on spatio-temporal source
> >         reconstruction data (MNE)
> > Message-ID: <6F3697BB-194F-422F-A1BF-EBBB132F805B at mersebak.dk>
> > Content-Type: text/plain; charset="iso-8859-1"
> >
> > Thanks to all of you for your comments and ideas - they are very helpful!
> >
> > I ( off course :) ) have some follow up questions.
> >
> > I have created an ERP structure for my MNE source, so the only think
> which I need and that is not straight forward is the neighbour structure.
> >
> > I am using the standard bem template
> (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model
> and use the following code to get a grid for all subjects as I don't have
> any subject specific information regarding the anatomy.
> >
> > cfg = [];
> > cfg.grid.xgrid  = -100:10:100;
> > cfg.grid.ygrid  = -100:10:100;
> > cfg.grid.zgrid  = -100:10:100;
> > cfg.grid.tight  = 'yes';
> > cfg.grid.unit   = hdm.unit; % unit: mm
> > cfg.vol        = hdm;
> > grid  = ft_prepare_sourcemodel(cfg);
> >
> >
> > @Jan-Mathijs and Stephan: I guess making a subject specific grid based
> on a warped template requires anatomic information for each subject, e.g. a
> MRI image like this tutorial shows:
> >
> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
> >
> > The final grid output in the tutorial - does it have this 3D grid which
> can be used as a neighbour structure ?
> >
> > I am not sure how to go from my cortical sheet [vertices x
> coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
> >
> > A second thing I would like to know is, if any of you have tried to use
> an atlas (e.g ALL template atlas) where the regions now are channels in the
> permutation test? Going from source points to atlas regions can be done
> through ft_sourcestatistics, but I am still interested in keeping the
> temporal dimension. The reason to use atlas regions instead of source
> points is to decrease the computation time.
> >
> > Best,
> >
> > Nicolai
> >
> >
>
>
> On Thu, Jun 13, 2013 at 5:05 AM, <fieldtrip-request at science.ru.nl> wrote:
>
>> Send fieldtrip mailing list submissions to
>>         fieldtrip at science.ru.nl
>>
>> To subscribe or unsubscribe via the World Wide Web, visit
>>         http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> or, via email, send a message with subject or body 'help' to
>>         fieldtrip-request at science.ru.nl
>>
>> You can reach the person managing the list at
>>         fieldtrip-owner at science.ru.nl
>>
>> When replying, please edit your Subject line so it is more specific
>> than "Re: Contents of fieldtrip digest..."
>>
>>
>> Today's Topics:
>>
>>    1. Re: Source statistics on spatio-temporal source
>>       reconstruction data (MNE) (Nicolai Mersebak)
>>
>>
>> ----------------------------------------------------------------------
>>
>> Message: 1
>> Date: Thu, 13 Jun 2013 12:04:34 +0200
>> From: Nicolai Mersebak <nicolai at mersebak.dk>
>> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
>> Subject: Re: [FieldTrip] Source statistics on spatio-temporal source
>>         reconstruction data (MNE)
>> Message-ID: <6F3697BB-194F-422F-A1BF-EBBB132F805B at mersebak.dk>
>> Content-Type: text/plain; charset="iso-8859-1"
>>
>> Thanks to all of you for your comments and ideas - they are very helpful!
>>
>> I ( off course :) ) have some follow up questions.
>>
>> I have created an ERP structure for my MNE source, so the only think
>> which I need and that is not straight forward is the neighbour structure.
>>
>> I am using the standard bem template
>> (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model
>> and use the following code to get a grid for all subjects as I don't have
>> any subject specific information regarding the anatomy.
>>
>> cfg = [];
>> cfg.grid.xgrid  = -100:10:100;
>> cfg.grid.ygrid  = -100:10:100;
>> cfg.grid.zgrid  = -100:10:100;
>> cfg.grid.tight  = 'yes';
>> cfg.grid.unit   = hdm.unit; % unit: mm
>> cfg.vol        = hdm;
>> grid  = ft_prepare_sourcemodel(cfg);
>>
>>
>> @Jan-Mathijs and Stephan: I guess making a subject specific grid based on
>> a warped template requires anatomic information for each subject, e.g. a
>> MRI image like this tutorial shows:
>>
>> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
>>
>> The final grid output in the tutorial - does it have this 3D grid which
>> can be used as a neighbour structure ?
>>
>> I am not sure how to go from my cortical sheet [vertices x
>> coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
>>
>> A second thing I would like to know is, if any of you have tried to use
>> an atlas (e.g ALL template atlas) where the regions now are channels in the
>> permutation test? Going from source points to atlas regions can be done
>> through ft_sourcestatistics, but I am still interested in keeping the
>> temporal dimension. The reason to use atlas regions instead of source
>> points is to decrease the computation time.
>>
>> Best,
>>
>> Nicolai
>>
>>
>> Den 12/06/2013 kl. 18.58 skrev "smoratti at psi.ucm.es" <smoratti at psi.ucm.es
>> >:
>>
>> >
>> > I think Jan.Mathijs alternative suggestion is quite attractive. With
>> the neighbors on a cortical sheet I also had the problems that sometimes
>> the vertices do not have the same distance and then clustering may be
>> biased to smaller or bigger clusters as the number of neighbors does not
>> guarantee same cluster sizes. With the interpolation onto a 3D grid, you
>> won't have that problem.
>> >
>> > best,
>> >
>> > Stephan
>> >
>> >
>> > ________________________________________________________
>> > Stephan Moratti, PhD
>> >
>> > see also: http://web.me.com/smoratti/
>> >
>> > Universidad Complutense de Madrid
>> > Facultad de Psicolog?a
>> > Departamento de Psicolog?a B?sica I
>> > Campus de Somosaguas
>> > 28223 Pozuelo de Alarc?n (Madrid)
>> > Spain
>> >
>> > and
>> >
>> > Center for Biomedical Technology
>> > Laboratory for Cognitive and Computational Neuroscience
>> > Parque Cient?fico y Tecnol?gico de la Universidad Politecnica de Madrid
>> > Campus Montegancedo
>> > 28223 Pozuelo de Alarc?n (Madrid)
>> > Spain
>> >
>> >
>> > email: smoratti at psi.ucm.es
>> > Tel.:    +34 679219982
>> >
>> > El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribi?:
>> >
>> >> An alternative would be to interpolate the cortical sheet to a 3D grid
>> (where the grid is defined for each subject based on a warped template grid
>> defined in a standard space), and then do clustering using a regular 3D
>> spatial neighbourhood structure. The rationale being that two vertices on
>> the sheet may appear as disconnected  (e.g. being on two sides of a sulcus)
>> whereas, given the poor spatial resolution, they belong to the same spatial
>> blob.
>> >>
>> >> Best,
>> >> Jan-Mathijs
>> >>
>> >> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
>> >>
>> >>> Dear Nicolai,
>> >>>
>> >>> Indeed I have used ft_timelockstatistics for minimum norm source
>> data. The trick is to put the source level data into a ERF structure.
>> Determining the neighbors of a source surface with vertices is not trivial.
>> However I used tess_vertconn.m from the BrainStorm toolbox to get the
>> connectivity matrix that tells you who is a neighbor. This you can feed
>> into timelockstats.
>> >>>
>> >>> Hope that helps,
>> >>>
>> >>> Stephan
>> >>>
>> >>> ________________________________________________________
>> >>> Stephan Moratti, PhD
>> >>>
>> >>> see also: http://web.me.com/smoratti/
>> >>>
>> >>> Universidad Complutense de Madrid
>> >>> Facultad de Psicolog?a
>> >>> Departamento de Psicolog?a B?sica I
>> >>> Campus de Somosaguas
>> >>> 28223 Pozuelo de Alarc?n (Madrid)
>> >>> Spain
>> >>>
>> >>> and
>> >>>
>> >>> Center for Biomedical Technology
>> >>> Laboratory for Cognitive and Computational Neuroscience
>> >>> Parque Cient?fico y Tecnol?gico de la Universidad Politecnica de
>> Madrid
>> >>> Campus Montegancedo
>> >>> 28223 Pozuelo de Alarc?n (Madrid)
>> >>> Spain
>> >>>
>> >>>
>> >>> email: smoratti at psi.ucm.es
>> >>> Tel.:    +34 679219982
>> >>>
>> >>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribi?:
>> >>>
>> >>>> Dear all,
>> >>>>
>> >>>> I have a question concerning the usage of ft_sourcegrandaverage and
>> ft_sourcestatistics.
>> >>>>
>> >>>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal
>> source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and
>> 897 time points.
>> >>>>
>> >>>> Now I would like to use the cluster-based permutation test on my
>> source reconstructed data. However it seems like ft_sourcegrandaverage and
>> ft_sourcestatistics don't support source level time courses. E.g when I am
>> using ft_sourcegrandaverage I am getting the following error:
>> >>>>
>> >>>> Error in ft_sourcegrandaverage (line 158)
>> >>>>   dat(:,i) = tmp(:);
>> >>>>
>> >>>> Looking into the code:
>> >>>>
>> >>>>   for i=1:Nsubject
>> >>>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter,
>> varargin{i}));
>> >>>>     dat(:,i) = tmp(:);
>> >>>>     tmp = getsubfield(varargin{i}, 'inside');
>> >>>>     inside(tmp,i) = 1;
>> >>>>   end
>> >>>>
>> >>>> I see that "tmp" are getting the structure [N_sources x timepoints]
>> from source.avg.pow for one subject, where "dat" requires the structure
>> [N_sources x 1].
>> >>>>
>> >>>> I seached the mailing list for similar issues and found this thread:
>> >>>>
>> >>>>
>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>> >>>>
>> >>>> Since I am interested in using the temporal dimension in my
>> statistics, I would like to know if it is still not possible to use
>> spatio-temporal source reconstructed data in ft_sourcestatistics and
>> ft_sourcegrandaverage ?
>> >>>>
>> >>>> Or if any have succeeded in using the cluster-based permutation test
>> on source level also including the temporal dimension ?
>> >>>>
>> >>>> Alternative I was thinking that I might could use
>> ft_timelockstatistics, where I substituted the channels with sources, e.g
>> instead of having 64 channels, I would now have 4050 "channels".
>> >>>> If so I need to calculate a label structure and an appropriate
>> neighbor structure, which I guess is possible as I have all the 3D
>> coordinates for each source, e.g in leadfield.pos ?
>> >>>> I know this is a work around solution, but have anyone tried or have
>> any experience using such an approach ?
>> >>>>
>> >>>> Best,
>> >>>>
>> >>>> Nicolai
>> >>>>
>> >>>> _______________________________________________
>> >>>> fieldtrip mailing list
>> >>>> fieldtrip at donders.ru.nl
>> >>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> >>>
>> >>> _______________________________________________
>> >>> fieldtrip mailing list
>> >>> fieldtrip at donders.ru.nl
>> >>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> >>
>> >> Jan-Mathijs Schoffelen, MD PhD
>> >>
>> >> Donders Institute for Brain, Cognition and Behaviour,
>> >> Centre for Cognitive Neuroimaging,
>> >> Radboud University Nijmegen, The Netherlands
>> >>
>> >> Max Planck Institute for Psycholinguistics,
>> >> Nijmegen, The Netherlands
>> >>
>> >> J.Schoffelen at donders.ru.nl
>> >> Telephone: +31-24-3614793
>> >>
>> >> http://www.hettaligebrein.nl
>> >>
>> >> _______________________________________________
>> >> fieldtrip mailing list
>> >> fieldtrip at donders.ru.nl
>> >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> >
>> > _______________________________________________
>> > fieldtrip mailing list
>> > fieldtrip at donders.ru.nl
>> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>> -------------- next part --------------
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>> >
>>
>> ------------------------------
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>> End of fieldtrip Digest, Vol 31, Issue 27
>> *****************************************
>>
>
>
>
> --
> Stephen Politzer-Ahles
> University of Kansas
> Linguistics Department
> http://people.ku.edu/~sjpa/
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
Joram van Driel, MSc.
PhD student at the University of Amsterdam
Department of Psychology, Brain & Cognition
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From mbj0310 at gmail.com  Tue Jun 25 13:04:15 2013
From: mbj0310 at gmail.com (Beom Jun Min)
Date: Tue, 25 Jun 2013 20:04:15 +0900
Subject: [FieldTrip] Decreased baseline level after using ICA in ERP data
In-Reply-To: <831995030.1708865.1372062324986.JavaMail.root@sculptor.zimbra.ru.nl>
References: <CA+v9jvKJnKAfsQDwoDhNVSPAKCmpOpwut8vdmFXa1akp_1WDGA@mail.gmail.com>
	<831995030.1708865.1372062324986.JavaMail.root@sculptor.zimbra.ru.nl>
Message-ID: <CA+v9jvLu5ox++Dt0AZnJrXtZ0COt_6421YquhOTUUHDbejsjTQ@mail.gmail.com>

Dear Diego,

Thank you for your kind answer.
The importance of 'quality' you mentioned and the references that you
attached could help me to understand the ICA algorithm further.
And I have an additional question about preprocessing before ICA. Is
detrending needed before the decomposition if there is a linear trend in
the segmented data?
Because I noticed one component showing linearly and consistently decreased
(or increased) activity during one segment in some trials after ICA, I
wondered why that happened.

Apart from that, I found the possible cause of the past problem. It looks
like the ft_rejectcomponent might remove the 'demean' effect.
After I used the function without any component removing, (cfg.component =
[];) the baseline level decreased again but the shape of the ERP does not
change.
However, I have not found the way to correct this decreased baseline yet.
The ft_preprocessing with demean pre-stimulus does not work.

Thanks.

BJ



2013/6/24 Lozano Soldevilla, D. (Diego) <d.lozanosoldevilla at fcdonders.ru.nl>

> Dear Beom Jun,
>
> I see multiple scenarios why this baseline activity decrease could happen.
> First of all, how the component you're rejecting look like (i.e. "blink
> component")? Do you see this activity decrease after the baseline period?
>
> The "quality" of the ICA decomposition, how well your artifact/component
> of interest has been isolated by algorithm in time (i.e. blink time
> courses) and space (marked frontal topography), will determine the activity
> that later on you'll reject/select. If your decomposition is not well
> suited, the rejection of a particular IC activity might have "extra"
> activity you don't want to reject (effect of interest), might be the
> algorithm is not able to isolate the components of interests (i.e.
> artifacts) or a combination of both.
>
> To evaluate the quality of your ICA decomposition you might have a look
> here (http://www.ncbi.nlm.nih.gov/pubmed/19162199). Basically, the
> authors find that the ICA decomposition improves significantly "increased
> by removing the mean EEG at each channel for each epoch of data rather than
> the mean EEG in a prestimulus baseline". In addition (see here:
> http://sccn.ucsd.edu/pipermail/eeglablist/2012/004925.html), high-pass
> filtering above ~1hz improve the results.
>
> It's very important to feed ICA as much relevant data as you can use. The
> more the data, the better the decomposition. There's a rule of thumb that
> says that for a reliable IC decomposition 20 time points per channel2  is
> needed (see here for a reference
> http://www.ncbi.nlm.nih.gov/pubmed/16904745)
>
> I hope that helps,
>
> Diego
> ------------------------------
>
> *From: *"Beom Jun Min" <mbj0310 at gmail.com>
> *To: *"FieldTrip discussion list" <fieldtrip at science.ru.nl>
> *Sent: *Monday, 24 June, 2013 6:27:47 AM
> *Subject: *[FieldTrip] Decreased baseline level after using ICA in ERP
> data
>
>
> Dear all,
>
> I have ERP data and now I am dealing with ICA to remove muscle and eye
> artifacts.
> However, I found that after ft_rejectcomponent, the baseline level of the
> segmented epoch decreased. (The baselinewindow is [-0.2 0].)
> The baseline level decreased even though I rejected only one component.
>
> My script is shown below.
>
> *%% Removing the Artifacts*
> *cfg = [];
> *
> *cfg.component = [ ]; % to be removed component(s)*
> *post_ICA_temp6 = ft_rejectcomponent(cfg, comp_detrand, data_raw);*
> *
> *
> *%% timelocking*
> *
> *
> *cfg = [];*
> *timelock_temp6 = ft_timelockanalysis(cfg, post_ICA_temp6);*
> *
> *
> *%% Plot*
> *
> *
> *figure;*
> *cfg = [];*
> *cfg.layout = lay;*
> *cfg.interactive = 'yes';*
> *cfg.channel = ['all', {'-EKG', '-EMG'}];*
> *ft_multiplotER(cfg, timelock_temp6)*
>
> Is there something that I missed?
>
> Thanks.
>
> BJ
>
> --
> BeomJun Min, M.D.
>
> Department of Medical System Engineering (DMSE)
> Gwangju Institute of Science and Technology (GIST)
> 261 Cheomdan-gwagiro(Oryong-dong), Buk-gu, Gwangju
> 500-712, Republic of Korea (South)
> Phone: +82-62-715-3266 / Fax: +82-62-715-3244
> E-mail: mbj0310 at gmail.com, http://bmssa.gist.ac.kr
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
>
> --
> PhD Student
> Neuronal Oscillations Group
> Donders Institute for Brain, Cognition and Behaviour
> Centre for Cognitive Neuroimaging
> Radboud University Nijmegen
> NL-6525 EN Nijmegen
> The Netherlands
> http://www.ru.nl/people/donders/lozano-soldevilla-d/
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
BeomJun Min, M.D.

Department of Medical System Engineering (DMSE)
Gwangju Institute of Science and Technology (GIST)
261 Cheomdan-gwagiro(Oryong-dong), Buk-gu, Gwangju
500-712, Republic of Korea (South)
Phone: +82-62-715-3266 / Fax: +82-62-715-3244
E-mail: mbj0310 at gmail.com, http://bmssa.gist.ac.kr
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From mengtongxiao at gmail.com  Tue Jun 25 15:29:41 2013
From: mengtongxiao at gmail.com (=?GB2312?B?s8LRqQ==?=)
Date: Tue, 25 Jun 2013 21:29:41 +0800
Subject: [FieldTrip] source reconstruction data (MNE .fif)
Message-ID: <CADiddyVSK6SqRU5BP1kNpSAR21f8heFkkZuOiAh1QKgCH+8xag@mail.gmail.com>

Dear all
 I have a .fif file and want to source  reconstruction .

I want use the template  sourcemodel in fieldtrip,but  I see there are two
different  coordinate system.
Shold I convert the fif coordinate to template coordinate?

thanks
best,
xiao
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From m.chait at ucl.ac.uk  Tue Jun 25 16:39:16 2013
From: m.chait at ucl.ac.uk (Chait, Maria)
Date: Tue, 25 Jun 2013 14:39:16 +0000
Subject: [FieldTrip] PhD studentship at the UCL Ear Institute
Message-ID: <3BA3DF582C0B7542AE0CB625F0119AB8378B0451@DB3PRD0111MB492.eurprd01.prod.exchangelabs.com>


Please forward to anyone who might be interested.

A 3 year PhD studentship in auditory cognitive neuroscience is available as part of a research collaboration between the UCL Ear Institute (London, UK) and NTT Communication Science Labs (Nippon Telegraph and Telephone corporation, Atsugi, Japan). The student will be based at the UCL Ear Institute and supervised by Dr. Maria Chait. They will also be working with Prof. Makio Kashino and Dr. Shigeto Furukawa (NTT).  The project will use psychophysics, eye tracking, autonomic response measures and MEG functional brain imaging to investigate which features of sound are perceptually salient. Namely, those sounds that automatically capture attention in a busy scene, even when listeners' initial perceptual focus is elsewhere.

The UCL Ear Institute provides state-of-the-art research facilities across a wide range of disciplines and is one of the foremost centres for hearing, speech and language-related research within Europe.

Key Requirements
The PhD start date would be September  2013.  Applicants should have a UK/EU nationality and a 1St class, or upper 2nd degree in a relevant discipline (e.g. Psychology, Neuroscience, Engineering). The PhD work would require good programming skills (e.g. in Matlab). Previous experience with auditory research, functional brain imaging, signal processing and/or acoustics is desirable.

For an informal discussion, or to submit an application please contact Dr. Maria Chait (m.chait at ucl.ac.uk<mailto:m.chait at ucl.ac.uk>). Applicants should submit a supporting statement, a CV, and the details of two academic referees.  The closing date for receipt of applications is July 15th, 2013.The studentship includes fees and a yearly stipend (about £16000;  tax free).


Maria Chait PhD
m.chait at ucl.ac.uk<mailto:m.chait at ucl.ac.uk>

Senior Lecturer
UCL Ear Institute
332 Gray's Inn Road
London WC1X 8EE

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From matt.craddock at uni-leipzig.de  Tue Jun 25 17:17:43 2013
From: matt.craddock at uni-leipzig.de (Matt Craddock)
Date: Tue, 25 Jun 2013 17:17:43 +0200
Subject: [FieldTrip] Decreased baseline level after using ICA in ERP data
In-Reply-To: <CA+v9jvLu5ox++Dt0AZnJrXtZ0COt_6421YquhOTUUHDbejsjTQ@mail.gmail.com>
References: <CA+v9jvKJnKAfsQDwoDhNVSPAKCmpOpwut8vdmFXa1akp_1WDGA@mail.gmail.com>
	<831995030.1708865.1372062324986.JavaMail.root@sculptor.zimbra.ru.nl>
	<CA+v9jvLu5ox++Dt0AZnJrXtZ0COt_6421YquhOTUUHDbejsjTQ@mail.gmail.com>
Message-ID: <51C9B497.7080105@uni-leipzig.de>

Dear Beom Jun,

Regarding detrending - ICA works better with relatively stationary data, 
which is why high-pass filtering - as Diego mentioned - is often 
performed. Both detrending and high-pass filtering remove/attenuate slow 
fluctuations in the signal, so I'd suggest using one or the other 
procedure before running ICA if you think such low frequency activity is 
affecting your decompositions.

Cheers,
Matt

On 25/06/2013 13:04, Beom Jun Min wrote:
> Dear Diego,
>
> Thank you for your kind answer.
> The importance of 'quality' you mentioned and the references that you
> attached could help me to understand the ICA algorithm further.
> And I have an additional question about preprocessing before ICA. Is
> detrending needed before the decomposition if there is a linear trend in
> the segmented data?
> Because I noticed one component showing linearly and consistently
> decreased (or increased) activity during one segment in some trials
> after ICA, I wondered why that happened.
> Apart from that, I found the possible cause of the past problem. It
> looks like the ft_rejectcomponent might remove the 'demean' effect.
> After I used the function without any component removing, (cfg.component
> = [];) the baseline level decreased again but the shape of the ERP does
> not change.
> However, I have not found the way to correct this decreased baseline
> yet. The ft_preprocessing with demean pre-stimulus does not work.
>
> Thanks.
>
> BJ



-- 
Dr. Matt Craddock

Post-doctoral researcher,
Institute of Psychology,
University of Leipzig,
Neumarkt 9-19,
04109 Leipzig, Germany
Phone: +49 341 973 95 44


From l.verhagen at fcdonders.ru.nl  Wed Jun 26 11:33:36 2013
From: l.verhagen at fcdonders.ru.nl (Verhagen, L. (Lennart))
Date: Wed, 26 Jun 2013 11:33:36 +0200 (CEST)
Subject: [FieldTrip] Brain Stimulation (TMS-tDCS-EEG) toolkit course at
	Donders, Nijmegen - registration is now open
Message-ID: <1380b01ce7250$3bba7a70$b32f6f50$@verhagen@fcdonders.ru.nl>

On September 2-4, 2013, we will host the “Toolkit of Cognitive Neuroscience: 
Transcranial Brain Stimulation” at the Donders Institute in Nijmegen.



This intensive three-day toolkit course will provide in-depth knowledge on 
transcranial magnetic stimulation (TMS) and transcranial current stimulation 
(tDCS/tACS). The course will cover both basic and advanced topics, 
discussing online and offline approaches of quantification, interference, 
and modulation of neural activity. We will specifically address multimodal 
applications of non-invasive brain stimulation, with an emphasis on 
concurrent electroencephalography (EEG).



The course involves a series of lectures and hands-on training of 
stimulation application, data acquisition and data analysis. These address 
fundamental paradigms, such as single-pulse TMS, repetitive TMS, tDCS and 
tACS, and advanced topics, such as paired-pulse TMS and concurrent 
TMS-tDCS-EEG. Keynote lectures will be given by Rogier Mars (Oxford), 
Jacinta O’Shea (Oxford), Alexander Sack (Maastricht), and Gregor Thut 
(Glasgow). Please see the program for more details.



The participation fee is €150 for (PhD) students and €300 for more senior 
researchers. This includes coffee/tea, Dutch sandwich lunches, and social 
diner and drinks on Monday and Tuesday. Because of space limitations the 
number of participants in the hands-on sessions is limited to 30; please 
indicate your preference to join these additional sessions when registering.



Location: Donders Institute for Brain, Cognition and Behaviour, Centre for 
Cognitive Neuroimaging, Kapittelweg 29, 6525 EN Nijmegen

Organizers: Lennart Verhagen (l.verhagen at donders.ru.nl) Til Ole Bergmann 
(t.bergmann at donders.ru.nl)

Registration: 
www.ru.nl/donders/course-information/2013courses/toolkit-cognitive-7



Best regards,

Lennart Verhagen and Til Ole Bergmann



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From graham at peyton.co.za  Wed Jun 26 12:13:58 2013
From: graham at peyton.co.za (Graham Peyton)
Date: Wed, 26 Jun 2013 12:13:58 +0200
Subject: [FieldTrip] QSUB toolbox on a multi-core computer
Message-ID: <CANOxK9E+ZCy9zFqYw1kR_aK7wnEpq0cF9efVj93wFxg5zJWmhQ@mail.gmail.com>

Dear FieldTrip community,

I am trying to carry out an MEG analysis using the qsub distributed
computing toolbox. I'm using a quad-core i7 computer, and was hoping that
I'd be able to distribute the workload over all four cores.

I have followed the tutorial below exactly:
http://fieldtrip.fcdonders.nl/tutorial/distributedcomputing

The problem I am having is this: I managed to run example 1 (with my own
dataset), but I am finding that when I use qsubcellfun, the function
ft_definetrial is executed *sequentially* (for each condition), *not* in *
parallel*. Is there a way I can correct this, so as to parallelize the
analysis? Or is the toolbox not designed for multi-core machines?

Many thanks,

Graham Peyton
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From m.vandenieuwenhuijzen at fcdonders.ru.nl  Wed Jun 26 15:07:02 2013
From: m.vandenieuwenhuijzen at fcdonders.ru.nl (Marieke van de Nieuwenhuijzen)
Date: Wed, 26 Jun 2013 15:07:02 +0200 (CEST)
Subject: [FieldTrip] ROI selection of beamformer grid points
Message-ID: <1483937264.1423478.1372252022737.JavaMail.root@draco.zimbra.ru.nl>

Dear Fieldtrippers,

I am running my analyses on time courses reconstructed in source space. Basically, that means that my working dataset is a matrix of grid point x time. What I want to do now is do some analyses on a subset of that dataset, a bit analogous to selecting some sensors to restrict analyses to. Therefore, what I would ideally want to do, is select a subset of grid points corresponding to a specific location (for example only the occipital grid points, or only the grid points corresponding to a specific atlas label).

Does anyone have any suggestions about how I should go about selecting specific grid points? Is there perhaps some grid based atlas, or is it possible to select grid points based on their corresponding mni coordinates which you get after running ft_sourceinterpolate and ft_volumenormalise (in other words, is it possible to reverse ft_volumenormalise and ft_sourceinterpolate to map the mni coordinates to the grid points instead of the grid points to mni representation).

Any pointers would be much appreciated.

Best,
Marieke


From jm.horschig at donders.ru.nl  Wed Jun 26 15:26:41 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Wed, 26 Jun 2013 15:26:41 +0200
Subject: [FieldTrip] ROI selection of beamformer grid points
In-Reply-To: <1483937264.1423478.1372252022737.JavaMail.root@draco.zimbra.ru.nl>
References: <1483937264.1423478.1372252022737.JavaMail.root@draco.zimbra.ru.nl>
Message-ID: <51CAEC11.10702@donders.ru.nl>

Hi Marieke,

I basically use two approaches (in the end, both failed, so any other 
hints are appreciated):

  (a) Select voxels purely based on anatomical labels, as found in an 
atlas or in literature.

  (b) Select voxels based on some local maxima or minima, e.g. power 
maximum or maximum difference of log-ratio


(a) should be pretty straight forward. In essence it involves getting 
MNI coordinates, inversely warping your grids to MNI space, getting 
closest voxel. If you have your region of interest not in MNI 
coordinates you need to transform them. I found some tal2mni functions 
on the web for this, but note that this is just an estimate. Of course, 
(a) is also applicable if you have a localizer task using fMRI and want 
to focus on some localized voxels.
(b) is a bit more tricky, because you might be faced with huge 
inter-subject variability. Best of course would be to have the 
subject-specific, fMRI localized voxel. What I done in the past is to 
define a rough region of interest, e.g. posterior neocortex (based on 
some quick&dirty coordinate thresholding), using ft_volumesmooth to 
apply a gaussian blur on single subject-activity and then select the 
voxel that suits me best (i.e. the one of maximum activity). Of course 
your ROI could also be based on the grand-average or what have you. I 
had the feeling that especially this latter approach (base ROI on GA +/- 
3 cm, smooth individual subject data, select most sensitive voxel) 
worked quite well, but I cannot tell for sure, because in the end my 
results were not reliable enough.

Oh and btw, if the question just aims on 'how' to select 
programming-wise: Match the coordinate with your template, store the 
index based on the template-grid and use this index on your 
subject-specific grid to get voxel of interest in subject-specific 
coordinates.

Good luck!
Best,
Jörn

On 6/26/2013 3:07 PM, Marieke van de Nieuwenhuijzen wrote:
> Dear Fieldtrippers,
>
> I am running my analyses on time courses reconstructed in source space. Basically, that means that my working dataset is a matrix of grid point x time. What I want to do now is do some analyses on a subset of that dataset, a bit analogous to selecting some sensors to restrict analyses to. Therefore, what I would ideally want to do, is select a subset of grid points corresponding to a specific location (for example only the occipital grid points, or only the grid points corresponding to a specific atlas label).
>
> Does anyone have any suggestions about how I should go about selecting specific grid points? Is there perhaps some grid based atlas, or is it possible to select grid points based on their corresponding mni coordinates which you get after running ft_sourceinterpolate and ft_volumenormalise (in other words, is it possible to reverse ft_volumenormalise and ft_sourceinterpolate to map the mni coordinates to the grid points instead of the grid points to mni representation).
>
> Any pointers would be much appreciated.
>
> Best,
> Marieke
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands



From andmib at gmail.com  Wed Jun 26 19:22:33 2013
From: andmib at gmail.com (Andrew Brooks)
Date: Wed, 26 Jun 2013 13:22:33 -0400
Subject: [FieldTrip] Siemens GUI Streamer Disconnecting
Message-ID: <CALJPz6_8Vrq9ebz3vj5N=FWwoTP9HuJiXd-=PV5nqDqSbiFZ5g@mail.gmail.com>

Hello all,

I have a protocol that includes three separate sequences. I start the
Siemens GUI streamer prior to the first sequence, and keep it open through
all three sequences. Only on the last sequence do I run
ft_omri_pipeline_nuisance. I've been running into a problem where the
Siemens GUI streamer disconnects as soon as the the third sequence starts
running (and the ft_omri_pipeline script is waiting for data). I have to
manually click 'connect' as soon as it disconnects, and then it works fine.

Any ideas as to why the streamer would disconnect like this?

Thanks!
Andrew
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From j.herring at fcdonders.ru.nl  Thu Jun 27 12:45:53 2013
From: j.herring at fcdonders.ru.nl (Herring, J.D. (Jim))
Date: Thu, 27 Jun 2013 12:45:53 +0200 (CEST)
Subject: [FieldTrip] QSUB toolbox on a multi-core computer
In-Reply-To: <CANOxK9E+ZCy9zFqYw1kR_aK7wnEpq0cF9efVj93wFxg5zJWmhQ@mail.gmail.com>
References: <CANOxK9E+ZCy9zFqYw1kR_aK7wnEpq0cF9efVj93wFxg5zJWmhQ@mail.gmail.com>
Message-ID: <004701ce7323$7fa9ff20$7efdfd60$@herring@fcdonders.ru.nl>

Dear Graham,

 

As stated in the tutorial the distributed computing functions are intended
to distribute workload over different computers running a Torque or SGE
batch system: "This tutorial covered how to distribute your
computations/workload over multiple computers in a cluster that uses the
Torque or SGE batch queue system". However, what you could do is make use
of Matlab's parallel processing tools. Matlab allows you to open a pool of
so-called 'workers' to distribute processing jobs to allowing you to run
multiple processes in parallel. Please see
http://www.mathworks.nl/help/distcomp/matlabpool.html and
http://www.mathworks.nl/help/matlab/ref/parfor.html.

 

Once you've opened a pool of workers using 'matlabpool', you can use
'parfor' in the same way as you would use 'for' to create a loop that runs
all processes in parallel over all four cores. 

 

Best,

Jim

From: fieldtrip-bounces at science.ru.nl
[mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of Graham Peyton
Sent: woensdag 26 juni 2013 12:14
To: fieldtrip at science.ru.nl
Subject: [FieldTrip] QSUB toolbox on a multi-core computer

 

Dear FieldTrip community,

I am trying to carry out an MEG analysis using the qsub distributed
computing toolbox. I'm using a quad-core i7 computer, and was hoping that
I'd be able to distribute the workload over all four cores. 

I have followed the tutorial below exactly:
http://fieldtrip.fcdonders.nl/tutorial/distributedcomputing

The problem I am having is this: I managed to run example 1 (with my own
dataset), but I am finding that when I use qsubcellfun, the function
ft_definetrial is executed sequentially (for each condition), not in
parallel. Is there a way I can correct this, so as to parallelize the
analysis? Or is the toolbox not designed for multi-core machines? 

 

Many thanks,

Graham Peyton

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From ana.hincapie at gmail.com  Fri Jun 28 09:31:24 2013
From: ana.hincapie at gmail.com (=?ISO-8859-1?Q?Ana_Sof=EDa_Hincapi=E9_Casas?=)
Date: Fri, 28 Jun 2013 09:31:24 +0200
Subject: [FieldTrip] In the forward problem,
 how are the points for the grid.inside and grid.outside defined?
Message-ID: <CAN+fi=zVBtweOXxwEWaHWnp1wKfDTXBXoUgeFgyoeVgQ=jCOxA@mail.gmail.com>

Hi,

I´am new in FieldTrip and I would like to what are the grid.inside and
grid.outside points and if I could used the whole grid to calculate the
leadfields.

Thanks in advance for the help you could bring me.

Regards,

-- 
Ana Hincapié
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From jm.horschig at donders.ru.nl  Fri Jun 28 10:42:03 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Fri, 28 Jun 2013 10:42:03 +0200
Subject: [FieldTrip] In the forward problem,
 how are the points for the grid.inside and grid.outside defined?
In-Reply-To: <CAN+fi=zVBtweOXxwEWaHWnp1wKfDTXBXoUgeFgyoeVgQ=jCOxA@mail.gmail.com>
References: <CAN+fi=zVBtweOXxwEWaHWnp1wKfDTXBXoUgeFgyoeVgQ=jCOxA@mail.gmail.com>
Message-ID: <51CD4C5B.5030909@donders.ru.nl>

Hi Ana,

inside and outside just describe whether the grid point is inside or 
outside the brain. You can plot this to see for yourself:
% plot only what is inside the brain
figure;
ft_plot_vol(vol, 'edgecolor', 'none'); alpha 0.4;
ft_plot_mesh(grid.pos(grid.inside,:));

% plot the whole grid
figure;
ft_plot_vol(vol, 'edgecolor', 'none'); alpha 0.4;
ft_plot_mesh(grid.pos(:,:));

FieldTrip will use that information automatically to only use grid 
points inside the brain, so yes, you can use the whole grid to compute 
the leadfield matrix. If you do not want that, you can modify 
grid.inside and grid.outside yourself.

Have fun fieldtrippin' :)
Jörn

On 6/28/2013 9:31 AM, Ana Sofía Hincapié Casas wrote:
> Hi,
>
> I´am new in FieldTrip and I would like to what are the grid.inside and 
> grid.outside points and if I could used the whole grid to calculate 
> the leadfields.
>
> Thanks in advance for the help you could bring me.
>
> Regards,
>
> -- 
> Ana Hincapié
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands

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From ggonesc at upo.es  Fri Jun 28 18:28:57 2013
From: ggonesc at upo.es (Gabriel Gonzalez Escamilla)
Date: Fri, 28 Jun 2013 18:28:57 +0200
Subject: [FieldTrip] problem appending data
Message-ID: <2350c7b9464ea50a.51cdd5e9@upo.es>

Dear Fieldtrip experts,

I'm working with restin-state EEG data, I'm looking for performing EEG coherence analysis between my normal EEG channels and a channel from the same subject but aquired with a different name

I did: data = ft_appenddata([], dataEEG_allchans, dataEEG_1chan)
and it did concatenate the one single channel at the end of the dataEEG_allchans, so now I have a matrix with Nchans+1, that looks perfect to me, then I did perform fourier transformations with a hanning window, and workded perfectly, but if I set 
cfg.method='coh'
cfg.complex='imag'
cfg.channelcbm={'all', 'ref-P7'}
icohe=ft_connectovityanalysis(cfg,)

I always get the following error:
???? attempted to access siz(4); index out of bounds because numel(siz=3)
Error in ==> ft_checkdata>fixcsd at 798

I have also tried something like:
cfg.channelcbm={{1x40cell}, 'ref-P7'}
where {1x40 cell} is a cell matrix containing the names of all my sensors

but it didn't worked.

Any help will be appreciated

Many thanks in advanced,
Gabriel

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From manuel.mercier at einstein.yu.edu  Fri Jun 28 22:43:54 2013
From: manuel.mercier at einstein.yu.edu (Manuel  Mercier)
Date: Fri, 28 Jun 2013 20:43:54 +0000
Subject: [FieldTrip] PLV formula
Message-ID: <D0B70B31DE8EC849948A63FAED36B67D2A14420D@AEWEXCPM21.yuad.uds.yu.edu>

Dear Fieldtripers
Sometime ago I wrote for myself a function that was computing PLV and some related non parametric statistics.
(Phase Locking Value as define as the mean across trials of the phase angle difference recorded at two loci ; based on Lachaux et al., 1999, HBM).
I implemented PLV in matlab using the following formula:
plv = squeeze(abs(mean(exp(1i*(angle(data.fourierspctrm(:,cmb(1),:,:)) ...
                                                -angle(data.fourierspctrm(:,cmb(2),:,:)))),1)));
with cmb(1) and cmb(2) being the indices of the electrodes of interest (between which PLV is computed).
I compared my results with the ft_connectivityanalysis function from Fieldtrip and the results were exactly the same.
So far so good.

But I recently went back to my code, and I was a little bit confused.
Since I was dealing with angles, I though that the best way to do the subtraction should be done in the complex plane
Like:
plv = squeeze(abs(mean(exp(1i*(angle(exp(1i*(angle(data.fourierspctrm(:,cmb(1),:,:)))) ...
                                                        - exp(1i*(angle(data.fourierspctrm(:,cmb(2),:,:))))))),1)));
(for instance if the two angles: pi/2 and -pi/2 the direct subtraction will give pi,
whereas in the complex plan it will be pi/2 - with the norm x2).

The result I got with this code is obviously different from the previous one, and what I got from Fieldtrip.
I went back to the archive of the mailing list but didn't find a clear answer to my point. Does anyone can enlighten me ?
Thanks !

Manuel


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From ebrahimi_nia at yahoo.com  Sat Jun  1 06:52:43 2013
From: ebrahimi_nia at yahoo.com (Fatemeh Ebrahimi nia)
Date: Fri, 31 May 2013 21:52:43 -0700 (PDT)
Subject: [FieldTrip] loreta2fieldtrip function error
In-Reply-To: <1370015815.5183.YahooMailNeo@web122402.mail.ne1.yahoo.com>
References: <1369934092.15336.YahooMailNeo@web122405.mail.ne1.yahoo.com>
	<51A78CC1.6030906@berkeley.edu>
	<1370015815.5183.YahooMailNeo@web122402.mail.ne1.yahoo.com>
Message-ID: <1370062363.83888.YahooMailNeo@web122406.mail.ne1.yahoo.com>



Hi Dear all,
Can any one give me information about the output structure of "loreta2fieldtrip" function (What do the matrixes refer to?) or advise a reference to study about that please? 

Best,
Fatemeh



________________________________
 From: Ingrid Nieuwenhuis <inieuwenhuis at berkeley.edu>
To: fieldtrip at science.ru.nl 
Sent: Thursday, May 30, 2013 10:30 AM
Subject: Re: [FieldTrip] loreta2fieldtrip function error
 


Hi Fatemeh,

I had the same error recently when I did the same. I filed the bug,
    see http://bugzilla.fcdonders.nl/show_bug.cgi?id=2144

I did create a work around. In the LORETA program, you can export
    the source data as a text file. You can read that text file in with
    loreta2fieldtrip.m. It's a bit of a patch, but it worked for me. 

Hope this helps,
Ingrid


On 5/30/2013 10:14 AM, Fatemeh Ebrahimi nia wrote:

Hi dear all,
>
>
>I am analyzing EEG data. I have computed sLORETA (.slor) from ERP data. Now I want to read and convert LORETA source reconstruction into a
>MATLAB data structure using "loreta2fieldtrip" function, But I have gotten the bellow error.
>
>
>**** Error using fread
>
>Invalid precision.
>Error in loreta2fieldtrip (line 85)
>activity = fread(fid, [voxnumber Ntime], 'float = >single'); ***
>
>
>Can someone give me a help?
>
>
>
>Best regards,
>Fatemeh
>
>
>
>
>_______________________________________________
fieldtrip mailing list fieldtrip at donders.ru.nl http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

-- 
Ingrid Nieuwenhuis PhD
Postdoctoral Fellow
Sleep and Neuroimaging Laboratory
Department of Psychology
University of California, Berkeley
California 94720-1650
Tolman Hall, room 5305 
_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl
http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl
http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
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From politzerahless at gmail.com  Sat Jun  1 20:44:04 2013
From: politzerahless at gmail.com (Stephen Politzer-Ahles)
Date: Sat, 1 Jun 2013 13:44:04 -0500
Subject: [FieldTrip] Question about minimum norm estimate pipeline
Message-ID: <CAJT2k_-Qba_X4uqQeR54LFApDSe31xkWCkCAwO-DnR5=zXxWpQ@mail.gmail.com>

Hi Arjen,

Thanks for your message. I did align the mri to Talairach; as you can see
from http://i.imgur.com/26nyHYZ.png, the volume conduction model and
sourcespace are both expressed in the same coordinate system (i.e.,
everything's pointing in the same direction) but they're just not sitting
on top of one another. If anyone has any ideas on where that problem was
introduced (or how to re-align them now), I would greatly appreciate it.
Below I have some more details about how I processed that data, if it helps.

I'm trying to go through the data one step at a time and track where the
problem might have happened. When I compare the sourcespace before having
applied any transformation (i.e., the headshape from
<subject>-oct-6-src.fif) to the original mri (orig-nomask.mgz), they look
ok (I don't know how to plot them together, but see
http://i.imgur.com/LGW7YnJ.png and http://i.imgur.com/JUoTxc9.png -- things
at least look like they're on more or less the same plane). Then I
re-register the mri to CTF (
http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate#source_modelco-registration_of_the_source_space_to_the_sensor-based_head_coordinate_system);
after that, in mri_nom_ctf, the axes are all going in the right direction
but the whole head is tilted forward and the origin of the axes is no
longer at the anterior commisure (see http://i.imgur.com/CTZNOTk.png for
the realigned MRI).  Applying the transformation matrix T to the
sourcespace also seems to tilt it like that (http://i.imgur.com/bcNIpf3.png),
although as can be seen from the first image in this message it doesn't
quite line up with the volume conduction model in the end. As for the
volume conduction model, here is what it looks like at first (
http://i.imgur.com/ZX3m38b.png) and here is what it looks like after
applying the transformation matrix (http://i.imgur.com/vXa3Cnc.png).
Obviously the transformation matrix is doing something, but it's not
getting the sourcespace and volume conduction model lined up; since it's
the same transformation matrix, all I can guess is that there was some
pre-existing difference between the source mesh (the .fif file) and the
anatomical mri (orig-nomask.mgz), but I'm not sure when that came in.

Another minor issue: when I first compared the volume conduction model and
the sourcespace, they were expressed in different units even though I
followed the code in the tutorial. See http://i.imgur.com/orwgcTJ.png: the
sourcespace looks 10x smaller than the volume conduction model, which I
assume is because it is expressed in cm whereas the volume conduction model
is expressed in mm. To get the figure linked at the very beginning of this
message, I had to convert the units of the volume conduction model to cm,
even though that's not in the tutorial.

I notice that the tutorial on the wiki hasn't been edited since October
2012 (other than a few edits I made this month which were just correcting
typos in the prose). Is it possible that what's on the wiki is out of date?
(Also cc'ing Lilla on this.)

Thanks,
Steve



> Message: 1
> Date: Fri, 31 May 2013 08:11:23 +0200 (CEST)
> From: "Stolk, A." <a.stolk at fcdonders.ru.nl>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] Question about minimum norm estimate pipeline
> Message-ID:
>         <
1914237354.1292588.1369980683984.JavaMail.root at sculptor.zimbra.ru.nl>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Steve, A quick guess; did you correctly align your resliced mri to
Talairach space by indicating the commissures (
http://imaging.mrc-cbu.cam.ac.uk/imaging/FindingCommissures ) and, if I'm
correct, a point in the same place, e.g. between the hemispheres? This
should update the transformation matrix. Best regards, Arjen -----
Oorspronkelijk bericht -----
> > Van: "Stephen Politzer-Ahles" <politzerahless at gmail.com>
> > Aan: fieldtrip at science.ru.nl
> > Verzonden: Vrijdag 31 mei 2013 05:53:45
> > Onderwerp: [FieldTrip] Question about minimum norm estimate pipeline
> > Hello all,
> > I have not yet gotten a response to my question below, but in the
> > meantime I have another question about the minimum norm estimate
> > workflow--specifically, about the coordinate system for the
> > skull-stripped anatomy in the step described at
> >
http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate#preprocessing_of_the_anatomical_mrisave_to_disk
> > . I'm confused by the following bit of code:
> > % ensure that the skull-stripped anatomy is expressed in the same
> > coordinate system as the anatomy
> > seg.transform = mri_tal.transform;
> > In my data, mri_tal.coordsys is 'spm' (I presume this is the result of
> > re-aligning to Talairach in the previous step?) whereas seg.coordsys
> > is 'ctf' (as a result of re-aligning to CTF several steps earlier).
> > (But mri_tal also has a field mri_tal.transformorig, which seg does
> > not have.) So should I really be using the same transform for both, as
> > shown in the tutorial?
> > Apologies if this question is pretty basic; I'm just trying to
> > pinpoint where the mis-alignment described in my message below
> > occurred, so I want to make sure I understand each step of the
> > workflow correctly
> > Best,
> > Steve
> > > Message: 1
> > > Date: Sat, 25 May 2013 08:11:18 -0500
> > > From: Stephen Politzer-Ahles < politzerahless at gmail.com >
> > > To: fieldtrip at donders.ru.nl
> > > Subject: [FieldTrip] Sourcespace and volume conductor misaligned
> > > Message-ID:
> > > <CAJT2k_9-hd_sM=hp4P-CUu+=aduSOMyZV7XPG0= fFk0ouR0wzA at mail.gmail.com
> > > >
> > > Content-Type: text/plain; charset="utf-8"
> > >
> > > Hello all,
> > >
> > > I am going through the workflow at
> > > http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate . After
> > > making
> > > the volume conduction model using ft_prepare_headmodel(), I noticed
> > > that
> > > although the volume conduction model and sourcespace have the same
> > > orientation and overall size/shape (after I converted the volume
> > > conduction
> > > model to cm, which wasn't in the tutorial but my original model came
> > > out in
> > > mm), they don't quite line up, as you can see in this figure:
> > >
> > > http://i.imgur.com/mGEtLOa.png
> > >
> > > I did interactively re-align the data to CTF (twice--in step 2 of
> > > "Preprocessing of the anatomical MRI" and in step 4 of "Source
> > > model")
> > > using fiducials, and to Talairach (step 5 of "Preprocessing of the
> > > anatomical data"), so I'm not sure how it ended up this way. The
> > > code I've
> > > used at each step is basically the same as that in the tutorial.
> > >
> > > Is there any way to line up my volume conduction model and
> > > sourcespace now,
> > > without going back and re-running most of the workflow?
> > >
> > > Best,
> > > Steve
> > >
> > > --
> > > Stephen Politzer-Ahles
> > > University of Kansas
> > > Linguistics Department
> > > http://people.ku.edu/~sjpa/
> > On Sat, May 25, 2013 at 1:56 PM, < fieldtrip-request at science.ru.nl >
> > wrote:
> > >
> > > Send fieldtrip mailing list submissions to
> > > fieldtrip at science.ru.nl
> > >
> > > To subscribe or unsubscribe via the World Wide Web, visit
> > > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > > or, via email, send a message with subject or body 'help' to
> > > fieldtrip-request at science.ru.nl
> > >
> > > You can reach the person managing the list at
> > > fieldtrip-owner at science.ru.nl
> > >
> > > When replying, please edit your Subject line so it is more specific
> > > than "Re: Contents of fieldtrip digest..."
> > >
> > >
> > > Today's Topics:
> > >
> > > 1. Sourcespace and volume conductor misaligned
> > > (Stephen Politzer-Ahles)
> > > 2. Re: fieldtrip Digest, Vol 30, Issue 31 (Johanna Zumer)
> > >
> > >
> > > ----------------------------------------------------------------------
> > >
> > > Message: 1
> > > Date: Sat, 25 May 2013 08:11:18 -0500
> > > From: Stephen Politzer-Ahles < politzerahless at gmail.com >
> > > To: fieldtrip at donders.ru.nl
> > > Subject: [FieldTrip] Sourcespace and volume conductor misaligned
> > > Message-ID:
> > > <CAJT2k_9-hd_sM=hp4P-CUu+=aduSOMyZV7XPG0= fFk0ouR0wzA at mail.gmail.com
> > > >
> > > Content-Type: text/plain; charset="utf-8"
> > >
> > > Hello all,
> > >
> > > I am going through the workflow at
> > > http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate . After
> > > making
> > > the volume conduction model using ft_prepare_headmodel(), I noticed
> > > that
> > > although the volume conduction model and sourcespace have the same
> > > orientation and overall size/shape (after I converted the volume
> > > conduction
> > > model to cm, which wasn't in the tutorial but my original model came
> > > out in
> > > mm), they don't quite line up, as you can see in this figure:
> > >
> > > http://i.imgur.com/mGEtLOa.png
> > >
> > > I did interactively re-align the data to CTF (twice--in step 2 of
> > > "Preprocessing of the anatomical MRI" and in step 4 of "Source
> > > model")
> > > using fiducials, and to Talairach (step 5 of "Preprocessing of the
> > > anatomical data"), so I'm not sure how it ended up this way. The
> > > code I've
> > > used at each step is basically the same as that in the tutorial.
> > >
> > > Is there any way to line up my volume conduction model and
> > > sourcespace now,
> > > without going back and re-running most of the workflow?
> > >
> > > Best,
> > > Steve
> > >
> > > --
> > > Stephen Politzer-Ahles
> > > University of Kansas
> > > Linguistics Department
> > > http://people.ku.edu/~sjpa/
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From Lilla.Magyari at mpi.nl  Sat Jun  1 23:22:34 2013
From: Lilla.Magyari at mpi.nl (Lilla.Magyari at mpi.nl)
Date: Sat, 1 Jun 2013 23:22:34 +0200 (CEST)
Subject: [FieldTrip] Question about minimum norm estimate pipeline
In-Reply-To: <CAJT2k_-Qba_X4uqQeR54LFApDSe31xkWCkCAwO-DnR5=zXxWpQ@mail.gmail.com>
References: <CAJT2k_-Qba_X4uqQeR54LFApDSe31xkWCkCAwO-DnR5=zXxWpQ@mail.gmail.com>
Message-ID: <2765.87.78.47.204.1370121754.squirrel@87.78.47.204>

hi Steve,

yes, it is possible that the tutorial is slightly out of the date. I can
look at your problem and the tutorial around the end of the next week.
Thanks a lot for the detailed email!

Lilla



> Hi Arjen,
>
> Thanks for your message. I did align the mri to Talairach; as you can see
> from http://i.imgur.com/26nyHYZ.png, the volume conduction model and
> sourcespace are both expressed in the same coordinate system (i.e.,
> everything's pointing in the same direction) but they're just not sitting
> on top of one another. If anyone has any ideas on where that problem was
> introduced (or how to re-align them now), I would greatly appreciate it.
> Below I have some more details about how I processed that data, if it
> helps.
>
> I'm trying to go through the data one step at a time and track where the
> problem might have happened. When I compare the sourcespace before having
> applied any transformation (i.e., the headshape from
> <subject>-oct-6-src.fif) to the original mri (orig-nomask.mgz), they look
> ok (I don't know how to plot them together, but see
> http://i.imgur.com/LGW7YnJ.png and http://i.imgur.com/JUoTxc9.png --
> things
> at least look like they're on more or less the same plane). Then I
> re-register the mri to CTF (
> http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate#source_modelco-registration_of_the_source_space_to_the_sensor-based_head_coordinate_system);
> after that, in mri_nom_ctf, the axes are all going in the right direction
> but the whole head is tilted forward and the origin of the axes is no
> longer at the anterior commisure (see http://i.imgur.com/CTZNOTk.png for
> the realigned MRI).  Applying the transformation matrix T to the
> sourcespace also seems to tilt it like that
> (http://i.imgur.com/bcNIpf3.png),
> although as can be seen from the first image in this message it doesn't
> quite line up with the volume conduction model in the end. As for the
> volume conduction model, here is what it looks like at first (
> http://i.imgur.com/ZX3m38b.png) and here is what it looks like after
> applying the transformation matrix (http://i.imgur.com/vXa3Cnc.png).
> Obviously the transformation matrix is doing something, but it's not
> getting the sourcespace and volume conduction model lined up; since it's
> the same transformation matrix, all I can guess is that there was some
> pre-existing difference between the source mesh (the .fif file) and the
> anatomical mri (orig-nomask.mgz), but I'm not sure when that came in.
>
> Another minor issue: when I first compared the volume conduction model and
> the sourcespace, they were expressed in different units even though I
> followed the code in the tutorial. See http://i.imgur.com/orwgcTJ.png: the
> sourcespace looks 10x smaller than the volume conduction model, which I
> assume is because it is expressed in cm whereas the volume conduction
> model
> is expressed in mm. To get the figure linked at the very beginning of this
> message, I had to convert the units of the volume conduction model to cm,
> even though that's not in the tutorial.
>
> I notice that the tutorial on the wiki hasn't been edited since October
> 2012 (other than a few edits I made this month which were just correcting
> typos in the prose). Is it possible that what's on the wiki is out of
> date?
> (Also cc'ing Lilla on this.)
>
> Thanks,
> Steve
>
>
>
>> Message: 1
>> Date: Fri, 31 May 2013 08:11:23 +0200 (CEST)
>> From: "Stolk, A." <a.stolk at fcdonders.ru.nl>
>> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
>> Subject: Re: [FieldTrip] Question about minimum norm estimate pipeline
>> Message-ID:
>>         <
> 1914237354.1292588.1369980683984.JavaMail.root at sculptor.zimbra.ru.nl>
>> Content-Type: text/plain; charset="utf-8"
>>
>> Hi Steve, A quick guess; did you correctly align your resliced mri to
> Talairach space by indicating the commissures (
> http://imaging.mrc-cbu.cam.ac.uk/imaging/FindingCommissures ) and, if I'm
> correct, a point in the same place, e.g. between the hemispheres? This
> should update the transformation matrix. Best regards, Arjen -----
> Oorspronkelijk bericht -----
>> > Van: "Stephen Politzer-Ahles" <politzerahless at gmail.com>
>> > Aan: fieldtrip at science.ru.nl
>> > Verzonden: Vrijdag 31 mei 2013 05:53:45
>> > Onderwerp: [FieldTrip] Question about minimum norm estimate pipeline
>> > Hello all,
>> > I have not yet gotten a response to my question below, but in the
>> > meantime I have another question about the minimum norm estimate
>> > workflow--specifically, about the coordinate system for the
>> > skull-stripped anatomy in the step described at
>> >
> http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate#preprocessing_of_the_anatomical_mrisave_to_disk
>> > . I'm confused by the following bit of code:
>> > % ensure that the skull-stripped anatomy is expressed in the same
>> > coordinate system as the anatomy
>> > seg.transform = mri_tal.transform;
>> > In my data, mri_tal.coordsys is 'spm' (I presume this is the result of
>> > re-aligning to Talairach in the previous step?) whereas seg.coordsys
>> > is 'ctf' (as a result of re-aligning to CTF several steps earlier).
>> > (But mri_tal also has a field mri_tal.transformorig, which seg does
>> > not have.) So should I really be using the same transform for both, as
>> > shown in the tutorial?
>> > Apologies if this question is pretty basic; I'm just trying to
>> > pinpoint where the mis-alignment described in my message below
>> > occurred, so I want to make sure I understand each step of the
>> > workflow correctly
>> > Best,
>> > Steve
>> > > Message: 1
>> > > Date: Sat, 25 May 2013 08:11:18 -0500
>> > > From: Stephen Politzer-Ahles < politzerahless at gmail.com >
>> > > To: fieldtrip at donders.ru.nl
>> > > Subject: [FieldTrip] Sourcespace and volume conductor misaligned
>> > > Message-ID:
>> > > <CAJT2k_9-hd_sM=hp4P-CUu+=aduSOMyZV7XPG0= fFk0ouR0wzA at mail.gmail.com
>> > > >
>> > > Content-Type: text/plain; charset="utf-8"
>> > >
>> > > Hello all,
>> > >
>> > > I am going through the workflow at
>> > > http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate . After
>> > > making
>> > > the volume conduction model using ft_prepare_headmodel(), I noticed
>> > > that
>> > > although the volume conduction model and sourcespace have the same
>> > > orientation and overall size/shape (after I converted the volume
>> > > conduction
>> > > model to cm, which wasn't in the tutorial but my original model came
>> > > out in
>> > > mm), they don't quite line up, as you can see in this figure:
>> > >
>> > > http://i.imgur.com/mGEtLOa.png
>> > >
>> > > I did interactively re-align the data to CTF (twice--in step 2 of
>> > > "Preprocessing of the anatomical MRI" and in step 4 of "Source
>> > > model")
>> > > using fiducials, and to Talairach (step 5 of "Preprocessing of the
>> > > anatomical data"), so I'm not sure how it ended up this way. The
>> > > code I've
>> > > used at each step is basically the same as that in the tutorial.
>> > >
>> > > Is there any way to line up my volume conduction model and
>> > > sourcespace now,
>> > > without going back and re-running most of the workflow?
>> > >
>> > > Best,
>> > > Steve
>> > >
>> > > --
>> > > Stephen Politzer-Ahles
>> > > University of Kansas
>> > > Linguistics Department
>> > > http://people.ku.edu/~sjpa/
>> > On Sat, May 25, 2013 at 1:56 PM, < fieldtrip-request at science.ru.nl >
>> > wrote:
>> > >
>> > > Send fieldtrip mailing list submissions to
>> > > fieldtrip at science.ru.nl
>> > >
>> > > To subscribe or unsubscribe via the World Wide Web, visit
>> > > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> > > or, via email, send a message with subject or body 'help' to
>> > > fieldtrip-request at science.ru.nl
>> > >
>> > > You can reach the person managing the list at
>> > > fieldtrip-owner at science.ru.nl
>> > >
>> > > When replying, please edit your Subject line so it is more specific
>> > > than "Re: Contents of fieldtrip digest..."
>> > >
>> > >
>> > > Today's Topics:
>> > >
>> > > 1. Sourcespace and volume conductor misaligned
>> > > (Stephen Politzer-Ahles)
>> > > 2. Re: fieldtrip Digest, Vol 30, Issue 31 (Johanna Zumer)
>> > >
>> > >
>> > > ----------------------------------------------------------------------
>> > >
>> > > Message: 1
>> > > Date: Sat, 25 May 2013 08:11:18 -0500
>> > > From: Stephen Politzer-Ahles < politzerahless at gmail.com >
>> > > To: fieldtrip at donders.ru.nl
>> > > Subject: [FieldTrip] Sourcespace and volume conductor misaligned
>> > > Message-ID:
>> > > <CAJT2k_9-hd_sM=hp4P-CUu+=aduSOMyZV7XPG0= fFk0ouR0wzA at mail.gmail.com
>> > > >
>> > > Content-Type: text/plain; charset="utf-8"
>> > >
>> > > Hello all,
>> > >
>> > > I am going through the workflow at
>> > > http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate . After
>> > > making
>> > > the volume conduction model using ft_prepare_headmodel(), I noticed
>> > > that
>> > > although the volume conduction model and sourcespace have the same
>> > > orientation and overall size/shape (after I converted the volume
>> > > conduction
>> > > model to cm, which wasn't in the tutorial but my original model came
>> > > out in
>> > > mm), they don't quite line up, as you can see in this figure:
>> > >
>> > > http://i.imgur.com/mGEtLOa.png
>> > >
>> > > I did interactively re-align the data to CTF (twice--in step 2 of
>> > > "Preprocessing of the anatomical MRI" and in step 4 of "Source
>> > > model")
>> > > using fiducials, and to Talairach (step 5 of "Preprocessing of the
>> > > anatomical data"), so I'm not sure how it ended up this way. The
>> > > code I've
>> > > used at each step is basically the same as that in the tutorial.
>> > >
>> > > Is there any way to line up my volume conduction model and
>> > > sourcespace now,
>> > > without going back and re-running most of the workflow?
>> > >
>> > > Best,
>> > > Steve
>> > >
>> > > --
>> > > Stephen Politzer-Ahles
>> > > University of Kansas
>> > > Linguistics Department
>> > > http://people.ku.edu/~sjpa/
>




From frank.ye.mei at gmail.com  Sun Jun  2 03:58:29 2013
From: frank.ye.mei at gmail.com (Frank Mei)
Date: Sat, 1 Jun 2013 21:58:29 -0400
Subject: [FieldTrip] error when using ctf2grad (Lozano Soldevilla,
	D. (Diego))
Message-ID: <CAF0J_Mts3imCMYaVE8QppR=oT8j0h9ceLKm=ANtW6JNyAxoPcA@mail.gmail.com>

Hello Diego,

Thank you for the reply. I was using fieldtrip20120822.

I found the bug in the fieldtrip20120822 file -ft_read_header.m.
In line 446 of the file:

-------
if any(~cellfun(@isempty,strfind(coeftype, 'G1AR')))
-------

should be:

-------
if any(~cellfun(@isempty,strfind(coeftype, 'G3AR')))
-------


The bug is corrected in the latest version of fieldtrip, and it runs
correctly now.

Now, grad.balance has 'G1BR','G2BR','G3BR''G3AR' in it.

The ctf sytem I use is ctf151.

Regards,
Ye
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From vitoria.piai at gmail.com  Sun Jun  2 11:17:25 2013
From: vitoria.piai at gmail.com (=?ISO-8859-1?Q?Vit=F3ria_Magalh=E3es_Piai?=)
Date: Sun, 02 Jun 2013 11:17:25 +0200
Subject: [FieldTrip] how to use ft_stratify?
Message-ID: <51AB0DA5.10805@gmail.com>

Hi all,

I'm trying to use ft_stratify for the first time, but (it could be just 
me) I don't find the help info helpful enough :)
What I want to achieve in the end is TFRs of two conditions for which 
the histogram of the reaction time over trials for each condition is 
matched.

If I understood ft_stratify correctly (and I doubt that), I could use 
this function to select the trials for each condition such that the 
histograms of the RTs match. Then knowing which trials to keep, I run 
ft_freqanalysis on those specifically.
So question number 1, is that how I should proceed? 'Cause as far as I 
can tell, ft_stratify will not take a whole raw data structure: The help 
says "each input is a Nchan X Nobs matrix". So I have to go for the RTs 
then.

Assuming my approach is correct (ft_stratify on RTs of two conditions, 
then move on with only those trials), I've made a matrix Nchan x 
N_trials for each condition.
% input1 = 265 sensors x 95 RT_trials;
% input2 = 265 sensors x 100 RT_trials;

         cfgst = [];
         cfgst.method      = 'histogram';
         cfgst.equalbinavg = 'no';
         cfgst.numbin      = 4;
         cfgst.numiter     = 2000; % default
         [output,bin] = ft_stratify(cfgst, input1, input2);

I then get an error in line 127:
linearhisto = zeros(ncond, cfg.numbin.^nchan);
??? Error using ==> zeros
Maximum variable size allowed by the program is exceeded.

Apparently, zeros(2, 4^265) is something matlab doesn't want to calculate!
Am I doing something wrong here? Has anyone worked with this function 
before (with such a number of sensors)?

Any help is greatly appreciated!
Cheers, Vitória


From a.stolk at fcdonders.ru.nl  Sun Jun  2 11:46:03 2013
From: a.stolk at fcdonders.ru.nl (Stolk, A.)
Date: Sun, 2 Jun 2013 11:46:03 +0200 (CEST)
Subject: [FieldTrip] how to use ft_stratify?
In-Reply-To: <51AB0DA5.10805@gmail.com>
Message-ID: <1910615072.1312606.1370166363974.JavaMail.root@sculptor.zimbra.ru.nl>

Hi Vitoria,

There is a wikipage that may help you get started, and answer your questions:
http://fieldtrip.fcdonders.nl/example/stratify

Best wishes,
Arjen  

----- Oorspronkelijk bericht -----
> Van: "Vitória Magalhães Piai" <vitoria.piai at gmail.com>
> Aan: fieldtrip at donders.ru.nl
> Verzonden: Zondag 2 juni 2013 11:17:25
> Onderwerp: [FieldTrip] how to use ft_stratify?
> Hi all,
> 
> I'm trying to use ft_stratify for the first time, but (it could be
> just
> me) I don't find the help info helpful enough :)
> What I want to achieve in the end is TFRs of two conditions for which
> the histogram of the reaction time over trials for each condition is
> matched.
> 
> If I understood ft_stratify correctly (and I doubt that), I could use
> this function to select the trials for each condition such that the
> histograms of the RTs match. Then knowing which trials to keep, I run
> ft_freqanalysis on those specifically.
> So question number 1, is that how I should proceed? 'Cause as far as I
> can tell, ft_stratify will not take a whole raw data structure: The
> help
> says "each input is a Nchan X Nobs matrix". So I have to go for the
> RTs
> then.
> 
> Assuming my approach is correct (ft_stratify on RTs of two conditions,
> then move on with only those trials), I've made a matrix Nchan x
> N_trials for each condition.
> % input1 = 265 sensors x 95 RT_trials;
> % input2 = 265 sensors x 100 RT_trials;
> 
> cfgst = [];
> cfgst.method = 'histogram';
> cfgst.equalbinavg = 'no';
> cfgst.numbin = 4;
> cfgst.numiter = 2000; % default
> [output,bin] = ft_stratify(cfgst, input1, input2);
> 
> I then get an error in line 127:
> linearhisto = zeros(ncond, cfg.numbin.^nchan);
> ??? Error using ==> zeros
> Maximum variable size allowed by the program is exceeded.
> 
> Apparently, zeros(2, 4^265) is something matlab doesn't want to
> calculate!
> Am I doing something wrong here? Has anyone worked with this function
> before (with such a number of sensors)?
> 
> Any help is greatly appreciated!
> Cheers, Vitória
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip



From vitoria.piai at gmail.com  Sun Jun  2 17:09:34 2013
From: vitoria.piai at gmail.com (=?ISO-8859-1?Q?Vit=F3ria_Magalh=E3es_Piai?=)
Date: Sun, 02 Jun 2013 17:09:34 +0200
Subject: [FieldTrip] how to use ft_stratify?
In-Reply-To: <mailman.11.1370167205.25821.fieldtrip@science.ru.nl>
References: <mailman.11.1370167205.25821.fieldtrip@science.ru.nl>
Message-ID: <51AB602E.8020609@gmail.com>

Thanx, Arjen!
Shame on me, I should have known that there would be a wikipage on that :)

And for the sake of archiving, in case someone else ever bumps into this 
thread because they're making the same mistake as me when using this 
function, here's what I was doing wrong:
The input Nchan x N_trials for each condition, Nchan should be 1 'cause 
my data are the RTs
So:

% input1 = RT_trials_cond1' ; % size = 1 x 95
% input2 = RT_trials_cond2' ;  % size = 1 x 100
cfgst = [];
cfgst.method = 'histogram';
output = ft_stratify(cfgst, input1, input2);

Now it will run and it won't even complain they are of different sizes 
either!

Hope this will help anyone in the future making the same mistake!
Cheers, Vitória



On 6/2/2013 12:00 PM, fieldtrip-request at science.ru.nl wrote:
> Message: 2
> Date: Sun, 02 Jun 2013 11:17:25 +0200
> From: Vit?ria Magalh?es Piai<vitoria.piai at gmail.com>
> To:fieldtrip at donders.ru.nl
> Subject: [FieldTrip] how to use ft_stratify?
> Message-ID:<51AB0DA5.10805 at gmail.com>
> Content-Type: text/plain; charset=ISO-8859-1; format=flowed
>
> Hi all,
>
> I'm trying to use ft_stratify for the first time, but (it could be just
> me) I don't find the help info helpful enough:)
> What I want to achieve in the end is TFRs of two conditions for which
> the histogram of the reaction time over trials for each condition is
> matched.
>
> If I understood ft_stratify correctly (and I doubt that), I could use
> this function to select the trials for each condition such that the
> histograms of the RTs match. Then knowing which trials to keep, I run
> ft_freqanalysis on those specifically.
> So question number 1, is that how I should proceed? 'Cause as far as I
> can tell, ft_stratify will not take a whole raw data structure: The help
> says "each input is a Nchan X Nobs matrix". So I have to go for the RTs
> then.
>
> Assuming my approach is correct (ft_stratify on RTs of two conditions,
> then move on with only those trials), I've made a matrix Nchan x
> N_trials for each condition.
> % input1 = 265 sensors x 95 RT_trials;
> % input2 = 265 sensors x 100 RT_trials;
>
>           cfgst = [];
>           cfgst.method      = 'histogram';
>           cfgst.equalbinavg = 'no';
>           cfgst.numbin      = 4;
>           cfgst.numiter     = 2000; % default
>           [output,bin] = ft_stratify(cfgst, input1, input2);
>
> I then get an error in line 127:
> linearhisto = zeros(ncond, cfg.numbin.^nchan);
> ??? Error using ==> zeros
> Maximum variable size allowed by the program is exceeded.
>
> Apparently, zeros(2, 4^265) is something matlab doesn't want to calculate!
> Am I doing something wrong here? Has anyone worked with this function
> before (with such a number of sensors)?
>
> Any help is greatly appreciated!
> Cheers, Vit?ria
>
>
> ------------------------------
>
> Message: 3
> Date: Sun, 2 Jun 2013 11:46:03 +0200 (CEST)
> From: "Stolk, A."<a.stolk at fcdonders.ru.nl>
> To: FieldTrip discussion list<fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] how to use ft_stratify?
> Message-ID:
> 	<1910615072.1312606.1370166363974.JavaMail.root at sculptor.zimbra.ru.nl>
> Content-Type: text/plain; charset=utf-8
>
> Hi Vitoria,
>
> There is a wikipage that may help you get started, and answer your questions:
> http://fieldtrip.fcdonders.nl/example/stratify
>
> Best wishes,
> Arjen

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From d.stoffers at gmail.com  Mon Jun  3 10:12:17 2013
From: d.stoffers at gmail.com (Diederick Stoffers)
Date: Mon, 3 Jun 2013 10:12:17 +0200
Subject: [FieldTrip] Postdoc positions available at the Netherlands
	Institute for Neuroscience in Amsterdam
In-Reply-To: <21E5F1A0-241E-43B6-957B-18A7767A7B51@gmail.com>
References: <21E5F1A0-241E-43B6-957B-18A7767A7B51@gmail.com>
Message-ID: <8B956BE9-4168-4ED4-B0E9-47FE260EAEE4@gmail.com>

Dear all,

Please find attached a description of postdoc positions available at the Netherlands Institute for Neuroscience in Amsterdam, which I am posting on behalf of my group leader Eus van Someren (cc). 

Relevant keywords for these positions are sleep, emotion, arousal, high-density EEG, fMRI, TMS, insomnia, internet assessment, database, latent class and latent trait analysis. 

Cheers,

Diederick


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From d.stoffers at gmail.com  Mon Jun  3 10:20:20 2013
From: d.stoffers at gmail.com (Diederick Stoffers)
Date: Mon, 3 Jun 2013 10:20:20 +0200
Subject: [FieldTrip] Postdoc positions available at the Netherlands
	Institute for Neuroscience in Amsterdam
In-Reply-To: <8B956BE9-4168-4ED4-B0E9-47FE260EAEE4@gmail.com>
References: <21E5F1A0-241E-43B6-957B-18A7767A7B51@gmail.com>
	<8B956BE9-4168-4ED4-B0E9-47FE260EAEE4@gmail.com>
Message-ID: <6DACABEC-925B-4E71-A7A2-FB8C7B2A60D1@gmail.com>

Dear all,

Please find attached a description of postdoc positions available at the Netherlands Institute for Neuroscience in Amsterdam, which I am posting on behalf of my group leader Eus van Someren (cc). 

Relevant keywords for these positions are sleep, emotion, arousal, high-density EEG, fMRI, TMS, insomnia, internet assessment, database, latent class and latent trait analysis. 

Cheers,

Diederick

NB Apologies if you receive this message twice, the initial message was rejected by some servers because it exceeded maximum message size.


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From jm.horschig at donders.ru.nl  Mon Jun  3 10:59:49 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Mon, 03 Jun 2013 10:59:49 +0200
Subject: [FieldTrip] channel combination problems
In-Reply-To: <27E5CAD9145EEC41BB9B34C01716A1983046156B@UM-EXCDAG-A01.um.gwdg.de>
References: <27E5CAD9145EEC41BB9B34C01716A1983046156B@UM-EXCDAG-A01.um.gwdg.de>
Message-ID: <51AC5B05.2020409@donders.ru.nl>

Hi Thomas,

that is indeed a bug that we are currently working on, see also here:
http://bugzilla.fcdonders.nl/show_bug.cgi?id=2148

A workaround for the moment is to call this:

   coh.dimord = 'chancmb_freq';
   coh = ft_checkdata(coh, 'cmbrepresentation', 'full');


As you asked what the difference between the two is:
Connectivity measures are define between two signals, or channels. So, 
for example you compute coherence between channel1 and channel2. In 
FieldTrip there are two ways to represent this: Either by a 3D NxMxF 
matrix or by a 2D (NxM)xF matrix, where F denotes the frequency 
dimension and N and M are the in- or output channels (coherence is a 
symmetric measure, so N=M). In other words, we can either represent it 
as a three dimensional matrix, where the first dimension denotes the 
input and the second the output channels, or we represent it as a two 
dimensional matrix, where the first dimension denotes the relation 
between in- and output channels. The latter is what we call a 
channelcombination (chancmb). It can be channel1->channel2 (meaning, 
influence from channel1 to channel 2). The same in a three dimensional 
matrix would be channel1 for dimension 1 and channel 2 for dimension 2. 
The workaround above converts from one to the other convention. If your 
data is in 'cmbrepresentation;, you will have 'labelcmb' which is a 2D 
cell-matrix, and your data dimensions (dimord) will be 'chancmb_XXX', 
where a single dimension respective to labelcmb defines the channel 
combination. If your data is not in 'cmbrepresentation', you will have a 
1D 'label' field and your data dimension (dimord) will be 
'chan_chan_XXX', this a 2D channel combinations that explains the 
channel combination.

Btw, I am not aware that you can define cfg.labelcmb in any function, 
imho it is always cfg.channelcmb.

Best,
Jörn


On 5/31/2013 11:42 AM, Wunderle, Thomas wrote:
>
> Hi all,
>
> I'm new in fieldtrip and I try to get the cfg.channelcmb to work, 
> because I want to plot the connectivity between the channels of 
> different laminar electrodes,
>
> let's say the connectivity between channel 1:24 and 25:38
>
> I tried the following:
>
> cfg           = [];
>
> cfg.method    = 'mtmfft';
>
> cfg.taper     = 'dpss';
>
> cfg.output    = 'fourier';
>
> cfg.tapsmofrq = 1;
>
> freq          = ft_freqanalysis(cfg, data)
>
> The output is:
>
> >> freq
>
> freq =
>
>             label: {3x1 cell}
>
>            dimord: 'rpttap_chan_freq'
>
>             freq: [1x101 double]
>
>             fourierspctrm: [500x3x101 double]
>
>             cumsumcnt: [500x1 double]
>
>             cumtapcnt: [500x1 double]
>
>              cfg: [1x1 struct]
>
> I then run
>
> cfg = [];
>
> cfg.method = 'coh';
>
> cfg.channelcmb = {freq.label{1} freq.label{2};freq.label{2} 
> freq.label{1}};
>
> coh= ft_connectivityanalysis(cfg, freq);
>
> And the output here is:
>
> >> coh
>
> coh =
>
>        labelcmb: {2x2 cell}
>
>        dimord: 'chan_freq'
>
>        cohspctrm: [2x101 double]
>
>         freq: [1x101 double]
>
>         dof: 500
>
>         cfg: [1x1 struct]
>
> As you can seen, the output of dimord is 'chan_freq' so in the 
> subsequent call of ft_connectivityplot I get an error message:
>
> cfg           = [];
>
> cfg.parameter = 'cohspctrm';
>
> ft_connectivityplot(cfg, coh);
>
> ??? Error using ==> ft_connectivityplot at 99
>
> the data should have a dimord of chan_chan_freq or chancmb_freq
>
> If I use in ft_freqanalysis the cfg.method = 'powandcsd', 
> cfg.channelcmb seems to have no effect at all,
>
> the coherence is computed for all possible pairs.
>
> I also don't understand the difference between "cfg.channelcmb" and 
> "cfg.labelcmb"
>
> Can you help me in how I should correctly use the cannelcmb and 
> labelcmb options?
>
> Thanks for your help,
>
> Thomas
>
> -----
>
> Dr. Thomas Wunderle
>
> Ernst Strüngmann Institute (ESI) for Neuroscience 
> <http://www.ncbi.nlm.nih.gov/feed/rss.cgi?ChanKey=PubMedNews>
>
> in Cooperation with Max Planck Society 
> <http://www.ncbi.nlm.nih.gov/feed/rss.cgi?ChanKey=PubMedNews>
>
> Deutschordenstrasse 46
>
> 60528 Frankfurt am Main, Germany
>
> www.esi-frankfurt.de <http://www.esi-frankfurt.de/>
>
> thomas.wunderle at esi-frankfurt.de <mailto:thomas.wunderle at esi-frankfurt.de>
>
> Tel: +49 69 96769 519
>
> Fax: +49 69 96769 555
>
> Sitz der Gesellschaft: Frankfurt am Main
>
> Registergericht: Amtsgericht Frankfurt - HRB 84266
>
> Geschäftsführer: Prof. Dr. Pascal Fries
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands

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From jm.horschig at donders.ru.nl  Mon Jun  3 11:30:34 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Mon, 03 Jun 2013 11:30:34 +0200
Subject: [FieldTrip] some of the requested samples occur twice
In-Reply-To: <CALsWBNOxcuA=LCMONaGWObU4fdZ3+vskGGFcKdTZE4jGRoW47Q@mail.gmail.com>
References: <CALsWBNOxcuA=LCMONaGWObU4fdZ3+vskGGFcKdTZE4jGRoW47Q@mail.gmail.com>
Message-ID: <51AC623A.1080207@donders.ru.nl>

Hi Robin,

it's not a bug that ft_fetch_data is not allowing for overlap. The 
function needs to be generic and eventually allow for fetching data 
extending over several trial segments. However, what should be the way 
to fetch  data that occurs twice, i.e. at the end of one trial and the 
beginning of another? If you have data with overlapping samples, it is 
not straight forward to define data from one trial as to be fetched and 
ignore the other. Since preprocessing options like filters are applied 
per trial segment, data will differ between trial segments if it 
overlaps. As there are a multitude of possibilities to deal with this 
and none of them is perfect (imho neither of them can even be called 
good), we decided to not allow for that.

For your problem, however, imho you can define negative trial padding in 
the function call to ft_artifact_zvalue, which should effectively pad. 
Have you tried this rather than padding manually?

Best,
Jörn

On 5/31/2013 6:14 PM, Robin wrote:
> I have a problem in preprocessing where I am getting this error:
>
> """
> some of the requested samples occur twice in the data
>
> Error in ft_artifact_zvalue (line 262)
>        dat{trlop} = ft_fetch_data(data,        'header', hdr, 'begsample',
>        trl(trlop,1)-fltpadding, 'endsample', trl(trlop,2)+fltpadding,
>        'chanindx', sgnind, 'checkboundary', strcmp(cfg.continuous,'no
> Error in ft_artifact_muscle (line 158)
>      [tmpcfg, artifact] = ft_artifact_zvalue(tmpcfg, data);
> """
>
> I think this is because I am manually adding some extra padding to the
> trials so that the artifact filtering can use that padding (I am doing
> the artifact filtering on data in memory which is output from
> ft_denoise_pca). So in this case it is not a problem if consecutive
> trials overlap a bit.
>
> I would therefore like to disable this error and wondered what is the
> best way to do it. I am a bit confused because ft_artifact_zvalue
> calls ft_fetch data with a "checkboundary" option which looks like it
> might be what I want (and set correctly), but ft_fetch_data doesn't
> seem to use that option. Instead it has an allowoverlap option.
>
> So for now I will manually add the allowoverlap option to the call in
> ft_artifact_zvalue, but I wondered what checkboundary doesn't appear
> in ft_fetch_data or if this might be a bug.
>
> Cheers
>
> Robin
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands



From julian.keil at gmail.com  Mon Jun  3 17:14:08 2013
From: julian.keil at gmail.com (Julian Keil)
Date: Mon, 3 Jun 2013 17:14:08 +0200
Subject: [FieldTrip] Polhemus Patriot
Message-ID: <67D8C434-4D28-40C3-94A6-A95C86BD6B78@gmail.com>

Dear FieldTrip-Users,

I have a not really FieldTrip-related question, but maybe one of you can help me anyways.
In our lab, we have a Polhemus Patriot 3D tracking system to acquire electrode positions.
Unfortunately, the recordings are severely distorted in the Z-axis (up-down).
After contacting the Polhemus Support, I got the information, that this is due to metal in the surroundings of the source which distorts the magnetic field.
I tried to get as far away from any metal as possible in our lab (~1.5 m to the walls and floor) but to no avail.

Now to my question: Has anyone any experience dealing with this? I'm quite puzzled by this as I know plenty of labs use Polhemus trackers, and I'm not sure if our lab is especially metal prone or if I'm missing something.

Thanks a lot for any help.

Julian

********************
Dr. Julian Keil

AG Multisensorische Integration
Psychiatrische Universitätsklinik
der Charité im St. Hedwig-Krankenhaus
Große Hamburger Straße 5-11, Raum E 307
10115 Berlin

Telefon: +49-30-2311-1879
Fax:        +49-30-2311-2209 
http://psy-ccm.charite.de/forschung/bildgebung/ag_multisensorische_integration

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From inieuwenhuis at berkeley.edu  Mon Jun  3 17:52:14 2013
From: inieuwenhuis at berkeley.edu (Ingrid Nieuwenhuis)
Date: Mon, 03 Jun 2013 08:52:14 -0700
Subject: [FieldTrip] loreta2fieldtrip function error
In-Reply-To: <1370015815.5183.YahooMailNeo@web122402.mail.ne1.yahoo.com>
References: <1369934092.15336.YahooMailNeo@web122405.mail.ne1.yahoo.com>
	<51A78CC1.6030906@berkeley.edu>
	<1370015815.5183.YahooMailNeo@web122402.mail.ne1.yahoo.com>
Message-ID: <51ACBBAE.4070508@berkeley.edu>

Hi Fatameh,

- In the LORETA program, you go to main utilities > Format converter.
- There you select: input binary file (sLORETA)
- It does not matter which format for output you choose, I coded it 
robust, it'll figure it out. As it says, rows are time points, columns 
are the volume-gridpoints (called voxels)
- After using loreta2fieldtrip the data is in normal FieldTrip volume 
format, see here: http://fieldtrip.fcdonders.nl/reference/ft_datatype_volume

To get familiar with FieldTrip source plotting etc, see the tutorials, 
for instance: http://fieldtrip.fcdonders.nl/tutorial/plotting
- The following steps are:
1) create a template: template = ft_read_mri([cur_path_FT, 
'\external\spm8\templates\T1.nii']);
2) interpolate your volume on the MNI template: [interp_mean] = 
ft_sourceinterpolate(cfg, GA_mean, template);
3) plot it using ft_sourceplot

Hope it helps,
Ingrid

On 5/31/2013 8:56 AM, Fatemeh Ebrahimi nia wrote:
> Dear respondent,
>
> Thank you for your advices.
> I have used the function that you have updated. It works out. Can you 
> give me information about the output structure (What do the matrixes 
> refer to?) or advise a reference to study about that please?
>
> Best,
> Fatemeh
>
>
> ------------------------------------------------------------------------
> *From:* Ingrid Nieuwenhuis <inieuwenhuis at berkeley.edu>
> *To:* fieldtrip at science.ru.nl
> *Sent:* Thursday, May 30, 2013 10:30 AM
> *Subject:* Re: [FieldTrip] loreta2fieldtrip function error
>
> Hi Fatemeh,
>
> I had the same error recently when I did the same. I filed the bug, 
> see http://bugzilla.fcdonders.nl/show_bug.cgi?id=2144
>
> I did create a work around. In the LORETA program, you can export the 
> source data as a text file. You can read that text file in with 
> loreta2fieldtrip.m. It's a bit of a patch, but it worked for me.
>
> Hope this helps,
> Ingrid
>
> On 5/30/2013 10:14 AM, Fatemeh Ebrahimi nia wrote:
>> Hi dear all,
>>
>> I am analyzing EEG data. I have computed sLORETA (.slor) from ERP 
>> data. Now I want to read and convert LORETA source reconstruction into a
>> MATLAB data structure using "loreta2fieldtrip" function, But I have 
>> gotten the bellow error.
>>
>> **** Error using fread
>> Invalid precision.
>> Error in loreta2fieldtrip (line 85)
>> activity = fread(fid, [voxnumber Ntime], 'float = >single'); ***
>>
>> Can someone give me a help?
>>
>> Best regards,
>> Fatemeh
>>
>>
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl  <mailto:fieldtrip at donders.ru.nl>
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
> -- 
> Ingrid Nieuwenhuis PhD
> Postdoctoral Fellow
> Sleep and Neuroimaging Laboratory
> Department of Psychology
> University of California, Berkeley
> California 94720-1650
> Tolman Hall, room 5305
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl <mailto:fieldtrip at donders.ru.nl>
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

-- 
Ingrid Nieuwenhuis PhD
Postdoctoral Fellow
Sleep and Neuroimaging Laboratory
Department of Psychology
University of California, Berkeley
California 94720-1650
Tolman Hall, room 5305

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From smoratti at psi.ucm.es  Mon Jun  3 18:07:40 2013
From: smoratti at psi.ucm.es (smoratti at psi.ucm.es)
Date: Mon, 3 Jun 2013 18:07:40 +0200
Subject: [FieldTrip] Polhemus Patriot
In-Reply-To: <67D8C434-4D28-40C3-94A6-A95C86BD6B78@gmail.com>
References: <67D8C434-4D28-40C3-94A6-A95C86BD6B78@gmail.com>
Message-ID: <C92FAB98-3619-4953-9C1D-DFD3186EFD40@psi.ucm.es>

Dear Julian,

Maybe a stupid answer and probably you have taken care of this already, but does the chair have any metal? We use an IKEA wooden garden chair.

Best,

Stephan

________________________________________________________
Stephan Moratti, PhD

see also: http://web.me.com/smoratti/

Universidad Complutense de Madrid
Facultad de Psicología
Departamento de Psicología Básica I
Campus de Somosaguas
28223 Pozuelo de Alarcón (Madrid)
Spain

and

Center for Biomedical Technology
Laboratory for Cognitive and Computational Neuroscience
Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
Campus Montegancedo
28223 Pozuelo de Alarcón (Madrid)
Spain


email: smoratti at psi.ucm.es
Tel.:    +34 679219982

El 03/06/2013, a las 17:14, Julian Keil escribió:

> Dear FieldTrip-Users,
> 
> I have a not really FieldTrip-related question, but maybe one of you can help me anyways.
> In our lab, we have a Polhemus Patriot 3D tracking system to acquire electrode positions.
> Unfortunately, the recordings are severely distorted in the Z-axis (up-down).
> After contacting the Polhemus Support, I got the information, that this is due to metal in the surroundings of the source which distorts the magnetic field.
> I tried to get as far away from any metal as possible in our lab (~1.5 m to the walls and floor) but to no avail.
> 
> Now to my question: Has anyone any experience dealing with this? I'm quite puzzled by this as I know plenty of labs use Polhemus trackers, and I'm not sure if our lab is especially metal prone or if I'm missing something.
> 
> Thanks a lot for any help.
> 
> Julian
> 
> ********************
> Dr. Julian Keil
> 
> AG Multisensorische Integration
> Psychiatrische Universitätsklinik
> der Charité im St. Hedwig-Krankenhaus
> Große Hamburger Straße 5-11, Raum E 307
> 10115 Berlin
> 
> Telefon: +49-30-2311-1879
> Fax:        +49-30-2311-2209 
> http://psy-ccm.charite.de/forschung/bildgebung/ag_multisensorische_integration
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From sarang.dalal at uni-konstanz.de  Mon Jun  3 18:16:02 2013
From: sarang.dalal at uni-konstanz.de (Sarang S. Dalal)
Date: Mon, 3 Jun 2013 09:16:02 -0700
Subject: [FieldTrip] Polhemus Patriot
In-Reply-To: <mailman.159.1370275680.1298.fieldtrip@science.ru.nl>
References: <mailman.159.1370275680.1298.fieldtrip@science.ru.nl>
Message-ID: <27A129F9-9570-4D6B-BBF9-48080801F980@uni-konstanz.de>

Dear Julian,

At UCSF, we were unable to use a Polhemus (an older model, not sure which) in the shielded room of the MEG, so we performed the digitization just outside the room before moving the subject inside. Perhaps if you have a nicely shielded EEG booth you have the same problem...

Sarang


On Jun 3, 2013, at 9:08 AM, fieldtrip-request at science.ru.nl wrote:
> Date: Mon, 3 Jun 2013 17:14:08 +0200
> From: Julian Keil <julian.keil at gmail.com>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: [FieldTrip] Polhemus Patriot
> Message-ID: <67D8C434-4D28-40C3-94A6-A95C86BD6B78 at gmail.com>
> Content-Type: text/plain; charset="iso-8859-1"
> 
> Dear FieldTrip-Users,
> 
> I have a not really FieldTrip-related question, but maybe one of you can help me anyways.
> In our lab, we have a Polhemus Patriot 3D tracking system to acquire electrode positions.
> Unfortunately, the recordings are severely distorted in the Z-axis (up-down).
> After contacting the Polhemus Support, I got the information, that this is due to metal in the surroundings of the source which distorts the magnetic field.
> I tried to get as far away from any metal as possible in our lab (~1.5 m to the walls and floor) but to no avail.
> 
> Now to my question: Has anyone any experience dealing with this? I'm quite puzzled by this as I know plenty of labs use Polhemus trackers, and I'm not sure if our lab is especially metal prone or if I'm missing something.
> 
> Thanks a lot for any help.
> 
> Julian
> 
> ********************
> Dr. Julian Keil
> 
> AG Multisensorische Integration
> Psychiatrische Universit?tsklinik
> der Charit? im St. Hedwig-Krankenhaus
> Gro?e Hamburger Stra?e 5-11, Raum E 307
> 10115 Berlin
> 
> Telefon: +49-30-2311-1879
> Fax:        +49-30-2311-2209 
> http://psy-ccm.charite.de/forschung/bildgebung/ag_multisensorische_integration




From inieuwenhuis at berkeley.edu  Mon Jun  3 18:25:47 2013
From: inieuwenhuis at berkeley.edu (Ingrid Nieuwenhuis)
Date: Mon, 03 Jun 2013 09:25:47 -0700
Subject: [FieldTrip] format conversion
In-Reply-To: <1369986505.7865.YahooMailNeo@web192306.mail.sg3.yahoo.com>
References: <1369986505.7865.YahooMailNeo@web192306.mail.sg3.yahoo.com>
Message-ID: <51ACC38B.9080802@berkeley.edu>

Hi Bahar,

I've added more info on the FieldTrip wiki about this for you and other. 
See here:
http://fieldtrip.fcdonders.nl/integrating_with_loreta

Hope it helps,
Ingrid


On 5/31/2013 12:48 AM, Bahar Bahar wrote:
> Hi dear all,
>
> I have a technical question about format converter module via sLORETA 
> software (.slor file to .txt one). Can any one give me some 
> information about the conversion procedure (and the meaning of the 
> column and row of the output file)?
>
> Thanks,
> bahar
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

-- 
Ingrid Nieuwenhuis PhD
Postdoctoral Fellow
Sleep and Neuroimaging Laboratory
Department of Psychology
University of California, Berkeley
California 94720-1650
Tolman Hall, room 5305

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From andmib at gmail.com  Mon Jun  3 22:15:49 2013
From: andmib at gmail.com (Andrew Brooks)
Date: Mon, 3 Jun 2013 16:15:49 -0400
Subject: [FieldTrip] Private function problems
Message-ID: <CALJPz69S8R+n+vWMYsmqC_Rqo63FbfECL+UStC0HcjQA3m8w2w@mail.gmail.com>

Hello all,

I followed the instructions on properly adding FieldTrip to the Matlab path
file. However, I continue to run into errors involving private functions.
In this case, I get the error 'undefined function 'hom2six' for input
arguments of type 'double''.

Does anybody have a suggestion as to why this is occurring?

Thanks!
Andrew
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From d.lozanosoldevilla at fcdonders.ru.nl  Mon Jun  3 22:53:41 2013
From: d.lozanosoldevilla at fcdonders.ru.nl (Lozano Soldevilla, D. (Diego))
Date: Mon, 3 Jun 2013 22:53:41 +0200 (CEST)
Subject: [FieldTrip] Private function problems
In-Reply-To: <CALJPz69S8R+n+vWMYsmqC_Rqo63FbfECL+UStC0HcjQA3m8w2w@mail.gmail.com>
Message-ID: <481032685.1338448.1370292821035.JavaMail.root@sculptor.zimbra.ru.nl>

Hi Andrew, Did you type the following? >> restoredefaultpath >> addpath /fieldtripxxxx >> ft_defaults What's the ft_* function you invoke to get the error 'undefined function 'hom2six'? And what's the fieldtrip version you're using? best, Diego ----- Original Message -----
> From: "Andrew Brooks" <andmib at gmail.com>
> To: "FieldTrip discussion list" <fieldtrip at science.ru.nl>
> Sent: Monday, 3 June, 2013 10:15:49 PM
> Subject: [FieldTrip] Private function problems
> Hello all,
> I followed the instructions on properly adding FieldTrip to the Matlab
> path file. However, I continue to run into errors involving private
> functions. In this case, I get the error 'undefined function 'hom2six'
> for input arguments of type 'double''.
> Does anybody have a suggestion as to why this is occurring?
> Thanks!
> Andrew
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
-- PhD Student Neuronal Oscillations Group Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Trigon, room 0.83 Kapittelweg 29 Radboud University Nijmegen NL-6525 EN Nijmegen The Netherlands E-Mail: d.lozanosoldevilla at fcdonders.ru.nl Tel: +31-(0)24-36-66274 Web: http://www.neuosc.com/ 
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From 13681530640 at 139.com  Tue Jun  4 04:16:18 2013
From: 13681530640 at 139.com (WangJing)
Date: Tue, 4 Jun 2013 10:16:18 +0800 (CST)
Subject: [FieldTrip] Question about Head Model
References: <mailman.159.1370275680.1298.fieldtrip@science.ru.nl>
Message-ID: <2af951ad49e020a-0000c.Richmail.00026806626265132618@139.com>


HI everyone,


 


    When I build head model,I encount some questions.


    1.for two Functions ft_volumereslice and ft_volumerealign,which should be run firstly?


    2. when surfaces are created at the boarders of the different tissue-types by the ft_prepare_mesh function. how to determine the parameter cfg.numvertices?


    3.when I build the head model,using the following codes:


     cfg        = [];
     cfg.method ='dipoli';
     cfg.cond =[0.3300 0.004125 0.3300];
     vol        = ft_prepare_headmodel(cfg, bnd);


     


the error message is:


 


??? Error using ==> surface_nesting at 26
the compartment nesting cannot be determined


Error in ==> ft_headmodel_dipoli at 84
order = surface_nesting(vol.bnd, 'outsidefirst');


Error in ==> ft_prepare_headmodel at 226
      vol = ft_headmodel_dipoli(geometry,'conductivity',cfg.conductivity,'isolatedsource',cfg.isolatedsource);


Error in ==> Myheadmodel at 5
vol        = ft_prepare_headmodel(cfg, bnd);


 


   I don't know where is wrong.who can help me? Thank you!


 


Best Regards,


Jing Wang


 


 






 
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From sauer.mpih at googlemail.com  Tue Jun  4 11:42:13 2013
From: sauer.mpih at googlemail.com (Andreas Sauer)
Date: Tue, 4 Jun 2013 11:42:13 +0200
Subject: [FieldTrip] NaNs as output of ft_sourceanalysis (DICS)
Message-ID: <CAHLSopU-XWo6-t=MW78POK-6CvN1hRoFcc74aRxEuXZXhiSjUQ@mail.gmail.com>

Dear all,

I would like to analyze sources with the beamforming approach using the
DICS method. I followed the steps in the tutorial and everything works
well. However, the output of ft_sourceanalysis contains only NaNs.

I checked the TF data that I calculated in the step before but that looks
fine, so I assume the error happens somewhere during ft_sourceanalysis.

That's how I calculate the TFRs:

        cfg = [];
        cfg.toilim = [-0.5 -0.3]; % baseline activity
        eval(['dataPre =
ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
        cfg.toilim = [0.1 1.0]; % task-related activity
        eval(['dataPost =
ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);

        % Combine the two datasets...
        data = appenddata(cfg, dataPre, dataPost);
        trialdesign = [ones(1,length(dataPost.trial))
ones(1,length(dataPre.trial))*2];

        % ... and compute the CSD matrices...
        cfg = [];
        cfg.output     = 'powandcsd';
        cfg.channel    = Channel.meg;
        cfg.method     = 'mtmfft';
        cfg.taper      = 'dpss';
        cfg.foilim     = [75 75];
        cfg.tapsmofrq  = 15; % amount of spectral smoothing = +/- 15 Hz
        cfg.channelcmb = {Channel.meg Channel.meg};

        % ... for the baseline and task part separately...
        eval(['freqPre.Cond_',num2str(cond(j)), ' =
ft_freqanalysis(cfg,dataPre);']);
        eval(['freqPost.Cond_',num2str(cond(j)), ' =
ft_freqanalysis(cfg,dataPost);']);

        % ... and for the whole trial
        eval(['freqAll.Cond_',num2str(cond(j)), ' =
ft_freqanalysis(cfg,data);']);
        eval(['freqAll.Cond_',num2str(cond(j)), '.trialdesign =
trialdesign;']); % pre and post info

And that's how I calculate the sources:

        cfg               = [];
        cfg.frequency     = 75;
        cfg.method        = 'dics';
        cfg.grid          = grid; % Here it gives .pos, .inside, .outside
to the structure
        cfg.vol           = vol;
        cfg.dim           = template_grid.dim; % Here I give the dimension
of the template grid
        cfg.grad          = Cond_101.hdr.grad;
        cfg.lambda        = '5%';
        cfg.reducerank    = 'no';
        cfg.projectnoise  = 'yes';
        cfg.realfilter    = 'yes';
        cfg.keepfilter    = 'yes'; % the output saves the computed inverse
filter

        eval(['SourceAll = ft_sourceanalysis(cfg,
freqAll.Cond_',num2str(cond(k)),');'])

        % use the common filter here
        cfg.grid.filter = SourceAll.avg.filter;
        eval(['sourcePre_con = ft_sourceanalysis(cfg,
freqPre.Cond_',num2str(cond(k)),');'])
        eval(['sourcePost_con = ft_sourceanalysis(cfg,
freqPost.Cond_',num2str(cond(k)),');'])



I would really appreciate any help with that! Thanks a lot!

Best,

Andreas

-- 
Andreas Sauer
Max Planck Institute for Brain Research
Deutschordenstr. 46
60528 Frankfurt am Main
Germany

T: +49 69 96769 278
F: +49 69 96769 327
Email: andreas.sauer at brain.mpg.de
www.brain.mpg.de
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From sauer.mpih at googlemail.com  Tue Jun  4 11:52:24 2013
From: sauer.mpih at googlemail.com (Andreas Sauer)
Date: Tue, 4 Jun 2013 11:52:24 +0200
Subject: [FieldTrip] NaNs as outpout of ft_sourceanalysis (DICS)
Message-ID: <CAHLSopUvv47POq0cHQD8iZfYnOvp+oz6VyCLcW4CsNhjJAvBVw@mail.gmail.com>

Dear all,

I would like to analyze sources with the beamforming approach using the
DICS method. I followed the steps in the tutorial and everything works
well. However, the output of ft_sourceanalysis contains only NaNs.

I checked the TF data that I calculated in the step before but that looks
fine, so I assume the error happens somewhere during ft_sourceanalysis.

That's how I calculate the TFRs:

        cfg = [];
        cfg.toilim = [-0.5 -0.3]; % baseline activity
        eval(['dataPre =
ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
        cfg.toilim = [0.1 1.0]; % task-related activity
        eval(['dataPost =
ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);

        % Combine the two datasets...
        data = appenddata(cfg, dataPre, dataPost);
        trialdesign = [ones(1,length(dataPost.trial))
ones(1,length(dataPre.trial))*2];

        % ... and compute the CSD matrices...
        cfg = [];
        cfg.output     = 'powandcsd';
        cfg.channel    = Channel.meg;
        cfg.method     = 'mtmfft';
        cfg.taper      = 'dpss';
        cfg.foilim     = [75 75];
        cfg.tapsmofrq  = 15; % amount of spectral smoothing = +/- 15 Hz
        cfg.channelcmb = {Channel.meg Channel.meg};

        % ... for the baseline and task part separately...
        eval(['freqPre.Cond_',num2str(cond(j)), ' =
ft_freqanalysis(cfg,dataPre);']);
        eval(['freqPost.Cond_',num2str(cond(j)), ' =
ft_freqanalysis(cfg,dataPost);']);

        % ... and for the whole trial
        eval(['freqAll.Cond_',num2str(cond(j)), ' =
ft_freqanalysis(cfg,data);']);
        eval(['freqAll.Cond_',num2str(cond(j)), '.trialdesign =
trialdesign;']); % pre and post info

And that's how I calculate the sources:

        cfg               = [];
        cfg.frequency     = 75;
        cfg.method        = 'dics';
        cfg.grid          = grid; % Here it gives .pos, .inside, .outside
to the structure
        cfg.vol           = vol;
        cfg.dim           = template_grid.dim; % Here I give the dimension
of the template grid
        cfg.grad          = Cond_101.hdr.grad;
        cfg.lambda        = '5%';
        cfg.reducerank    = 'no';
        cfg.projectnoise  = 'yes';
        cfg.realfilter    = 'yes';
        cfg.keepfilter    = 'yes'; % the output saves the computed inverse
filter

        eval(['SourceAll = ft_sourceanalysis(cfg,
freqAll.Cond_',num2str(cond(k)),');'])

        % use the common filter here
        cfg.grid.filter = SourceAll.avg.filter;
        eval(['sourcePre_con = ft_sourceanalysis(cfg,
freqPre.Cond_',num2str(cond(k)),');'])
        eval(['sourcePost_con = ft_sourceanalysis(cfg,
freqPost.Cond_',num2str(cond(k)),');'])



I would really appreciate any help with that! Thanks a lot!

Best,

Andreas


-- 
Andreas Sauer
Max Planck Institute for Brain Research
Deutschordenstr. 46
60528 Frankfurt am Main
Germany

T: +49 69 96769 278
F: +49 69 96769 327
Email: andreas.sauer at brain.mpg.de <sauer.mpih at gmail.com>
www.brain.mpg.de
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From eelke.spaak at donders.ru.nl  Tue Jun  4 11:54:51 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Tue, 4 Jun 2013 11:54:51 +0200
Subject: [FieldTrip] NaNs as output of ft_sourceanalysis (DICS)
In-Reply-To: <CAHLSopU-XWo6-t=MW78POK-6CvN1hRoFcc74aRxEuXZXhiSjUQ@mail.gmail.com>
References: <CAHLSopU-XWo6-t=MW78POK-6CvN1hRoFcc74aRxEuXZXhiSjUQ@mail.gmail.com>
Message-ID: <CABPNLUoRezPPHDCNMJqvw3T3-dOqnC32VP_ihdmDqqpXQF0aNQ@mail.gmail.com>

Dear Andreas,

How many NaNs do you get exactly and in which field? If it is some
NaNs in source.avg.pow, then it is quite normal: the estimates for
dipole locations which were flagged as outside the brain are always
NaN, as they are not scanned. The following should hold:

sum(isnan(source.avg.pow)) == numel(source.outside)
&&
sum(~isnan(source.avg.pow)) == numel(source.inside)

Best,
Eelke

On 4 June 2013 11:42, Andreas Sauer <sauer.mpih at googlemail.com> wrote:
> Dear all,
>
> I would like to analyze sources with the beamforming approach using the DICS
> method. I followed the steps in the tutorial and everything works well.
> However, the output of ft_sourceanalysis contains only NaNs.
>
> I checked the TF data that I calculated in the step before but that looks
> fine, so I assume the error happens somewhere during ft_sourceanalysis.
>
> That's how I calculate the TFRs:
>
>         cfg = [];
>         cfg.toilim = [-0.5 -0.3]; % baseline activity
>         eval(['dataPre =
> ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
>         cfg.toilim = [0.1 1.0]; % task-related activity
>         eval(['dataPost =
> ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
>
>         % Combine the two datasets...
>         data = appenddata(cfg, dataPre, dataPost);
>         trialdesign = [ones(1,length(dataPost.trial))
> ones(1,length(dataPre.trial))*2];
>
>         % ... and compute the CSD matrices...
>         cfg = [];
>         cfg.output     = 'powandcsd';
>         cfg.channel    = Channel.meg;
>         cfg.method     = 'mtmfft';
>         cfg.taper      = 'dpss';
>         cfg.foilim     = [75 75];
>         cfg.tapsmofrq  = 15; % amount of spectral smoothing = +/- 15 Hz
>         cfg.channelcmb = {Channel.meg Channel.meg};
>
>         % ... for the baseline and task part separately...
>         eval(['freqPre.Cond_',num2str(cond(j)), ' =
> ft_freqanalysis(cfg,dataPre);']);
>         eval(['freqPost.Cond_',num2str(cond(j)), ' =
> ft_freqanalysis(cfg,dataPost);']);
>
>         % ... and for the whole trial
>         eval(['freqAll.Cond_',num2str(cond(j)), ' =
> ft_freqanalysis(cfg,data);']);
>         eval(['freqAll.Cond_',num2str(cond(j)), '.trialdesign =
> trialdesign;']); % pre and post info
>
> And that's how I calculate the sources:
>
>         cfg               = [];
>         cfg.frequency     = 75;
>         cfg.method        = 'dics';
>         cfg.grid          = grid; % Here it gives .pos, .inside, .outside to
> the structure
>         cfg.vol           = vol;
>         cfg.dim           = template_grid.dim; % Here I give the dimension
> of the template grid
>         cfg.grad          = Cond_101.hdr.grad;
>         cfg.lambda        = '5%';
>         cfg.reducerank    = 'no';
>         cfg.projectnoise  = 'yes';
>         cfg.realfilter    = 'yes';
>         cfg.keepfilter    = 'yes'; % the output saves the computed inverse
> filter
>
>         eval(['SourceAll = ft_sourceanalysis(cfg,
> freqAll.Cond_',num2str(cond(k)),');'])
>
>         % use the common filter here
>         cfg.grid.filter = SourceAll.avg.filter;
>         eval(['sourcePre_con = ft_sourceanalysis(cfg,
> freqPre.Cond_',num2str(cond(k)),');'])
>         eval(['sourcePost_con = ft_sourceanalysis(cfg,
> freqPost.Cond_',num2str(cond(k)),');'])
>
>
>
> I would really appreciate any help with that! Thanks a lot!
>
> Best,
>
> Andreas
>
> --
> Andreas Sauer
> Max Planck Institute for Brain Research
> Deutschordenstr. 46
> 60528 Frankfurt am Main
> Germany
>
> T: +49 69 96769 278
> F: +49 69 96769 327
> Email: andreas.sauer at brain.mpg.de
> www.brain.mpg.de
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From jm.horschig at donders.ru.nl  Tue Jun  4 12:17:37 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Tue, 04 Jun 2013 12:17:37 +0200
Subject: [FieldTrip] NaNs as output of ft_sourceanalysis (DICS)
In-Reply-To: <CABPNLUoRezPPHDCNMJqvw3T3-dOqnC32VP_ihdmDqqpXQF0aNQ@mail.gmail.com>
References: <CAHLSopU-XWo6-t=MW78POK-6CvN1hRoFcc74aRxEuXZXhiSjUQ@mail.gmail.com>
	<CABPNLUoRezPPHDCNMJqvw3T3-dOqnC32VP_ihdmDqqpXQF0aNQ@mail.gmail.com>
Message-ID: <51ADBEC1.5060204@donders.ru.nl>

Hi Andreas,

could it be related to the fact that you redefine your trials and when 
estimating the frequency content, there is no exact 75Hz bin, thus 
ft_sourceanalysis cannot beam the frequency you specify? Since you cut 
out the pre- and poststimulus periods with different lengths, the 
frequency resolution will be strongly different, thus an estimate of 
75Hz will effectively be somewhere around 75Hz, but not exactly 75Hz. 
You could try to set 
cfg.frequency=freqAll.Cond_(yourNumberedCondition).freq instead of 
cfg.frequency=75. Note that in this case, sourceAll might have non-nans, 
but sourcePre and sourcePost will probably still have nans due to the 
resolution issue
If that's not the case, then I agree also with Eelke that more 
information is needed to help you, e.g. in which of the three source 
structures are nans? How many nans are there (try 
all(isnan(source.avg.pow(:))))?

Best,
Jörn

On 6/4/2013 11:54 AM, Eelke Spaak wrote:
> Dear Andreas,
>
> How many NaNs do you get exactly and in which field? If it is some
> NaNs in source.avg.pow, then it is quite normal: the estimates for
> dipole locations which were flagged as outside the brain are always
> NaN, as they are not scanned. The following should hold:
>
> sum(isnan(source.avg.pow)) == numel(source.outside)
> &&
> sum(~isnan(source.avg.pow)) == numel(source.inside)
>
> Best,
> Eelke
>
> On 4 June 2013 11:42, Andreas Sauer <sauer.mpih at googlemail.com> wrote:
>> Dear all,
>>
>> I would like to analyze sources with the beamforming approach using the DICS
>> method. I followed the steps in the tutorial and everything works well.
>> However, the output of ft_sourceanalysis contains only NaNs.
>>
>> I checked the TF data that I calculated in the step before but that looks
>> fine, so I assume the error happens somewhere during ft_sourceanalysis.
>>
>> That's how I calculate the TFRs:
>>
>>          cfg = [];
>>          cfg.toilim = [-0.5 -0.3]; % baseline activity
>>          eval(['dataPre =
>> ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
>>          cfg.toilim = [0.1 1.0]; % task-related activity
>>          eval(['dataPost =
>> ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
>>
>>          % Combine the two datasets...
>>          data = appenddata(cfg, dataPre, dataPost);
>>          trialdesign = [ones(1,length(dataPost.trial))
>> ones(1,length(dataPre.trial))*2];
>>
>>          % ... and compute the CSD matrices...
>>          cfg = [];
>>          cfg.output     = 'powandcsd';
>>          cfg.channel    = Channel.meg;
>>          cfg.method     = 'mtmfft';
>>          cfg.taper      = 'dpss';
>>          cfg.foilim     = [75 75];
>>          cfg.tapsmofrq  = 15; % amount of spectral smoothing = +/- 15 Hz
>>          cfg.channelcmb = {Channel.meg Channel.meg};
>>
>>          % ... for the baseline and task part separately...
>>          eval(['freqPre.Cond_',num2str(cond(j)), ' =
>> ft_freqanalysis(cfg,dataPre);']);
>>          eval(['freqPost.Cond_',num2str(cond(j)), ' =
>> ft_freqanalysis(cfg,dataPost);']);
>>
>>          % ... and for the whole trial
>>          eval(['freqAll.Cond_',num2str(cond(j)), ' =
>> ft_freqanalysis(cfg,data);']);
>>          eval(['freqAll.Cond_',num2str(cond(j)), '.trialdesign =
>> trialdesign;']); % pre and post info
>>
>> And that's how I calculate the sources:
>>
>>          cfg               = [];
>>          cfg.frequency     = 75;
>>          cfg.method        = 'dics';
>>          cfg.grid          = grid; % Here it gives .pos, .inside, .outside to
>> the structure
>>          cfg.vol           = vol;
>>          cfg.dim           = template_grid.dim; % Here I give the dimension
>> of the template grid
>>          cfg.grad          = Cond_101.hdr.grad;
>>          cfg.lambda        = '5%';
>>          cfg.reducerank    = 'no';
>>          cfg.projectnoise  = 'yes';
>>          cfg.realfilter    = 'yes';
>>          cfg.keepfilter    = 'yes'; % the output saves the computed inverse
>> filter
>>
>>          eval(['SourceAll = ft_sourceanalysis(cfg,
>> freqAll.Cond_',num2str(cond(k)),');'])
>>
>>          % use the common filter here
>>          cfg.grid.filter = SourceAll.avg.filter;
>>          eval(['sourcePre_con = ft_sourceanalysis(cfg,
>> freqPre.Cond_',num2str(cond(k)),');'])
>>          eval(['sourcePost_con = ft_sourceanalysis(cfg,
>> freqPost.Cond_',num2str(cond(k)),');'])
>>
>>
>>
>> I would really appreciate any help with that! Thanks a lot!
>>
>> Best,
>>
>> Andreas
>>
>> --
>> Andreas Sauer
>> Max Planck Institute for Brain Research
>> Deutschordenstr. 46
>> 60528 Frankfurt am Main
>> Germany
>>
>> T: +49 69 96769 278
>> F: +49 69 96769 327
>> Email: andreas.sauer at brain.mpg.de
>> www.brain.mpg.de
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands



From sauer.mpih at googlemail.com  Tue Jun  4 12:31:32 2013
From: sauer.mpih at googlemail.com (Andreas Sauer)
Date: Tue, 4 Jun 2013 12:31:32 +0200
Subject: [FieldTrip] NaNs as output of ft_sourceanalysis (DICS)
In-Reply-To: <CABPNLUoRezPPHDCNMJqvw3T3-dOqnC32VP_ihdmDqqpXQF0aNQ@mail.gmail.com>
References: <CAHLSopU-XWo6-t=MW78POK-6CvN1hRoFcc74aRxEuXZXhiSjUQ@mail.gmail.com>
	<CABPNLUoRezPPHDCNMJqvw3T3-dOqnC32VP_ihdmDqqpXQF0aNQ@mail.gmail.com>
Message-ID: <CAHLSopUkz1XxH+2VoLH9FYOE_97ouFDCxV8Qvy8fO2oP-vU6iw@mail.gmail.com>

Dear Eelke and Jörn,

thanks for the super quick responses! And sorry for the double post...

I tried Eelke's suggestion and that holds. So, I have only NaNs in the
fields for the dipole locations outside the brain.
However, if I continue and calculate the contrast between pre and post and
plot it I don't see any activation.

I will try your suggestion, Jörn, as well and see whether it has to do with
the re-definition.

Thanks again for your suggestions!

Best,

Andreas


2013/6/4 Eelke Spaak <eelke.spaak at donders.ru.nl>

> Dear Andreas,
>
> How many NaNs do you get exactly and in which field? If it is some
> NaNs in source.avg.pow, then it is quite normal: the estimates for
> dipole locations which were flagged as outside the brain are always
> NaN, as they are not scanned. The following should hold:
>
> sum(isnan(source.avg.pow)) == numel(source.outside)
> &&
> sum(~isnan(source.avg.pow)) == numel(source.inside)
>
> Best,
> Eelke
>
> On 4 June 2013 11:42, Andreas Sauer <sauer.mpih at googlemail.com> wrote:
> > Dear all,
> >
> > I would like to analyze sources with the beamforming approach using the
> DICS
> > method. I followed the steps in the tutorial and everything works well.
> > However, the output of ft_sourceanalysis contains only NaNs.
> >
> > I checked the TF data that I calculated in the step before but that looks
> > fine, so I assume the error happens somewhere during ft_sourceanalysis.
> >
> > That's how I calculate the TFRs:
> >
> >         cfg = [];
> >         cfg.toilim = [-0.5 -0.3]; % baseline activity
> >         eval(['dataPre =
> > ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
> >         cfg.toilim = [0.1 1.0]; % task-related activity
> >         eval(['dataPost =
> > ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
> >
> >         % Combine the two datasets...
> >         data = appenddata(cfg, dataPre, dataPost);
> >         trialdesign = [ones(1,length(dataPost.trial))
> > ones(1,length(dataPre.trial))*2];
> >
> >         % ... and compute the CSD matrices...
> >         cfg = [];
> >         cfg.output     = 'powandcsd';
> >         cfg.channel    = Channel.meg;
> >         cfg.method     = 'mtmfft';
> >         cfg.taper      = 'dpss';
> >         cfg.foilim     = [75 75];
> >         cfg.tapsmofrq  = 15; % amount of spectral smoothing = +/- 15 Hz
> >         cfg.channelcmb = {Channel.meg Channel.meg};
> >
> >         % ... for the baseline and task part separately...
> >         eval(['freqPre.Cond_',num2str(cond(j)), ' =
> > ft_freqanalysis(cfg,dataPre);']);
> >         eval(['freqPost.Cond_',num2str(cond(j)), ' =
> > ft_freqanalysis(cfg,dataPost);']);
> >
> >         % ... and for the whole trial
> >         eval(['freqAll.Cond_',num2str(cond(j)), ' =
> > ft_freqanalysis(cfg,data);']);
> >         eval(['freqAll.Cond_',num2str(cond(j)), '.trialdesign =
> > trialdesign;']); % pre and post info
> >
> > And that's how I calculate the sources:
> >
> >         cfg               = [];
> >         cfg.frequency     = 75;
> >         cfg.method        = 'dics';
> >         cfg.grid          = grid; % Here it gives .pos, .inside,
> .outside to
> > the structure
> >         cfg.vol           = vol;
> >         cfg.dim           = template_grid.dim; % Here I give the
> dimension
> > of the template grid
> >         cfg.grad          = Cond_101.hdr.grad;
> >         cfg.lambda        = '5%';
> >         cfg.reducerank    = 'no';
> >         cfg.projectnoise  = 'yes';
> >         cfg.realfilter    = 'yes';
> >         cfg.keepfilter    = 'yes'; % the output saves the computed
> inverse
> > filter
> >
> >         eval(['SourceAll = ft_sourceanalysis(cfg,
> > freqAll.Cond_',num2str(cond(k)),');'])
> >
> >         % use the common filter here
> >         cfg.grid.filter = SourceAll.avg.filter;
> >         eval(['sourcePre_con = ft_sourceanalysis(cfg,
> > freqPre.Cond_',num2str(cond(k)),');'])
> >         eval(['sourcePost_con = ft_sourceanalysis(cfg,
> > freqPost.Cond_',num2str(cond(k)),');'])
> >
> >
> >
> > I would really appreciate any help with that! Thanks a lot!
> >
> > Best,
> >
> > Andreas
> >
> > --
> > Andreas Sauer
> > Max Planck Institute for Brain Research
> > Deutschordenstr. 46
> > 60528 Frankfurt am Main
> > Germany
> >
> > T: +49 69 96769 278
> > F: +49 69 96769 327
> > Email: andreas.sauer at brain.mpg.de
> > www.brain.mpg.de
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
Dipl.-Psych. Andreas Sauer
Max Planck Institute for Brain Research
Deutschordenstraße 46
60528 Frankfurt am Main
Germany

T: +49 69 96769 278
F: +49 69 96769 327
Email: sauer.mpih at gmail.com
www.brain.mpg.de
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From r.cox at uva.nl  Tue Jun  4 14:31:06 2013
From: r.cox at uva.nl (Roy Cox)
Date: Tue, 4 Jun 2013 14:31:06 +0200
Subject: [FieldTrip] ft_freqstatistics & ft_clusterplot
Message-ID: <CABafTZd5GXvBG=Xa=252EGwEsQysX1zaCnn+iuRH575F6byo7Q@mail.gmail.com>

Dear all,

I recently joined your trip and I want to make use of fieldtrip's cluster
correction capabilities. But I can't seem to get it to work. Perhaps some
of you can clarify some things I can't figure out easily from the tutorials
or functions themselves.

A potentially important thing to know is that I performed all
single-subject tf analyes using custom scripts, and now I want to have
fieldtrip perform the overall statistics (8 subjects, 2 within-subj
conditions).

ft_freqstatistics works. However, I wonder: does it matter for the
statistics what latency and frequency range you choose and/or whether you
average across time/freq bins? I tried a number of variants, but the
command window output "found [] positive/negative clusters in observed
data" is always identical. Which confuses me.

is it possible to call ft_freqstatistics and neither average over time nor
frequency bins? or am I supposed to average across at least one to end up
with less-dimensional data for ft_clusterplot?

regardless of how I call ft_freqstatistics, ft_clusterplot crashes like
this:

 Assignment has more non-singleton rhs dimensions than non-singleton
subscripts

Error in ==> ft_clusterplot at 179
    sigposCLM(:,:,iPos) = (posCLM == sigpos(iPos));

here, my posCLM is a 126(chan)x35(freqs)x301(time) array, which indeed does
not fit the left-hand side.

If anyone has any ideas/suggestions I'd be happy to hear them.

Roy

-- 
Roy Cox, M.Sc. | Brain & Cognition Group | Department of Psychology |
University of Amsterdam | Weesperplein 4 | 1018 XA Amsterdam | the
Netherlands | room 3.21 | phone: +31 20 525 6847 | email: r.cox at uva.nl
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From andmib at gmail.com  Tue Jun  4 17:01:43 2013
From: andmib at gmail.com (Andrew Brooks)
Date: Tue, 4 Jun 2013 11:01:43 -0400
Subject: [FieldTrip] Private function problems
In-Reply-To: <481032685.1338448.1370292821035.JavaMail.root@sculptor.zimbra.ru.nl>
References: <CALJPz69S8R+n+vWMYsmqC_Rqo63FbfECL+UStC0HcjQA3m8w2w@mail.gmail.com>
	<481032685.1338448.1370292821035.JavaMail.root@sculptor.zimbra.ru.nl>
Message-ID: <CALJPz69LZ_35=Z6YR5E6yRymDcZ3bBjaOpXOMyz3+CTWDjDNcw@mail.gmail.com>

Hello Diego,

I am using the example pipeline script from an earlier version of FieldTrip
(ft_omri_pipeline_nuisance). The exact code that is throwing the
error: curSixDof = hom2six(M).

I did run the three lines of code to reset the default paths, add
fieldtrip, and then ran ft_defaults. The version of FieldTrip I am using is
20130602.

Thanks,
Andrew






On Mon, Jun 3, 2013 at 4:53 PM, Lozano Soldevilla, D. (Diego) <
d.lozanosoldevilla at fcdonders.ru.nl> wrote:

> Hi Andrew,
>
> Did you type the following?
>
> >> restoredefaultpath
> >> addpath /fieldtripxxxx
> >> ft_defaults
>
> What's the ft_* function you invoke to get the error 'undefined function
> 'hom2six'? And what's the fieldtrip version you're using?
>
> best,
>
> Diego
>
> ------------------------------
>
> *From: *"Andrew Brooks" <andmib at gmail.com>
> *To: *"FieldTrip discussion list" <fieldtrip at science.ru.nl>
> *Sent: *Monday, 3 June, 2013 10:15:49 PM
> *Subject: *[FieldTrip] Private function problems
>
>
> Hello all,
>
> I followed the instructions on properly adding FieldTrip to the Matlab
> path file. However, I continue to run into errors involving private
> functions. In this case, I get the error 'undefined function 'hom2six' for
> input arguments of type 'double''.
>
> Does anybody have a suggestion as to why this is occurring?
>
> Thanks!
> Andrew
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
>
> --
> PhD Student
> Neuronal Oscillations Group
> Donders Institute for Brain, Cognition and Behaviour
> Centre for Cognitive Neuroimaging
> Trigon, room 0.83
> Kapittelweg 29
> Radboud University Nijmegen
> NL-6525 EN Nijmegen
> The Netherlands
> E-Mail: d.lozanosoldevilla at fcdonders.ru.nl
> Tel:     +31-(0)24-36-66274
> Web:   http://www.neuosc.com/
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From frank.ye.mei at gmail.com  Tue Jun  4 22:47:08 2013
From: frank.ye.mei at gmail.com (Frank Mei)
Date: Tue, 4 Jun 2013 16:47:08 -0400
Subject: [FieldTrip] How to set a small window when doing source
	localization?
Message-ID: <CAF0J_Mu4csTxGVM=3UQajwDQFbM3igEyjLUUMwvW9GBVcZpW7w@mail.gmail.com>

Hello all,

I want to be more precise in time, when doing source localization. So I
tried to set a small cfg.toilim, before the 'ft_redefinetrial'.   But if it
is set smaller than 0.3(corresponding to 300ms), an error will pop up.

How to solve that problem?

thanks ahead,
Ye Mei
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From d.lozanosoldevilla at fcdonders.ru.nl  Wed Jun  5 15:39:14 2013
From: d.lozanosoldevilla at fcdonders.ru.nl (Lozano Soldevilla, D. (Diego))
Date: Wed, 5 Jun 2013 15:39:14 +0200 (CEST)
Subject: [FieldTrip] Private function problems
In-Reply-To: <CALJPz69LZ_35=Z6YR5E6yRymDcZ3bBjaOpXOMyz3+CTWDjDNcw@mail.gmail.com>
Message-ID: <2127428772.1387542.1370439554352.JavaMail.root@sculptor.zimbra.ru.nl>

Hi Andrew, Could you please check inside your matlab path there's the realtime/mri directory where ft_omri_pipeline_nuisance.m function is located? Mine looks like this: '/home/electromag/dieloz/matlab/ fieldtrip-dev/realtime/online_mri/ ' If it's there, you shouldn't have the private folder problem. Otherwise, add from the command window and tell me. best, Diego ----- Original Message -----
> From: "Andrew Brooks" <andmib at gmail.com>
> To: "Diego Lozano" <diego.lozanosoldevilla at fcdonders.ru.nl>,
> "FieldTrip discussion list" <fieldtrip at science.ru.nl>
> Sent: Tuesday, 4 June, 2013 5:01:43 PM
> Subject: Re: [FieldTrip] Private function problems
> Hello Diego,
> I am using the example pipeline script from an earlier version of
> FieldTrip (ft_omri_pipeline_nuisance). The exact code that is throwing
> the error: curSixDof = hom2six(M).
> I did run the three lines of code to reset the default paths, add
> fieldtrip, and then ran ft_defaults. The version of FieldTrip I am
> using is 20130602.
> Thanks,
> Andrew
> On Mon, Jun 3, 2013 at 4:53 PM, Lozano Soldevilla, D. (Diego) <
> d.lozanosoldevilla at fcdonders.ru.nl > wrote:
> > Hi Andrew,
> > Did you type the following?
> > >> restoredefaultpath
> > >> addpath /fieldtripxxxx
> > >> ft_defaults
> > What's the ft_* function you invoke to get the error 'undefined
> > function 'hom2six'? And what's the fieldtrip version you're using?
> > best,
> > Diego
> > > From: "Andrew Brooks" < andmib at gmail.com >
> > > To: "FieldTrip discussion list" < fieldtrip at science.ru.nl >
> > > Sent: Monday, 3 June, 2013 10:15:49 PM
> > > Subject: [FieldTrip] Private function problems
> > > Hello all,
> > > I followed the instructions on properly adding FieldTrip to the
> > > Matlab
> > > path file. However, I continue to run into errors involving
> > > private
> > > functions. In this case, I get the error 'undefined function
> > > 'hom2six'
> > > for input arguments of type 'double''.
> > > Does anybody have a suggestion as to why this is occurring?
> > > Thanks!
> > > Andrew
> > > _______________________________________________
> > > fieldtrip mailing list
> > > fieldtrip at donders.ru.nl
> > > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > --
> > PhD Student
> > Neuronal Oscillations Group
> > Donders Institute for Brain, Cognition and Behaviour
> > Centre for Cognitive Neuroimaging
> > Trigon, room 0.83
> > Kapittelweg 29
> > Radboud University Nijmegen
> > NL-6525 EN Nijmegen
> > The Netherlands
> > E-Mail: d.lozanosoldevilla at fcdonders.ru.nl
> > Tel: +31-(0)24-36-66274
> > Web: http://www.neuosc.com/
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
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From elizabeth.bock at mcgill.ca  Wed Jun  5 17:53:36 2013
From: elizabeth.bock at mcgill.ca (Elizabeth Anne Bock, Ms)
Date: Wed, 5 Jun 2013 15:53:36 +0000
Subject: [FieldTrip] Polhemus Patriot
In-Reply-To: <67D8C434-4D28-40C3-94A6-A95C86BD6B78@gmail.com>
References: <67D8C434-4D28-40C3-94A6-A95C86BD6B78@gmail.com>
Message-ID: <86D86365C4E767468A79EB52DFBFB46F051E242F@exmbx2010-8.campus.MCGILL.CA>

Hi Julian,
We have experienced this problem as well.  We solved it using the following guidelines:

No metal near the polhemus or any of the receivers/transmitters - you will need to move the setup around the room to find the perfect spot.
Use a wooden or plastic chair
Use plastic or cloth glasses/holder to attach the receiver to the subject

My system is sensitive to the proximity of the transmitter and the receiver.  I use two receivers, #1 is the stylus and #2 is secured to plastic glasses that the subject wears.  The transmitter is taped to the back of the chair.  If #2 and the transmitter are too close to each other (i.e. a short person or child), then the measurement are inaccurate.  You would have to experiment with different distances that give good results.

Hope this helps!
Beth


------------------------------------------------------------------------------------------

Elizabeth Bock / MEG System Engineer

McConnell Brain Imaging Centre / Montreal Neurological Institute

McGill University / 3801 University St. / Montreal, QC H3A 2B4


Office: 514.398.3706

MEG Lab: 514.398.6056

Mobile: 514.718.6342

________________________________
From: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl] on behalf of Julian Keil [julian.keil at gmail.com]
Sent: Monday, June 03, 2013 11:14 AM
To: FieldTrip discussion list
Subject: [FieldTrip] Polhemus Patriot

Dear FieldTrip-Users,

I have a not really FieldTrip-related question, but maybe one of you can help me anyways.
In our lab, we have a Polhemus Patriot 3D tracking system to acquire electrode positions.
Unfortunately, the recordings are severely distorted in the Z-axis (up-down).
After contacting the Polhemus Support, I got the information, that this is due to metal in the surroundings of the source which distorts the magnetic field.
I tried to get as far away from any metal as possible in our lab (~1.5 m to the walls and floor) but to no avail.

Now to my question: Has anyone any experience dealing with this? I'm quite puzzled by this as I know plenty of labs use Polhemus trackers, and I'm not sure if our lab is especially metal prone or if I'm missing something.

Thanks a lot for any help.

Julian

********************
Dr. Julian Keil

AG Multisensorische Integration
Psychiatrische Universitätsklinik
der Charité im St. Hedwig-Krankenhaus
Große Hamburger Straße 5-11, Raum E 307
10115 Berlin

Telefon: +49-30-2311-1879
Fax:        +49-30-2311-2209
http://psy-ccm.charite.de/forschung/bildgebung/ag_multisensorische_integration

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From julian.keil at gmail.com  Wed Jun  5 18:02:55 2013
From: julian.keil at gmail.com (Julian Keil)
Date: Wed, 5 Jun 2013 18:02:55 +0200
Subject: [FieldTrip] Polhemus Patriot
In-Reply-To: <86D86365C4E767468A79EB52DFBFB46F051E242F@exmbx2010-8.campus.MCGILL.CA>
References: <67D8C434-4D28-40C3-94A6-A95C86BD6B78@gmail.com>
	<86D86365C4E767468A79EB52DFBFB46F051E242F@exmbx2010-8.campus.MCGILL.CA>
Message-ID: <CC0BDDFC-CF83-47BE-8B49-C18B3D1EC701@gmail.com>

Dear all,

thank you very much for your input.
I'll have to experiment a bit more with the distance to the walls (which probably contain metal) and the chair.
Thank you also for the idea with the second sensor, I hadn't tried this before.

Best,

Julian

Am 05.06.2013 um 17:53 schrieb Elizabeth Anne Bock, Ms:

> Hi Julian,
> We have experienced this problem as well.  We solved it using the following guidelines:
> 
> No metal near the polhemus or any of the receivers/transmitters - you will need to move the setup around the room to find the perfect spot.
> Use a wooden or plastic chair
> Use plastic or cloth glasses/holder to attach the receiver to the subject
> 
> My system is sensitive to the proximity of the transmitter and the receiver.  I use two receivers, #1 is the stylus and #2 is secured to plastic glasses that the subject wears.  The transmitter is taped to the back of the chair.  If #2 and the transmitter are too close to each other (i.e. a short person or child), then the measurement are inaccurate.  You would have to experiment with different distances that give good results.
> 
> Hope this helps!
> Beth
> 
> ------------------------------------------------------------------------------------------
> Elizabeth Bock / MEG System Engineer
> McConnell Brain Imaging Centre / Montreal Neurological Institute
> McGill University / 3801 University St. / Montreal, QC H3A 2B4
> 
> Office: 514.398.3706 
> MEG Lab: 514.398.6056
> Mobile: 514.718.6342
> From: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl] on behalf of Julian Keil [julian.keil at gmail.com]
> Sent: Monday, June 03, 2013 11:14 AM
> To: FieldTrip discussion list
> Subject: [FieldTrip] Polhemus Patriot
> 
> Dear FieldTrip-Users,
> 
> I have a not really FieldTrip-related question, but maybe one of you can help me anyways.
> In our lab, we have a Polhemus Patriot 3D tracking system to acquire electrode positions.
> Unfortunately, the recordings are severely distorted in the Z-axis (up-down).
> After contacting the Polhemus Support, I got the information, that this is due to metal in the surroundings of the source which distorts the magnetic field.
> I tried to get as far away from any metal as possible in our lab (~1.5 m to the walls and floor) but to no avail.
> 
> Now to my question: Has anyone any experience dealing with this? I'm quite puzzled by this as I know plenty of labs use Polhemus trackers, and I'm not sure if our lab is especially metal prone or if I'm missing something.
> 
> Thanks a lot for any help.
> 
> Julian
> 
> ********************
> Dr. Julian Keil
> 
> AG Multisensorische Integration
> Psychiatrische Universitätsklinik
> der Charité im St. Hedwig-Krankenhaus
> Große Hamburger Straße 5-11, Raum E 307
> 10115 Berlin
> 
> Telefon: +49-30-2311-1879
> Fax:        +49-30-2311-2209 
> http://psy-ccm.charite.de/forschung/bildgebung/ag_multisensorische_integration
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From mje.mads at gmail.com  Thu Jun  6 09:16:01 2013
From: mje.mads at gmail.com (Mads Jensen)
Date: Thu, 06 Jun 2013 09:16:01 +0200
Subject: [FieldTrip] Extracting the time of a cluster
Message-ID: <51B03731.2080303@gmail.com>

Dear all,

I have made a statistics analysis on ERP data using 
ft_timelockstatistics and got a significant cluster I would like to know 
the time course of this cluster(i.e. when it starts and ends being 
significant) , is that possible?

I take to the cirange that is computed in the output for the cluster 
from ft_timelockstatistics be the upper and lower limit of the 
confidence interval, so the cluster.prop +/- the cirange gives the 
95%confidence intervals. Is that correct?

best wishes,
Mads


From jm.horschig at donders.ru.nl  Thu Jun  6 10:17:50 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Thu, 06 Jun 2013 10:17:50 +0200
Subject: [FieldTrip] Extracting the time of a cluster
In-Reply-To: <51B03731.2080303@gmail.com>
References: <51B03731.2080303@gmail.com>
Message-ID: <51B045AE.3010305@donders.ru.nl>

Hi Mads,

there is a stats.posclusterlabelmat and stats.negclusterlabelmat field, 
which contain the indices of all your clusters. You can use these 
indices and to index the period where your test shows some significant 
effect(e.g. for timelock.avg or timelock.time). See here for an example, 
which does not quite do what you want, but gets close
http://fieldtrip.fcdonders.nl/tutorial/cluster_permutation_timelock#plotting_the_results

And, yes, cirange defines the range of the confidence interval for that 
particular cluster, so pvalue - cirange gives the lower bound and pvalue 
+ cirange the upper bound. If your upper bound extends beyond the 
critical alpha-value, I would advise to use more randomizations.

Best,
Jörn

On 6/6/2013 9:16 AM, Mads Jensen wrote:
> Dear all,
>
> I have made a statistics analysis on ERP data using 
> ft_timelockstatistics and got a significant cluster I would like to 
> know the time course of this cluster(i.e. when it starts and ends 
> being significant) , is that possible?
>
> I take to the cirange that is computed in the output for the cluster 
> from ft_timelockstatistics be the upper and lower limit of the 
> confidence interval, so the cluster.prop +/- the cirange gives the 
> 95%confidence intervals. Is that correct?
>
> best wishes,
> Mads
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands



From mje.mads at gmail.com  Thu Jun  6 12:48:02 2013
From: mje.mads at gmail.com (Mads Jensen)
Date: Thu, 06 Jun 2013 12:48:02 +0200
Subject: [FieldTrip] Extracting the time of a cluster
In-Reply-To: <51B045AE.3010305@donders.ru.nl>
References: <51B03731.2080303@gmail.com> <51B045AE.3010305@donders.ru.nl>
Message-ID: <51B068E2.3010500@gmail.com>

Hi Jörn,

thanks for the swift and very useful reply.

best,
mads

On 06/06/13 10:17, "Jörn M. Horschig" wrote:
> Hi Mads,
>
> there is a stats.posclusterlabelmat and stats.negclusterlabelmat field,
> which contain the indices of all your clusters. You can use these
> indices and to index the period where your test shows some significant
> effect(e.g. for timelock.avg or timelock.time). See here for an example,
> which does not quite do what you want, but gets close
> http://fieldtrip.fcdonders.nl/tutorial/cluster_permutation_timelock#plotting_the_results
>
>
> And, yes, cirange defines the range of the confidence interval for that
> particular cluster, so pvalue - cirange gives the lower bound and pvalue
> + cirange the upper bound. If your upper bound extends beyond the
> critical alpha-value, I would advise to use more randomizations.
>
> Best,
> Jörn
>
> On 6/6/2013 9:16 AM, Mads Jensen wrote:
>> Dear all,
>>
>> I have made a statistics analysis on ERP data using
>> ft_timelockstatistics and got a significant cluster I would like to
>> know the time course of this cluster(i.e. when it starts and ends
>> being significant) , is that possible?
>>
>> I take to the cirange that is computed in the output for the cluster
>> from ft_timelockstatistics be the upper and lower limit of the
>> confidence interval, so the cluster.prop +/- the cirange gives the
>> 95%confidence intervals. Is that correct?
>>
>> best wishes,
>> Mads
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>


From antony.passaro at gmail.com  Thu Jun  6 15:59:22 2013
From: antony.passaro at gmail.com (Antony Passaro)
Date: Thu, 6 Jun 2013 09:59:22 -0400
Subject: [FieldTrip] Statistics for correlation across subjects using
	cluster analysis
Message-ID: <CAB8wAYRKGor5kv1KYB4z-z92AGyyFFgqTkpUgkZTYQVHefeVyw@mail.gmail.com>

Hi,

I came across an email in the mailing list archives from this time last
year when a user ( Ingrid ) was asking about using a statistical model with
a cluster analysis to correct for multiple comparisons based on performing
a correlation across trials (and/or subjects). Jan-mathijs replied saying
he had a copy of statfun_corr and statfun_glm but I don't see a copy of
either of those functions in the latest fieldtrip release. Would anyone be
so kind as to point my in the right directions to tackle this problem?

Thank you,
-Tony
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From andmib at gmail.com  Thu Jun  6 17:06:25 2013
From: andmib at gmail.com (Andrew Brooks)
Date: Thu, 6 Jun 2013 11:06:25 -0400
Subject: [FieldTrip] Private function problems
In-Reply-To: <2127428772.1387542.1370439554352.JavaMail.root@sculptor.zimbra.ru.nl>
References: <CALJPz69LZ_35=Z6YR5E6yRymDcZ3bBjaOpXOMyz3+CTWDjDNcw@mail.gmail.com>
	<2127428772.1387542.1370439554352.JavaMail.root@sculptor.zimbra.ru.nl>
Message-ID: <CALJPz68nhn6pRVcDaKSazaic76pw+OsZaowVtWsBmhkWora_kg@mail.gmail.com>

Diego,

Thank you, that was indeed the problem. I had moved the ft_omri_pipeline
script out of the /realtime/online_mri directory, which caused the problems.

Thanks,
Andrew


On Wed, Jun 5, 2013 at 9:39 AM, Lozano Soldevilla, D. (Diego) <
d.lozanosoldevilla at fcdonders.ru.nl> wrote:

> Hi Andrew,
>
> Could you please check inside your matlab path there's the realtime/mri
> directory where ft_omri_pipeline_nuisance.m function is located?
>
> Mine looks like this:
>
> '/home/electromag/dieloz/matlab/*fieldtrip-dev/realtime/online_mri/*'
>
> If it's there, you shouldn't have the private folder problem. Otherwise,
> add from the command window and tell me.
>
> best,
>
> Diego
>
> ------------------------------
>
> *From: *"Andrew Brooks" <andmib at gmail.com>
> *To: *"Diego Lozano" <diego.lozanosoldevilla at fcdonders.ru.nl>, "FieldTrip
> discussion list" <fieldtrip at science.ru.nl>
> *Sent: *Tuesday, 4 June, 2013 5:01:43 PM
> *Subject: *Re: [FieldTrip] Private function problems
>
>
> Hello Diego,
>
> I am using the example pipeline script from an earlier version of
> FieldTrip (ft_omri_pipeline_nuisance). The exact code that is throwing the
> error: curSixDof = hom2six(M).
>
> I did run the three lines of code to reset the default paths, add
> fieldtrip, and then ran ft_defaults. The version of FieldTrip I am using is
> 20130602.
>
> Thanks,
> Andrew
>
>
>
>
>
>
> On Mon, Jun 3, 2013 at 4:53 PM, Lozano Soldevilla, D. (Diego) <
> d.lozanosoldevilla at fcdonders.ru.nl> wrote:
>
>> Hi Andrew,
>>
>> Did you type the following?
>>
>> >> restoredefaultpath
>> >> addpath /fieldtripxxxx
>> >> ft_defaults
>>
>> What's the ft_* function you invoke to get the error 'undefined function
>> 'hom2six'? And what's the fieldtrip version you're using?
>>
>> best,
>>
>> Diego
>>
>> ------------------------------
>>
>> *From: *"Andrew Brooks" <andmib at gmail.com>
>> *To: *"FieldTrip discussion list" <fieldtrip at science.ru.nl>
>> *Sent: *Monday, 3 June, 2013 10:15:49 PM
>> *Subject: *[FieldTrip] Private function problems
>>
>>
>> Hello all,
>>
>> I followed the instructions on properly adding FieldTrip to the Matlab
>> path file. However, I continue to run into errors involving private
>> functions. In this case, I get the error 'undefined function 'hom2six' for
>> input arguments of type 'double''.
>>
>> Does anybody have a suggestion as to why this is occurring?
>>
>> Thanks!
>> Andrew
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>>
>>
>>
>> --
>> PhD Student
>> Neuronal Oscillations Group
>> Donders Institute for Brain, Cognition and Behaviour
>> Centre for Cognitive Neuroimaging
>> Trigon, room 0.83
>> Kapittelweg 29
>> Radboud University Nijmegen
>> NL-6525 EN Nijmegen
>> The Netherlands
>> E-Mail: d.lozanosoldevilla at fcdonders.ru.nl
>> Tel:     +31-(0)24-36-66274
>> Web:   http://www.neuosc.com/
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From jkamienk at gmail.com  Thu Jun  6 17:49:27 2013
From: jkamienk at gmail.com (Juan Kamienkowski)
Date: Thu, 6 Jun 2013 12:49:27 -0300
Subject: [FieldTrip] Oscillatory power normalization
In-Reply-To: <CAJB8axm9J3=ktKM16bVhjFiToBOcD1RrVbn+1xxD4HiiqP1_WA@mail.gmail.com>
References: <CAJB8axm9J3=ktKM16bVhjFiToBOcD1RrVbn+1xxD4HiiqP1_WA@mail.gmail.com>
Message-ID: <CAARjoQSOKzcBL8qF6LYLd4CYzCOfzOhYiSQbfwhVDBB16bu2dg@mail.gmail.com>

Hi everybody,

More than one year later we come up with the same questions. Does anybody
have suggestions on this topic?

Thanks a lot!

Best,

juan


On Fri, Mar 9, 2012 at 4:16 PM, Matt Mollison <matt.mollison at gmail.com>wrote:

> My questions essentially boil down to: what do people do for power
> normalization when assessing statistical differences?
>
> It gets more detailed below regarding examining event-related power
> changes relative to a baseline (within-subjects, comparing two conditions,
> stimulus onset = 0 ms). I didn't find much discussion of this on the list
> or the wiki. Any references for these issues would also be appreciated.
>
> (1) Does power data need to be baseline normalized for statistical tests
> comparing conditions? Normalization would put power on equal footing across
> all subjects, conditions, sensors, times, frequencies, etc., but it will
> surely affect power during the stimulus period in a particular way. If so,
> do the two (or more) conditions need to use the same baseline condition, or
> can each trial be normalized to its own pre-stim baseline period (a la
> ft_freqbaseline)? For either, it seems like you'd always need
> keeptrials='yes' in ft_freqanalysis. However, it does not seem to get
> normalized in the cluster_permutation_freq tutorial (within-subjects)---am
> I missing something?
>
> If we should normalize:
> (2) I've read a number of papers that Z-transform stimulus period power
> relative to pre-stim activity (subtract mean, divide by std) before doing
> statistics. I've also read a lot that don't mention baselines, or e.g. do a
> decibel [dB] transform. ft_freqbaseline does not have a Z-transform option.
> There is ft_preproc_standardize, but this seems to operate at a lower level
> than is usually recommended. Z-transforming seems like a good option, but
> how can I use it in the FT pipeline for within-subjects analyses
> (especially with keeptrials='no')? Alternatively, when should one use
> 'absolute', 'relative', or 'relchange'?
>
> Regarding choosing the baseline period:
> (3) It seems that the baseline period needs to precede stimulus onset by a
> sufficient amount of time so that the stimulus period doesn't bleed into
> the baseline; this time would be specific to both the frequency and either
> wavelet width or taper window length. For example, at 4 Hz with wavelet
> width=6 or a taper with 6 cycles per time window (t_ftimwin) the
> wavelet/window would be 1500 ms long, and the end of the baseline must
> precede stimulus onset by at least half this to keep them separate. At
> lower frequencies this could get quite unruly (e.g., 1 Hz would require
> ending 3000 ms before stimulus). Is this correct? Maybe that's why it's
> better to have a single separate baseline condition. Anyway, the
> timefrequencyanalysis tutorial seems to disregard this separation of
> baseline and stimulus activity (as have many papers I've read), so maybe
> I'm wrong about this being necessary.
>
> Thanks for your time,
> Matt Mollison
>
> --
> Univ. of Colorado at Boulder
> Dept. of Psychology and Neuroscience
> matthew.mollison at colorado.edu
> http://psych.colorado.edu/~mollison/
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
Juan E Kamienkowski
Laboratorio de Neurociencia Integrativa
Departamento de Fisica, FCEN-UBA
Ciudad Universitaria, Pabellon I
(1428) Buenos Aires, Argentina
Phone: (54-11) 4576 3300 (282)
Fax: (54-11) 4576 3357
http://www.neurociencia.df.uba.ar/
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From S.J.Johnston at swansea.ac.uk  Fri Jun  7 11:23:20 2013
From: S.J.Johnston at swansea.ac.uk (Steve Johnston)
Date: Fri, 7 Jun 2013 10:23:20 +0100
Subject: [FieldTrip] Bad channel correction problems and ICA
Message-ID: <55D211F2-5D76-43EE-B41A-EA05C8FFCE6F@swansea.ac.uk>

Dear fters

I've just started using ft and, although being able to run through a test run of eye movement data just fine, I'm now getting into the more detailed stuff and I'm hitting a snag that I hope you can help me with.

Specifically I'm struggling to get any real ICA results after using ft_channelrepair but not if I go through without it. 

Data was recorded on a biosemi 128 system and the trials are just eye movements that I want to identify via ICA (simple test). 

If I just run through the procedure of importing data, set markers, remove gross artifacts (keeping all channels, including 3 bad ones) and then run the ICA - I get lovely eye movement components appearing. However, now I want to do it 'properly' and replace the bad channels. Currently I do the following … (sorry, for completeness I included everything to be on the safe side).

%%
% Standard cfg for import
 
cfg                         = [];
cfg.trialdef.prestim        = .2;
cfg.trialdef.poststim       = 2;
cfg.trialdef.eventtype      = 'STATUS';
 
%%
%Load each dataset and examine for channels that are bad - starting with EOG Localiser.
 
cfg.dataset                 = [subjectdata.dir filesep subjectdata.artifactfile];
cfg.trialdef.eventvalue     = markers.artifact;
cfg                         = ft_definetrial(cfg);
 
cfg.demean                  = 'yes';
data                        = ft_preprocessing(cfg);
 
% After the above, run ChannelRepair after identifying bad channels.
%%
% Channel Replace - get nearest neighbours
cfg                      = [];
cfg.method               = 'distance'
cfg.layout               = 'biosemi128.lay';
cfg.neighbourdist        = 0.13;
[neighbours]             = ft_prepare_neighbours(cfg,data)
 
%% Interpolate and put into new data structure
cfg                      = [];
cfg.badchannel           = replace_channels;
cfg.layout               = 'biosemi128.lay';
cfg.method               = 'nearest';
cfg.neighbours           = neighbours;
cfg.neighbourdist        = 0.13;
artifact_cleandata       = ft_channelrepair(cfg,data)

% Visualise data for and mark uncorrectable artifacts.
cfg.viewmode                = 'vertical';
cfg.continuous              = 'yes';
cfg.blocksize               = 12;
cfg                         = ft_databrowser(cfg,artifact_cleandata)
 
%%
% Do artifact rejection (also redefine settings lost during re-cfg in artefact rejection) 
cfg.trialdef.prestim        = .2;
cfg.trialdef.poststim       = 2;
cfg.trialdef.eventtype      = 'STATUS';
cfg.artifact.reject         = 'complete';
cfg.channel                 = 'EEG';
cfg                         = ft_rejectartifact(cfg, artifact_cleandata);
trialdata                   = ft_preprocessing(cfg, artifact_cleandata);
 
%%
cfg                         = [];
comp                        = ft_componentanalysis(cfg, trialdata); 
cfg                         = [];
cfg.component               = [1:20]
cfg.layout                  = 'biosemi128.lay'
cfg.comment                 = 'no'
ft_topoplotIC(cfg,comp)

So, the big question is - why do I get nothing after doing the channel repair. I've been through it several times and that seems to be the step where everything goes wrong. I've looked at the data post re-interpolation and it looks good - for now I'm assuming I've missed something.

Thanks for any help

Steve 
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From jm.horschig at donders.ru.nl  Fri Jun  7 11:47:11 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Fri, 07 Jun 2013 11:47:11 +0200
Subject: [FieldTrip] Bad channel correction problems and ICA
In-Reply-To: <55D211F2-5D76-43EE-B41A-EA05C8FFCE6F@swansea.ac.uk>
References: <55D211F2-5D76-43EE-B41A-EA05C8FFCE6F@swansea.ac.uk>
Message-ID: <51B1AC1F.1010008@donders.ru.nl>

Hi Steve,

I'm not quite sure what you mean with getting nothing (nothing like, 
empty? or an error?) or not getting real ICA results (real in contrast 
to complex?). My hunge is that you need to take the rank of your data 
into account. Interpolating missing channels is done by combining 
already existing information, i.e. channels, to reconstruct a 
time-course at another spatial location, i.e. another channel. Since you 
do not add any new information by this (it's just a linear combination 
of your existing data matrix), you can leave that step out prior to 
doing ICA. Otherwise, you can set something like ica_cfg.XXXica.pca = 
rank(data.trial{1}), then afaik ft_componentanalysis will perform a PCA 
and essentially identify that the interpolated channels are a linear 
combination of other channels (ICA is then done of the PCA components). 
Both methods are equivalent, so you might as well just drop the 
interpolation and remove bad channels completely.

Best,
Jörn


On 6/7/2013 11:23 AM, Steve Johnston wrote:
> Dear fters
>
> I've just started using ft and, although being able to run through a 
> test run of eye movement data just fine, I'm now getting into the more 
> detailed stuff and I'm hitting a snag that I hope you can help me with.
>
> Specifically I'm struggling to get any real ICA results after using 
> ft_channelrepair but not if I go through without it.
>
> Data was recorded on a biosemi 128 system and the trials are just eye 
> movements that I want to identify via ICA (simple test).
>
> If I just run through the procedure of importing data, set markers, 
> remove gross artifacts (keeping all channels, including 3 bad ones) 
> and then run the ICA - I get lovely eye movement components appearing. 
> However, now I want to do it 'properly' and replace the bad channels. 
> Currently I do the following ... (sorry, for completeness I included 
> everything to be on the safe side).
>
> %%
> % Standard cfg for import
>
> cfg                         = [];
> cfg.trialdef.prestim       = .2;
> cfg.trialdef.poststim       = 2;
> cfg.trialdef.eventtype     = 'STATUS';
>
> %%
> %Load each dataset and examine for channels that are bad - starting 
> with EOG Localiser.
>
> cfg.dataset                 = [subjectdata.dir filesep 
> subjectdata.artifactfile];
> cfg.trialdef.eventvalue     = markers.artifact;
> cfg                         = ft_definetrial(cfg);
>
> cfg.demean                 = 'yes';
> data                       = ft_preprocessing(cfg);
>
> % After the above, run ChannelRepair after identifying bad channels.
> %%
> % Channel Replace - get nearest neighbours
> cfg                      = [];
> cfg.method               = 'distance'
> cfg.layout               = 'biosemi128.lay';
> cfg.neighbourdist        = 0.13;
> [neighbours]             = ft_prepare_neighbours(cfg,data)
>
> %% Interpolate and put into new data structure
> cfg                      = [];
> cfg.badchannel           = replace_channels;
> cfg.layout               = 'biosemi128.lay';
> cfg.method               = 'nearest';
> cfg.neighbours           = neighbours;
> cfg.neighbourdist        = 0.13;
> artifact_cleandata       = ft_channelrepair(cfg,data)
>
> % Visualise data for and mark uncorrectable artifacts.
> cfg.viewmode                = 'vertical';
> cfg.continuous              = 'yes';
> cfg.blocksize               = 12;
> cfg                         = ft_databrowser(cfg,artifact_cleandata)
>
> %%
> % Do artifact rejection (also redefine settings lost during re-cfg in 
> artefact rejection)
> cfg.trialdef.prestim        = .2;
> cfg.trialdef.poststim       = 2;
> cfg.trialdef.eventtype      = 'STATUS';
> cfg.artifact.reject         = 'complete';
> cfg.channel                 = 'EEG';
> cfg                         = ft_rejectartifact(cfg, artifact_cleandata);
> trialdata                   = ft_preprocessing(cfg, artifact_cleandata);
>
> %%
> cfg                         = [];
> comp                        = ft_componentanalysis(cfg, trialdata);
> cfg                         = [];
> cfg.component               = [1:20]
> cfg.layout                  = 'biosemi128.lay'
> cfg.comment                 = 'no'
> ft_topoplotIC(cfg,comp)
>
> So, the big question is - why do I get nothing after doing the channel 
> repair. I've been through it several times and that seems to be the 
> step where everything goes wrong. I've looked at the data post 
> re-interpolation and it looks good - for now I'm assuming I've missed 
> something.
>
> Thanks for any help
>
> Steve
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands

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From S.J.Johnston at swansea.ac.uk  Fri Jun  7 11:59:10 2013
From: S.J.Johnston at swansea.ac.uk (Steve Johnston)
Date: Fri, 7 Jun 2013 10:59:10 +0100
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 15
In-Reply-To: <mailman.405.1370598433.1298.fieldtrip@science.ru.nl>
References: <mailman.405.1370598433.1298.fieldtrip@science.ru.nl>
Message-ID: <49AE80C3-1CA6-402B-8819-3140FCFF7DC3@swansea.ac.uk>

Thanks, and sorry, that was a pretty poor description of the results by me. Yes, I am getting a result, but the error/warning is 

'Warning: Matrix is close to singular or badly scaled.
Results may be inaccurate. RCOND = 1.376132e-17. '

I figured that matrix singularity may have been the problem, although I hadn't appreciated that replacing only three channels could lead to it -  I was expecting that to result from more channel replacements or using a lot of electrodes to interpolate with.

Thanks a lot for the help, will try as you suggest

Steve



> 
> 
> ----------------------------------------------------------------------
> 
> Message: 1
> Date: Fri, 7 Jun 2013 10:23:20 +0100
> From: Steve Johnston <S.J.Johnston at swansea.ac.uk>
> To: "fieldtrip at science.ru.nl" <fieldtrip at science.ru.nl>
> Subject: [FieldTrip] Bad channel correction problems and ICA
> Message-ID: <55D211F2-5D76-43EE-B41A-EA05C8FFCE6F at swansea.ac.uk>
> Content-Type: text/plain; charset="windows-1252"
> 
> Dear fters
> 
> I've just started using ft and, although being able to run through a test run of eye movement data just fine, I'm now getting into the more detailed stuff and I'm hitting a snag that I hope you can help me with.
> 
> Specifically I'm struggling to get any real ICA results after using ft_channelrepair but not if I go through without it. 
> 
> Data was recorded on a biosemi 128 system and the trials are just eye movements that I want to identify via ICA (simple test). 
> 
> If I just run through the procedure of importing data, set markers, remove gross artifacts (keeping all channels, including 3 bad ones) and then run the ICA - I get lovely eye movement components appearing. However, now I want to do it 'properly' and replace the bad channels. Currently I do the following ? (sorry, for completeness I included everything to be on the safe side).
> 
> %%
> % Standard cfg for import
> 
> cfg                         = [];
> cfg.trialdef.prestim        = .2;
> cfg.trialdef.poststim       = 2;
> cfg.trialdef.eventtype      = 'STATUS';
> 
> %%
> %Load each dataset and examine for channels that are bad - starting with EOG Localiser.
> 
> cfg.dataset                 = [subjectdata.dir filesep subjectdata.artifactfile];
> cfg.trialdef.eventvalue     = markers.artifact;
> cfg                         = ft_definetrial(cfg);
> 
> cfg.demean                  = 'yes';
> data                        = ft_preprocessing(cfg);
> 
> % After the above, run ChannelRepair after identifying bad channels.
> %%
> % Channel Replace - get nearest neighbours
> cfg                      = [];
> cfg.method               = 'distance'
> cfg.layout               = 'biosemi128.lay';
> cfg.neighbourdist        = 0.13;
> [neighbours]             = ft_prepare_neighbours(cfg,data)
> 
> %% Interpolate and put into new data structure
> cfg                      = [];
> cfg.badchannel           = replace_channels;
> cfg.layout               = 'biosemi128.lay';
> cfg.method               = 'nearest';
> cfg.neighbours           = neighbours;
> cfg.neighbourdist        = 0.13;
> artifact_cleandata       = ft_channelrepair(cfg,data)
> 
> % Visualise data for and mark uncorrectable artifacts.
> cfg.viewmode                = 'vertical';
> cfg.continuous              = 'yes';
> cfg.blocksize               = 12;
> cfg                         = ft_databrowser(cfg,artifact_cleandata)
> 
> %%
> % Do artifact rejection (also redefine settings lost during re-cfg in artefact rejection) 
> cfg.trialdef.prestim        = .2;
> cfg.trialdef.poststim       = 2;
> cfg.trialdef.eventtype      = 'STATUS';
> cfg.artifact.reject         = 'complete';
> cfg.channel                 = 'EEG';
> cfg                         = ft_rejectartifact(cfg, artifact_cleandata);
> trialdata                   = ft_preprocessing(cfg, artifact_cleandata);
> 
> %%
> cfg                         = [];
> comp                        = ft_componentanalysis(cfg, trialdata); 
> cfg                         = [];
> cfg.component               = [1:20]
> cfg.layout                  = 'biosemi128.lay'
> cfg.comment                 = 'no'
> ft_topoplotIC(cfg,comp)
> 
> So, the big question is - why do I get nothing after doing the channel repair. I've been through it several times and that seems to be the step where everything goes wrong. I've looked at the data post re-interpolation and it looks good - for now I'm assuming I've missed something.
> 
> Thanks for any help
> 
> Steve 
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> 
> ------------------------------
> 
> Message: 2
> Date: Fri, 07 Jun 2013 11:47:11 +0200
> From: "J?rn M. Horschig" <jm.horschig at donders.ru.nl>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] Bad channel correction problems and ICA
> Message-ID: <51B1AC1F.1010008 at donders.ru.nl>
> Content-Type: text/plain; charset="iso-8859-1"; Format="flowed"
> 
> Hi Steve,
> 
> I'm not quite sure what you mean with getting nothing (nothing like, 
> empty? or an error?) or not getting real ICA results (real in contrast 
> to complex?). My hunge is that you need to take the rank of your data 
> into account. Interpolating missing channels is done by combining 
> already existing information, i.e. channels, to reconstruct a 
> time-course at another spatial location, i.e. another channel. Since you 
> do not add any new information by this (it's just a linear combination 
> of your existing data matrix), you can leave that step out prior to 
> doing ICA. Otherwise, you can set something like ica_cfg.XXXica.pca = 
> rank(data.trial{1}), then afaik ft_componentanalysis will perform a PCA 
> and essentially identify that the interpolated channels are a linear 
> combination of other channels (ICA is then done of the PCA components). 
> Both methods are equivalent, so you might as well just drop the 
> interpolation and remove bad channels completely.
> 
> Best,
> J?rn
> 
> 
> On 6/7/2013 11:23 AM, Steve Johnston wrote:
>> Dear fters
>> 
>> I've just started using ft and, although being able to run through a 
>> test run of eye movement data just fine, I'm now getting into the more 
>> detailed stuff and I'm hitting a snag that I hope you can help me with.
>> 
>> Specifically I'm struggling to get any real ICA results after using 
>> ft_channelrepair but not if I go through without it.
>> 
>> Data was recorded on a biosemi 128 system and the trials are just eye 
>> movements that I want to identify via ICA (simple test).
>> 
>> If I just run through the procedure of importing data, set markers, 
>> remove gross artifacts (keeping all channels, including 3 bad ones) 
>> and then run the ICA - I get lovely eye movement components appearing. 
>> However, now I want to do it 'properly' and replace the bad channels. 
>> Currently I do the following ... (sorry, for completeness I included 
>> everything to be on the safe side).
>> 
>> %%
>> % Standard cfg for import
>> 
>> cfg                         = [];
>> cfg.trialdef.prestim       = .2;
>> cfg.trialdef.poststim       = 2;
>> cfg.trialdef.eventtype     = 'STATUS';
>> 
>> %%
>> %Load each dataset and examine for channels that are bad - starting 
>> with EOG Localiser.
>> 
>> cfg.dataset                 = [subjectdata.dir filesep 
>> subjectdata.artifactfile];
>> cfg.trialdef.eventvalue     = markers.artifact;
>> cfg                         = ft_definetrial(cfg);
>> 
>> cfg.demean                 = 'yes';
>> data                       = ft_preprocessing(cfg);
>> 
>> % After the above, run ChannelRepair after identifying bad channels.
>> %%
>> % Channel Replace - get nearest neighbours
>> cfg                      = [];
>> cfg.method               = 'distance'
>> cfg.layout               = 'biosemi128.lay';
>> cfg.neighbourdist        = 0.13;
>> [neighbours]             = ft_prepare_neighbours(cfg,data)
>> 
>> %% Interpolate and put into new data structure
>> cfg                      = [];
>> cfg.badchannel           = replace_channels;
>> cfg.layout               = 'biosemi128.lay';
>> cfg.method               = 'nearest';
>> cfg.neighbours           = neighbours;
>> cfg.neighbourdist        = 0.13;
>> artifact_cleandata       = ft_channelrepair(cfg,data)
>> 
>> % Visualise data for and mark uncorrectable artifacts.
>> cfg.viewmode                = 'vertical';
>> cfg.continuous              = 'yes';
>> cfg.blocksize               = 12;
>> cfg                         = ft_databrowser(cfg,artifact_cleandata)
>> 
>> %%
>> % Do artifact rejection (also redefine settings lost during re-cfg in 
>> artefact rejection)
>> cfg.trialdef.prestim        = .2;
>> cfg.trialdef.poststim       = 2;
>> cfg.trialdef.eventtype      = 'STATUS';
>> cfg.artifact.reject         = 'complete';
>> cfg.channel                 = 'EEG';
>> cfg                         = ft_rejectartifact(cfg, artifact_cleandata);
>> trialdata                   = ft_preprocessing(cfg, artifact_cleandata);
>> 
>> %%
>> cfg                         = [];
>> comp                        = ft_componentanalysis(cfg, trialdata);
>> cfg                         = [];
>> cfg.component               = [1:20]
>> cfg.layout                  = 'biosemi128.lay'
>> cfg.comment                 = 'no'
>> ft_topoplotIC(cfg,comp)
>> 
>> So, the big question is - why do I get nothing after doing the channel 
>> repair. I've been through it several times and that seems to be the 
>> step where everything goes wrong. I've looked at the data post 
>> re-interpolation and it looks good - for now I'm assuming I've missed 
>> something.
>> 
>> Thanks for any help
>> 
>> Steve
>> 
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> 
> -- 
> J?rn M. Horschig
> PhD Student
> Donders Institute for Brain, Cognition and Behaviour
> Centre for Cognitive Neuroimaging
> Radboud University Nijmegen
> Neuronal Oscillations Group
> FieldTrip Development Team
> 
> P.O. Box 9101
> NL-6500 HB Nijmegen
> The Netherlands
> 
> Contact:
> E-Mail: jm.horschig at donders.ru.nl
> Tel:    +31-(0)24-36-68493
> Web: http://www.ru.nl/donders
> 
> Visiting address:
> Trigon, room 2.30
> Kapittelweg 29
> NL-6525 EN Nijmegen
> The Netherlands
> 
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> 
> ------------------------------
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> End of fieldtrip Digest, Vol 31, Issue 15
> *****************************************




From robince at gmail.com  Fri Jun  7 17:03:21 2013
From: robince at gmail.com (Robin)
Date: Fri, 7 Jun 2013 16:03:21 +0100
Subject: [FieldTrip] some of the requested samples occur twice
In-Reply-To: <51AC623A.1080207@donders.ru.nl>
References: <CALsWBNOxcuA=LCMONaGWObU4fdZ3+vskGGFcKdTZE4jGRoW47Q@mail.gmail.com>
	<51AC623A.1080207@donders.ru.nl>
Message-ID: <CALsWBNOe7BiBuBcHGeLOSAf0diPUzGdLg0E+M3wq9MnZ21t6FA@mail.gmail.com>

Hi Jörn,

Thanks.

I am already using negative trlpadding.

In this case I am trying to do the artifact detection on in memory trial
data, because I want to do it after denoise_pca. I am not sure if this is
correct but it seemed to me that denoise_pca is to correct physical
aquisition artifacts so it would be better to do it before trying to
identify biological artifacts that are a part of the recorded signal.

The code I am using is below. If you could point out how to add padding for
the ft*artifact* section so that it can work on in memory data it would be
great.

Thanks,

Robin

%% Automatic artifact rejection
% for each run
run_data = cell(1,length(sub.blocks));
trl_idx = 0;
for ri=1:length(sub.blocks)
    % extra data to allow padding in artifact detection
    filterpad = 0.2;
    prestim = 0.5;
    poststim = 0.6;
    % extract trials
    cfg = [];
    cfg.dataset = fullfile(sub.megDataPath, num2str(sub.blocks(ri)), 'c,rfDC');
    cfg.trialdef.eventtype  = 'TRIGGER';
    cfg.trialdef.eventvalue = 192;
    cfg.trialdef.prestim    = prestim + filterpad;
    cfg.trialdef.poststim   = poststim + filterpad;
    cfg.trialfun = 'ft_trialfun_general';
    cfg.continuous = 'yes';

    cfg = ft_definetrial(cfg);
    % overwrite unnecessary constant eventvalue
    % with trial number within this block
    cfg.trl(:,4) = (1:size(cfg.trl,1)) + trl_idx;
    trl_idx = trl_idx + size(cfg.trl,1);

    % remove jump artifact trials
    trlidx = ismember(cfg.trl(:,4), good_trials);
    cfg.trl = cfg.trl(trlidx, :);

    % load
    cfg.detrend = 'yes';
    % long padding for line noise removal
    cfg.dftfilter = 'yes';
    cfg.padding = 10;
    run_raw = ft_preprocessing(cfg);

    % apply denoise_pca
    cfg = [];
    if isfield(sub,'posthoc_badchannels')
        remove_chans = sub.posthoc_badchannels;
    else
        remove_chans = {};
    end
    cfg.channel = ft_channelselection([{'all'} remove_chans],
good_meg_channels);
    cfg.trials = find(ismember(run_raw.trialinfo, good_trials));
    run_clean = ft_denoise_pca(cfg, run_raw);

    % artifact detection
    cfg = [];
    cfg.continuous = 'no'; % some trials are excluded
    cfg.trl = run_clean.sampleinfo;
    cfg.artfctdef.muscle.trlpadding = -filterpad;
    cfg.artfctdef.muscle.cutoff     = 20;
    [cfg, artifact] = ft_artifact_muscle(cfg, run_clean);

    cfg.artfctdef.eog.trlpadding = -filterpad;
    cfg.artfctdef.eog.channel    = {'A150' 'A124'};
    cfg.artfctdef.eog.cutoff     = 5;
    [cfg, artifact] = ft_artifact_eog(cfg, run_clean);

    % reject artifacts
    cfg.artfctdef.reject = 'complete';
    run_artfree = ft_rejectartifact(cfg, run_clean);

    % reduce to the original window
    cfg = [];
    cfg.toilim = [-prestim poststim];
    run_artfree = ft_redefinetrial(cfg, run_artfree);

    run_data{ri} = run_artfree;end

On Mon, Jun 3, 2013 at 10:30 AM, "Jörn M. Horschig" <
jm.horschig at donders.ru.nl> wrote:

Hi Robin,
>
> it's not a bug that ft_fetch_data is not allowing for overlap. The
> function needs to be generic and eventually allow for fetching data
> extending over several trial segments. However, what should be the way to
> fetch  data that occurs twice, i.e. at the end of one trial and the
> beginning of another? If you have data with overlapping samples, it is not
> straight forward to define data from one trial as to be fetched and ignore
> the other. Since preprocessing options like filters are applied per trial
> segment, data will differ between trial segments if it overlaps. As there
> are a multitude of possibilities to deal with this and none of them is
> perfect (imho neither of them can even be called good), we decided to not
> allow for that.
>
> For your problem, however, imho you can define negative trial padding in
> the function call to ft_artifact_zvalue, which should effectively pad. Have
> you tried this rather than padding manually?
>
> Best,
> Jörn
>
>
> On 5/31/2013 6:14 PM, Robin wrote:
>
>> I have a problem in preprocessing where I am getting this error:
>>
>> """
>> some of the requested samples occur twice in the data
>>
>> Error in ft_artifact_zvalue (line 262)
>>        dat{trlop} = ft_fetch_data(data,        'header', hdr, 'begsample',
>>        trl(trlop,1)-fltpadding, 'endsample', trl(trlop,2)+fltpadding,
>>        'chanindx', sgnind, 'checkboundary', strcmp(cfg.continuous,'no
>> Error in ft_artifact_muscle (line 158)
>>      [tmpcfg, artifact] = ft_artifact_zvalue(tmpcfg, data);
>> """
>>
>> I think this is because I am manually adding some extra padding to the
>> trials so that the artifact filtering can use that padding (I am doing
>> the artifact filtering on data in memory which is output from
>> ft_denoise_pca). So in this case it is not a problem if consecutive
>> trials overlap a bit.
>>
>> I would therefore like to disable this error and wondered what is the
>> best way to do it. I am a bit confused because ft_artifact_zvalue
>> calls ft_fetch data with a "checkboundary" option which looks like it
>> might be what I want (and set correctly), but ft_fetch_data doesn't
>> seem to use that option. Instead it has an allowoverlap option.
>>
>> So for now I will manually add the allowoverlap option to the call in
>> ft_artifact_zvalue, but I wondered what checkboundary doesn't appear
>> in ft_fetch_data or if this might be a bug.
>>
>> Cheers
>>
>> Robin
>> ______________________________**_________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/**mailman/listinfo/fieldtrip<http://mailman.science.ru.nl/mailman/listinfo/fieldtrip>
>>
>
>
> --
> Jörn M. Horschig
> PhD Student
> Donders Institute for Brain, Cognition and Behaviour
> Centre for Cognitive Neuroimaging
> Radboud University Nijmegen
> Neuronal Oscillations Group
> FieldTrip Development Team
>
> P.O. Box 9101
> NL-6500 HB Nijmegen
> The Netherlands
>
> Contact:
> E-Mail: jm.horschig at donders.ru.nl
> Tel:    +31-(0)24-36-68493
> Web: http://www.ru.nl/donders
>
> Visiting address:
> Trigon, room 2.30
> Kapittelweg 29
> NL-6525 EN Nijmegen
> The Netherlands
>
> ______________________________**_________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/**mailman/listinfo/fieldtrip<http://mailman.science.ru.nl/mailman/listinfo/fieldtrip>
>
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From jkamienk at gmail.com  Fri Jun  7 19:02:22 2013
From: jkamienk at gmail.com (Juan Kamienkowski)
Date: Fri, 7 Jun 2013 14:02:22 -0300
Subject: [FieldTrip] Cluster-based permutation tests on single channel
Message-ID: <CAARjoQQ-HQ7ML+2krPKvVePZo_ckfZQ8iy=4M4P7M2bvVCr_bA@mail.gmail.com>

Hi,

I wanted to perform a Cluster-based permutation tests on time-frequency
data, on a single channel (one Independent Component). But the
ft_freqstatistics() function ask me for the "neighbours" field in the "cfg"
structure, although I set the cfg.minnbchan to 0. Is there a way to run
this analysis in a single channel?

Thanks a lot in advance!

Best,

Juan

-- 
Juan E Kamienkowski
Laboratorio de Neurociencia Integrativa
Departamento de Fisica, FCEN-UBA
Ciudad Universitaria, Pabellon I
(1428) Buenos Aires, Argentina
Phone: (54-11) 4576 3300 (282)
Fax: (54-11) 4576 3357
http://www.neurociencia.df.uba.ar/
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From Don.Rojas at ucdenver.edu  Fri Jun  7 23:37:10 2013
From: Don.Rojas at ucdenver.edu (Rojas, Don)
Date: Fri, 7 Jun 2013 15:37:10 -0600
Subject: [FieldTrip] Cluster-based permutation tests on single channel
In-Reply-To: <CAARjoQQ-HQ7ML+2krPKvVePZo_ckfZQ8iy=4M4P7M2bvVCr_bA@mail.gmail.com>
References: <CAARjoQQ-HQ7ML+2krPKvVePZo_ckfZQ8iy=4M4P7M2bvVCr_bA@mail.gmail.com>
Message-ID: <E59258AC-98B2-40CB-8986-D047C55F2BB2@ucdenver.edu>

Juan,

The neighbours field is for defining adjacent channels for multi-channel multiple comparison correction. I'm not sure if you've gotten a response on this yet, but you simply set the cfg.neighbours field to be empty in your call to ft_freqstatistics for using cluster based corrections within time-frequency space for single channels.

cfg.neighbours = [];

Best,

Don

On Jun 7, 2013, at 11:02 AM, Juan Kamienkowski <jkamienk at gmail.com<mailto:jkamienk at gmail.com>> wrote:

Hi,

I wanted to perform a Cluster-based permutation tests on time-frequency data, on a single channel (one Independent Component). But the ft_freqstatistics() function ask me for the "neighbours" field in the "cfg" structure, although I set the cfg.minnbchan to 0. Is there a way to run this analysis in a single channel?

Thanks a lot in advance!

Best,

Juan

--
Juan E Kamienkowski
Laboratorio de Neurociencia Integrativa
Departamento de Fisica, FCEN-UBA
Ciudad Universitaria, Pabellon I
(1428) Buenos Aires, Argentina
Phone: (54-11) 4576 3300 (282)
Fax: (54-11) 4576 3357
http://www.neurociencia.df.uba.ar/
_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From Don.Rojas at ucdenver.edu  Fri Jun  7 23:37:10 2013
From: Don.Rojas at ucdenver.edu (Rojas, Don)
Date: Fri, 7 Jun 2013 15:37:10 -0600
Subject: [FieldTrip] Cluster-based permutation tests on single channel
In-Reply-To: <CAARjoQQ-HQ7ML+2krPKvVePZo_ckfZQ8iy=4M4P7M2bvVCr_bA@mail.gmail.com>
References: <CAARjoQQ-HQ7ML+2krPKvVePZo_ckfZQ8iy=4M4P7M2bvVCr_bA@mail.gmail.com>
Message-ID: <E59258AC-98B2-40CB-8986-D047C55F2BB2@ucdenver.edu>

Juan,

The neighbours field is for defining adjacent channels for multi-channel multiple comparison correction. I'm not sure if you've gotten a response on this yet, but you simply set the cfg.neighbours field to be empty in your call to ft_freqstatistics for using cluster based corrections within time-frequency space for single channels.

cfg.neighbours = [];

Best,

Don

On Jun 7, 2013, at 11:02 AM, Juan Kamienkowski <jkamienk at gmail.com<mailto:jkamienk at gmail.com>> wrote:

Hi,

I wanted to perform a Cluster-based permutation tests on time-frequency data, on a single channel (one Independent Component). But the ft_freqstatistics() function ask me for the "neighbours" field in the "cfg" structure, although I set the cfg.minnbchan to 0. Is there a way to run this analysis in a single channel?

Thanks a lot in advance!

Best,

Juan

--
Juan E Kamienkowski
Laboratorio de Neurociencia Integrativa
Departamento de Fisica, FCEN-UBA
Ciudad Universitaria, Pabellon I
(1428) Buenos Aires, Argentina
Phone: (54-11) 4576 3300 (282)
Fax: (54-11) 4576 3357
http://www.neurociencia.df.uba.ar/
_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From haristz at gmail.com  Sat Jun  8 00:25:03 2013
From: haristz at gmail.com (Charidimos Tzagarakis)
Date: Fri, 7 Jun 2013 17:25:03 -0500
Subject: [FieldTrip] Using ft_rejectcomponent after PCA reduction
Message-ID: <CAFN2X+fGYE6maW7X6_eyGrbt7+wvWggv4xXvu6PhebXPgSpq5A@mail.gmail.com>

Dear Fieldtripverse,
I have been experimenting with using ICA for artifact correction and have
the following question:
Because of the relatively large number of channels vs samples I have, I use
the option to first reduce the dimensionality of the data with PCA (I have
248 MEG channels and I select, say 100 components, using the <for
cfg.method="runica"> cfg.numcomponent=100 and cfg.runica.pca=100 in the
call to ft_componentanalysis ).
So the "topo" matrix in the component output structure has dimensions
248x100 and the unmixing matrix has dimensions 100x248. I then use
something like "data = ft_rejectcomponent(cfg, comp,data)" to say reject 2
components cfg.component=[30 40] that contain ECG signal. Note: data here
is the original data I fed in the ft_componentanalysis function.
This is all pretty straightforward and as described in the Fieldtrip
tutorial (minus the PCA part) . I am however a bit worried by the
message:"removing 2 components
keeping 246 components" I get in the end. Should it not be "removing 2
components
keeping 98 components"? When I look in the code for ft_rejectcomponent, I
can see that if "hasdata" is True the message is calculated based on the
number of channels : fprintf('keeping %d components\n',
nchans-length(cfg.component));
On the other hand (as far as I can tell, not being an ICA expert) the
actual calculation for the removal of the desired components seems to
correctly use the components selected for removal :
  mixing = comp.topo(selcomp,:);
  unmixing = comp.unmixing(:,selcomp);
  tra = eye(length(selcomp)) - mixing(:, cfg.component)*unmixing(cfg.
component, :);
(I do note the comment under that snippet!:
 %I am not sure about this, but it gives comparable results to the ~hasdata
case
  %when comp contains non-orthogonal (=ica) topographies, and contains a
complete decomposition)

Further down the function code there are however more operations (eg remove
unused channels, remove unused components ) where I am less able to follow
things to make sure it is robust to non-square mixing and unmixing
matrices.

In summary, I wanted to ask if it is OK to use ft_rejectcomponent in this
way (ie without decomposing to the full number of ICA's and then using it
on the original data).
With Thanks and Best Wishes,
Haris

Charidimos [Haris] Tzagarakis MD, PhD, MRCPsych
University of Minnesota Dept of Neuroscience and Brain Sciences Center
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From mengtongxiao at gmail.com  Sun Jun  9 03:31:56 2013
From: mengtongxiao at gmail.com (=?GB2312?B?s8LRqQ==?=)
Date: Sun, 9 Jun 2013 09:31:56 +0800
Subject: [FieldTrip] what is the MNI-template be use to constructed
	sourcemodel , MNI125 or colin27?
Message-ID: <CADiddyX5sgXN2qhoVPCmDsm9sbjSCkUGp=sv6PKBy1UBF_+arw@mail.gmail.com>

Dear all
I use the model ( fieldtrip/template/sourcemodel )  doing source
reconstruction with beamformer .
I want to know  the template is matching  MNI125 or colin27 .

thanks.
best ,
xiao
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From nomeserio at gmail.com  Mon Jun 10 10:29:21 2013
From: nomeserio at gmail.com (Michele Barsotti)
Date: Mon, 10 Jun 2013 10:29:21 +0200
Subject: [FieldTrip] Downloading FieldTrip
Message-ID: <CAGZjeH4vNQBHOYe7kp6jQXjtcnRD=Wvic99OkjARq57h=hm1Vg@mail.gmail.com>

Dear FieldTrip users and staff,

  I'm dealing with the download of fieldtrip but everytime I try a download
error occurs with this message:
"...fieldtrip-aaaammgg.zip could not be saved, because the source file
could not be read. Try again later, or contact the server administrator."

Can someone help me?

Thank in advance

-- 
        -Michele-
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From joramvandriel at gmail.com  Mon Jun 10 16:09:25 2013
From: joramvandriel at gmail.com (Joram van Driel)
Date: Mon, 10 Jun 2013 16:09:25 +0200
Subject: [FieldTrip] BEM for MEG data
Message-ID: <CAKk__WVoQL5s4NwxPFpLJm7WRgFzwX1CxQk4k4WtRToormTEhA@mail.gmail.com>

Dear Fieldtrip users and developers,

I've been struggling quite some time now with the following problem.

We want to do source localization of MEG data from an experiment with 10
subjects. We collected MRIs using a Phillips scanner (UvA), and MEG data
using the Neuromag Elekta scanner (VUmc).

Using Neuromag software in Linux (seglab, xfit), I've created BEM forward
models based on coregistered MRIs (coregistration also done using the
Neuromag package), which result in .fif files (extension *bem-sol.fif).

Using these models we want to continue computing the leadfields and doing
source reconstruction in Matlab. For the latter, we have our own customized
codes; to get the leadfield, we need some step in between. I'm trying to
use fieldtrip functions for this but I get stuck. Here's what I do:

- Import the bem fif files using the mne toolbox (function:
mne_read_bem_surfaces).
- Attach the imported boundary data to a vol structure as follows:

[bem] = mne_read_bem_surfaces(bemfilz(subno).name);
vol                 = [];
vol.bnd.pnt         = bem.rr;
vol.bnd.tri         = double(bem.tris);
vol.unit            = 'mm';
vol.cfg.sourceunits = 'mm';
vol.type            = 'bemcp';
vol.cfg.numvertices = bem.np;

- Import the sensor locations using ft_read_sens and convert to mm using
ft_convert_units.
- Check whether the resulting structures are OK for leadfield computation
using ft_prepare_vol_sens. This results in an error "Unsupported volume
conductor model for MEG".

I also tried ft_read_vol, but for Neuromag this needs the meg-pd toolbox
which doesn't run on Windows (the Linux we use for the Neuromag software,
in turn, is a virtual machine and doesn't have Matlab).

Is there a way around this? Using BEM models for MEG data should in
principle be possible, but not using Fieldtrip?

Any suggestions would be much appreciated!
Thanks in advance,

Joram


-- 
Joram van Driel, MSc.
PhD student at the University of Amsterdam
Department of Psychology, Brain & Cognition
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From aaron.schurger at gmail.com  Mon Jun 10 18:11:23 2013
From: aaron.schurger at gmail.com (Aaron Schurger)
Date: Mon, 10 Jun 2013 18:11:23 +0200
Subject: [FieldTrip] What are the units output by ft_freqanalysis_tfr?
Message-ID: <CALeeyAQiEs-GM+40MU-O4QJQq29iO4XaK97_6utb2dLjpCqW_Q@mail.gmail.com>

Hi,
I am preparing figures for a paper, one of which is a time-frequency
plot of the output from ft_freqanalysis (using the tfr method). The
units of the data going in were on the order of 10e-11 or smaller (MEG
data), but the units on the color (power) axis of the plot are on the
order of 10e-1. Are the units normalized by default when you use
ft_freqanalysis? If not then what are the units? The help on these
functions was short on this kind of detail.
Thanks!
Aaron Schurger

--
Aaron Schurger, PhD
Post-doctoral researcher
INSERM U992 / NeuroSpin
CEA - Saclay, France
+33-1-69-08-66-47
aaron.schurger at gmail.com
http://www.unicog.org


From ivan.skelin at uleth.ca  Tue Jun 11 03:57:55 2013
From: ivan.skelin at uleth.ca (Skelin, Ivan)
Date: Mon, 10 Jun 2013 18:57:55 -0700
Subject: [FieldTrip] ncs file downsampling and further processing
Message-ID: <CA+pymnfq-RTSQuP_LQvZLGACQPetbdWeaT_zY81_cwA+hKATPw@mail.gmail.com>

Hi,

I am recording from the anesthetized rats using the two NeuroNexus silicone
probes with 8 tetrodes (32 channels) each and Neuralynx Cheetah system at
32556 Hz sampling frequency. I choose to analyze the .ncs files from 1/4 of
the channels or 1 channel per tetrode. Since the recordings took about 150
mins, the .ncs files are too bulky (0.5 GB) for the standard procedure that
the FieldTrip recommends for discontinuous data recorded using Neuralynx
system. More precisely, when I preprocess the channels separately and
subsequently run the ft_read_neuralynx_interp on them, I get the "out of
memory" error message (even when running it on only two .ncs files at the
time).

My question is if I can first downsample all the .csc files that I want to
analyze using the ft_spikedownsample, before I run the ft_read_neuralynx_interp
on them?



Thank you very much,

Ivan


-- 
Ivan Skelin, MD, PhD
Postdoctoral Fellow
Polaris Brain Dynamics Research Group
Canadian Centre for Behavioural Neuroscience
The University of Lethbridge
4401 University Dr W
Lethbridge, AB, T1K 3M4
Canada
http://lethbridgebraindynamics.com
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From explena at gmail.com  Tue Jun 11 09:48:34 2013
From: explena at gmail.com (Shen-Mou Hsu)
Date: Tue, 11 Jun 2013 15:48:34 +0800
Subject: [FieldTrip] ROC_based permutation test
Message-ID: <CAFg6g2eKEb-EmYa=BkWTwUVx20+oP92rs6u06w9m+Ehz5ni8qg@mail.gmail.com>

Dear all,

I was trying to perform signle-trial ROC-based permutation tests using the
statfun_roc. However I encountered two questions and wondered if anyone
could kindly shed some light on the issues. First, is it necessary to
perform baseline normalization for each trial before the tests? Second, an
error message returned stating "Error using roc. Too many input arguments.
Error using ft_statistics_montecarlo (line 223) could not determine the
parametric critical value for clustering", after running the following
script:

load (['t_RF_EpoRejDePow']); load (['t_RN_EpoRejDePow']);

cfg = [];
cfg.channel     = 'MEG';
cfg.latency     = [-0.35 0.55];
cfg.frequency   = [8 12];
cfg.parameter   = 'powspctrm';
cfg.method      = 'montecarlo';
cfg.statistic   = 'roc';
cfg.alpha       = 0.025;
cfg.tail = 0;
cfg.correctm    = 'cluster';
cfg.clusteralpha = 0.05;
% cfg.correcttail = 'prob';
cfg.clustertail = 0;
cfg.numrandomization = 1000;
cfg.minnbchan        = 2;
cfg_neighb.method    = 'distance';
cfg.neighbours       = ft_prepare_neighbours(cfg_neighb, t_RN_EpoRejDePow);
cfg.logtransform = 'yes';

design = [1*ones(1,size(t_RF_EpoRejDePow.powspctrm,1))
2*ones(1,size(t_RN_EpoRejDePow.powspctrm,1))]; % the first dimension of
these variable is the trial number.
cfg.design  = design;

P_ROC_t_RFvsRN = ft_freqstatistics(cfg,t_RF_EpoRejDePow,t_RN_EpoRejDePow);


Any help is greatly appreciated.

Best regards,

Shen-Mou Hsu
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From eelke.spaak at donders.ru.nl  Tue Jun 11 09:58:58 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Tue, 11 Jun 2013 09:58:58 +0200
Subject: [FieldTrip] What are the units output by ft_freqanalysis_tfr?
In-Reply-To: <CALeeyAQiEs-GM+40MU-O4QJQq29iO4XaK97_6utb2dLjpCqW_Q@mail.gmail.com>
References: <CALeeyAQiEs-GM+40MU-O4QJQq29iO4XaK97_6utb2dLjpCqW_Q@mail.gmail.com>
Message-ID: <CABPNLUrhOFUV30iN8SWGEbR_613nYXVa6=gFaE8toDB+rNwTwA@mail.gmail.com>

Hi Aaron,

How are you plotting the data? If you are using
ft_single/multi/topoplotTFR, did you use baseline correction
(cfg.baseline = 'yes' or [begin end])? If you use cfg.baselinetype =
'relative' or cfg.baselinetype = 'relchange', data plotted will
typically be on the order of 10e-1. It represents ratio vs baseline
('relative') or relative change vs baseline ('relchange').

If you did not specify baseline correction, then there is something
else going on. In any case, ft_freqanalysis does not explicitly
transform/normalize units; it does not care about them.

Best,
Eelke

On 10 June 2013 18:11, Aaron Schurger <aaron.schurger at gmail.com> wrote:
> Hi,
> I am preparing figures for a paper, one of which is a time-frequency
> plot of the output from ft_freqanalysis (using the tfr method). The
> units of the data going in were on the order of 10e-11 or smaller (MEG
> data), but the units on the color (power) axis of the plot are on the
> order of 10e-1. Are the units normalized by default when you use
> ft_freqanalysis? If not then what are the units? The help on these
> functions was short on this kind of detail.
> Thanks!
> Aaron Schurger
>
> --
> Aaron Schurger, PhD
> Post-doctoral researcher
> INSERM U992 / NeuroSpin
> CEA - Saclay, France
> +33-1-69-08-66-47
> aaron.schurger at gmail.com
> http://www.unicog.org
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From eelke.spaak at donders.ru.nl  Tue Jun 11 10:18:09 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Tue, 11 Jun 2013 10:18:09 +0200
Subject: [FieldTrip] ROC_based permutation test
In-Reply-To: <CAFg6g2eKEb-EmYa=BkWTwUVx20+oP92rs6u06w9m+Ehz5ni8qg@mail.gmail.com>
References: <CAFg6g2eKEb-EmYa=BkWTwUVx20+oP92rs6u06w9m+Ehz5ni8qg@mail.gmail.com>
Message-ID: <CABPNLUpB9DHCQCszf7WuujVgKT4g9Dp3GPNd19-O65b160y8NQ@mail.gmail.com>

Dear Shen-Mou Hsu,

With regards to your first question, I do not know the answer, so
someone else might help you there.

In response to your second question, regarding the error "could not
determine the parametric critical value for clustering", this is
caused by the value of cfg.clusterthreshold used. The default value
there is 'parametric', meaning that the statistics routine will ask
your 'statfun' to compute a parametric threshold for considering a
(time/frequency/channel)-voxel a cluster-member candidate. This can be
done by e.g. depsamplesT or indepsamplesT, as it is possible to
analytically compute a T value corresponding to p < 0.05. However, in
the case of the ROC statistic, no such parametric estimate can be
computed (or perhaps it can be in some way, I don't know, but at least
I know the FT implementation does not).

Fortunately, the statistics routines also allow you to use a
nonparametric threshold for cluster-member candidates, based on the
generated distribution of the test statistic under the null
hypothesis. To use this, simply specify cfg.clusterthreshold =
'nonparametric_individual' or cfg.clusterthreshold =
'nonparametric_common'. The difference between the two is that the
former computes a threshold per voxel, and the latter uses the same
threshold for all voxels. Which one is appropriate for you I don't
know. (Good reasons for using 'nonparametric_individual' might be a
strong variation of your test statistic with frequency. I know for a
fact this is the case with certain quantifications of phase-amplitude
coupling; these show much higher values in the low frequencies even
when computed on noise.)

Hope this helps.

Best,
Eelke

On 11 June 2013 09:48, Shen-Mou Hsu <explena at gmail.com> wrote:
> Dear all,
>
> I was trying to perform signle-trial ROC-based permutation tests using the
> statfun_roc. However I encountered two questions and wondered if anyone
> could kindly shed some light on the issues. First, is it necessary to
> perform baseline normalization for each trial before the tests? Second, an
> error message returned stating "Error using roc. Too many input arguments.
> Error using ft_statistics_montecarlo (line 223) could not determine the
> parametric critical value for clustering", after running the following
> script:
>
> load (['t_RF_EpoRejDePow']); load (['t_RN_EpoRejDePow']);
>
> cfg = [];
> cfg.channel     = 'MEG';
> cfg.latency     = [-0.35 0.55];
> cfg.frequency   = [8 12];
> cfg.parameter   = 'powspctrm';
> cfg.method      = 'montecarlo';
> cfg.statistic   = 'roc';
> cfg.alpha       = 0.025;
> cfg.tail = 0;
> cfg.correctm    = 'cluster';
> cfg.clusteralpha = 0.05;
> % cfg.correcttail = 'prob';
> cfg.clustertail = 0;
> cfg.numrandomization = 1000;
> cfg.minnbchan        = 2;
> cfg_neighb.method    = 'distance';
> cfg.neighbours       = ft_prepare_neighbours(cfg_neighb, t_RN_EpoRejDePow);
> cfg.logtransform = 'yes';
>
> design = [1*ones(1,size(t_RF_EpoRejDePow.powspctrm,1))
> 2*ones(1,size(t_RN_EpoRejDePow.powspctrm,1))]; % the first dimension of
> these variable is the trial number.
> cfg.design  = design;
>
> P_ROC_t_RFvsRN = ft_freqstatistics(cfg,t_RF_EpoRejDePow,t_RN_EpoRejDePow);
>
>
> Any help is greatly appreciated.
>
> Best regards,
>
> Shen-Mou Hsu
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From aaron.schurger at gmail.com  Tue Jun 11 11:00:03 2013
From: aaron.schurger at gmail.com (Aaron Schurger)
Date: Tue, 11 Jun 2013 11:00:03 +0200
Subject: [FieldTrip] What are the units output by ft_freqanalysis_tfr?
In-Reply-To: <CABPNLUrhOFUV30iN8SWGEbR_613nYXVa6=gFaE8toDB+rNwTwA@mail.gmail.com>
References: <CALeeyAQiEs-GM+40MU-O4QJQq29iO4XaK97_6utb2dLjpCqW_Q@mail.gmail.com>
	<CABPNLUrhOFUV30iN8SWGEbR_613nYXVa6=gFaE8toDB+rNwTwA@mail.gmail.com>
Message-ID: <CALeeyAS=CgYuqCh0cve-euKptDk2AGNyS8vLXZtQ987244zAaQ@mail.gmail.com>

Hi, Eelke,
Thanks for your reply. I think that might explain it. When I step
through my code, I see that the units are as expected for MEG in the
output from ft_freqanalysis, so it must be something after that stage
that is changing.
Thanks for the tip!
Best wishes,
Aaron

On Tue, Jun 11, 2013 at 9:58 AM, Eelke Spaak <eelke.spaak at donders.ru.nl> wrote:
> Hi Aaron,
>
> How are you plotting the data? If you are using
> ft_single/multi/topoplotTFR, did you use baseline correction
> (cfg.baseline = 'yes' or [begin end])? If you use cfg.baselinetype =
> 'relative' or cfg.baselinetype = 'relchange', data plotted will
> typically be on the order of 10e-1. It represents ratio vs baseline
> ('relative') or relative change vs baseline ('relchange').
>
> If you did not specify baseline correction, then there is something
> else going on. In any case, ft_freqanalysis does not explicitly
> transform/normalize units; it does not care about them.
>
> Best,
> Eelke
>
> On 10 June 2013 18:11, Aaron Schurger <aaron.schurger at gmail.com> wrote:
>> Hi,
>> I am preparing figures for a paper, one of which is a time-frequency
>> plot of the output from ft_freqanalysis (using the tfr method). The
>> units of the data going in were on the order of 10e-11 or smaller (MEG
>> data), but the units on the color (power) axis of the plot are on the
>> order of 10e-1. Are the units normalized by default when you use
>> ft_freqanalysis? If not then what are the units? The help on these
>> functions was short on this kind of detail.
>> Thanks!
>> Aaron Schurger
>>
>> --
>> Aaron Schurger, PhD
>> Post-doctoral researcher
>> INSERM U992 / NeuroSpin
>> CEA - Saclay, France
>> +33-1-69-08-66-47
>> aaron.schurger at gmail.com
>> http://www.unicog.org
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip



-- 
Aaron Schurger, PhD
Post-doctoral researcher
INSERM U992 / NeuroSpin
CEA - Saclay, France
+33-1-69-08-66-47
aaron.schurger at gmail.com
http://www.unicog.org


From nicolai at mersebak.dk  Wed Jun 12 15:44:00 2013
From: nicolai at mersebak.dk (Nicolai Mersebak)
Date: Wed, 12 Jun 2013 15:44:00 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
Message-ID: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>

Dear all,

I have a question concerning the usage of ft_sourcegrandaverage and
ft_sourcestatistics.

After using ft_sourceanalysis (method: MNE), I get spatio-temporal source
reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897
time points.

Now I would like to use the cluster-based permutation test on my source
reconstructed data. However it seems like ft_sourcegrandaverage and
ft_sourcestatistics
don't support source level time courses. E.g when I am using
ft_sourcegrandaverage
I am getting the following error:

Error in ft_sourcegrandaverage (line 158)
  dat(:,i) = tmp(:);

Looking into the code:

  for i=1:Nsubject

    tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter,
varargin{i}));

    dat(:,i) = tmp(:);

    tmp = getsubfield(varargin{i}, 'inside');

    inside(tmp,i) = 1;

  end

I see that "tmp" are getting the structure [N_sources x timepoints] from
source.avg.pow for one subject, where "dat" requires the structure
[N_sources x 1].

I seached the mailing list for similar issues and found this thread:

http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html

Since I am interested in using the temporal dimension in my statistics, I
would like to know if it is still not possible to use spatio-temporal
source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?

Or if any have succeeded in using the cluster-based permutation test on
source level also including the temporal dimension ?

Alternative I was thinking that I might could use ft_timelockstatistics,
where I substituted the channels with sources, e.g instead of having 64
channels, I would now have 4050 "channels".
If so I need to calculate a label structure and an appropriate neighbor
structure, which I guess is possible as I have all the 3D coordinates for
each source, e.g in leadfield.pos ?
I know this is a work around solution, but have anyone tried or have any
experience using such an approach ?

Best,

Nicolai
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From johanna.zumer at donders.ru.nl  Wed Jun 12 16:03:16 2013
From: johanna.zumer at donders.ru.nl (Johanna Zumer)
Date: Wed, 12 Jun 2013 16:03:16 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
 reconstruction data (MNE)
In-Reply-To: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
Message-ID: <CAL4kA6dpzj6xWWs0kXOeQ60WKVixowZtF6N4Kse0ubeoA=4vLQ@mail.gmail.com>

Dear Nicolai,

Good timing, I have just last week filed a 'bug' for this code modification
request:  http://bugzilla.fcdonders.nl/show_bug.cgi?id=2185
You may add yourself to the CC list if you wish to receive updates on the
bug progress.

I would be interested to hear if anyone else has thoughts on your
suggestion to 'hack' it as a timelock structure with channels.

Best,
Johanna


2013/6/12 Nicolai Mersebak <nicolai at mersebak.dk>

> Dear all,
>
> I have a question concerning the usage of ft_sourcegrandaverage and
> ft_sourcestatistics.
>
> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source
> reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897
> time points.
>
> Now I would like to use the cluster-based permutation test on my source
> reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics
> don't support source level time courses. E.g when I am using ft_sourcegrandaverage
> I am getting the following error:
>
> Error in ft_sourcegrandaverage (line 158)
>   dat(:,i) = tmp(:);
>
> Looking into the code:
>
>   for i=1:Nsubject
>
>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter,
> varargin{i}));
>
>     dat(:,i) = tmp(:);
>
>     tmp = getsubfield(varargin{i}, 'inside');
>
>     inside(tmp,i) = 1;
>
>   end
>
> I see that "tmp" are getting the structure [N_sources x timepoints] from
> source.avg.pow for one subject, where "dat" requires the structure
> [N_sources x 1].
>
> I seached the mailing list for similar issues and found this thread:
>
> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>
> Since I am interested in using the temporal dimension in my statistics, I
> would like to know if it is still not possible to use spatio-temporal
> source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
>
> Or if any have succeeded in using the cluster-based permutation test on
> source level also including the temporal dimension ?
>
> Alternative I was thinking that I might could use ft_timelockstatistics,
> where I substituted the channels with sources, e.g instead of having 64
> channels, I would now have 4050 "channels".
> If so I need to calculate a label structure and an appropriate neighbor
> structure, which I guess is possible as I have all the 3D coordinates for
> each source, e.g in leadfield.pos ?
> I know this is a work around solution, but have anyone tried or have any
> experience using such an approach ?
>
> Best,
>
> Nicolai
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From jm.horschig at donders.ru.nl  Wed Jun 12 16:20:29 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Wed, 12 Jun 2013 16:20:29 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
 reconstruction data (MNE)
In-Reply-To: <CAL4kA6dpzj6xWWs0kXOeQ60WKVixowZtF6N4Kse0ubeoA=4vLQ@mail.gmail.com>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
	<CAL4kA6dpzj6xWWs0kXOeQ60WKVixowZtF6N4Kse0ubeoA=4vLQ@mail.gmail.com>
Message-ID: <51B883AD.8020707@donders.ru.nl>

Heyho,

it might be a good way, at least I am doing it that way :) But think 
about defining neighbouring voxels beforehands (easily doable for a 
decent programmer, hard for a not-so-experienced programmer). In the 
upcoming months/years there will be something changing on the 
source-front anyway, so maybe it is best to use the temporary solution 
with ft_timelockXXX until then. Note that my personal opinion does not 
necessarily reflect the opinion of the core dev team ;)

Best,
Jörn

On 6/12/2013 4:03 PM, Johanna Zumer wrote:
> Dear Nicolai,
>
> Good timing, I have just last week filed a 'bug' for this code 
> modification request: http://bugzilla.fcdonders.nl/show_bug.cgi?id=2185
> You may add yourself to the CC list if you wish to receive updates on 
> the bug progress.
>
> I would be interested to hear if anyone else has thoughts on your 
> suggestion to 'hack' it as a timelock structure with channels.
>
> Best,
> Johanna
>
>
> 2013/6/12 Nicolai Mersebak <nicolai at mersebak.dk 
> <mailto:nicolai at mersebak.dk>>
>
>     Dear all,
>
>     I have a question concerning the usage of ft_sourcegrandaverage
>     and ft_sourcestatistics.
>
>     After using ft_sourceanalysis (method: MNE), I get spatio-temporal
>     source reconstructed data in source.avg.pow (4050 x 897): 4050
>     sources and 897 time points.
>
>     Now I would like to use the cluster-based permutation test on my
>     source reconstructed data. However it seems like
>     ft_sourcegrandaverage and ft_sourcestatistics don't support source
>     level time courses. E.g when I am using ft_sourcegrandaverage I am
>     getting the following error:
>
>     Error in ft_sourcegrandaverage (line 158)
>       dat(:,i) = tmp(:);
>
>     Looking into the code:
>
>     for i=1:Nsubject
>
>       tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter,
>     varargin{i}));
>
>       dat(:,i) = tmp(:);
>
>       tmp = getsubfield(varargin{i}, 'inside');
>
>       inside(tmp,i) = 1;
>
>     end
>
>
>     I see that "tmp" are getting the structure [N_sources x
>     timepoints] from source.avg.pow for one subject, where "dat"
>     requires the structure [N_sources x 1].
>
>     I seached the mailing list for similar issues and found this thread:
>
>     http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>
>     Since I am interested in using the temporal dimension in my
>     statistics, I would like to know if it is still not possible to
>     use spatio-temporal source reconstructed data in
>     ft_sourcestatistics and ft_sourcegrandaverage ?
>
>     Or if any have succeeded in using the cluster-based permutation
>     test on source level also including the temporal dimension ?
>
>     Alternative I was thinking that I might could use
>     ft_timelockstatistics, where I substituted the channels with
>     sources, e.g instead of having 64 channels, I would now have 4050
>     "channels".
>     If so I need to calculate a label structure and an appropriate
>     neighbor structure, which I guess is possible as I have all the 3D
>     coordinates for each source, e.g in leadfield.pos ?
>     I know this is a work around solution, but have anyone tried or
>     have any experience using such an approach ?
>
>     Best,
>
>     Nicolai
>
>
>     _______________________________________________
>     fieldtrip mailing list
>     fieldtrip at donders.ru.nl <mailto:fieldtrip at donders.ru.nl>
>     http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands

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From smoratti at psi.ucm.es  Wed Jun 12 17:44:59 2013
From: smoratti at psi.ucm.es (smoratti at psi.ucm.es)
Date: Wed, 12 Jun 2013 17:44:59 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
In-Reply-To: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
Message-ID: <05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>

Dear Nicolai,

Indeed I have used ft_timelockstatistics for minimum norm source data. The trick is to put the source level data into a ERF structure. Determining the neighbors of a source surface with vertices is not trivial. However I used tess_vertconn.m from the BrainStorm toolbox to get the connectivity matrix that tells you who is a neighbor. This you can feed into timelockstats.

Hope that helps,

Stephan

________________________________________________________
Stephan Moratti, PhD

see also: http://web.me.com/smoratti/

Universidad Complutense de Madrid
Facultad de Psicología
Departamento de Psicología Básica I
Campus de Somosaguas
28223 Pozuelo de Alarcón (Madrid)
Spain

and

Center for Biomedical Technology
Laboratory for Cognitive and Computational Neuroscience
Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
Campus Montegancedo
28223 Pozuelo de Alarcón (Madrid)
Spain


email: smoratti at psi.ucm.es
Tel.:    +34 679219982

El 12/06/2013, a las 15:44, Nicolai Mersebak escribió:

> Dear all,
> 
> I have a question concerning the usage of ft_sourcegrandaverage and ft_sourcestatistics. 
> 
> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897 time points. 
> 
> Now I would like to use the cluster-based permutation test on my source reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics don't support source level time courses. E.g when I am using ft_sourcegrandaverage I am getting the following error:
> 
> Error in ft_sourcegrandaverage (line 158)
>   dat(:,i) = tmp(:);
> 
> Looking into the code:
> 
>   for i=1:Nsubject
>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter, varargin{i}));
>     dat(:,i) = tmp(:);
>     tmp = getsubfield(varargin{i}, 'inside');
>     inside(tmp,i) = 1;
>   end
> 
> I see that "tmp" are getting the structure [N_sources x timepoints] from source.avg.pow for one subject, where "dat" requires the structure [N_sources x 1]. 
> 
> I seached the mailing list for similar issues and found this thread:
> 
> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
> 
> Since I am interested in using the temporal dimension in my statistics, I would like to know if it is still not possible to use spatio-temporal source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
> 
> Or if any have succeeded in using the cluster-based permutation test on source level also including the temporal dimension ? 
> 
> Alternative I was thinking that I might could use ft_timelockstatistics, where I substituted the channels with sources, e.g instead of having 64 channels, I would now have 4050 "channels". 
> If so I need to calculate a label structure and an appropriate neighbor structure, which I guess is possible as I have all the 3D coordinates for each source, e.g in leadfield.pos ?
> I know this is a work around solution, but have anyone tried or have any experience using such an approach ? 
> 
> Best,
> 
> Nicolai
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From jan.schoffelen at donders.ru.nl  Wed Jun 12 18:00:46 2013
From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen)
Date: Wed, 12 Jun 2013 18:00:46 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
In-Reply-To: <05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
	<05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>
Message-ID: <683ABC6E-9FC6-420A-9DCF-E54D6FC6A27E@donders.ru.nl>

An alternative would be to interpolate the cortical sheet to a 3D grid (where the grid is defined for each subject based on a warped template grid defined in a standard space), and then do clustering using a regular 3D spatial neighbourhood structure. The rationale being that two vertices on the sheet may appear as disconnected  (e.g. being on two sides of a sulcus) whereas, given the poor spatial resolution, they belong to the same spatial blob.

Best,
Jan-Mathijs

On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:

> Dear Nicolai,
> 
> Indeed I have used ft_timelockstatistics for minimum norm source data. The trick is to put the source level data into a ERF structure. Determining the neighbors of a source surface with vertices is not trivial. However I used tess_vertconn.m from the BrainStorm toolbox to get the connectivity matrix that tells you who is a neighbor. This you can feed into timelockstats.
> 
> Hope that helps,
> 
> Stephan
> 
> ________________________________________________________
> Stephan Moratti, PhD
> 
> see also: http://web.me.com/smoratti/
> 
> Universidad Complutense de Madrid
> Facultad de Psicología
> Departamento de Psicología Básica I
> Campus de Somosaguas
> 28223 Pozuelo de Alarcón (Madrid)
> Spain
> 
> and
> 
> Center for Biomedical Technology
> Laboratory for Cognitive and Computational Neuroscience
> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
> Campus Montegancedo
> 28223 Pozuelo de Alarcón (Madrid)
> Spain
> 
> 
> email: smoratti at psi.ucm.es
> Tel.:    +34 679219982
> 
> El 12/06/2013, a las 15:44, Nicolai Mersebak escribió:
> 
>> Dear all,
>> 
>> I have a question concerning the usage of ft_sourcegrandaverage and ft_sourcestatistics. 
>> 
>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897 time points. 
>> 
>> Now I would like to use the cluster-based permutation test on my source reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics don't support source level time courses. E.g when I am using ft_sourcegrandaverage I am getting the following error:
>> 
>> Error in ft_sourcegrandaverage (line 158)
>>   dat(:,i) = tmp(:);
>> 
>> Looking into the code:
>> 
>>   for i=1:Nsubject
>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter, varargin{i}));
>>     dat(:,i) = tmp(:);
>>     tmp = getsubfield(varargin{i}, 'inside');
>>     inside(tmp,i) = 1;
>>   end
>> 
>> I see that "tmp" are getting the structure [N_sources x timepoints] from source.avg.pow for one subject, where "dat" requires the structure [N_sources x 1]. 
>> 
>> I seached the mailing list for similar issues and found this thread:
>> 
>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>> 
>> Since I am interested in using the temporal dimension in my statistics, I would like to know if it is still not possible to use spatio-temporal source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
>> 
>> Or if any have succeeded in using the cluster-based permutation test on source level also including the temporal dimension ? 
>> 
>> Alternative I was thinking that I might could use ft_timelockstatistics, where I substituted the channels with sources, e.g instead of having 64 channels, I would now have 4050 "channels". 
>> If so I need to calculate a label structure and an appropriate neighbor structure, which I guess is possible as I have all the 3D coordinates for each source, e.g in leadfield.pos ?
>> I know this is a work around solution, but have anyone tried or have any experience using such an approach ? 
>> 
>> Best,
>> 
>> Nicolai
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

Jan-Mathijs Schoffelen, MD PhD 

Donders Institute for Brain, Cognition and Behaviour, 
Centre for Cognitive Neuroimaging,
Radboud University Nijmegen, The Netherlands

Max Planck Institute for Psycholinguistics,
Nijmegen, The Netherlands

J.Schoffelen at donders.ru.nl
Telephone: +31-24-3614793

http://www.hettaligebrein.nl

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From smoratti at psi.ucm.es  Wed Jun 12 18:58:40 2013
From: smoratti at psi.ucm.es (smoratti at psi.ucm.es)
Date: Wed, 12 Jun 2013 18:58:40 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
In-Reply-To: <683ABC6E-9FC6-420A-9DCF-E54D6FC6A27E@donders.ru.nl>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
	<05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>
	<683ABC6E-9FC6-420A-9DCF-E54D6FC6A27E@donders.ru.nl>
Message-ID: <8D369E00-7FF3-4CC7-8B91-A55AD9ECE385@psi.ucm.es>


I think Jan.Mathijs alternative suggestion is quite attractive. With the neighbors on a cortical sheet I also had the problems that sometimes the vertices do not have the same distance and then clustering may be biased to smaller or bigger clusters as the number of neighbors does not guarantee same cluster sizes. With the interpolation onto a 3D grid, you won't have that problem.

best,

Stephan


________________________________________________________
Stephan Moratti, PhD

see also: http://web.me.com/smoratti/

Universidad Complutense de Madrid
Facultad de Psicología
Departamento de Psicología Básica I
Campus de Somosaguas
28223 Pozuelo de Alarcón (Madrid)
Spain

and

Center for Biomedical Technology
Laboratory for Cognitive and Computational Neuroscience
Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
Campus Montegancedo
28223 Pozuelo de Alarcón (Madrid)
Spain


email: smoratti at psi.ucm.es
Tel.:    +34 679219982

El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribió:

> An alternative would be to interpolate the cortical sheet to a 3D grid (where the grid is defined for each subject based on a warped template grid defined in a standard space), and then do clustering using a regular 3D spatial neighbourhood structure. The rationale being that two vertices on the sheet may appear as disconnected  (e.g. being on two sides of a sulcus) whereas, given the poor spatial resolution, they belong to the same spatial blob.
> 
> Best,
> Jan-Mathijs
> 
> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
> 
>> Dear Nicolai,
>> 
>> Indeed I have used ft_timelockstatistics for minimum norm source data. The trick is to put the source level data into a ERF structure. Determining the neighbors of a source surface with vertices is not trivial. However I used tess_vertconn.m from the BrainStorm toolbox to get the connectivity matrix that tells you who is a neighbor. This you can feed into timelockstats.
>> 
>> Hope that helps,
>> 
>> Stephan
>> 
>> ________________________________________________________
>> Stephan Moratti, PhD
>> 
>> see also: http://web.me.com/smoratti/
>> 
>> Universidad Complutense de Madrid
>> Facultad de Psicología
>> Departamento de Psicología Básica I
>> Campus de Somosaguas
>> 28223 Pozuelo de Alarcón (Madrid)
>> Spain
>> 
>> and
>> 
>> Center for Biomedical Technology
>> Laboratory for Cognitive and Computational Neuroscience
>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>> Campus Montegancedo
>> 28223 Pozuelo de Alarcón (Madrid)
>> Spain
>> 
>> 
>> email: smoratti at psi.ucm.es
>> Tel.:    +34 679219982
>> 
>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribió:
>> 
>>> Dear all,
>>> 
>>> I have a question concerning the usage of ft_sourcegrandaverage and ft_sourcestatistics. 
>>> 
>>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897 time points. 
>>> 
>>> Now I would like to use the cluster-based permutation test on my source reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics don't support source level time courses. E.g when I am using ft_sourcegrandaverage I am getting the following error:
>>> 
>>> Error in ft_sourcegrandaverage (line 158)
>>>   dat(:,i) = tmp(:);
>>> 
>>> Looking into the code:
>>> 
>>>   for i=1:Nsubject
>>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter, varargin{i}));
>>>     dat(:,i) = tmp(:);
>>>     tmp = getsubfield(varargin{i}, 'inside');
>>>     inside(tmp,i) = 1;
>>>   end
>>> 
>>> I see that "tmp" are getting the structure [N_sources x timepoints] from source.avg.pow for one subject, where "dat" requires the structure [N_sources x 1]. 
>>> 
>>> I seached the mailing list for similar issues and found this thread:
>>> 
>>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>>> 
>>> Since I am interested in using the temporal dimension in my statistics, I would like to know if it is still not possible to use spatio-temporal source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
>>> 
>>> Or if any have succeeded in using the cluster-based permutation test on source level also including the temporal dimension ? 
>>> 
>>> Alternative I was thinking that I might could use ft_timelockstatistics, where I substituted the channels with sources, e.g instead of having 64 channels, I would now have 4050 "channels". 
>>> If so I need to calculate a label structure and an appropriate neighbor structure, which I guess is possible as I have all the 3D coordinates for each source, e.g in leadfield.pos ?
>>> I know this is a work around solution, but have anyone tried or have any experience using such an approach ? 
>>> 
>>> Best,
>>> 
>>> Nicolai
>>> 
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> Jan-Mathijs Schoffelen, MD PhD 
> 
> Donders Institute for Brain, Cognition and Behaviour, 
> Centre for Cognitive Neuroimaging,
> Radboud University Nijmegen, The Netherlands
> 
> Max Planck Institute for Psycholinguistics,
> Nijmegen, The Netherlands
> 
> J.Schoffelen at donders.ru.nl
> Telephone: +31-24-3614793
> 
> http://www.hettaligebrein.nl
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From mengtongxiao at gmail.com  Thu Jun 13 10:10:14 2013
From: mengtongxiao at gmail.com (=?GB2312?B?s8LRqQ==?=)
Date: Thu, 13 Jun 2013 16:10:14 +0800
Subject: [FieldTrip] PDC
Message-ID: <CADiddyUvconnj1o5n+=RYKyDE0LsFsH7_Eg0re0+a5D-2oz9Xw@mail.gmail.com>

Dear  all

I want to use compute  PDC,
I want to  Konw   when I got the chan*chan*freq，
Dose the information flow from row (chan) to column(chan)?

best,
xiao

   
   
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From jan.schoffelen at donders.ru.nl  Thu Jun 13 10:20:48 2013
From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen)
Date: Thu, 13 Jun 2013 10:20:48 +0200
Subject: [FieldTrip] PDC
In-Reply-To: <CADiddyUvconnj1o5n+=RYKyDE0LsFsH7_Eg0re0+a5D-2oz9Xw@mail.gmail.com>
References: <CADiddyUvconnj1o5n+=RYKyDE0LsFsH7_Eg0re0+a5D-2oz9Xw@mail.gmail.com>
Message-ID: <756060F3-17D2-420B-B55F-FFE7671B067B@donders.ru.nl>

Hi Xiao,

this would be from row to column.

Best,
Jan-Mathijs

On Jun 13, 2013, at 10:10 AM, 陈雪 wrote:

> Dear  all
> 
> I want to use compute  PDC,
> I want to  Konw   when I got the chan*chan*freq，
> Dose the information flow from row (chan) to column(chan)?
> 
> best,
> xiao 
> 	
> 	
> 	
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

Jan-Mathijs Schoffelen, MD PhD 

Donders Institute for Brain, Cognition and Behaviour, 
Centre for Cognitive Neuroimaging,
Radboud University Nijmegen, The Netherlands

Max Planck Institute for Psycholinguistics,
Nijmegen, The Netherlands

J.Schoffelen at donders.ru.nl
Telephone: +31-24-3614793

http://www.hettaligebrein.nl

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From explena at gmail.com  Thu Jun 13 11:15:11 2013
From: explena at gmail.com (Shen-Mou Hsu)
Date: Thu, 13 Jun 2013 17:15:11 +0800
Subject: [FieldTrip] ROC_based permutation test
In-Reply-To: <CABPNLUpB9DHCQCszf7WuujVgKT4g9Dp3GPNd19-O65b160y8NQ@mail.gmail.com>
References: <CAFg6g2eKEb-EmYa=BkWTwUVx20+oP92rs6u06w9m+Ehz5ni8qg@mail.gmail.com>
	<CABPNLUpB9DHCQCszf7WuujVgKT4g9Dp3GPNd19-O65b160y8NQ@mail.gmail.com>
Message-ID: <CAFg6g2ewK2N54R0coEbShh1AxUrCkcL6gAgnEskEA5_sAa=h-A@mail.gmail.com>

Dear Eelke,

Many thanks for your helpful and detailed answers. I think that there is an
error in the documentation about the configuration option for performing
ROC analysis. The correct one should be cfg.statistic = 'ft_statfun_roc'.
Otherwise, it will call the matlab built-in ROC function.

Meanwhile, just to clarify my concept about the ROC_based permutation
tests. In the initial stage, does the test calculate whether for every
sample, the area under ROC curve is significant from 0.5. In this sense,
should I specify cfg.clusteralpha = 0.5?

Best regards,

Shen-Mou Hsu


On Tue, Jun 11, 2013 at 4:18 PM, Eelke Spaak <eelke.spaak at donders.ru.nl>wrote:

> Dear Shen-Mou Hsu,
>
> With regards to your first question, I do not know the answer, so
> someone else might help you there.
>
> In response to your second question, regarding the error "could not
> determine the parametric critical value for clustering", this is
> caused by the value of cfg.clusterthreshold used. The default value
> there is 'parametric', meaning that the statistics routine will ask
> your 'statfun' to compute a parametric threshold for considering a
> (time/frequency/channel)-voxel a cluster-member candidate. This can be
> done by e.g. depsamplesT or indepsamplesT, as it is possible to
> analytically compute a T value corresponding to p < 0.05. However, in
> the case of the ROC statistic, no such parametric estimate can be
> computed (or perhaps it can be in some way, I don't know, but at least
> I know the FT implementation does not).
>
> Fortunately, the statistics routines also allow you to use a
> nonparametric threshold for cluster-member candidates, based on the
> generated distribution of the test statistic under the null
> hypothesis. To use this, simply specify cfg.clusterthreshold =
> 'nonparametric_individual' or cfg.clusterthreshold =
> 'nonparametric_common'. The difference between the two is that the
> former computes a threshold per voxel, and the latter uses the same
> threshold for all voxels. Which one is appropriate for you I don't
> know. (Good reasons for using 'nonparametric_individual' might be a
> strong variation of your test statistic with frequency. I know for a
> fact this is the case with certain quantifications of phase-amplitude
> coupling; these show much higher values in the low frequencies even
> when computed on noise.)
>
> Hope this helps.
>
> Best,
> Eelke
>
> On 11 June 2013 09:48, Shen-Mou Hsu <explena at gmail.com> wrote:
> > Dear all,
> >
> > I was trying to perform signle-trial ROC-based permutation tests using
> the
> > statfun_roc. However I encountered two questions and wondered if anyone
> > could kindly shed some light on the issues. First, is it necessary to
> > perform baseline normalization for each trial before the tests? Second,
> an
> > error message returned stating "Error using roc. Too many input
> arguments.
> > Error using ft_statistics_montecarlo (line 223) could not determine the
> > parametric critical value for clustering", after running the following
> > script:
> >
> > load (['t_RF_EpoRejDePow']); load (['t_RN_EpoRejDePow']);
> >
> > cfg = [];
> > cfg.channel     = 'MEG';
> > cfg.latency     = [-0.35 0.55];
> > cfg.frequency   = [8 12];
> > cfg.parameter   = 'powspctrm';
> > cfg.method      = 'montecarlo';
> > cfg.statistic   = 'roc';
> > cfg.alpha       = 0.025;
> > cfg.tail = 0;
> > cfg.correctm    = 'cluster';
> > cfg.clusteralpha = 0.05;
> > % cfg.correcttail = 'prob';
> > cfg.clustertail = 0;
> > cfg.numrandomization = 1000;
> > cfg.minnbchan        = 2;
> > cfg_neighb.method    = 'distance';
> > cfg.neighbours       = ft_prepare_neighbours(cfg_neighb,
> t_RN_EpoRejDePow);
> > cfg.logtransform = 'yes';
> >
> > design = [1*ones(1,size(t_RF_EpoRejDePow.powspctrm,1))
> > 2*ones(1,size(t_RN_EpoRejDePow.powspctrm,1))]; % the first dimension of
> > these variable is the trial number.
> > cfg.design  = design;
> >
> > P_ROC_t_RFvsRN =
> ft_freqstatistics(cfg,t_RF_EpoRejDePow,t_RN_EpoRejDePow);
> >
> >
> > Any help is greatly appreciated.
> >
> > Best regards,
> >
> > Shen-Mou Hsu
> >
> >
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From nicolai at mersebak.dk  Thu Jun 13 12:04:34 2013
From: nicolai at mersebak.dk (Nicolai Mersebak)
Date: Thu, 13 Jun 2013 12:04:34 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
In-Reply-To: <8D369E00-7FF3-4CC7-8B91-A55AD9ECE385@psi.ucm.es>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
	<05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>
	<683ABC6E-9FC6-420A-9DCF-E54D6FC6A27E@donders.ru.nl>
	<8D369E00-7FF3-4CC7-8B91-A55AD9ECE385@psi.ucm.es>
Message-ID: <6F3697BB-194F-422F-A1BF-EBBB132F805B@mersebak.dk>

Thanks to all of you for your comments and ideas - they are very helpful! 

I ( off course :) ) have some follow up questions. 

I have created an ERP structure for my MNE source, so the only think which I need and that is not straight forward is the neighbour structure. 

I am using the standard bem template (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model and use the following code to get a grid for all subjects as I don't have any subject specific information regarding the anatomy. 

cfg = [];
cfg.grid.xgrid  = -100:10:100;
cfg.grid.ygrid  = -100:10:100;
cfg.grid.zgrid  = -100:10:100;
cfg.grid.tight  = 'yes';
cfg.grid.unit   = hdm.unit; % unit: mm
cfg.vol        = hdm;
grid  = ft_prepare_sourcemodel(cfg);


@Jan-Mathijs and Stephan: I guess making a subject specific grid based on a warped template requires anatomic information for each subject, e.g. a MRI image like this tutorial shows:
http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B

The final grid output in the tutorial - does it have this 3D grid which can be used as a neighbour structure ? 

I am not sure how to go from my cortical sheet [vertices x coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
 
A second thing I would like to know is, if any of you have tried to use an atlas (e.g ALL template atlas) where the regions now are channels in the permutation test? Going from source points to atlas regions can be done through ft_sourcestatistics, but I am still interested in keeping the temporal dimension. The reason to use atlas regions instead of source points is to decrease the computation time. 

Best,

Nicolai


Den 12/06/2013 kl. 18.58 skrev "smoratti at psi.ucm.es" <smoratti at psi.ucm.es>:

> 
> I think Jan.Mathijs alternative suggestion is quite attractive. With the neighbors on a cortical sheet I also had the problems that sometimes the vertices do not have the same distance and then clustering may be biased to smaller or bigger clusters as the number of neighbors does not guarantee same cluster sizes. With the interpolation onto a 3D grid, you won't have that problem.
> 
> best,
> 
> Stephan
> 
> 
> ________________________________________________________
> Stephan Moratti, PhD
> 
> see also: http://web.me.com/smoratti/
> 
> Universidad Complutense de Madrid
> Facultad de Psicología
> Departamento de Psicología Básica I
> Campus de Somosaguas
> 28223 Pozuelo de Alarcón (Madrid)
> Spain
> 
> and
> 
> Center for Biomedical Technology
> Laboratory for Cognitive and Computational Neuroscience
> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
> Campus Montegancedo
> 28223 Pozuelo de Alarcón (Madrid)
> Spain
> 
> 
> email: smoratti at psi.ucm.es
> Tel.:    +34 679219982
> 
> El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribió:
> 
>> An alternative would be to interpolate the cortical sheet to a 3D grid (where the grid is defined for each subject based on a warped template grid defined in a standard space), and then do clustering using a regular 3D spatial neighbourhood structure. The rationale being that two vertices on the sheet may appear as disconnected  (e.g. being on two sides of a sulcus) whereas, given the poor spatial resolution, they belong to the same spatial blob.
>> 
>> Best,
>> Jan-Mathijs
>> 
>> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
>> 
>>> Dear Nicolai,
>>> 
>>> Indeed I have used ft_timelockstatistics for minimum norm source data. The trick is to put the source level data into a ERF structure. Determining the neighbors of a source surface with vertices is not trivial. However I used tess_vertconn.m from the BrainStorm toolbox to get the connectivity matrix that tells you who is a neighbor. This you can feed into timelockstats.
>>> 
>>> Hope that helps,
>>> 
>>> Stephan
>>> 
>>> ________________________________________________________
>>> Stephan Moratti, PhD
>>> 
>>> see also: http://web.me.com/smoratti/
>>> 
>>> Universidad Complutense de Madrid
>>> Facultad de Psicología
>>> Departamento de Psicología Básica I
>>> Campus de Somosaguas
>>> 28223 Pozuelo de Alarcón (Madrid)
>>> Spain
>>> 
>>> and
>>> 
>>> Center for Biomedical Technology
>>> Laboratory for Cognitive and Computational Neuroscience
>>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>>> Campus Montegancedo
>>> 28223 Pozuelo de Alarcón (Madrid)
>>> Spain
>>> 
>>> 
>>> email: smoratti at psi.ucm.es
>>> Tel.:    +34 679219982
>>> 
>>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribió:
>>> 
>>>> Dear all,
>>>> 
>>>> I have a question concerning the usage of ft_sourcegrandaverage and ft_sourcestatistics. 
>>>> 
>>>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897 time points. 
>>>> 
>>>> Now I would like to use the cluster-based permutation test on my source reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics don't support source level time courses. E.g when I am using ft_sourcegrandaverage I am getting the following error:
>>>> 
>>>> Error in ft_sourcegrandaverage (line 158)
>>>>   dat(:,i) = tmp(:);
>>>> 
>>>> Looking into the code:
>>>> 
>>>>   for i=1:Nsubject
>>>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter, varargin{i}));
>>>>     dat(:,i) = tmp(:);
>>>>     tmp = getsubfield(varargin{i}, 'inside');
>>>>     inside(tmp,i) = 1;
>>>>   end
>>>> 
>>>> I see that "tmp" are getting the structure [N_sources x timepoints] from source.avg.pow for one subject, where "dat" requires the structure [N_sources x 1]. 
>>>> 
>>>> I seached the mailing list for similar issues and found this thread:
>>>> 
>>>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>>>> 
>>>> Since I am interested in using the temporal dimension in my statistics, I would like to know if it is still not possible to use spatio-temporal source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
>>>> 
>>>> Or if any have succeeded in using the cluster-based permutation test on source level also including the temporal dimension ? 
>>>> 
>>>> Alternative I was thinking that I might could use ft_timelockstatistics, where I substituted the channels with sources, e.g instead of having 64 channels, I would now have 4050 "channels". 
>>>> If so I need to calculate a label structure and an appropriate neighbor structure, which I guess is possible as I have all the 3D coordinates for each source, e.g in leadfield.pos ?
>>>> I know this is a work around solution, but have anyone tried or have any experience using such an approach ? 
>>>> 
>>>> Best,
>>>> 
>>>> Nicolai
>>>> 
>>>> _______________________________________________
>>>> fieldtrip mailing list
>>>> fieldtrip at donders.ru.nl
>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>> 
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> 
>> Jan-Mathijs Schoffelen, MD PhD 
>> 
>> Donders Institute for Brain, Cognition and Behaviour, 
>> Centre for Cognitive Neuroimaging,
>> Radboud University Nijmegen, The Netherlands
>> 
>> Max Planck Institute for Psycholinguistics,
>> Nijmegen, The Netherlands
>> 
>> J.Schoffelen at donders.ru.nl
>> Telephone: +31-24-3614793
>> 
>> http://www.hettaligebrein.nl
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From smoratti at psi.ucm.es  Thu Jun 13 15:50:30 2013
From: smoratti at psi.ucm.es (smoratti at psi.ucm.es)
Date: Thu, 13 Jun 2013 15:50:30 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
In-Reply-To: <6F3697BB-194F-422F-A1BF-EBBB132F805B@mersebak.dk>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
	<05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>
	<683ABC6E-9FC6-420A-9DCF-E54D6FC6A27E@donders.ru.nl>
	<8D369E00-7FF3-4CC7-8B91-A55AD9ECE385@psi.ucm.es>
	<6F3697BB-194F-422F-A1BF-EBBB132F805B@mersebak.dk>
Message-ID: <4755A6E7-44B5-4E98-B536-A19F544ED284@psi.ucm.es>

Dear Nikolai,

In ft_sourceplot there is the possibility of projecting grid data to surface data. However, I am not sure if the other way round is implemented in field trip.

With respect to the other (maybe less accurate solution) of providing a neighbor matrix of the vertices of your brain surface:

if you do " channeigbststructmat = your_neighbor_matrix" in clusterstat.m should work.

Best,

Stephan



________________________________________________________
Stephan Moratti, PhD

see also: http://web.me.com/smoratti/

Universidad Complutense de Madrid
Facultad de Psicología
Departamento de Psicología Básica I
Campus de Somosaguas
28223 Pozuelo de Alarcón (Madrid)
Spain

and

Center for Biomedical Technology
Laboratory for Cognitive and Computational Neuroscience
Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
Campus Montegancedo
28223 Pozuelo de Alarcón (Madrid)
Spain


email: smoratti at psi.ucm.es
Tel.:    +34 679219982

El 13/06/2013, a las 12:04, Nicolai Mersebak escribió:

> Thanks to all of you for your comments and ideas - they are very helpful! 
> 
> I ( off course :) ) have some follow up questions. 
> 
> I have created an ERP structure for my MNE source, so the only think which I need and that is not straight forward is the neighbour structure. 
> 
> I am using the standard bem template (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model and use the following code to get a grid for all subjects as I don't have any subject specific information regarding the anatomy. 
> 
> cfg = [];
> cfg.grid.xgrid  = -100:10:100;
> cfg.grid.ygrid  = -100:10:100;
> cfg.grid.zgrid  = -100:10:100;
> cfg.grid.tight  = 'yes';
> cfg.grid.unit   = hdm.unit; % unit: mm
> cfg.vol        = hdm;
> grid  = ft_prepare_sourcemodel(cfg);
> 
> 
> @Jan-Mathijs and Stephan: I guess making a subject specific grid based on a warped template requires anatomic information for each subject, e.g. a MRI image like this tutorial shows:
> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
> 
> The final grid output in the tutorial - does it have this 3D grid which can be used as a neighbour structure ? 
> 
> I am not sure how to go from my cortical sheet [vertices x coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
>  
> A second thing I would like to know is, if any of you have tried to use an atlas (e.g ALL template atlas) where the regions now are channels in the permutation test? Going from source points to atlas regions can be done through ft_sourcestatistics, but I am still interested in keeping the temporal dimension. The reason to use atlas regions instead of source points is to decrease the computation time. 
> 
> Best,
> 
> Nicolai
> 
> 
> Den 12/06/2013 kl. 18.58 skrev "smoratti at psi.ucm.es" <smoratti at psi.ucm.es>:
> 
>> 
>> I think Jan.Mathijs alternative suggestion is quite attractive. With the neighbors on a cortical sheet I also had the problems that sometimes the vertices do not have the same distance and then clustering may be biased to smaller or bigger clusters as the number of neighbors does not guarantee same cluster sizes. With the interpolation onto a 3D grid, you won't have that problem.
>> 
>> best,
>> 
>> Stephan
>> 
>> 
>> ________________________________________________________
>> Stephan Moratti, PhD
>> 
>> see also: http://web.me.com/smoratti/
>> 
>> Universidad Complutense de Madrid
>> Facultad de Psicología
>> Departamento de Psicología Básica I
>> Campus de Somosaguas
>> 28223 Pozuelo de Alarcón (Madrid)
>> Spain
>> 
>> and
>> 
>> Center for Biomedical Technology
>> Laboratory for Cognitive and Computational Neuroscience
>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>> Campus Montegancedo
>> 28223 Pozuelo de Alarcón (Madrid)
>> Spain
>> 
>> 
>> email: smoratti at psi.ucm.es
>> Tel.:    +34 679219982
>> 
>> El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribió:
>> 
>>> An alternative would be to interpolate the cortical sheet to a 3D grid (where the grid is defined for each subject based on a warped template grid defined in a standard space), and then do clustering using a regular 3D spatial neighbourhood structure. The rationale being that two vertices on the sheet may appear as disconnected  (e.g. being on two sides of a sulcus) whereas, given the poor spatial resolution, they belong to the same spatial blob.
>>> 
>>> Best,
>>> Jan-Mathijs
>>> 
>>> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
>>> 
>>>> Dear Nicolai,
>>>> 
>>>> Indeed I have used ft_timelockstatistics for minimum norm source data. The trick is to put the source level data into a ERF structure. Determining the neighbors of a source surface with vertices is not trivial. However I used tess_vertconn.m from the BrainStorm toolbox to get the connectivity matrix that tells you who is a neighbor. This you can feed into timelockstats.
>>>> 
>>>> Hope that helps,
>>>> 
>>>> Stephan
>>>> 
>>>> ________________________________________________________
>>>> Stephan Moratti, PhD
>>>> 
>>>> see also: http://web.me.com/smoratti/
>>>> 
>>>> Universidad Complutense de Madrid
>>>> Facultad de Psicología
>>>> Departamento de Psicología Básica I
>>>> Campus de Somosaguas
>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>> Spain
>>>> 
>>>> and
>>>> 
>>>> Center for Biomedical Technology
>>>> Laboratory for Cognitive and Computational Neuroscience
>>>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>>>> Campus Montegancedo
>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>> Spain
>>>> 
>>>> 
>>>> email: smoratti at psi.ucm.es
>>>> Tel.:    +34 679219982
>>>> 
>>>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribió:
>>>> 
>>>>> Dear all,
>>>>> 
>>>>> I have a question concerning the usage of ft_sourcegrandaverage and ft_sourcestatistics. 
>>>>> 
>>>>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897 time points. 
>>>>> 
>>>>> Now I would like to use the cluster-based permutation test on my source reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics don't support source level time courses. E.g when I am using ft_sourcegrandaverage I am getting the following error:
>>>>> 
>>>>> Error in ft_sourcegrandaverage (line 158)
>>>>>   dat(:,i) = tmp(:);
>>>>> 
>>>>> Looking into the code:
>>>>> 
>>>>>   for i=1:Nsubject
>>>>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter, varargin{i}));
>>>>>     dat(:,i) = tmp(:);
>>>>>     tmp = getsubfield(varargin{i}, 'inside');
>>>>>     inside(tmp,i) = 1;
>>>>>   end
>>>>> 
>>>>> I see that "tmp" are getting the structure [N_sources x timepoints] from source.avg.pow for one subject, where "dat" requires the structure [N_sources x 1]. 
>>>>> 
>>>>> I seached the mailing list for similar issues and found this thread:
>>>>> 
>>>>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>>>>> 
>>>>> Since I am interested in using the temporal dimension in my statistics, I would like to know if it is still not possible to use spatio-temporal source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
>>>>> 
>>>>> Or if any have succeeded in using the cluster-based permutation test on source level also including the temporal dimension ? 
>>>>> 
>>>>> Alternative I was thinking that I might could use ft_timelockstatistics, where I substituted the channels with sources, e.g instead of having 64 channels, I would now have 4050 "channels". 
>>>>> If so I need to calculate a label structure and an appropriate neighbor structure, which I guess is possible as I have all the 3D coordinates for each source, e.g in leadfield.pos ?
>>>>> I know this is a work around solution, but have anyone tried or have any experience using such an approach ? 
>>>>> 
>>>>> Best,
>>>>> 
>>>>> Nicolai
>>>>> 
>>>>> _______________________________________________
>>>>> fieldtrip mailing list
>>>>> fieldtrip at donders.ru.nl
>>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>> 
>>>> _______________________________________________
>>>> fieldtrip mailing list
>>>> fieldtrip at donders.ru.nl
>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>> 
>>> Jan-Mathijs Schoffelen, MD PhD 
>>> 
>>> Donders Institute for Brain, Cognition and Behaviour, 
>>> Centre for Cognitive Neuroimaging,
>>> Radboud University Nijmegen, The Netherlands
>>> 
>>> Max Planck Institute for Psycholinguistics,
>>> Nijmegen, The Netherlands
>>> 
>>> J.Schoffelen at donders.ru.nl
>>> Telephone: +31-24-3614793
>>> 
>>> http://www.hettaligebrein.nl
>>> 
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From jan.schoffelen at donders.ru.nl  Thu Jun 13 15:58:47 2013
From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen)
Date: Thu, 13 Jun 2013 15:58:47 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
In-Reply-To: <4755A6E7-44B5-4E98-B536-A19F544ED284@psi.ucm.es>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
	<05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>
	<683ABC6E-9FC6-420A-9DCF-E54D6FC6A27E@donders.ru.nl>
	<8D369E00-7FF3-4CC7-8B91-A55AD9ECE385@psi.ucm.es>
	<6F3697BB-194F-422F-A1BF-EBBB132F805B@mersebak.dk>
	<4755A6E7-44B5-4E98-B536-A19F544ED284@psi.ucm.es>
Message-ID: <944F6EF6-C03A-46F4-BFF4-3D9EC324E602@donders.ru.nl>

Hi all,

ft_sourceinterpolate can interpolate from between arbitrary point clouds, so also between a set of points defined on the cortical sheet, and a more or less regular 3D grid.

JM

On Jun 13, 2013, at 3:50 PM, smoratti at psi.ucm.es wrote:

> Dear Nikolai,
> 
> In ft_sourceplot there is the possibility of projecting grid data to surface data. However, I am not sure if the other way round is implemented in field trip.
> 
> With respect to the other (maybe less accurate solution) of providing a neighbor matrix of the vertices of your brain surface:
> 
> if you do " channeigbststructmat = your_neighbor_matrix" in clusterstat.m should work.
> 
> Best,
> 
> Stephan
> 
> 
> 
> ________________________________________________________
> Stephan Moratti, PhD
> 
> see also: http://web.me.com/smoratti/
> 
> Universidad Complutense de Madrid
> Facultad de Psicología
> Departamento de Psicología Básica I
> Campus de Somosaguas
> 28223 Pozuelo de Alarcón (Madrid)
> Spain
> 
> and
> 
> Center for Biomedical Technology
> Laboratory for Cognitive and Computational Neuroscience
> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
> Campus Montegancedo
> 28223 Pozuelo de Alarcón (Madrid)
> Spain
> 
> 
> email: smoratti at psi.ucm.es
> Tel.:    +34 679219982
> 
> El 13/06/2013, a las 12:04, Nicolai Mersebak escribió:
> 
>> Thanks to all of you for your comments and ideas - they are very helpful! 
>> 
>> I ( off course :) ) have some follow up questions. 
>> 
>> I have created an ERP structure for my MNE source, so the only think which I need and that is not straight forward is the neighbour structure. 
>> 
>> I am using the standard bem template (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model and use the following code to get a grid for all subjects as I don't have any subject specific information regarding the anatomy. 
>> 
>> cfg = [];
>> cfg.grid.xgrid  = -100:10:100;
>> cfg.grid.ygrid  = -100:10:100;
>> cfg.grid.zgrid  = -100:10:100;
>> cfg.grid.tight  = 'yes';
>> cfg.grid.unit   = hdm.unit; % unit: mm
>> cfg.vol        = hdm;
>> grid  = ft_prepare_sourcemodel(cfg);
>> 
>> 
>> @Jan-Mathijs and Stephan: I guess making a subject specific grid based on a warped template requires anatomic information for each subject, e.g. a MRI image like this tutorial shows:
>> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
>> 
>> The final grid output in the tutorial - does it have this 3D grid which can be used as a neighbour structure ? 
>> 
>> I am not sure how to go from my cortical sheet [vertices x coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
>>  
>> A second thing I would like to know is, if any of you have tried to use an atlas (e.g ALL template atlas) where the regions now are channels in the permutation test? Going from source points to atlas regions can be done through ft_sourcestatistics, but I am still interested in keeping the temporal dimension. The reason to use atlas regions instead of source points is to decrease the computation time. 
>> 
>> Best,
>> 
>> Nicolai
>> 
>> 
>> Den 12/06/2013 kl. 18.58 skrev "smoratti at psi.ucm.es" <smoratti at psi.ucm.es>:
>> 
>>> 
>>> I think Jan.Mathijs alternative suggestion is quite attractive. With the neighbors on a cortical sheet I also had the problems that sometimes the vertices do not have the same distance and then clustering may be biased to smaller or bigger clusters as the number of neighbors does not guarantee same cluster sizes. With the interpolation onto a 3D grid, you won't have that problem.
>>> 
>>> best,
>>> 
>>> Stephan
>>> 
>>> 
>>> ________________________________________________________
>>> Stephan Moratti, PhD
>>> 
>>> see also: http://web.me.com/smoratti/
>>> 
>>> Universidad Complutense de Madrid
>>> Facultad de Psicología
>>> Departamento de Psicología Básica I
>>> Campus de Somosaguas
>>> 28223 Pozuelo de Alarcón (Madrid)
>>> Spain
>>> 
>>> and
>>> 
>>> Center for Biomedical Technology
>>> Laboratory for Cognitive and Computational Neuroscience
>>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>>> Campus Montegancedo
>>> 28223 Pozuelo de Alarcón (Madrid)
>>> Spain
>>> 
>>> 
>>> email: smoratti at psi.ucm.es
>>> Tel.:    +34 679219982
>>> 
>>> El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribió:
>>> 
>>>> An alternative would be to interpolate the cortical sheet to a 3D grid (where the grid is defined for each subject based on a warped template grid defined in a standard space), and then do clustering using a regular 3D spatial neighbourhood structure. The rationale being that two vertices on the sheet may appear as disconnected  (e.g. being on two sides of a sulcus) whereas, given the poor spatial resolution, they belong to the same spatial blob.
>>>> 
>>>> Best,
>>>> Jan-Mathijs
>>>> 
>>>> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
>>>> 
>>>>> Dear Nicolai,
>>>>> 
>>>>> Indeed I have used ft_timelockstatistics for minimum norm source data. The trick is to put the source level data into a ERF structure. Determining the neighbors of a source surface with vertices is not trivial. However I used tess_vertconn.m from the BrainStorm toolbox to get the connectivity matrix that tells you who is a neighbor. This you can feed into timelockstats.
>>>>> 
>>>>> Hope that helps,
>>>>> 
>>>>> Stephan
>>>>> 
>>>>> ________________________________________________________
>>>>> Stephan Moratti, PhD
>>>>> 
>>>>> see also: http://web.me.com/smoratti/
>>>>> 
>>>>> Universidad Complutense de Madrid
>>>>> Facultad de Psicología
>>>>> Departamento de Psicología Básica I
>>>>> Campus de Somosaguas
>>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>>> Spain
>>>>> 
>>>>> and
>>>>> 
>>>>> Center for Biomedical Technology
>>>>> Laboratory for Cognitive and Computational Neuroscience
>>>>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>>>>> Campus Montegancedo
>>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>>> Spain
>>>>> 
>>>>> 
>>>>> email: smoratti at psi.ucm.es
>>>>> Tel.:    +34 679219982
>>>>> 
>>>>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribió:
>>>>> 
>>>>>> Dear all,
>>>>>> 
>>>>>> I have a question concerning the usage of ft_sourcegrandaverage and ft_sourcestatistics. 
>>>>>> 
>>>>>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897 time points. 
>>>>>> 
>>>>>> Now I would like to use the cluster-based permutation test on my source reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics don't support source level time courses. E.g when I am using ft_sourcegrandaverage I am getting the following error:
>>>>>> 
>>>>>> Error in ft_sourcegrandaverage (line 158)
>>>>>>   dat(:,i) = tmp(:);
>>>>>> 
>>>>>> Looking into the code:
>>>>>> 
>>>>>>   for i=1:Nsubject
>>>>>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter, varargin{i}));
>>>>>>     dat(:,i) = tmp(:);
>>>>>>     tmp = getsubfield(varargin{i}, 'inside');
>>>>>>     inside(tmp,i) = 1;
>>>>>>   end
>>>>>> 
>>>>>> I see that "tmp" are getting the structure [N_sources x timepoints] from source.avg.pow for one subject, where "dat" requires the structure [N_sources x 1]. 
>>>>>> 
>>>>>> I seached the mailing list for similar issues and found this thread:
>>>>>> 
>>>>>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>>>>>> 
>>>>>> Since I am interested in using the temporal dimension in my statistics, I would like to know if it is still not possible to use spatio-temporal source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
>>>>>> 
>>>>>> Or if any have succeeded in using the cluster-based permutation test on source level also including the temporal dimension ? 
>>>>>> 
>>>>>> Alternative I was thinking that I might could use ft_timelockstatistics, where I substituted the channels with sources, e.g instead of having 64 channels, I would now have 4050 "channels". 
>>>>>> If so I need to calculate a label structure and an appropriate neighbor structure, which I guess is possible as I have all the 3D coordinates for each source, e.g in leadfield.pos ?
>>>>>> I know this is a work around solution, but have anyone tried or have any experience using such an approach ? 
>>>>>> 
>>>>>> Best,
>>>>>> 
>>>>>> Nicolai
>>>>>> 
>>>>>> _______________________________________________
>>>>>> fieldtrip mailing list
>>>>>> fieldtrip at donders.ru.nl
>>>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>> 
>>>>> _______________________________________________
>>>>> fieldtrip mailing list
>>>>> fieldtrip at donders.ru.nl
>>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>> 
>>>> Jan-Mathijs Schoffelen, MD PhD 
>>>> 
>>>> Donders Institute for Brain, Cognition and Behaviour, 
>>>> Centre for Cognitive Neuroimaging,
>>>> Radboud University Nijmegen, The Netherlands
>>>> 
>>>> Max Planck Institute for Psycholinguistics,
>>>> Nijmegen, The Netherlands
>>>> 
>>>> J.Schoffelen at donders.ru.nl
>>>> Telephone: +31-24-3614793
>>>> 
>>>> http://www.hettaligebrein.nl
>>>> 
>>>> _______________________________________________
>>>> fieldtrip mailing list
>>>> fieldtrip at donders.ru.nl
>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>> 
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

Jan-Mathijs Schoffelen, MD PhD 

Donders Institute for Brain, Cognition and Behaviour, 
Centre for Cognitive Neuroimaging,
Radboud University Nijmegen, The Netherlands

Max Planck Institute for Psycholinguistics,
Nijmegen, The Netherlands

J.Schoffelen at donders.ru.nl
Telephone: +31-24-3614793

http://www.hettaligebrein.nl

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From jan.schoffelen at donders.ru.nl  Thu Jun 13 16:12:26 2013
From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen)
Date: Thu, 13 Jun 2013 16:12:26 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
In-Reply-To: <944F6EF6-C03A-46F4-BFF4-3D9EC324E602@donders.ru.nl>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
	<05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>
	<683ABC6E-9FC6-420A-9DCF-E54D6FC6A27E@donders.ru.nl>
	<8D369E00-7FF3-4CC7-8B91-A55AD9ECE385@psi.ucm.es>
	<6F3697BB-194F-422F-A1BF-EBBB132F805B@mersebak.dk>
	<4755A6E7-44B5-4E98-B536-A19F544ED284@psi.ucm.es>
	<944F6EF6-C03A-46F4-BFF4-3D9EC324E602@donders.ru.nl>
Message-ID: <C58208AA-1DC3-40CD-9E55-F1B3ADD3CCD4@donders.ru.nl>

Hi all,

As a follow up to my previous message: it is intended in the future to remove the functionality in ft_sourceplot, doing the interpolation on the fly when cfg.method='surface' but when the input contains data defined on a 3D grid, and to request the user to go through ft_sourceinterpolate before visualization. Stay tuned...

JM

On Jun 13, 2013, at 3:58 PM, jan-mathijs schoffelen wrote:

> Hi all,
> 
> ft_sourceinterpolate can interpolate from between arbitrary point clouds, so also between a set of points defined on the cortical sheet, and a more or less regular 3D grid.
> 
> JM
> 
> On Jun 13, 2013, at 3:50 PM, smoratti at psi.ucm.es wrote:
> 
>> Dear Nikolai,
>> 
>> In ft_sourceplot there is the possibility of projecting grid data to surface data. However, I am not sure if the other way round is implemented in field trip.
>> 
>> With respect to the other (maybe less accurate solution) of providing a neighbor matrix of the vertices of your brain surface:
>> 
>> if you do " channeigbststructmat = your_neighbor_matrix" in clusterstat.m should work.
>> 
>> Best,
>> 
>> Stephan
>> 
>> 
>> 
>> ________________________________________________________
>> Stephan Moratti, PhD
>> 
>> see also: http://web.me.com/smoratti/
>> 
>> Universidad Complutense de Madrid
>> Facultad de Psicología
>> Departamento de Psicología Básica I
>> Campus de Somosaguas
>> 28223 Pozuelo de Alarcón (Madrid)
>> Spain
>> 
>> and
>> 
>> Center for Biomedical Technology
>> Laboratory for Cognitive and Computational Neuroscience
>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>> Campus Montegancedo
>> 28223 Pozuelo de Alarcón (Madrid)
>> Spain
>> 
>> 
>> email: smoratti at psi.ucm.es
>> Tel.:    +34 679219982
>> 
>> El 13/06/2013, a las 12:04, Nicolai Mersebak escribió:
>> 
>>> Thanks to all of you for your comments and ideas - they are very helpful! 
>>> 
>>> I ( off course :) ) have some follow up questions. 
>>> 
>>> I have created an ERP structure for my MNE source, so the only think which I need and that is not straight forward is the neighbour structure. 
>>> 
>>> I am using the standard bem template (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model and use the following code to get a grid for all subjects as I don't have any subject specific information regarding the anatomy. 
>>> 
>>> cfg = [];
>>> cfg.grid.xgrid  = -100:10:100;
>>> cfg.grid.ygrid  = -100:10:100;
>>> cfg.grid.zgrid  = -100:10:100;
>>> cfg.grid.tight  = 'yes';
>>> cfg.grid.unit   = hdm.unit; % unit: mm
>>> cfg.vol        = hdm;
>>> grid  = ft_prepare_sourcemodel(cfg);
>>> 
>>> 
>>> @Jan-Mathijs and Stephan: I guess making a subject specific grid based on a warped template requires anatomic information for each subject, e.g. a MRI image like this tutorial shows:
>>> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
>>> 
>>> The final grid output in the tutorial - does it have this 3D grid which can be used as a neighbour structure ? 
>>> 
>>> I am not sure how to go from my cortical sheet [vertices x coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
>>>  
>>> A second thing I would like to know is, if any of you have tried to use an atlas (e.g ALL template atlas) where the regions now are channels in the permutation test? Going from source points to atlas regions can be done through ft_sourcestatistics, but I am still interested in keeping the temporal dimension. The reason to use atlas regions instead of source points is to decrease the computation time. 
>>> 
>>> Best,
>>> 
>>> Nicolai
>>> 
>>> 
>>> Den 12/06/2013 kl. 18.58 skrev "smoratti at psi.ucm.es" <smoratti at psi.ucm.es>:
>>> 
>>>> 
>>>> I think Jan.Mathijs alternative suggestion is quite attractive. With the neighbors on a cortical sheet I also had the problems that sometimes the vertices do not have the same distance and then clustering may be biased to smaller or bigger clusters as the number of neighbors does not guarantee same cluster sizes. With the interpolation onto a 3D grid, you won't have that problem.
>>>> 
>>>> best,
>>>> 
>>>> Stephan
>>>> 
>>>> 
>>>> ________________________________________________________
>>>> Stephan Moratti, PhD
>>>> 
>>>> see also: http://web.me.com/smoratti/
>>>> 
>>>> Universidad Complutense de Madrid
>>>> Facultad de Psicología
>>>> Departamento de Psicología Básica I
>>>> Campus de Somosaguas
>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>> Spain
>>>> 
>>>> and
>>>> 
>>>> Center for Biomedical Technology
>>>> Laboratory for Cognitive and Computational Neuroscience
>>>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>>>> Campus Montegancedo
>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>> Spain
>>>> 
>>>> 
>>>> email: smoratti at psi.ucm.es
>>>> Tel.:    +34 679219982
>>>> 
>>>> El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribió:
>>>> 
>>>>> An alternative would be to interpolate the cortical sheet to a 3D grid (where the grid is defined for each subject based on a warped template grid defined in a standard space), and then do clustering using a regular 3D spatial neighbourhood structure. The rationale being that two vertices on the sheet may appear as disconnected  (e.g. being on two sides of a sulcus) whereas, given the poor spatial resolution, they belong to the same spatial blob.
>>>>> 
>>>>> Best,
>>>>> Jan-Mathijs
>>>>> 
>>>>> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
>>>>> 
>>>>>> Dear Nicolai,
>>>>>> 
>>>>>> Indeed I have used ft_timelockstatistics for minimum norm source data. The trick is to put the source level data into a ERF structure. Determining the neighbors of a source surface with vertices is not trivial. However I used tess_vertconn.m from the BrainStorm toolbox to get the connectivity matrix that tells you who is a neighbor. This you can feed into timelockstats.
>>>>>> 
>>>>>> Hope that helps,
>>>>>> 
>>>>>> Stephan
>>>>>> 
>>>>>> ________________________________________________________
>>>>>> Stephan Moratti, PhD
>>>>>> 
>>>>>> see also: http://web.me.com/smoratti/
>>>>>> 
>>>>>> Universidad Complutense de Madrid
>>>>>> Facultad de Psicología
>>>>>> Departamento de Psicología Básica I
>>>>>> Campus de Somosaguas
>>>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>>>> Spain
>>>>>> 
>>>>>> and
>>>>>> 
>>>>>> Center for Biomedical Technology
>>>>>> Laboratory for Cognitive and Computational Neuroscience
>>>>>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>>>>>> Campus Montegancedo
>>>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>>>> Spain
>>>>>> 
>>>>>> 
>>>>>> email: smoratti at psi.ucm.es
>>>>>> Tel.:    +34 679219982
>>>>>> 
>>>>>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribió:
>>>>>> 
>>>>>>> Dear all,
>>>>>>> 
>>>>>>> I have a question concerning the usage of ft_sourcegrandaverage and ft_sourcestatistics. 
>>>>>>> 
>>>>>>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897 time points. 
>>>>>>> 
>>>>>>> Now I would like to use the cluster-based permutation test on my source reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics don't support source level time courses. E.g when I am using ft_sourcegrandaverage I am getting the following error:
>>>>>>> 
>>>>>>> Error in ft_sourcegrandaverage (line 158)
>>>>>>>   dat(:,i) = tmp(:);
>>>>>>> 
>>>>>>> Looking into the code:
>>>>>>> 
>>>>>>>   for i=1:Nsubject
>>>>>>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter, varargin{i}));
>>>>>>>     dat(:,i) = tmp(:);
>>>>>>>     tmp = getsubfield(varargin{i}, 'inside');
>>>>>>>     inside(tmp,i) = 1;
>>>>>>>   end
>>>>>>> 
>>>>>>> I see that "tmp" are getting the structure [N_sources x timepoints] from source.avg.pow for one subject, where "dat" requires the structure [N_sources x 1]. 
>>>>>>> 
>>>>>>> I seached the mailing list for similar issues and found this thread:
>>>>>>> 
>>>>>>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>>>>>>> 
>>>>>>> Since I am interested in using the temporal dimension in my statistics, I would like to know if it is still not possible to use spatio-temporal source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
>>>>>>> 
>>>>>>> Or if any have succeeded in using the cluster-based permutation test on source level also including the temporal dimension ? 
>>>>>>> 
>>>>>>> Alternative I was thinking that I might could use ft_timelockstatistics, where I substituted the channels with sources, e.g instead of having 64 channels, I would now have 4050 "channels". 
>>>>>>> If so I need to calculate a label structure and an appropriate neighbor structure, which I guess is possible as I have all the 3D coordinates for each source, e.g in leadfield.pos ?
>>>>>>> I know this is a work around solution, but have anyone tried or have any experience using such an approach ? 
>>>>>>> 
>>>>>>> Best,
>>>>>>> 
>>>>>>> Nicolai
>>>>>>> 
>>>>>>> _______________________________________________
>>>>>>> fieldtrip mailing list
>>>>>>> fieldtrip at donders.ru.nl
>>>>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>>> 
>>>>>> _______________________________________________
>>>>>> fieldtrip mailing list
>>>>>> fieldtrip at donders.ru.nl
>>>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>> 
>>>>> Jan-Mathijs Schoffelen, MD PhD 
>>>>> 
>>>>> Donders Institute for Brain, Cognition and Behaviour, 
>>>>> Centre for Cognitive Neuroimaging,
>>>>> Radboud University Nijmegen, The Netherlands
>>>>> 
>>>>> Max Planck Institute for Psycholinguistics,
>>>>> Nijmegen, The Netherlands
>>>>> 
>>>>> J.Schoffelen at donders.ru.nl
>>>>> Telephone: +31-24-3614793
>>>>> 
>>>>> http://www.hettaligebrein.nl
>>>>> 
>>>>> _______________________________________________
>>>>> fieldtrip mailing list
>>>>> fieldtrip at donders.ru.nl
>>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>> 
>>>> _______________________________________________
>>>> fieldtrip mailing list
>>>> fieldtrip at donders.ru.nl
>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>> 
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> Jan-Mathijs Schoffelen, MD PhD 
> 
> Donders Institute for Brain, Cognition and Behaviour, 
> Centre for Cognitive Neuroimaging,
> Radboud University Nijmegen, The Netherlands
> 
> Max Planck Institute for Psycholinguistics,
> Nijmegen, The Netherlands
> 
> J.Schoffelen at donders.ru.nl
> Telephone: +31-24-3614793
> 
> http://www.hettaligebrein.nl
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

Jan-Mathijs Schoffelen, MD PhD 

Donders Institute for Brain, Cognition and Behaviour, 
Centre for Cognitive Neuroimaging,
Radboud University Nijmegen, The Netherlands

Max Planck Institute for Psycholinguistics,
Nijmegen, The Netherlands

J.Schoffelen at donders.ru.nl
Telephone: +31-24-3614793

http://www.hettaligebrein.nl

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From gopalar.ccf at gmail.com  Fri Jun 14 17:37:54 2013
From: gopalar.ccf at gmail.com (Raghavan Gopalakrishnan)
Date: Fri, 14 Jun 2013 11:37:54 -0400
Subject: [FieldTrip] Butter command
Message-ID: <CAHz=SkUHMvCSLf+uZ=rJiEOvxJJGCJAiPq0RHtc0G34u7ToZhA@mail.gmail.com>

I noticed that 'butter' command in the fieldtrip toolbox
'/fieldtrip-20130609/external/signal/butter.m'
is interfering with the 'butter' command in the Matlab signal processing
toolbox. Can the name be changed?
There are probably more commands in fieldtrip that has same names as
regular matlab commands.
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From eelke.spaak at donders.ru.nl  Fri Jun 14 20:56:17 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Fri, 14 Jun 2013 20:56:17 +0200
Subject: [FieldTrip] Butter command
In-Reply-To: <CAHz=SkUHMvCSLf+uZ=rJiEOvxJJGCJAiPq0RHtc0G34u7ToZhA@mail.gmail.com>
References: <CAHz=SkUHMvCSLf+uZ=rJiEOvxJJGCJAiPq0RHtc0G34u7ToZhA@mail.gmail.com>
Message-ID: <CABPNLUo2=TjM0dqE41syJLtqAcmTEN2mAYsMmA045SGNabvRnQ@mail.gmail.com>

Dear Raghavan,

The /external/signal/ functions are meant as drop-in replacements for
functions in the MATLAB Signal Processing Toolbox, so they should
behave exactly the same as the functions they are shadowing. They are
included in the FieldTrip release for people who do not have Signal
Processing Toolbox licenses, or who would prefer not to use those
licenses just for tapering or filter coefficient functions.

Best,
Eelke

On 14 June 2013 17:37, Raghavan Gopalakrishnan <gopalar.ccf at gmail.com> wrote:
>
> I noticed that 'butter' command in the fieldtrip toolbox
> '/fieldtrip-20130609/external/signal/butter.m'
> is interfering with the 'butter' command in the Matlab signal processing
> toolbox. Can the name be changed?
> There are probably more commands in fieldtrip that has same names as regular
> matlab commands.
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From karenschuil at gmail.com  Mon Jun 17 13:56:09 2013
From: karenschuil at gmail.com (Karen Schuil)
Date: Mon, 17 Jun 2013 13:56:09 +0200
Subject: [FieldTrip] ERP average Brain Vision is different from ERP average
	FieldTrip
Message-ID: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>

Dear Fieldtrip Users,

I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision Analyser
are different from the ERPS of FieldTrip. It seems that in Fieldtrip a slow
negative drift is added and peaks are more/less pronounced than in BVA
(attached is a picture of the two different plots).

An expert FieldTrip User and I could not find a solution for this problem.
I hope one of you has a suggestion for this problem.

The individual trial data was exported from BVA (version 2.02.5859) with
the following settings:
File extension: .seg
Write header file: yes
Write marker file: yes
Format: BINARY
Orientation: MULTIPLEXED
Line Delimiter: CRLF (PC style)
Binary format: 16-Bit signed integer format
Set resolution manually: no
Individually optimized resolution for each channel: yes
Convert to big-endian order: no
Export all channels: no
Export the following channels:
AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5
CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5
FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5
P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8
Created Using Component Version 2.0.2.5827

We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
tried a version from 2011).

The scripts we used are read_analyzer_data and timelockanalysis. This is
the code we used for calling the scripts:
% read data into fieldtrip
cfg = [];

cfg.inputfile = 'pp10_A';
cfg.triggercode = 'S 20';
cfg.triggertype = 'Stimulus';
cfg.prestim = 1.2;
cfg.poststim = 1.7;

pp10_l = read_analyzer_data(cfg);

% check: compute ERP
%
cfg = [];
pp10_ERP = timelockanalysis(cfg, pp10_l);

%plot ERP

cfg = [];
cfg.layout = 'elec1010.lay';
cfg.xlim = [-0.15 1.7];
cfg.ylim = [-12.25 12.25];
% cfg.baseline = 'yes';
% cfg.baselinetype = 'absolute';
cfg.showlabels = 'yes';
cfg.interactive = 'yes';

multiplotER(cfg, pp10_ERP);


I hope you can help!

Kind regards,
Karen
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From j.herring at fcdonders.ru.nl  Mon Jun 17 14:23:13 2013
From: j.herring at fcdonders.ru.nl (Herring, J.D. (Jim))
Date: Mon, 17 Jun 2013 14:23:13 +0200 (CEST)
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
	average	FieldTrip
In-Reply-To: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
References: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
Message-ID: <001901ce6b55$6fcf4590$4f6dd0b0$@herring@fcdonders.ru.nl>

Dear Karen,

 

Comparing the BVA and Fieldtrip images it seems that the trials in BVA
have been filtered using at least a high-pass filter. I can see from the
BVA image that you have applied filters prior to averaging your trials.
>From the Fieldtrip code you've posted I cannot see any filtering applied.
If you could find out what filters were applied to the trials in BVA and
apply the same filters to the trials in FieldTrip using ft_preprocessing
your results will most likely be the same.

 

Best,

 

Jim

 

From: fieldtrip-bounces at science.ru.nl
[mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of Karen Schuil
Sent: maandag 17 juni 2013 13:56
To: fieldtrip at science.ru.nl
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
average FieldTrip

 

Dear Fieldtrip Users,

 

I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision Analyser
are different from the ERPS of FieldTrip. It seems that in Fieldtrip a
slow negative drift is added and peaks are more/less pronounced than in
BVA (attached is a picture of the two different plots). 

 

An expert FieldTrip User and I could not find a solution for this problem.
I hope one of you has a suggestion for this problem.

 

The individual trial data was exported from BVA (version 2.02.5859) with
the following settings:

File extension: .seg
Write header file: yes
Write marker file: yes
Format: BINARY
Orientation: MULTIPLEXED
Line Delimiter: CRLF (PC style)
Binary format: 16-Bit signed integer format
Set resolution manually: no
Individually optimized resolution for each channel: yes
Convert to big-endian order: no
Export all channels: no
Export the following channels:
AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5 
CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5 
FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5 
P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8

Created Using Component Version 2.0.2.5827

 

We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
tried a version from 2011).

 

The scripts we used are read_analyzer_data and timelockanalysis. This is
the code we used for calling the scripts:

% read data into fieldtrip

cfg = [];

 

cfg.inputfile = 'pp10_A';

cfg.triggercode = 'S 20';

cfg.triggertype = 'Stimulus';

cfg.prestim = 1.2;

cfg.poststim = 1.7;

 

pp10_l = read_analyzer_data(cfg);

 

% check: compute ERP

% 

cfg = [];

pp10_ERP = timelockanalysis(cfg, pp10_l);

 

%plot ERP

 

cfg = [];

cfg.layout = 'elec1010.lay';

cfg.xlim = [-0.15 1.7];

cfg.ylim = [-12.25 12.25];

% cfg.baseline = 'yes';

% cfg.baselinetype = 'absolute';

cfg.showlabels = 'yes';

cfg.interactive = 'yes';

 

multiplotER(cfg, pp10_ERP);

 

 

I hope you can help! 

 

Kind regards,

Karen

 

 

 

 

 

 

 

 

 

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From aaron.schurger at gmail.com  Mon Jun 17 14:25:25 2013
From: aaron.schurger at gmail.com (Aaron Schurger)
Date: Mon, 17 Jun 2013 14:25:25 +0200
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
 average FieldTrip
In-Reply-To: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
References: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
Message-ID: <CALeeyASM1BMtZu5GUUQfDocnPq+S=bdJyUrx0AYhB2_ON95ODA@mail.gmail.com>

To me it really looks like BVA is applying a high-pass filter at some
stage. When you export the data, the high-pass filter has probably
already been applied. It is typical in EEG (though not a good idea in
my opinion) to apply a high-pass filter with a cutoff at around 0.05
or 0.1 Hz. There should be a setting somewhere in BVA to turn off the
high-pass filter. Anyway, that's my guess just from looking at the
figure you attached.
Cheers,
Aaron

On Mon, Jun 17, 2013 at 1:56 PM, Karen Schuil <karenschuil at gmail.com> wrote:
> Dear Fieldtrip Users,
>
> I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision Analyser
> are different from the ERPS of FieldTrip. It seems that in Fieldtrip a slow
> negative drift is added and peaks are more/less pronounced than in BVA
> (attached is a picture of the two different plots).
>
> An expert FieldTrip User and I could not find a solution for this problem. I
> hope one of you has a suggestion for this problem.
>
> The individual trial data was exported from BVA (version 2.02.5859) with the
> following settings:
> File extension: .seg
> Write header file: yes
> Write marker file: yes
> Format: BINARY
> Orientation: MULTIPLEXED
> Line Delimiter: CRLF (PC style)
> Binary format: 16-Bit signed integer format
> Set resolution manually: no
> Individually optimized resolution for each channel: yes
> Convert to big-endian order: no
> Export all channels: no
> Export the following channels:
> AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5
> CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5
> FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5
> P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8
> Created Using Component Version 2.0.2.5827
>
> We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
> tried a version from 2011).
>
> The scripts we used are read_analyzer_data and timelockanalysis. This is the
> code we used for calling the scripts:
> % read data into fieldtrip
> cfg = [];
>
> cfg.inputfile = 'pp10_A';
> cfg.triggercode = 'S 20';
> cfg.triggertype = 'Stimulus';
> cfg.prestim = 1.2;
> cfg.poststim = 1.7;
>
> pp10_l = read_analyzer_data(cfg);
>
> % check: compute ERP
> %
> cfg = [];
> pp10_ERP = timelockanalysis(cfg, pp10_l);
>
> %plot ERP
>
> cfg = [];
> cfg.layout = 'elec1010.lay';
> cfg.xlim = [-0.15 1.7];
> cfg.ylim = [-12.25 12.25];
> % cfg.baseline = 'yes';
> % cfg.baselinetype = 'absolute';
> cfg.showlabels = 'yes';
> cfg.interactive = 'yes';
>
> multiplotER(cfg, pp10_ERP);
>
>
> I hope you can help!
>
> Kind regards,
> Karen
>
>
>
>
>
>
>
>
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip



-- 
Aaron Schurger, PhD
Post-doctoral researcher
INSERM U992 / NeuroSpin
CEA - Saclay, France
+33-1-69-08-66-47
aaron.schurger at gmail.com
http://www.unicog.org


From r.vandermeij at donders.ru.nl  Mon Jun 17 14:48:18 2013
From: r.vandermeij at donders.ru.nl (Roemer van der Meij)
Date: Mon, 17 Jun 2013 14:48:18 +0200
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
 average FieldTrip
In-Reply-To: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
References: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
Message-ID: <CA+WpQ345PZtMY27cMXWTsJNantCXJUd_E5ZUi86gFUNUpGREeg@mail.gmail.com>

Hi Karen,

In case the data wasn't exported with the filtering applied in BVA (see
email Jim) then that looks like a probable cause.
In case the data was exported with the filterings, I noticed in the BVA
part of the attached image that it says AF7 - ref, where I see no such
thing in your exported channel list (and thus not in the fieldtrip image).
What the AF7 - ref is referring to I don't know, it seems like a uncommon
place in the pipeline to do rereferencing, but maybe I'm missing something
obvious. Nevertheless, it might lead you somewhere.

All the best,
Roemer


On Mon, Jun 17, 2013 at 1:56 PM, Karen Schuil <karenschuil at gmail.com> wrote:

> Dear Fieldtrip Users,
>
> I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision Analyser
> are different from the ERPS of FieldTrip. It seems that in Fieldtrip a slow
> negative drift is added and peaks are more/less pronounced than in BVA
> (attached is a picture of the two different plots).
>
> An expert FieldTrip User and I could not find a solution for this problem.
> I hope one of you has a suggestion for this problem.
>
> The individual trial data was exported from BVA (version 2.02.5859) with
> the following settings:
> File extension: .seg
> Write header file: yes
> Write marker file: yes
> Format: BINARY
> Orientation: MULTIPLEXED
> Line Delimiter: CRLF (PC style)
> Binary format: 16-Bit signed integer format
> Set resolution manually: no
> Individually optimized resolution for each channel: yes
> Convert to big-endian order: no
> Export all channels: no
> Export the following channels:
> AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5
> CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5
> FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5
> P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8
> Created Using Component Version 2.0.2.5827
>
>  We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
> tried a version from 2011).
>
> The scripts we used are read_analyzer_data and timelockanalysis. This is
> the code we used for calling the scripts:
> % read data into fieldtrip
> cfg = [];
>
> cfg.inputfile = 'pp10_A';
> cfg.triggercode = 'S 20';
> cfg.triggertype = 'Stimulus';
> cfg.prestim = 1.2;
> cfg.poststim = 1.7;
>
> pp10_l = read_analyzer_data(cfg);
>
> % check: compute ERP
> %
> cfg = [];
> pp10_ERP = timelockanalysis(cfg, pp10_l);
>
> %plot ERP
>
> cfg = [];
> cfg.layout = 'elec1010.lay';
> cfg.xlim = [-0.15 1.7];
> cfg.ylim = [-12.25 12.25];
> % cfg.baseline = 'yes';
> % cfg.baselinetype = 'absolute';
> cfg.showlabels = 'yes';
> cfg.interactive = 'yes';
>
> multiplotER(cfg, pp10_ERP);
>
>
> I hope you can help!
>
> Kind regards,
> Karen
>
>
>
>
>
>
>
>
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
Roemer van der Meij M.Sc.
PhD Candidate
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognition
P.O. Box 9104
6500 HE Nijmegen
The Netherlands
Tel: +31(0)24 3655932
E-mail: r.vandermeij at donders.ru.nl
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From t.grent-tjong at donders.ru.nl  Mon Jun 17 14:55:43 2013
From: t.grent-tjong at donders.ru.nl (Tineke Grent-'t-Jong)
Date: Mon, 17 Jun 2013 14:55:43 +0200
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 32
References: <mailman.55.1371470195.980.fieldtrip@science.ru.nl>
Message-ID: <5819595A0394409287071472F2D6352A@socrates>

Hi Karen,

To me it looks like the only thing you need to do is subtract the baseline, 
like you have done in BVA (specifying the same window with cfg.baseline = 
[xmin xmax], not 'yes'). The average ERP that you are plotting in BVA has 
already been baselined, but the single trials that go into the 
ft_timelockanalysis function are not, hence the need for baselining later, 
like in your case at the level of plotting.

Hope this helps,

Tineke


----- Original Message ----- 
From: <fieldtrip-request at science.ru.nl>
To: <fieldtrip at science.ru.nl>
Sent: Monday, June 17, 2013 1:56 PM
Subject: fieldtrip Digest, Vol 31, Issue 32


> Send fieldtrip mailing list submissions to
> fieldtrip at science.ru.nl
>
> To subscribe or unsubscribe via the World Wide Web, visit
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> or, via email, send a message with subject or body 'help' to
> fieldtrip-request at science.ru.nl
>
> You can reach the person managing the list at
> fieldtrip-owner at science.ru.nl
>
> When replying, please edit your Subject line so it is more specific
> than "Re: Contents of fieldtrip digest..."
>


--------------------------------------------------------------------------------


> Today's Topics:
>
>   1. ERP average Brain Vision is different from ERP average
>      FieldTrip (Karen Schuil)
>


--------------------------------------------------------------------------------


> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip 



From aaron.schurger at gmail.com  Mon Jun 17 15:08:25 2013
From: aaron.schurger at gmail.com (Aaron Schurger)
Date: Mon, 17 Jun 2013 15:08:25 +0200
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 32
In-Reply-To: <5819595A0394409287071472F2D6352A@socrates>
References: <mailman.55.1371470195.980.fieldtrip@science.ru.nl>
	<5819595A0394409287071472F2D6352A@socrates>
Message-ID: <CALeeyASpsHCvVHZ_dYVt-aJt6F7vsuzLvb4wsmsDeYWCYJDphQ@mail.gmail.com>

Hi, Karen, Tineke,
To me it looks like more than just a baseline shift. It looks like
either linear de-trending or high-pass filtering was applied to the
BVA data. I don't see how a baseline shift could get rid of the low
frequency component that is clearly visible in the FT plot, but not
the BVA plot.
Cheers,
Aaron

On Mon, Jun 17, 2013 at 2:55 PM, Tineke Grent-'t-Jong
<t.grent-tjong at donders.ru.nl> wrote:
> Hi Karen,
>
> To me it looks like the only thing you need to do is subtract the baseline,
> like you have done in BVA (specifying the same window with cfg.baseline =
> [xmin xmax], not 'yes'). The average ERP that you are plotting in BVA has
> already been baselined, but the single trials that go into the
> ft_timelockanalysis function are not, hence the need for baselining later,
> like in your case at the level of plotting.
>
> Hope this helps,
>
> Tineke
>
>
> ----- Original Message ----- From: <fieldtrip-request at science.ru.nl>
> To: <fieldtrip at science.ru.nl>
> Sent: Monday, June 17, 2013 1:56 PM
> Subject: fieldtrip Digest, Vol 31, Issue 32
>
>
>> Send fieldtrip mailing list submissions to
>> fieldtrip at science.ru.nl
>>
>> To subscribe or unsubscribe via the World Wide Web, visit
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> or, via email, send a message with subject or body 'help' to
>> fieldtrip-request at science.ru.nl
>>
>> You can reach the person managing the list at
>> fieldtrip-owner at science.ru.nl
>>
>> When replying, please edit your Subject line so it is more specific
>> than "Re: Contents of fieldtrip digest..."
>>
>
>
> --------------------------------------------------------------------------------
>
>
>> Today's Topics:
>>
>>   1. ERP average Brain Vision is different from ERP average
>>      FieldTrip (Karen Schuil)
>>
>
>
> --------------------------------------------------------------------------------
>
>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip



-- 
Aaron Schurger, PhD
Post-doctoral researcher
INSERM U992 / NeuroSpin
CEA - Saclay, France
+33-1-69-08-66-47
aaron.schurger at gmail.com
http://www.unicog.org


From schuil at fsw.eur.nl  Mon Jun 17 15:22:22 2013
From: schuil at fsw.eur.nl (Karen Schuil)
Date: Mon, 17 Jun 2013 15:22:22 +0200
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
 average FieldTrip
In-Reply-To: <CALeeyASM1BMtZu5GUUQfDocnPq+S=bdJyUrx0AYhB2_ON95ODA@mail.gmail.com>
References: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
	<CALeeyASM1BMtZu5GUUQfDocnPq+S=bdJyUrx0AYhB2_ON95ODA@mail.gmail.com>
Message-ID: <CAGnbK6gqEqLBXuATfXHzh2M7ofohp_z7=i8x=WQtX4RxPEMx6A@mail.gmail.com>

Dear Jim, Aaron, Roemer and Tineke,

Thanks for your quick response and suggestions! The whole preprocessing
(including the filters) was done in BVA. After segmentatation of the
conditions, we exported the data to Fieldtrip. The only steps we did in
Fieldtrip was averaging, creating and plotting an ERP. Therefore it can't
be the filters, right? Unless, the averaging step in BVA applies filters as
well.

The ref in AF7-ref is added by BVA and refers to the channels being linked
to the mastoids.

We have also tried it with subtracting a baseline, but this unfortunately
did not help.

Do you have any other suggestions?

Cheers, Karen




On Mon, Jun 17, 2013 at 2:25 PM, Aaron Schurger <aaron.schurger at gmail.com>wrote:

> To me it really looks like BVA is applying a high-pass filter at some
> stage. When you export the data, the high-pass filter has probably
> already been applied. It is typical in EEG (though not a good idea in
> my opinion) to apply a high-pass filter with a cutoff at around 0.05
> or 0.1 Hz. There should be a setting somewhere in BVA to turn off the
> high-pass filter. Anyway, that's my guess just from looking at the
> figure you attached.
> Cheers,
> Aaron
>
> On Mon, Jun 17, 2013 at 1:56 PM, Karen Schuil <karenschuil at gmail.com>
> wrote:
> > Dear Fieldtrip Users,
> >
> > I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision Analyser
> > are different from the ERPS of FieldTrip. It seems that in Fieldtrip a
> slow
> > negative drift is added and peaks are more/less pronounced than in BVA
> > (attached is a picture of the two different plots).
> >
> > An expert FieldTrip User and I could not find a solution for this
> problem. I
> > hope one of you has a suggestion for this problem.
> >
> > The individual trial data was exported from BVA (version 2.02.5859) with
> the
> > following settings:
> > File extension: .seg
> > Write header file: yes
> > Write marker file: yes
> > Format: BINARY
> > Orientation: MULTIPLEXED
> > Line Delimiter: CRLF (PC style)
> > Binary format: 16-Bit signed integer format
> > Set resolution manually: no
> > Individually optimized resolution for each channel: yes
> > Convert to big-endian order: no
> > Export all channels: no
> > Export the following channels:
> > AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5
> > CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5
> > FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5
> > P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8
> > Created Using Component Version 2.0.2.5827
> >
> > We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
> > tried a version from 2011).
> >
> > The scripts we used are read_analyzer_data and timelockanalysis. This is
> the
> > code we used for calling the scripts:
> > % read data into fieldtrip
> > cfg = [];
> >
> > cfg.inputfile = 'pp10_A';
> > cfg.triggercode = 'S 20';
> > cfg.triggertype = 'Stimulus';
> > cfg.prestim = 1.2;
> > cfg.poststim = 1.7;
> >
> > pp10_l = read_analyzer_data(cfg);
> >
> > % check: compute ERP
> > %
> > cfg = [];
> > pp10_ERP = timelockanalysis(cfg, pp10_l);
> >
> > %plot ERP
> >
> > cfg = [];
> > cfg.layout = 'elec1010.lay';
> > cfg.xlim = [-0.15 1.7];
> > cfg.ylim = [-12.25 12.25];
> > % cfg.baseline = 'yes';
> > % cfg.baselinetype = 'absolute';
> > cfg.showlabels = 'yes';
> > cfg.interactive = 'yes';
> >
> > multiplotER(cfg, pp10_ERP);
> >
> >
> > I hope you can help!
> >
> > Kind regards,
> > Karen
> >
> >
> >
> >
> >
> >
> >
> >
> >
> >
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
> --
> Aaron Schurger, PhD
> Post-doctoral researcher
> INSERM U992 / NeuroSpin
> CEA - Saclay, France
> +33-1-69-08-66-47
> aaron.schurger at gmail.com
> http://www.unicog.org
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
-------------------
Karen Schuil
PhD student

Erasmus University Rotterdam
Institute of Psychology, T 13-09
Burgemeester Oudlaan 50
P.O. Box 1738
3000 DR Rotterdam
The Netherlands
Phone: +31 (0) 10 408 2293
Email:  schuil at fsw.eur.nl
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From t.grent-tjong at donders.ru.nl  Mon Jun 17 15:39:30 2013
From: t.grent-tjong at donders.ru.nl (Tineke Grent-'t-Jong)
Date: Mon, 17 Jun 2013 15:39:30 +0200
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 32
References: <mailman.55.1371470195.980.fieldtrip@science.ru.nl><5819595A0394409287071472F2D6352A@socrates>
	<CALeeyASpsHCvVHZ_dYVt-aJt6F7vsuzLvb4wsmsDeYWCYJDphQ@mail.gmail.com>
Message-ID: <0840040570ED4FE896ED4FAE33DE1355@socrates>

Hi Karen,

Aaron is right that it could be an effect of de-trending or high-pass 
filtering. You could try running the ft_timelockanalyis step again with 
option cfg.removemean = 'no' ('yes' is the default option!). If this
solves the problem then it indeed was some kind of de-trending problem.

Cheers,
Tineke



----- Original Message ----- 
From: "Aaron Schurger" <aaron.schurger at gmail.com>
To: "Tineke Grent-'t-Jong" <t.grent-tjong at donders.ru.nl>; "FieldTrip 
discussion list" <fieldtrip at science.ru.nl>
Sent: Monday, June 17, 2013 3:08 PM
Subject: Re: [FieldTrip] fieldtrip Digest, Vol 31, Issue 32


> Hi, Karen, Tineke,
> To me it looks like more than just a baseline shift. It looks like
> either linear de-trending or high-pass filtering was applied to the
> BVA data. I don't see how a baseline shift could get rid of the low
> frequency component that is clearly visible in the FT plot, but not
> the BVA plot.
> Cheers,
> Aaron
>
> On Mon, Jun 17, 2013 at 2:55 PM, Tineke Grent-'t-Jong
> <t.grent-tjong at donders.ru.nl> wrote:
>> Hi Karen,
>>
>> To me it looks like the only thing you need to do is subtract the 
>> baseline,
>> like you have done in BVA (specifying the same window with cfg.baseline =
>> [xmin xmax], not 'yes'). The average ERP that you are plotting in BVA has
>> already been baselined, but the single trials that go into the
>> ft_timelockanalysis function are not, hence the need for baselining 
>> later,
>> like in your case at the level of plotting.
>>
>> Hope this helps,
>>
>> Tineke
>>
>>
>> ----- Original Message ----- From: <fieldtrip-request at science.ru.nl>
>> To: <fieldtrip at science.ru.nl>
>> Sent: Monday, June 17, 2013 1:56 PM
>> Subject: fieldtrip Digest, Vol 31, Issue 32
>>
>>
>>> Send fieldtrip mailing list submissions to
>>> fieldtrip at science.ru.nl
>>>
>>> To subscribe or unsubscribe via the World Wide Web, visit
>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>> or, via email, send a message with subject or body 'help' to
>>> fieldtrip-request at science.ru.nl
>>>
>>> You can reach the person managing the list at
>>> fieldtrip-owner at science.ru.nl
>>>
>>> When replying, please edit your Subject line so it is more specific
>>> than "Re: Contents of fieldtrip digest..."
>>>
>>
>>
>> --------------------------------------------------------------------------------
>>
>>
>>> Today's Topics:
>>>
>>>   1. ERP average Brain Vision is different from ERP average
>>>      FieldTrip (Karen Schuil)
>>>
>>
>>
>> --------------------------------------------------------------------------------
>>
>>
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
> -- 
> Aaron Schurger, PhD
> Post-doctoral researcher
> INSERM U992 / NeuroSpin
> CEA - Saclay, France
> +33-1-69-08-66-47
> aaron.schurger at gmail.com
> http://www.unicog.org
> 



From berryv.dberg at gmail.com  Mon Jun 17 15:40:14 2013
From: berryv.dberg at gmail.com (berry van den berg)
Date: Mon, 17 Jun 2013 09:40:14 -0400
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
 average FieldTrip
In-Reply-To: <CAGnbK6gqEqLBXuATfXHzh2M7ofohp_z7=i8x=WQtX4RxPEMx6A@mail.gmail.com>
References: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
	<CALeeyASM1BMtZu5GUUQfDocnPq+S=bdJyUrx0AYhB2_ON95ODA@mail.gmail.com>
	<CAGnbK6gqEqLBXuATfXHzh2M7ofohp_z7=i8x=WQtX4RxPEMx6A@mail.gmail.com>
Message-ID: <CAL-qV4JzQmdy=-JNvpm1HwEEvVuLrjQ02sAzjdDffbCV+Ys0ew@mail.gmail.com>

I dont know BVA but it looks like the ERPs are a bit more different (for
example at timepoint 100ms) then I would expect just based on high pass
filtering.... Suggesting that there is different data going into averaging.
Maybe brain vision just detects trials with artifacts and does not throw
out the trials until the averaging step (similar to ERPlab). Can you check
the number of trials?

Cheers,

Berry van den Berg



On 17 June 2013 09:22, Karen Schuil <schuil at fsw.eur.nl> wrote:

> Dear Jim, Aaron, Roemer and Tineke,
>
> Thanks for your quick response and suggestions! The whole preprocessing
> (including the filters) was done in BVA. After segmentatation of the
> conditions, we exported the data to Fieldtrip. The only steps we did in
> Fieldtrip was averaging, creating and plotting an ERP. Therefore it can't
> be the filters, right? Unless, the averaging step in BVA applies filters as
> well.
>
> The ref in AF7-ref is added by BVA and refers to the channels being linked
> to the mastoids.
>
> We have also tried it with subtracting a baseline, but this unfortunately
> did not help.
>
> Do you have any other suggestions?
>
> Cheers, Karen
>
>
>
>
> On Mon, Jun 17, 2013 at 2:25 PM, Aaron Schurger <aaron.schurger at gmail.com>wrote:
>
>> To me it really looks like BVA is applying a high-pass filter at some
>> stage. When you export the data, the high-pass filter has probably
>> already been applied. It is typical in EEG (though not a good idea in
>> my opinion) to apply a high-pass filter with a cutoff at around 0.05
>> or 0.1 Hz. There should be a setting somewhere in BVA to turn off the
>> high-pass filter. Anyway, that's my guess just from looking at the
>> figure you attached.
>> Cheers,
>> Aaron
>>
>> On Mon, Jun 17, 2013 at 1:56 PM, Karen Schuil <karenschuil at gmail.com>
>> wrote:
>> > Dear Fieldtrip Users,
>> >
>> > I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision
>> Analyser
>> > are different from the ERPS of FieldTrip. It seems that in Fieldtrip a
>> slow
>> > negative drift is added and peaks are more/less pronounced than in BVA
>> > (attached is a picture of the two different plots).
>> >
>> > An expert FieldTrip User and I could not find a solution for this
>> problem. I
>> > hope one of you has a suggestion for this problem.
>> >
>> > The individual trial data was exported from BVA (version 2.02.5859)
>> with the
>> > following settings:
>> > File extension: .seg
>> > Write header file: yes
>> > Write marker file: yes
>> > Format: BINARY
>> > Orientation: MULTIPLEXED
>> > Line Delimiter: CRLF (PC style)
>> > Binary format: 16-Bit signed integer format
>> > Set resolution manually: no
>> > Individually optimized resolution for each channel: yes
>> > Convert to big-endian order: no
>> > Export all channels: no
>> > Export the following channels:
>> > AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5
>> > CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5
>> > FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5
>> > P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8
>> > Created Using Component Version 2.0.2.5827
>> >
>> > We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
>> > tried a version from 2011).
>> >
>> > The scripts we used are read_analyzer_data and timelockanalysis. This
>> is the
>> > code we used for calling the scripts:
>> > % read data into fieldtrip
>> > cfg = [];
>> >
>> > cfg.inputfile = 'pp10_A';
>> > cfg.triggercode = 'S 20';
>> > cfg.triggertype = 'Stimulus';
>> > cfg.prestim = 1.2;
>> > cfg.poststim = 1.7;
>> >
>> > pp10_l = read_analyzer_data(cfg);
>> >
>> > % check: compute ERP
>> > %
>> > cfg = [];
>> > pp10_ERP = timelockanalysis(cfg, pp10_l);
>> >
>> > %plot ERP
>> >
>> > cfg = [];
>> > cfg.layout = 'elec1010.lay';
>> > cfg.xlim = [-0.15 1.7];
>> > cfg.ylim = [-12.25 12.25];
>> > % cfg.baseline = 'yes';
>> > % cfg.baselinetype = 'absolute';
>> > cfg.showlabels = 'yes';
>> > cfg.interactive = 'yes';
>> >
>> > multiplotER(cfg, pp10_ERP);
>> >
>> >
>> > I hope you can help!
>> >
>> > Kind regards,
>> > Karen
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> > _______________________________________________
>> > fieldtrip mailing list
>> > fieldtrip at donders.ru.nl
>> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>>
>>
>> --
>> Aaron Schurger, PhD
>> Post-doctoral researcher
>> INSERM U992 / NeuroSpin
>> CEA - Saclay, France
>> +33-1-69-08-66-47
>> aaron.schurger at gmail.com
>> http://www.unicog.org
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>
>
>
> --
> -------------------
> Karen Schuil
> PhD student
>
> Erasmus University Rotterdam
> Institute of Psychology, T 13-09
> Burgemeester Oudlaan 50
> P.O. Box 1738
> 3000 DR Rotterdam
> The Netherlands
> Phone: +31 (0) 10 408 2293
> Email:  schuil at fsw.eur.nl
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
Berry van den Berg
berryv.dberg at gmail.com
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From aaron.schurger at gmail.com  Mon Jun 17 15:44:05 2013
From: aaron.schurger at gmail.com (Aaron Schurger)
Date: Mon, 17 Jun 2013 15:44:05 +0200
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
 average FieldTrip
In-Reply-To: <CAGnbK6gqEqLBXuATfXHzh2M7ofohp_z7=i8x=WQtX4RxPEMx6A@mail.gmail.com>
References: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
	<CALeeyASM1BMtZu5GUUQfDocnPq+S=bdJyUrx0AYhB2_ON95ODA@mail.gmail.com>
	<CAGnbK6gqEqLBXuATfXHzh2M7ofohp_z7=i8x=WQtX4RxPEMx6A@mail.gmail.com>
Message-ID: <CALeeyASwKFoiJ-YL_q1Me+QvFTCtsFvyWpM5i3J4FjgiC8Tuww@mail.gmail.com>

Hi, Karen,
Yes, you're right - it would have to be the case that the averaging
step in BVA applies the filters. That would be where I would check. If
nothing there then it really is mysterious!
Aaron

On Mon, Jun 17, 2013 at 3:22 PM, Karen Schuil <schuil at fsw.eur.nl> wrote:
> Dear Jim, Aaron, Roemer and Tineke,
>
> Thanks for your quick response and suggestions! The whole preprocessing
> (including the filters) was done in BVA. After segmentatation of the
> conditions, we exported the data to Fieldtrip. The only steps we did in
> Fieldtrip was averaging, creating and plotting an ERP. Therefore it can't be
> the filters, right? Unless, the averaging step in BVA applies filters as
> well.
>
> The ref in AF7-ref is added by BVA and refers to the channels being linked
> to the mastoids.
>
> We have also tried it with subtracting a baseline, but this unfortunately
> did not help.
>
> Do you have any other suggestions?
>
> Cheers, Karen
>
>
>
>
> On Mon, Jun 17, 2013 at 2:25 PM, Aaron Schurger <aaron.schurger at gmail.com>
> wrote:
>>
>> To me it really looks like BVA is applying a high-pass filter at some
>> stage. When you export the data, the high-pass filter has probably
>> already been applied. It is typical in EEG (though not a good idea in
>> my opinion) to apply a high-pass filter with a cutoff at around 0.05
>> or 0.1 Hz. There should be a setting somewhere in BVA to turn off the
>> high-pass filter. Anyway, that's my guess just from looking at the
>> figure you attached.
>> Cheers,
>> Aaron
>>
>> On Mon, Jun 17, 2013 at 1:56 PM, Karen Schuil <karenschuil at gmail.com>
>> wrote:
>> > Dear Fieldtrip Users,
>> >
>> > I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision
>> > Analyser
>> > are different from the ERPS of FieldTrip. It seems that in Fieldtrip a
>> > slow
>> > negative drift is added and peaks are more/less pronounced than in BVA
>> > (attached is a picture of the two different plots).
>> >
>> > An expert FieldTrip User and I could not find a solution for this
>> > problem. I
>> > hope one of you has a suggestion for this problem.
>> >
>> > The individual trial data was exported from BVA (version 2.02.5859) with
>> > the
>> > following settings:
>> > File extension: .seg
>> > Write header file: yes
>> > Write marker file: yes
>> > Format: BINARY
>> > Orientation: MULTIPLEXED
>> > Line Delimiter: CRLF (PC style)
>> > Binary format: 16-Bit signed integer format
>> > Set resolution manually: no
>> > Individually optimized resolution for each channel: yes
>> > Convert to big-endian order: no
>> > Export all channels: no
>> > Export the following channels:
>> > AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5
>> > CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5
>> > FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5
>> > P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8
>> > Created Using Component Version 2.0.2.5827
>> >
>> > We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
>> > tried a version from 2011).
>> >
>> > The scripts we used are read_analyzer_data and timelockanalysis. This is
>> > the
>> > code we used for calling the scripts:
>> > % read data into fieldtrip
>> > cfg = [];
>> >
>> > cfg.inputfile = 'pp10_A';
>> > cfg.triggercode = 'S 20';
>> > cfg.triggertype = 'Stimulus';
>> > cfg.prestim = 1.2;
>> > cfg.poststim = 1.7;
>> >
>> > pp10_l = read_analyzer_data(cfg);
>> >
>> > % check: compute ERP
>> > %
>> > cfg = [];
>> > pp10_ERP = timelockanalysis(cfg, pp10_l);
>> >
>> > %plot ERP
>> >
>> > cfg = [];
>> > cfg.layout = 'elec1010.lay';
>> > cfg.xlim = [-0.15 1.7];
>> > cfg.ylim = [-12.25 12.25];
>> > % cfg.baseline = 'yes';
>> > % cfg.baselinetype = 'absolute';
>> > cfg.showlabels = 'yes';
>> > cfg.interactive = 'yes';
>> >
>> > multiplotER(cfg, pp10_ERP);
>> >
>> >
>> > I hope you can help!
>> >
>> > Kind regards,
>> > Karen
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> > _______________________________________________
>> > fieldtrip mailing list
>> > fieldtrip at donders.ru.nl
>> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>>
>>
>> --
>> Aaron Schurger, PhD
>> Post-doctoral researcher
>> INSERM U992 / NeuroSpin
>> CEA - Saclay, France
>> +33-1-69-08-66-47
>> aaron.schurger at gmail.com
>> http://www.unicog.org
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
>
> --
> -------------------
> Karen Schuil
> PhD student
>
> Erasmus University Rotterdam
> Institute of Psychology, T 13-09
> Burgemeester Oudlaan 50
> P.O. Box 1738
> 3000 DR Rotterdam
> The Netherlands
> Phone: +31 (0) 10 408 2293
> Email:  schuil at fsw.eur.nl
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip



-- 
Aaron Schurger, PhD
Post-doctoral researcher
INSERM U992 / NeuroSpin
CEA - Saclay, France
+33-1-69-08-66-47
aaron.schurger at gmail.com
http://www.unicog.org


From eelke.spaak at donders.ru.nl  Tue Jun 18 10:29:34 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Tue, 18 Jun 2013 10:29:34 +0200
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
 average FieldTrip
In-Reply-To: <CAGnbK6gqEqLBXuATfXHzh2M7ofohp_z7=i8x=WQtX4RxPEMx6A@mail.gmail.com>
References: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
	<CALeeyASM1BMtZu5GUUQfDocnPq+S=bdJyUrx0AYhB2_ON95ODA@mail.gmail.com>
	<CAGnbK6gqEqLBXuATfXHzh2M7ofohp_z7=i8x=WQtX4RxPEMx6A@mail.gmail.com>
Message-ID: <CABPNLUomcmtO7B9phMmV9-aGAfJqURGjyxt-RV0v+z_RS_p4aA@mail.gmail.com>

Dear Karen,

It seems likely (as the other responses also indicate) that
BrainVision Analyzer is doing something to the data that FieldTrip is
not; in other words, the FieldTrip ERP is probably more 'pure'.
Therefore, perhaps it might be worth asking around on the BVA mailing
list if the people there know what BVA is doing to the data prior to
computing and displaying the average?

It is easy to check whether FieldTrip is doing something unexpected to
the data, by computing and plotting the average yourself:

erp = mean(cat(3, pp10_l.trial{:}), 3);
chanind = strmatch('AF7', pp10_l.label);
plot(pp10_l.time{1}, erp(chanind,:));

This only works if all trials have identical time axes, but judging
from your script I think they do. It the above steps give a different
plot than the FT functions, something is possibly (/probably) wrong in
the FT code.

Best,
Eelke

On 17 June 2013 15:22, Karen Schuil <schuil at fsw.eur.nl> wrote:
> Dear Jim, Aaron, Roemer and Tineke,
>
> Thanks for your quick response and suggestions! The whole preprocessing
> (including the filters) was done in BVA. After segmentatation of the
> conditions, we exported the data to Fieldtrip. The only steps we did in
> Fieldtrip was averaging, creating and plotting an ERP. Therefore it can't be
> the filters, right? Unless, the averaging step in BVA applies filters as
> well.
>
> The ref in AF7-ref is added by BVA and refers to the channels being linked
> to the mastoids.
>
> We have also tried it with subtracting a baseline, but this unfortunately
> did not help.
>
> Do you have any other suggestions?
>
> Cheers, Karen
>
>
>
>
> On Mon, Jun 17, 2013 at 2:25 PM, Aaron Schurger <aaron.schurger at gmail.com>
> wrote:
>>
>> To me it really looks like BVA is applying a high-pass filter at some
>> stage. When you export the data, the high-pass filter has probably
>> already been applied. It is typical in EEG (though not a good idea in
>> my opinion) to apply a high-pass filter with a cutoff at around 0.05
>> or 0.1 Hz. There should be a setting somewhere in BVA to turn off the
>> high-pass filter. Anyway, that's my guess just from looking at the
>> figure you attached.
>> Cheers,
>> Aaron
>>
>> On Mon, Jun 17, 2013 at 1:56 PM, Karen Schuil <karenschuil at gmail.com>
>> wrote:
>> > Dear Fieldtrip Users,
>> >
>> > I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision
>> > Analyser
>> > are different from the ERPS of FieldTrip. It seems that in Fieldtrip a
>> > slow
>> > negative drift is added and peaks are more/less pronounced than in BVA
>> > (attached is a picture of the two different plots).
>> >
>> > An expert FieldTrip User and I could not find a solution for this
>> > problem. I
>> > hope one of you has a suggestion for this problem.
>> >
>> > The individual trial data was exported from BVA (version 2.02.5859) with
>> > the
>> > following settings:
>> > File extension: .seg
>> > Write header file: yes
>> > Write marker file: yes
>> > Format: BINARY
>> > Orientation: MULTIPLEXED
>> > Line Delimiter: CRLF (PC style)
>> > Binary format: 16-Bit signed integer format
>> > Set resolution manually: no
>> > Individually optimized resolution for each channel: yes
>> > Convert to big-endian order: no
>> > Export all channels: no
>> > Export the following channels:
>> > AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5
>> > CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5
>> > FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5
>> > P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8
>> > Created Using Component Version 2.0.2.5827
>> >
>> > We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
>> > tried a version from 2011).
>> >
>> > The scripts we used are read_analyzer_data and timelockanalysis. This is
>> > the
>> > code we used for calling the scripts:
>> > % read data into fieldtrip
>> > cfg = [];
>> >
>> > cfg.inputfile = 'pp10_A';
>> > cfg.triggercode = 'S 20';
>> > cfg.triggertype = 'Stimulus';
>> > cfg.prestim = 1.2;
>> > cfg.poststim = 1.7;
>> >
>> > pp10_l = read_analyzer_data(cfg);
>> >
>> > % check: compute ERP
>> > %
>> > cfg = [];
>> > pp10_ERP = timelockanalysis(cfg, pp10_l);
>> >
>> > %plot ERP
>> >
>> > cfg = [];
>> > cfg.layout = 'elec1010.lay';
>> > cfg.xlim = [-0.15 1.7];
>> > cfg.ylim = [-12.25 12.25];
>> > % cfg.baseline = 'yes';
>> > % cfg.baselinetype = 'absolute';
>> > cfg.showlabels = 'yes';
>> > cfg.interactive = 'yes';
>> >
>> > multiplotER(cfg, pp10_ERP);
>> >
>> >
>> > I hope you can help!
>> >
>> > Kind regards,
>> > Karen
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> > _______________________________________________
>> > fieldtrip mailing list
>> > fieldtrip at donders.ru.nl
>> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>>
>>
>> --
>> Aaron Schurger, PhD
>> Post-doctoral researcher
>> INSERM U992 / NeuroSpin
>> CEA - Saclay, France
>> +33-1-69-08-66-47
>> aaron.schurger at gmail.com
>> http://www.unicog.org
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
>
> --
> -------------------
> Karen Schuil
> PhD student
>
> Erasmus University Rotterdam
> Institute of Psychology, T 13-09
> Burgemeester Oudlaan 50
> P.O. Box 1738
> 3000 DR Rotterdam
> The Netherlands
> Phone: +31 (0) 10 408 2293
> Email:  schuil at fsw.eur.nl
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From mje.mads at gmail.com  Tue Jun 18 10:44:01 2013
From: mje.mads at gmail.com (Mads Jensen)
Date: Tue, 18 Jun 2013 10:44:01 +0200
Subject: [FieldTrip] select trial by previous trigger code
Message-ID: <51C01DD1.5070005@gmail.com>

Hi all,

I would like to know if it is possible select a trail based on the 
previous trigger code?

I got a dataset (MEG, neuromeg) where sometimes the subject just press a 
button and sometimes a cue is shown and they then press the button, the 
button presses are coded "1" and the cue "2". So, what I would like is 
to datasets one with trials where there has been no cue and one dataset 
where the trials that have cue is. Is that possible to do automatically 
or do I have to do a "by hand"?

best wishes,
mads


From s.vanpelt at fcdonders.ru.nl  Tue Jun 18 11:11:06 2013
From: s.vanpelt at fcdonders.ru.nl (Stan van Pelt)
Date: Tue, 18 Jun 2013 11:11:06 +0200 (CEST)
Subject: [FieldTrip] select trial by previous trigger code
References: <51C01DD1.5070005@gmail.com> 
Message-ID: <03cc01ce6c03$c403fb20$4c0bf160$@vanpelt@fcdonders.ru.nl>

Dear Mads,

It is not possible to do this automatically. However, by writing your own
'trialfun', you should be able to program this in a relative
straightforward manner. You can enter this trialfun-name in the
cfg.trialfun configuration option when subsequently calling
ft_definetrial.
See
http://fieldtrip.fcdonders.nl/example/making_your_own_trialfun_for_conditi
onal_trial_definition

Best,
Stan

Stan van Pelt, PhD
Donders Institute for Brain, Cognition and Behaviour Centre for Cognition
Montessorilaan 3, B.01.19
6525 HR Nijmegen
tel: 024-3616288


-----Original Message-----
From: fieldtrip-bounces at science.ru.nl
[mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of Mads Jensen
Sent: dinsdag 18 juni 2013 10:44
To: FieldTrip discussion list
Subject: [FieldTrip] select trial by previous trigger code

Hi all,

I would like to know if it is possible select a trail based on the
previous trigger code?

I got a dataset (MEG, neuromeg) where sometimes the subject just press a
button and sometimes a cue is shown and they then press the button, the
button presses are coded "1" and the cue "2". So, what I would like is to
datasets one with trials where there has been no cue and one dataset where
the trials that have cue is. Is that possible to do automatically or do I
have to do a "by hand"?

best wishes,
mads
_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl
http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From jm.horschig at donders.ru.nl  Tue Jun 18 11:11:50 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Tue, 18 Jun 2013 11:11:50 +0200
Subject: [FieldTrip] select trial by previous trigger code
In-Reply-To: <51C01DD1.5070005@gmail.com>
References: <51C01DD1.5070005@gmail.com>
Message-ID: <51C02456.2000800@donders.ru.nl>

Hi Mads,

such things are possible if you write your own trial function. 
Basically, you need to read in the events (i.e. trigger values) and then 
make a selection based on that, see also here:
http://fieldtrip.fcdonders.nl/example/making_your_own_trialfun_for_conditional_trial_definition?s[]=trialfun
http://fieldtrip.fcdonders.nl/faq/what_is_the_relation_between_events_such_as_triggers_and_trials?s[]=trialfun

Hope that helps!
Best,
Jörn

On 6/18/2013 10:44 AM, Mads Jensen wrote:
> Hi all,
>
> I would like to know if it is possible select a trail based on the 
> previous trigger code?
>
> I got a dataset (MEG, neuromeg) where sometimes the subject just press 
> a button and sometimes a cue is shown and they then press the button, 
> the button presses are coded "1" and the cue "2". So, what I would 
> like is to datasets one with trials where there has been no cue and 
> one dataset where the trials that have cue is. Is that possible to do 
> automatically or do I have to do a "by hand"?
>
> best wishes,
> mads
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands



From yuvharpaz at gmail.com  Tue Jun 18 14:58:15 2013
From: yuvharpaz at gmail.com (Yuval Harpaz)
Date: Tue, 18 Jun 2013 15:58:15 +0300
Subject: [FieldTrip] fixed dipole orientation for MNE
Message-ID: <CAGQZS_m+RSW6LDOmbYc9MDtwf1dUM==a4c3Nc9BRA5WYneTp6w@mail.gmail.com>

Dear group
I would like to ask again (
http://mailman.science.ru.nl/pipermail/fieldtrip/2011-February/003456.html)
about head model with fixed dipole orientation (obtained from freesurfer),
as I saw no reply to the previous message.

I understand that there is no civilized way, currently, to tell MNE or
beamforming to use fixed orientation, or am I wrong?

applying 'sam' I managed to set dipole orinetation by making a dip.mom
field in addition to dip.pos and by
gain = lf;
instead of the existing
gain = lf * UnitMDip';
note that here lf is a vector (no 3 columns).

However this is patchy and not thorough. So can you please tell me if there
is a way to do it with regular ft functions?
thank you
Yuval




Dr .Harpaz

BIU MEG lab <http://faculty.biu.ac.il/~goldsa/index.html>
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From eelke.spaak at donders.ru.nl  Tue Jun 18 15:16:41 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Tue, 18 Jun 2013 15:16:41 +0200
Subject: [FieldTrip] fixed dipole orientation for MNE
In-Reply-To: <CAGQZS_m+RSW6LDOmbYc9MDtwf1dUM==a4c3Nc9BRA5WYneTp6w@mail.gmail.com>
References: <CAGQZS_m+RSW6LDOmbYc9MDtwf1dUM==a4c3Nc9BRA5WYneTp6w@mail.gmail.com>
Message-ID: <CABPNLUpqBxHFfrw=9mvesB2RXirhnyQH_-Mt5+icKA5HMcrkXQ@mail.gmail.com>

Dear Yuval,

The LCMV and DICS beamforming implementations in FieldTrip support
cfg.<method>.fixedori = 'yes', where <method> is either 'lcmv' or
'dics'. This will compute a filter which constrains each dipole to
point in the strongest orientation. For SAM I think this is not
implemented, and for MNE I have no clue.

Does this answer your question? Or are you lookling for another type
of fixed orientation, maybe based on anatomy or so?

Best,
Eelke

On 18 June 2013 14:58, Yuval Harpaz <yuvharpaz at gmail.com> wrote:
> Dear group
> I would like to ask again
> (http://mailman.science.ru.nl/pipermail/fieldtrip/2011-February/003456.html)
> about head model with fixed dipole orientation (obtained from freesurfer),
> as I saw no reply to the previous message.
>
> I understand that there is no civilized way, currently, to tell MNE or
> beamforming to use fixed orientation, or am I wrong?
>
> applying 'sam' I managed to set dipole orinetation by making a dip.mom field
> in addition to dip.pos and by
> gain = lf;
> instead of the existing
> gain = lf * UnitMDip';
> note that here lf is a vector (no 3 columns).
>
> However this is patchy and not thorough. So can you please tell me if there
> is a way to do it with regular ft functions?
> thank you
> Yuval
>
>
>
>
> Dr .Harpaz
>
> BIU MEG lab
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From yuvharpaz at gmail.com  Tue Jun 18 19:01:40 2013
From: yuvharpaz at gmail.com (Yuval Harpaz)
Date: Tue, 18 Jun 2013 20:01:40 +0300
Subject: [FieldTrip] fixed dipole orientation for MNE
In-Reply-To: <CABPNLUpqBxHFfrw=9mvesB2RXirhnyQH_-Mt5+icKA5HMcrkXQ@mail.gmail.com>
References: <CAGQZS_m+RSW6LDOmbYc9MDtwf1dUM==a4c3Nc9BRA5WYneTp6w@mail.gmail.com>
	<CABPNLUpqBxHFfrw=9mvesB2RXirhnyQH_-Mt5+icKA5HMcrkXQ@mail.gmail.com>
Message-ID: <CAGQZS_=G15YJw-Cc+aQrHhwSXq9pXC8P5qrCpbU8LAkqkMCBUg@mail.gmail.com>

Well, it uses fixed orientation but it calculates the orientation based on
the signal, not on the anatomy. I am trying to reduce leakage problems by
limiting orientation according to structure. you CAN specify dip.mom but
this is really buggy.
thanks


On 18 June 2013 16:16, Eelke Spaak <eelke.spaak at donders.ru.nl> wrote:

> Dear Yuval,
>
> The LCMV and DICS beamforming implementations in FieldTrip support
> cfg.<method>.fixedori = 'yes', where <method> is either 'lcmv' or
> 'dics'. This will compute a filter which constrains each dipole to
> point in the strongest orientation. For SAM I think this is not
> implemented, and for MNE I have no clue.
>
> Does this answer your question? Or are you lookling for another type
> of fixed orientation, maybe based on anatomy or so?
>
> Best,
> Eelke
>
> On 18 June 2013 14:58, Yuval Harpaz <yuvharpaz at gmail.com> wrote:
> > Dear group
> > I would like to ask again
> > (
> http://mailman.science.ru.nl/pipermail/fieldtrip/2011-February/003456.html
> )
> > about head model with fixed dipole orientation (obtained from
> freesurfer),
> > as I saw no reply to the previous message.
> >
> > I understand that there is no civilized way, currently, to tell MNE or
> > beamforming to use fixed orientation, or am I wrong?
> >
> > applying 'sam' I managed to set dipole orinetation by making a dip.mom
> field
> > in addition to dip.pos and by
> > gain = lf;
> > instead of the existing
> > gain = lf * UnitMDip';
> > note that here lf is a vector (no 3 columns).
> >
> > However this is patchy and not thorough. So can you please tell me if
> there
> > is a way to do it with regular ft functions?
> > thank you
> > Yuval
> >
> >
> >
> >
> > Dr .Harpaz
> >
> > BIU MEG lab
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
Yuval




Dr .Harpaz

BIU MEG lab <http://faculty.biu.ac.il/~goldsa/index.html>
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From mje.mads at gmail.com  Tue Jun 18 23:52:02 2013
From: mje.mads at gmail.com (Mads Jensen)
Date: Tue, 18 Jun 2013 23:52:02 +0200
Subject: [FieldTrip] select trial by previous trigger code
In-Reply-To: <51C02456.2000800@donders.ru.nl>
References: <51C01DD1.5070005@gmail.com> <51C02456.2000800@donders.ru.nl>
Message-ID: <51C0D682.7070008@gmail.com>

HI Jörn & Stan,

Thanks for your replies and advises. It worked.

thanks, best
mads



On 06/18/2013 11:11 AM, "Jörn M. Horschig" wrote:
> Hi Mads,
>
> such things are possible if you write your own trial function.
> Basically, you need to read in the events (i.e. trigger values) and then
> make a selection based on that, see also here:
> http://fieldtrip.fcdonders.nl/example/making_your_own_trialfun_for_conditional_trial_definition?s[]=trialfun
>
> http://fieldtrip.fcdonders.nl/faq/what_is_the_relation_between_events_such_as_triggers_and_trials?s[]=trialfun
>
>
> Hope that helps!
> Best,
> Jörn
>
> On 6/18/2013 10:44 AM, Mads Jensen wrote:
>> Hi all,
>>
>> I would like to know if it is possible select a trail based on the
>> previous trigger code?
>>
>> I got a dataset (MEG, neuromeg) where sometimes the subject just press
>> a button and sometimes a cue is shown and they then press the button,
>> the button presses are coded "1" and the cue "2". So, what I would
>> like is to datasets one with trials where there has been no cue and
>> one dataset where the trials that have cue is. Is that possible to do
>> automatically or do I have to do a "by hand"?
>>
>> best wishes,
>> mads
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>


From marco.porta88 at gmail.com  Wed Jun 19 16:41:47 2013
From: marco.porta88 at gmail.com (Marco Porta)
Date: Wed, 19 Jun 2013 16:41:47 +0200
Subject: [FieldTrip] statistics on non-event-related fields
Message-ID: <CAP6m0dHxFfYpYHFqeSMf83drbHD8TxU=9LqO8eAr8K0QC4mdNw@mail.gmail.com>

Dear Fieldtrip experts,
I have a question regarding the statistics. How can I statistics on non
event-related fields in a between-trials.
Thanks,

Marco
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From eelke.spaak at donders.ru.nl  Wed Jun 19 16:50:48 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Wed, 19 Jun 2013 16:50:48 +0200
Subject: [FieldTrip] statistics on non-event-related fields
In-Reply-To: <CAP6m0dHxFfYpYHFqeSMf83drbHD8TxU=9LqO8eAr8K0QC4mdNw@mail.gmail.com>
References: <CAP6m0dHxFfYpYHFqeSMf83drbHD8TxU=9LqO8eAr8K0QC4mdNw@mail.gmail.com>
Message-ID: <CABPNLUp6KKoApdcKEXJ2EFY29=JoXPJD+utHZ+jpcR3x0pW2=g@mail.gmail.com>

Dear Marco,

What do you mean exactly with "non event-related fields"? I presume
there is some structure in your data that you want to consider as the
independent variable of interest, right? Some more information on what
you want to do would help us to help you.

Best,
Eelke

On 19 June 2013 16:41, Marco Porta <marco.porta88 at gmail.com> wrote:
> Dear Fieldtrip experts,
> I have a question regarding the statistics. How can I statistics on non
> event-related fields in a between-trials.
> Thanks,
>
> Marco
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From jdien07 at mac.com  Thu Jun 20 02:35:35 2013
From: jdien07 at mac.com (Joseph Dien)
Date: Wed, 19 Jun 2013 20:35:35 -0400
Subject: [FieldTrip] ft_dipolefitting options no longer working
Message-ID: <C1AE459D-6A06-4743-ABD1-CAE20510BD28@mac.com>

Hi,
    it looks like changes have been made to ft_dipolefitting that have resulted in the following options no longer working:

        cfg.grid.xgrid  = 'auto';
        cfg.grid.ygrid  = 'auto';
        cfg.grid.zgrid  = 'auto';

The header of the ft_dipolefitting file as of the 20130619 release says:

% This function depends on FT_PREPARE_DIPOLE_GRID which has the following options:
% cfg.grid.xgrid (default set in FT_PREPARE_DIPOLE_GRID: cfg.grid.xgrid = 'auto'), documented
% cfg.grid.ygrid (default set in FT_PREPARE_DIPOLE_GRID: cfg.grid.ygrid = 'auto'), documented
% cfg.grid.zgrid (default set in FT_PREPARE_DIPOLE_GRID: cfg.grid.zgrid = 'auto'), documented

but a Find Files search indicates that FT_PREPARE_DIPOLE_GRID no longer exists.

I don't have copies of FieldTrip older than Feb 2013 so I can't check directly but I know that my function call used to work and no longer does.

Can someone help me find a fix for this?

Any help appreciated!

Joe

--------------------------------------------------------------------------------

Joseph Dien,
Senior Research Scientist
University of Maryland 

E-mail: jdien07 at mac.com
Phone: 301-226-8848
Fax: 301-226-8811
http://joedien.com//











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From jdien07 at mac.com  Thu Jun 20 04:41:49 2013
From: jdien07 at mac.com (Joseph Dien)
Date: Wed, 19 Jun 2013 22:41:49 -0400
Subject: [FieldTrip] ft_dipolefitting options no longer working
In-Reply-To: <C1AE459D-6A06-4743-ABD1-CAE20510BD28@mac.com>
References: <C1AE459D-6A06-4743-ABD1-CAE20510BD28@mac.com>
Message-ID: <B8CFEB76-33B2-474E-856C-4ABE53E5290C@mac.com>

Okay, I got this sorted out.  I was able to use ft_prepare_sourcemodel to set up the config variable.
The header info of ft_dipolefitting should get updated though.

Cheers!

Joe

On Jun 19, 2013, at 8:35 PM, Joseph Dien <jdien07 at mac.com> wrote:

> Hi,
>     it looks like changes have been made to ft_dipolefitting that have resulted in the following options no longer working:
> 
>         cfg.grid.xgrid  = 'auto';
>         cfg.grid.ygrid  = 'auto';
>         cfg.grid.zgrid  = 'auto';
> 
> The header of the ft_dipolefitting file as of the 20130619 release says:
> 
> % This function depends on FT_PREPARE_DIPOLE_GRID which has the following options:
> % cfg.grid.xgrid (default set in FT_PREPARE_DIPOLE_GRID: cfg.grid.xgrid = 'auto'), documented
> % cfg.grid.ygrid (default set in FT_PREPARE_DIPOLE_GRID: cfg.grid.ygrid = 'auto'), documented
> % cfg.grid.zgrid (default set in FT_PREPARE_DIPOLE_GRID: cfg.grid.zgrid = 'auto'), documented
> 
> but a Find Files search indicates that FT_PREPARE_DIPOLE_GRID no longer exists.
> 
> I don't have copies of FieldTrip older than Feb 2013 so I can't check directly but I know that my function call used to work and no longer does.
> 
> Can someone help me find a fix for this?
> 
> Any help appreciated!
> 
> Joe
> 
> --------------------------------------------------------------------------------
> 
> Joseph Dien,
> Senior Research Scientist
> University of Maryland 
> 
> E-mail: jdien07 at mac.com
> Phone: 301-226-8848
> Fax: 301-226-8811
> http://joedien.com//
> 
> 
> 
> 
> 
> 
> 
> 
> 
> 
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


--------------------------------------------------------------------------------

Joseph Dien,
Senior Research Scientist
University of Maryland 

E-mail: jdien07 at mac.com
Phone: 301-226-8848
Fax: 301-226-8811
http://joedien.com//











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From marco.porta88 at gmail.com  Thu Jun 20 14:48:18 2013
From: marco.porta88 at gmail.com (Marco Porta)
Date: Thu, 20 Jun 2013 14:48:18 +0200
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 37
In-Reply-To: <mailman.1.1371722418.14241.fieldtrip@science.ru.nl>
References: <mailman.1.1371722418.14241.fieldtrip@science.ru.nl>
Message-ID: <CAP6m0dGkRm0uo+zweS10nmv6Oj-c-_gmFapqNRDyg9TL3SVE+A@mail.gmail.com>

Dear Users and Eelke,
I have spontaneous LFP data recorded intracranially. I'm interested in
studying phase correlation between sensors and assess such correlation
within single subjects studies. Is it possible to study statistical
significance in such correlation study or should i implement my own
statistic?
Thanks,

Marco



Dear Marco,
>
> What do you mean exactly with "non event-related fields"? I presume
> there is some structure in your data that you want to consider as the
> independent variable of interest, right? Some more information on what
> you want to do would help us to help you.
>
> Best,
> Eelke
>
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From marco.porta88 at gmail.com  Fri Jun 21 14:26:12 2013
From: marco.porta88 at gmail.com (Marco Porta)
Date: Fri, 21 Jun 2013 14:26:12 +0200
Subject: [FieldTrip] statistics on non-event-related fields
Message-ID: <CAP6m0dGJTG=i9dFLsOhL4o9+wp_TXZfMYOa2917ik2TGu-dJeg@mail.gmail.com>

Dear Users and Eelke,
I have spontaneous LFP data recorded intracranially. I'm interested in studying
phase correlation between sensors and assess such correlation within single
subjects studies. Is it possible to study statistical significance in such
correlation study or should i implement my own statistic?
Thanks,

Marco



> Dear Marco,
>
> What do you mean exactly with "non event-related fields"? I presume
> there is some structure in your data that you want to consider as the
> independent variable of interest, right? Some more information on what
> you want to do would help us to help you.
>
> Best,
> Eelke
>
>
>
>
> Dear Fieldtrip experts,
> I have a question regarding the statistics. How can I statistics on non
> event-related fields in a between-trials.
> Thanks,
> Marco
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From politzerahless at gmail.com  Fri Jun 21 20:42:32 2013
From: politzerahless at gmail.com (Stephen Politzer-Ahles)
Date: Fri, 21 Jun 2013 13:42:32 -0500
Subject: [FieldTrip] Using fsaverage in the minimum norm pipeline?
Message-ID: <CAJT2k_8-nPkauRD0ciptFjPJtqbXTXv-0Xnj5GNw1aJ2LR6LJA@mail.gmail.com>

Hello everyone,

I am working through the minimum norm pipeline (
http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate) on functional
data for multiple participants; for all but one of these participants I
also have anatomical MRI. For the one participant for whom I couldn't get
an MRI, I was hoping to use the freesurfer average surface (fsaverage), but
I'm having some difficulty getting volume conduction models and
sourcespaces from this brain aligned to CTF.

Basically, I'm able to read in the data and create a sourcespace and volume
conduction model using the code below. These models seem to be aligned to
MNI (see the axes on http://i.imgur.com/g0DPs8A.png). To to re-align them
to CTF, what I tried to do was manually do ft_volumerealign on the original
anatomical MRI, and then apply that transformation matrix (which I assume
specifies the transformation from MNI to CTF) to the sourcespace and volume
conductor (in the third and fourth blocks of code below). But the resulting
sourcespace and volume conductor are clearly not aligned to CTF (see the
axes on http://i.imgur.com/MAjyDkL.png), so I assume I am doing something
wrong with the transformation matrix. I admit I do not fully understand how
the transformation matrix is supposed to work, so if anyone has any
feedback I would greatly appreciate it.

Thank you!
Steve


% Read the source space
bnd  =
ft_read_headshape('/tools/freesurfer/subjects/fsaverage/bem/fsaverage-oct-6-src.fif',
'format', 'mne_source');
sourcespace = ft_convert_units(bnd, 'mm');

% Read in the anatomical MRI, segment, and make volume conduction model
fsaverage = ft_read_mri('orig.mgz');
cfg           = [];
cfg.coordsys  = 'spm';
cfg.output    = {'skullstrip' 'brain'};
seg = ft_volumesegment( cfg, fsaverage);
cfg = []
cfg.method = 'singleshell';
cfg.tissue = 'brain';
vol = ft_prepare_headmodel( cfg, seg );

% Get a transformation matrix from MNI to CTF
cfg = [];
cfg.method = 'interactive';
seg_ctf = ft_volumerealign(cfg2, seg); % manually identify NAS, LAP, and RAP
T = seg_ctf.transform;

% Transform the sourcespace and vol
sourcespace_trans = ft_transform_geometry( T, sourcespace );
vol_trans = vol;
vol_trans.bnd = ft_transform_geometry( T, vol_trans.bnd );

% Plot the un-transformed vol and sourcespace (aligned to MNI)
figure;hold on;
ft_plot_vol(vol, 'facecolor', 'none');alpha 0.5;
ft_plot_mesh(sourcespace, 'edgecolor', 'none'); camlight

% Plot the transformed vol and sourcespace
figure;hold on;
ft_plot_vol(vol_trans, 'facecolor', 'none');alpha 0.5;
ft_plot_mesh(sourcespace_trans, 'edgecolor', 'none'); camlight



--
Stephen Politzer-Ahles
University of Kansas
Linguistics Department
http://people.ku.edu/~sjpa/
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From polomacnenad at gmail.com  Sat Jun 22 13:34:56 2013
From: polomacnenad at gmail.com (Nenad Polomac)
Date: Sat, 22 Jun 2013 13:34:56 +0200
Subject: [FieldTrip] padding of segmented data
Message-ID: <CAEk4EpFoOvobO+Ay2GQgx9k4h3g1wZAOoHoZ-t8u-qSodoYN5A@mail.gmail.com>

Dear all,

In my pipeline I need two times to filter data with ft_preprocessing. Is it
somehow possible to pad trials after segmentation? I need this in order to
avoid filter artifacts during the second filtering.

Thank you in advance!

Nenad
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From caspervanheck at gmail.com  Sat Jun 22 14:32:45 2013
From: caspervanheck at gmail.com (Casper van Heck)
Date: Sat, 22 Jun 2013 14:32:45 +0200
Subject: [FieldTrip] padding of segmented data
In-Reply-To: <CAEk4EpFoOvobO+Ay2GQgx9k4h3g1wZAOoHoZ-t8u-qSodoYN5A@mail.gmail.com>
References: <CAEk4EpFoOvobO+Ay2GQgx9k4h3g1wZAOoHoZ-t8u-qSodoYN5A@mail.gmail.com>
Message-ID: <CAJ7RtREwKrgNVCko=XkrjofHJduL64iEU0mESovdcrXqsm7M0A@mail.gmail.com>

Dear Nenad,

I think the option cfg.padding only works for that iteration of
ft_preprocessing, but what you can do, is select larger segments initially,
and then run ft_preprocessing again with smaller segments.

While you can set ft_preprocessing to apply multiple different filters in
one go (like a low-pass, a high-pass, and a DFT-filter, for example), using
a similar filter multiple times (like a high-pass filter at 4Hz, and
another at 8Hz) is usually not required, or recommended. If you do multiple
analyses on the same data (which, for example, require different filters)
you could find it useful to create multiple smaller pipelines with their
own ft_preprocessing. Debugging complex analyses can be a lot easier that
way:)

Hope this helps,

Casper


On Sat, Jun 22, 2013 at 1:34 PM, Nenad Polomac <polomacnenad at gmail.com>wrote:

> Dear all,
>
> In my pipeline I need two times to filter data with ft_preprocessing. Is
> it somehow possible to pad trials after segmentation? I need this in order
> to avoid filter artifacts during the second filtering.
>
> Thank you in advance!
>
> Nenad
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From mbj0310 at gmail.com  Mon Jun 24 06:27:47 2013
From: mbj0310 at gmail.com (Beom Jun Min)
Date: Mon, 24 Jun 2013 13:27:47 +0900
Subject: [FieldTrip] Decreased baseline level after using ICA in ERP data
Message-ID: <CA+v9jvKJnKAfsQDwoDhNVSPAKCmpOpwut8vdmFXa1akp_1WDGA@mail.gmail.com>

Dear all,

I have ERP data and now I am dealing with ICA to remove muscle and eye
artifacts.
However, I found that after ft_rejectcomponent, the baseline level of the
segmented epoch decreased. (The baselinewindow is [-0.2 0].)
The baseline level decreased even though I rejected only one component.

My script is shown below.

*%% Removing the Artifacts*
*cfg = [];
*
*cfg.component = [ ]; % to be removed component(s)*
*post_ICA_temp6 = ft_rejectcomponent(cfg, comp_detrand, data_raw);*
*
*
*%% timelocking*
*
*
*cfg = [];*
*timelock_temp6 = ft_timelockanalysis(cfg, post_ICA_temp6);*
*
*
*%% Plot*
*
*
*figure;*
*cfg = [];*
*cfg.layout = lay;*
*cfg.interactive = 'yes';*
*cfg.channel = ['all', {'-EKG', '-EMG'}];*
*ft_multiplotER(cfg, timelock_temp6)*

Is there something that I missed?

Thanks.

BJ

-- 
BeomJun Min, M.D.

Department of Medical System Engineering (DMSE)
Gwangju Institute of Science and Technology (GIST)
261 Cheomdan-gwagiro(Oryong-dong), Buk-gu, Gwangju
500-712, Republic of Korea (South)
Phone: +82-62-715-3266 / Fax: +82-62-715-3244
E-mail: mbj0310 at gmail.com, http://bmssa.gist.ac.kr
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From d.lozanosoldevilla at fcdonders.ru.nl  Mon Jun 24 10:25:24 2013
From: d.lozanosoldevilla at fcdonders.ru.nl (Lozano Soldevilla, D. (Diego))
Date: Mon, 24 Jun 2013 10:25:24 +0200 (CEST)
Subject: [FieldTrip] Decreased baseline level after using ICA in ERP data
In-Reply-To: <CA+v9jvKJnKAfsQDwoDhNVSPAKCmpOpwut8vdmFXa1akp_1WDGA@mail.gmail.com>
Message-ID: <831995030.1708865.1372062324986.JavaMail.root@sculptor.zimbra.ru.nl>

Dear Beom Jun, I see multiple scenarios why this baseline activity decrease could happen. First of all, how the component you're rejecting look like (i.e. "blink component")? Do you see this activity decrease after the baseline period? The "quality" of the ICA decomposition, how well your artifact/component of interest has been isolated by algorithm in time (i.e. blink time courses) and space (marked frontal topography), will determine the activity that later on you'll reject/select. If your decomposition is not well suited, the rejection of a particular IC activity might have "extra" activity you don't want to reject (effect of interest), might be the algorithm is not able to isolate the components of interests (i.e. artifacts) or a combination of both. To evaluate the quality of your ICA decomposition you might have a look here ( http://www.ncbi.nlm.nih.gov/pubmed/19162199 ). Basically, the authors find that the ICA decomposition improves significantly " increased by removing the mean EEG at each channel for each epoch of data rather than the mean EEG in a prestimulus baseline" . In addition (see here: http://sccn.ucsd.edu/pipermail/eeglablist/2012/004925.html ), high-pass filtering above ~1hz improve the results. It's very important to feed ICA as much relevant data as you can use. The more the data, the better the decomposition. There's a rule of thumb that says that for a reliable IC decomposition 20 time points per channel 2 is needed (see here for a reference http://www.ncbi.nlm.nih.gov/pubmed/16904745 ) I hope that helps, Diego ----- Original Message -----
> From: "Beom Jun Min" <mbj0310 at gmail.com>
> To: "FieldTrip discussion list" <fieldtrip at science.ru.nl>
> Sent: Monday, 24 June, 2013 6:27:47 AM
> Subject: [FieldTrip] Decreased baseline level after using ICA in ERP
> data
> Dear all,
> I have ERP data and now I am dealing with ICA to remove muscle and eye
> artifacts.
> However, I found that after ft_rejectcomponent, the baseline level of
> the segmented epoch decreased. (The baselinewindow is [-0.2 0].)
> The baseline level decreased even though I rejected only one
> component.
> My script is shown below.
> %% Removing the Artifacts
> cfg = [];
> cfg.component = [ ]; % to be removed component(s)
> post_ICA_temp6 = ft_rejectcomponent(cfg, comp_detrand, data_raw);
> %% timelocking
> cfg = [];
> timelock_temp6 = ft_timelockanalysis(cfg, post_ICA_temp6);
> %% Plot
> figure;
> cfg = [];
> cfg.layout = lay;
> cfg.interactive = 'yes';
> cfg.channel = ['all', {'-EKG', '-EMG'}];
> ft_multiplotER(cfg, timelock_temp6)
> Is there something that I missed?
> Thanks.
> BJ
> --
> BeomJun Min, M.D.
> Department of Medical System Engineering (DMSE)
> Gwangju Institute of Science and Technology (GIST)
> 261 Cheomdan-gwagiro(Oryong-dong), Buk-gu, Gwangju
> 500-712, Republic of Korea (South)
> Phone: +82-62-715-3266 / Fax: +82-62-715-3244
> E-mail: mbj0310 at gmail.com , http://bmssa.gist.ac.kr
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
-- PhD Student Neuronal Oscillations Group Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen NL-6525 EN Nijmegen The Netherlands http://www.ru.nl/people/donders/lozano-soldevilla-d/
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From jm.horschig at donders.ru.nl  Mon Jun 24 10:43:11 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Mon, 24 Jun 2013 10:43:11 +0200
Subject: [FieldTrip] padding of segmented data
In-Reply-To: <CAJ7RtREwKrgNVCko=XkrjofHJduL64iEU0mESovdcrXqsm7M0A@mail.gmail.com>
References: <CAEk4EpFoOvobO+Ay2GQgx9k4h3g1wZAOoHoZ-t8u-qSodoYN5A@mail.gmail.com>
	<CAJ7RtREwKrgNVCko=XkrjofHJduL64iEU0mESovdcrXqsm7M0A@mail.gmail.com>
Message-ID: <51C8069F.5070707@donders.ru.nl>

Hi Nenad,

what Casper said is not quite true. You can pad segmented trials, but 
you are limited in how to pad. There are different ways of padding, and 
what Casper was referring to is true data padding. Once you segmented 
your trials you cannot get back to your recorded data and attach more 
data to it. This is because filtering artifacts at edges etc would 
result in discontinuities and the like. However, there are other ways to 
achieve what you want. The most elegant way in my opinion is what Casper 
already suggested. Just for completeness, you can still pad using 
zero-padding (i.e. adding a bunch of 0s in the beginning and at the end 
of your trials). Other ways are mean-padding (pad with the mean value), 
or edge-padding (using the first/last value to padding). However, with 
all these methods you mostly also add a discontinuity, but you 
explicitly ask for that in this case :) The most elegant solution here 
might be to use mirror-padding, which is recently implemented.
See here:
http://fieldtrip.fcdonders.nl/reference/ft_preprocessing
and here:
http://fieldtrip.fcdonders.nl/reference/ft_preproc_padding

Best,
Jörn

On 6/22/2013 2:32 PM, Casper van Heck wrote:
> Dear Nenad,
>
> I think the option cfg.padding only works for that iteration of 
> ft_preprocessing, but what you can do, is select larger segments 
> initially, and then run ft_preprocessing again with smaller segments.
>
> While you can set ft_preprocessing to apply multiple different filters 
> in one go (like a low-pass, a high-pass, and a DFT-filter, for 
> example), using a similar filter multiple times (like a high-pass 
> filter at 4Hz, and another at 8Hz) is usually not required, or 
> recommended. If you do multiple analyses on the same data (which, for 
> example, require different filters) you could find it useful to create 
> multiple smaller pipelines with their own ft_preprocessing. Debugging 
> complex analyses can be a lot easier that way:)
>
> Hope this helps,
>
> Casper
>
>
> On Sat, Jun 22, 2013 at 1:34 PM, Nenad Polomac <polomacnenad at gmail.com 
> <mailto:polomacnenad at gmail.com>> wrote:
>
>     Dear all,
>
>     In my pipeline I need two times to filter data with
>     ft_preprocessing. Is it somehow possible to pad trials
>     after segmentation? I need this in order to avoid filter artifacts
>     during the second filtering.
>
>     Thank you in advance!
>
>     Nenad
>
>     _______________________________________________
>     fieldtrip mailing list
>     fieldtrip at donders.ru.nl <mailto:fieldtrip at donders.ru.nl>
>     http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands

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From polomacnenad at gmail.com  Mon Jun 24 11:02:18 2013
From: polomacnenad at gmail.com (Nenad Polomac)
Date: Mon, 24 Jun 2013 11:02:18 +0200
Subject: [FieldTrip] padding of segmented data
Message-ID: <CAEk4EpHDCCqhQvGRLShGfFU98Q2ccCsy1D=CRbadOzJf6G3ReA@mail.gmail.com>

Hi Jörn and Casper,

Thank you very for your answers
I will use Jörns suggestion. I wasn't aware that you upgraded
ft_preprocessing.
All the best!

Nenad

On 24 June 2013 10:44, <fieldtrip-request at science.ru.nl> wrote:

> Send fieldtrip mailing list submissions to
>         fieldtrip at science.ru.nl
>
> To subscribe or unsubscribe via the World Wide Web, visit
>         http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> or, via email, send a message with subject or body 'help' to
>         fieldtrip-request at science.ru.nl
>
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>
> When replying, please edit your Subject line so it is more specific
> than "Re: Contents of fieldtrip digest..."
>
>
> Today's Topics:
>
>    1. Decreased baseline level after using ICA in ERP data
>       (Beom Jun Min)
>    2. Re: Decreased baseline level after using ICA in ERP data
>       (Lozano Soldevilla, D. (Diego))
>    3. Re: padding of segmented data (J?rn M. Horschig)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Mon, 24 Jun 2013 13:27:47 +0900
> From: Beom Jun Min <mbj0310 at gmail.com>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: [FieldTrip] Decreased baseline level after using ICA in ERP
>         data
> Message-ID:
>         <
> CA+v9jvKJnKAfsQDwoDhNVSPAKCmpOpwut8vdmFXa1akp_1WDGA at mail.gmail.com>
> Content-Type: text/plain; charset="iso-8859-1"
>
> Dear all,
>
> I have ERP data and now I am dealing with ICA to remove muscle and eye
> artifacts.
> However, I found that after ft_rejectcomponent, the baseline level of the
> segmented epoch decreased. (The baselinewindow is [-0.2 0].)
> The baseline level decreased even though I rejected only one component.
>
> My script is shown below.
>
> *%% Removing the Artifacts*
> *cfg = [];
> *
> *cfg.component = [ ]; % to be removed component(s)*
> *post_ICA_temp6 = ft_rejectcomponent(cfg, comp_detrand, data_raw);*
> *
> *
> *%% timelocking*
> *
> *
> *cfg = [];*
> *timelock_temp6 = ft_timelockanalysis(cfg, post_ICA_temp6);*
> *
> *
> *%% Plot*
> *
> *
> *figure;*
> *cfg = [];*
> *cfg.layout = lay;*
> *cfg.interactive = 'yes';*
> *cfg.channel = ['all', {'-EKG', '-EMG'}];*
> *ft_multiplotER(cfg, timelock_temp6)*
>
> Is there something that I missed?
>
> Thanks.
>
> BJ
>
> --
> BeomJun Min, M.D.
>
> Department of Medical System Engineering (DMSE)
> Gwangju Institute of Science and Technology (GIST)
> 261 Cheomdan-gwagiro(Oryong-dong), Buk-gu, Gwangju
> 500-712, Republic of Korea (South)
> Phone: +82-62-715-3266 / Fax: +82-62-715-3244
> E-mail: mbj0310 at gmail.com, http://bmssa.gist.ac.kr
> -------------- next part --------------
> An HTML attachment was scrubbed...
> URL: <
> http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20130624/02dd2d57/attachment-0001.html
> >
>
> ------------------------------
>
> Message: 2
> Date: Mon, 24 Jun 2013 10:25:24 +0200 (CEST)
> From: "Lozano Soldevilla, D. (Diego)"
>         <d.lozanosoldevilla at fcdonders.ru.nl>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] Decreased baseline level after using ICA in
>         ERP data
> Message-ID:
>         <
> 831995030.1708865.1372062324986.JavaMail.root at sculptor.zimbra.ru.nl>
> Content-Type: text/plain; charset="utf-8"
>
> Dear Beom Jun, I see multiple scenarios why this baseline activity
> decrease could happen. First of all, how the component you're rejecting
> look like (i.e. "blink component")? Do you see this activity decrease after
> the baseline period? The "quality" of the ICA decomposition, how well your
> artifact/component of interest has been isolated by algorithm in time (i.e.
> blink time courses) and space (marked frontal topography), will determine
> the activity that later on you'll reject/select. If your decomposition is
> not well suited, the rejection of a particular IC activity might have
> "extra" activity you don't want to reject (effect of interest), might be
> the algorithm is not able to isolate the components of interests (i.e.
> artifacts) or a combination of both. To evaluate the quality of your ICA
> decomposition you might have a look here (
> http://www.ncbi.nlm.nih.gov/pubmed/19162199 ). Basically, the authors
> find that the ICA decomposition improves significantly " increased by
> removing the mean EEG at each channel for each epoch of data rather than
> the mean EEG in a prestimulus baseline" . In addition (see here:
> http://sccn.ucsd.edu/pipermail/eeglablist/2012/004925.html ), high-pass
> filtering above ~1hz improve the results. It's very important to feed ICA
> as much relevant data as you can use. The more the data, the better the
> decomposition. There's a rule of thumb that says that for a reliable IC
> decomposition 20 time points per channel 2 is needed (see here for a
> reference http://www.ncbi.nlm.nih.gov/pubmed/16904745 ) I hope that
> helps, Diego ----- Original Message -----
> > From: "Beom Jun Min" <mbj0310 at gmail.com>
> > To: "FieldTrip discussion list" <fieldtrip at science.ru.nl>
> > Sent: Monday, 24 June, 2013 6:27:47 AM
> > Subject: [FieldTrip] Decreased baseline level after using ICA in ERP
> > data
> > Dear all,
> > I have ERP data and now I am dealing with ICA to remove muscle and eye
> > artifacts.
> > However, I found that after ft_rejectcomponent, the baseline level of
> > the segmented epoch decreased. (The baselinewindow is [-0.2 0].)
> > The baseline level decreased even though I rejected only one
> > component.
> > My script is shown below.
> > %% Removing the Artifacts
> > cfg = [];
> > cfg.component = [ ]; % to be removed component(s)
> > post_ICA_temp6 = ft_rejectcomponent(cfg, comp_detrand, data_raw);
> > %% timelocking
> > cfg = [];
> > timelock_temp6 = ft_timelockanalysis(cfg, post_ICA_temp6);
> > %% Plot
> > figure;
> > cfg = [];
> > cfg.layout = lay;
> > cfg.interactive = 'yes';
> > cfg.channel = ['all', {'-EKG', '-EMG'}];
> > ft_multiplotER(cfg, timelock_temp6)
> > Is there something that I missed?
> > Thanks.
> > BJ
> > --
> > BeomJun Min, M.D.
> > Department of Medical System Engineering (DMSE)
> > Gwangju Institute of Science and Technology (GIST)
> > 261 Cheomdan-gwagiro(Oryong-dong), Buk-gu, Gwangju
> > 500-712, Republic of Korea (South)
> > Phone: +82-62-715-3266 / Fax: +82-62-715-3244
> > E-mail: mbj0310 at gmail.com , http://bmssa.gist.ac.kr
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> -- PhD Student Neuronal Oscillations Group Donders Institute for Brain,
> Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud
> University Nijmegen NL-6525 EN Nijmegen The Netherlands
> http://www.ru.nl/people/donders/lozano-soldevilla-d/
> -------------- next part --------------
> An HTML attachment was scrubbed...
> URL: <
> http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20130624/ea1393f7/attachment-0001.html
> >
>
> ------------------------------
>
> Message: 3
> Date: Mon, 24 Jun 2013 10:43:11 +0200
> From: "J?rn M. Horschig" <jm.horschig at donders.ru.nl>
> To: fieldtrip at science.ru.nl
> Subject: Re: [FieldTrip] padding of segmented data
> Message-ID: <51C8069F.5070707 at donders.ru.nl>
> Content-Type: text/plain; charset="iso-8859-1"; Format="flowed"
>
> Hi Nenad,
>
> what Casper said is not quite true. You can pad segmented trials, but
> you are limited in how to pad. There are different ways of padding, and
> what Casper was referring to is true data padding. Once you segmented
> your trials you cannot get back to your recorded data and attach more
> data to it. This is because filtering artifacts at edges etc would
> result in discontinuities and the like. However, there are other ways to
> achieve what you want. The most elegant way in my opinion is what Casper
> already suggested. Just for completeness, you can still pad using
> zero-padding (i.e. adding a bunch of 0s in the beginning and at the end
> of your trials). Other ways are mean-padding (pad with the mean value),
> or edge-padding (using the first/last value to padding). However, with
> all these methods you mostly also add a discontinuity, but you
> explicitly ask for that in this case :) The most elegant solution here
> might be to use mirror-padding, which is recently implemented.
> See here:
> http://fieldtrip.fcdonders.nl/reference/ft_preprocessing
> and here:
> http://fieldtrip.fcdonders.nl/reference/ft_preproc_padding
>
> Best,
> J?rn
>
> On 6/22/2013 2:32 PM, Casper van Heck wrote:
> > Dear Nenad,
> >
> > I think the option cfg.padding only works for that iteration of
> > ft_preprocessing, but what you can do, is select larger segments
> > initially, and then run ft_preprocessing again with smaller segments.
> >
> > While you can set ft_preprocessing to apply multiple different filters
> > in one go (like a low-pass, a high-pass, and a DFT-filter, for
> > example), using a similar filter multiple times (like a high-pass
> > filter at 4Hz, and another at 8Hz) is usually not required, or
> > recommended. If you do multiple analyses on the same data (which, for
> > example, require different filters) you could find it useful to create
> > multiple smaller pipelines with their own ft_preprocessing. Debugging
> > complex analyses can be a lot easier that way:)
> >
> > Hope this helps,
> >
> > Casper
> >
> >
> > On Sat, Jun 22, 2013 at 1:34 PM, Nenad Polomac <polomacnenad at gmail.com
> > <mailto:polomacnenad at gmail.com>> wrote:
> >
> >     Dear all,
> >
> >     In my pipeline I need two times to filter data with
> >     ft_preprocessing. Is it somehow possible to pad trials
> >     after segmentation? I need this in order to avoid filter artifacts
> >     during the second filtering.
> >
> >     Thank you in advance!
> >
> >     Nenad
> >
> >     _______________________________________________
> >     fieldtrip mailing list
> >     fieldtrip at donders.ru.nl <mailto:fieldtrip at donders.ru.nl>
> >     http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >
> >
> >
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
> --
> J?rn M. Horschig
> PhD Student
> Donders Institute for Brain, Cognition and Behaviour
> Centre for Cognitive Neuroimaging
> Radboud University Nijmegen
> Neuronal Oscillations Group
> FieldTrip Development Team
>
> P.O. Box 9101
> NL-6500 HB Nijmegen
> The Netherlands
>
> Contact:
> E-Mail: jm.horschig at donders.ru.nl
> Tel:    +31-(0)24-36-68493
> Web: http://www.ru.nl/donders
>
> Visiting address:
> Trigon, room 2.30
> Kapittelweg 29
> NL-6525 EN Nijmegen
> The Netherlands
>
> -------------- next part --------------
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>
> ------------------------------
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
> End of fieldtrip Digest, Vol 31, Issue 41
> *****************************************
>
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From eelke.spaak at donders.ru.nl  Mon Jun 24 11:31:35 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Mon, 24 Jun 2013 11:31:35 +0200
Subject: [FieldTrip] statistics on non-event-related fields
In-Reply-To: <CAP6m0dGJTG=i9dFLsOhL4o9+wp_TXZfMYOa2917ik2TGu-dJeg@mail.gmail.com>
References: <CAP6m0dGJTG=i9dFLsOhL4o9+wp_TXZfMYOa2917ik2TGu-dJeg@mail.gmail.com>
Message-ID: <CABPNLUrej3zMr7F7JW1Uvbz5ogdyFORFGhKuWVqr0a2pYN=NcA@mail.gmail.com>

Dear Marco,

The FieldTrip statistics routines support permutation of condition
labels among units of observation. I guess in your data you don't
really have 'units of observation', i.e. you have continuous data of
one (or several) subjects. In that case I would recommend taking care
of the statistics outside of FieldTrip, for instance by using a
randomisation approach based on shifting time series of different
channels by different, random, amounts. The coupling values obtained
by these shifted time series can serve as a distribution under the
null hypothesis of no coupling. The usual cluster machinery can then
be applied (i.e. combining above-(nonparametric)threshold
time-frequency-channel voxels into cluster candidates, compute cluster
statistics per randomization, and compare the observed cluster
statistic to the randomization distribution). You would also need to
write this yourself, but it should not be very difficult. The
mex-files bwlabel and spm_bwlabel (distributed with FieldTrip) are
very useful; they give index labels to connected clusters in a binary
matrix.

Note, however, that there is an important caveat with the approach I
describe here. The time shifting per channel also destroys the
between-channel structure in your data that is due to electric volume
conduction. So even if you find significant connectivity by this
approach, although the connectivity would be 'real' in a sense, it
still might not be meaningful if you do not account for this volume
conduction. This is something to think about apart from the
statistics.

Hope this helps.
Best,
Eelke

On 21 June 2013 14:26, Marco Porta <marco.porta88 at gmail.com> wrote:
> Dear Users and Eelke,
> I have spontaneous LFP data recorded intracranially. I'm interested in
> studying phase correlation between sensors and assess such correlation
> within single subjects studies. Is it possible to study statistical
> significance in such correlation study or should i implement my own
> statistic?
> Thanks,
>
> Marco
>
>
>
>> Dear Marco,
>>
>> What do you mean exactly with "non event-related fields"? I presume
>> there is some structure in your data that you want to consider as the
>> independent variable of interest, right? Some more information on what
>> you want to do would help us to help you.
>>
>> Best,
>> Eelke
>>
>>
>>
>>
>> Dear Fieldtrip experts,
>> I have a question regarding the statistics. How can I statistics on non
>> event-related fields in a between-trials.
>> Thanks,
>> Marco
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From nomeserio at gmail.com  Mon Jun 24 14:43:06 2013
From: nomeserio at gmail.com (Michele Barsotti)
Date: Mon, 24 Jun 2013 14:43:06 +0200
Subject: [FieldTrip] Loading Data into a fieldtrip structure
Message-ID: <CAGZjeH68Aq61DQBgPvVhOj2=f2ndrtWDuxFn58TKb8An4BUm7g@mail.gmail.com>

Dear FieldTrip Users,
  I'm working with eeglab since 2 years and now I would like to use also
fieldtrip. I've got many dataset in .mat format organized as [channels x
dataframe]. For each dataset I've got the channel location in a .ced file
format.
Can anyone help me to import these dataset into a fieldtrip data structure?

The channels (rows of the variable contained in the .mat file) are
organized like that:
1- time
2:17 - eeg channels
18:end - possible triggers

thank you in advance

cheers

-- 
        -Michele-
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From d.lozanosoldevilla at fcdonders.ru.nl  Mon Jun 24 14:55:18 2013
From: d.lozanosoldevilla at fcdonders.ru.nl (Diego Lozano Soldevilla)
Date: Mon, 24 Jun 2013 14:55:18 +0200
Subject: [FieldTrip] Loading Data into a fieldtrip structure
In-Reply-To: <CAGZjeH68Aq61DQBgPvVhOj2=f2ndrtWDuxFn58TKb8An4BUm7g@mail.gmail.com>
References: <CAGZjeH68Aq61DQBgPvVhOj2=f2ndrtWDuxFn58TKb8An4BUm7g@mail.gmail.com>
Message-ID: <CAEVBUjgj4FBxO-oGC5AcaS2h4V-2L=9DaGq1zbcB7a6B0CVz-A@mail.gmail.com>

Dear Michele,

You might have a look to the following FAQ:
http://fieldtrip.fcdonders.nl/faq/how_can_i_import_my_own_dataformat?s[]=import&s[]=data

I'm not sure about the state of the art of the eeglab2fieldtrip.m function
but it might help you out as well. To know more about the fieldtrip data
type field structures you need to have to work in Fieldtrip, the
ft_datatype* functions will be important for you, i.e.:

ft_datatype_freq
ft_datatype_raw
ft_datatype_sens
ft_datatype_timelock

I hope that helps

Diego






On 24 June 2013 14:43, Michele Barsotti <nomeserio at gmail.com> wrote:

> Dear FieldTrip Users,
>   I'm working with eeglab since 2 years and now I would like to use also
> fieldtrip. I've got many dataset in .mat format organized as [channels x
> dataframe]. For each dataset I've got the channel location in a .ced file
> format.
> Can anyone help me to import these dataset into a fieldtrip data structure?
>
> The channels (rows of the variable contained in the .mat file) are
> organized like that:
> 1- time
> 2:17 - eeg channels
> 18:end - possible triggers
>
> thank you in advance
>
> cheers
>
> --
>         -Michele-
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From david.schubring at uni-konstanz.de  Mon Jun 24 16:34:46 2013
From: david.schubring at uni-konstanz.de (David Schubring)
Date: Mon, 24 Jun 2013 16:34:46 +0200
Subject: [FieldTrip]  Matlab 2012/2013
In-Reply-To: <CAEVBUjgj4FBxO-oGC5AcaS2h4V-2L=9DaGq1zbcB7a6B0CVz-A@mail.gmail.com>
References: <CAGZjeH68Aq61DQBgPvVhOj2=f2ndrtWDuxFn58TKb8An4BUm7g@mail.gmail.com>
	<CAEVBUjgj4FBxO-oGC5AcaS2h4V-2L=9DaGq1zbcB7a6B0CVz-A@mail.gmail.com>
Message-ID: <51C85906.2090204@uni-konstanz.de>

Dear FieldTrip Users,

I was wondering if the incompatibility issues with fieldtrip and the 
latest MATLAB 2013a version still exist (and if so, which bugs exactly 
occur)?

(Some of our Matlab 2012a/b installations stopped working, maybe due to 
the latest java-update, and only the 2013 version still works.)

Thanks in advance and best regards,
David Schubring


From politzerahless at gmail.com  Mon Jun 24 17:19:59 2013
From: politzerahless at gmail.com (Stephen Politzer-Ahles)
Date: Mon, 24 Jun 2013 10:19:59 -0500
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 27
In-Reply-To: <mailman.200.1371117940.1243.fieldtrip@science.ru.nl>
References: <mailman.200.1371117940.1243.fieldtrip@science.ru.nl>
Message-ID: <CAJT2k_-XpQZ0diLY+pYtyOmD0R1s_0rKKRNSzfT2Ac9iuWPEbA@mail.gmail.com>

Hi everyone,

I recently tried
http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_spaceand
noticed some inconsistencies between the example code and the results;
I updated the code on the wiki but I wanted to send a message to the list
to double-check whether my changes are ok. Firstly, I had to add a call to
ft_convert_units, because otherwise the vol was expressed in mm and the
grid in cm, causing the grid to be much smaller than the volume conductor
(see http://i.imgur.com/gzct9Dm.png). Is this change ok?

The result I get is still not quite consistent with the examples shown on
that page, though; in my result, the grid is a cube (
http://i.imgur.com/NSgCFpg.png), whereas in the example the grid is
brain-shaped. I used the same Fieldtrip brain template and the same code
from the example (except for the change above), so I'm not sure if the
difference is due to different plot settings, a change in the Fieldtrip
code since this example was made, or a change in the sample brain included
in Fieldtrip since the example was made.

Best,
Steve


On Thu, Jun 13, 2013 at 5:05 AM, <fieldtrip-request at science.ru.nl> wrote:
>
> Send fieldtrip mailing list submissions to
>         fieldtrip at science.ru.nl
>
> To subscribe or unsubscribe via the World Wide Web, visit
>         http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> or, via email, send a message with subject or body 'help' to
>         fieldtrip-request at science.ru.nl
>
> You can reach the person managing the list at
>         fieldtrip-owner at science.ru.nl
>
> When replying, please edit your Subject line so it is more specific
> than "Re: Contents of fieldtrip digest..."
>
>
> Today's Topics:
>
>    1. Re: Source statistics on spatio-temporal source
>       reconstruction data (MNE) (Nicolai Mersebak)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Thu, 13 Jun 2013 12:04:34 +0200
> From: Nicolai Mersebak <nicolai at mersebak.dk>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] Source statistics on spatio-temporal source
>         reconstruction data (MNE)
> Message-ID: <6F3697BB-194F-422F-A1BF-EBBB132F805B at mersebak.dk>
> Content-Type: text/plain; charset="iso-8859-1"
>
> Thanks to all of you for your comments and ideas - they are very helpful!
>
> I ( off course :) ) have some follow up questions.
>
> I have created an ERP structure for my MNE source, so the only think
which I need and that is not straight forward is the neighbour structure.
>
> I am using the standard bem template
(fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model
and use the following code to get a grid for all subjects as I don't have
any subject specific information regarding the anatomy.
>
> cfg = [];
> cfg.grid.xgrid  = -100:10:100;
> cfg.grid.ygrid  = -100:10:100;
> cfg.grid.zgrid  = -100:10:100;
> cfg.grid.tight  = 'yes';
> cfg.grid.unit   = hdm.unit; % unit: mm
> cfg.vol        = hdm;
> grid  = ft_prepare_sourcemodel(cfg);
>
>
> @Jan-Mathijs and Stephan: I guess making a subject specific grid based on
a warped template requires anatomic information for each subject, e.g. a
MRI image like this tutorial shows:
>
http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
>
> The final grid output in the tutorial - does it have this 3D grid which
can be used as a neighbour structure ?
>
> I am not sure how to go from my cortical sheet [vertices x
coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
>
> A second thing I would like to know is, if any of you have tried to use
an atlas (e.g ALL template atlas) where the regions now are channels in the
permutation test? Going from source points to atlas regions can be done
through ft_sourcestatistics, but I am still interested in keeping the
temporal dimension. The reason to use atlas regions instead of source
points is to decrease the computation time.
>
> Best,
>
> Nicolai
>
>


On Thu, Jun 13, 2013 at 5:05 AM, <fieldtrip-request at science.ru.nl> wrote:

> Send fieldtrip mailing list submissions to
>         fieldtrip at science.ru.nl
>
> To subscribe or unsubscribe via the World Wide Web, visit
>         http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> or, via email, send a message with subject or body 'help' to
>         fieldtrip-request at science.ru.nl
>
> You can reach the person managing the list at
>         fieldtrip-owner at science.ru.nl
>
> When replying, please edit your Subject line so it is more specific
> than "Re: Contents of fieldtrip digest..."
>
>
> Today's Topics:
>
>    1. Re: Source statistics on spatio-temporal source
>       reconstruction data (MNE) (Nicolai Mersebak)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Thu, 13 Jun 2013 12:04:34 +0200
> From: Nicolai Mersebak <nicolai at mersebak.dk>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] Source statistics on spatio-temporal source
>         reconstruction data (MNE)
> Message-ID: <6F3697BB-194F-422F-A1BF-EBBB132F805B at mersebak.dk>
> Content-Type: text/plain; charset="iso-8859-1"
>
> Thanks to all of you for your comments and ideas - they are very helpful!
>
> I ( off course :) ) have some follow up questions.
>
> I have created an ERP structure for my MNE source, so the only think which
> I need and that is not straight forward is the neighbour structure.
>
> I am using the standard bem template
> (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model
> and use the following code to get a grid for all subjects as I don't have
> any subject specific information regarding the anatomy.
>
> cfg = [];
> cfg.grid.xgrid  = -100:10:100;
> cfg.grid.ygrid  = -100:10:100;
> cfg.grid.zgrid  = -100:10:100;
> cfg.grid.tight  = 'yes';
> cfg.grid.unit   = hdm.unit; % unit: mm
> cfg.vol        = hdm;
> grid  = ft_prepare_sourcemodel(cfg);
>
>
> @Jan-Mathijs and Stephan: I guess making a subject specific grid based on
> a warped template requires anatomic information for each subject, e.g. a
> MRI image like this tutorial shows:
>
> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
>
> The final grid output in the tutorial - does it have this 3D grid which
> can be used as a neighbour structure ?
>
> I am not sure how to go from my cortical sheet [vertices x
> coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
>
> A second thing I would like to know is, if any of you have tried to use an
> atlas (e.g ALL template atlas) where the regions now are channels in the
> permutation test? Going from source points to atlas regions can be done
> through ft_sourcestatistics, but I am still interested in keeping the
> temporal dimension. The reason to use atlas regions instead of source
> points is to decrease the computation time.
>
> Best,
>
> Nicolai
>
>
> Den 12/06/2013 kl. 18.58 skrev "smoratti at psi.ucm.es" <smoratti at psi.ucm.es
> >:
>
> >
> > I think Jan.Mathijs alternative suggestion is quite attractive. With the
> neighbors on a cortical sheet I also had the problems that sometimes the
> vertices do not have the same distance and then clustering may be biased to
> smaller or bigger clusters as the number of neighbors does not guarantee
> same cluster sizes. With the interpolation onto a 3D grid, you won't have
> that problem.
> >
> > best,
> >
> > Stephan
> >
> >
> > ________________________________________________________
> > Stephan Moratti, PhD
> >
> > see also: http://web.me.com/smoratti/
> >
> > Universidad Complutense de Madrid
> > Facultad de Psicolog?a
> > Departamento de Psicolog?a B?sica I
> > Campus de Somosaguas
> > 28223 Pozuelo de Alarc?n (Madrid)
> > Spain
> >
> > and
> >
> > Center for Biomedical Technology
> > Laboratory for Cognitive and Computational Neuroscience
> > Parque Cient?fico y Tecnol?gico de la Universidad Politecnica de Madrid
> > Campus Montegancedo
> > 28223 Pozuelo de Alarc?n (Madrid)
> > Spain
> >
> >
> > email: smoratti at psi.ucm.es
> > Tel.:    +34 679219982
> >
> > El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribi?:
> >
> >> An alternative would be to interpolate the cortical sheet to a 3D grid
> (where the grid is defined for each subject based on a warped template grid
> defined in a standard space), and then do clustering using a regular 3D
> spatial neighbourhood structure. The rationale being that two vertices on
> the sheet may appear as disconnected  (e.g. being on two sides of a sulcus)
> whereas, given the poor spatial resolution, they belong to the same spatial
> blob.
> >>
> >> Best,
> >> Jan-Mathijs
> >>
> >> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
> >>
> >>> Dear Nicolai,
> >>>
> >>> Indeed I have used ft_timelockstatistics for minimum norm source data.
> The trick is to put the source level data into a ERF structure. Determining
> the neighbors of a source surface with vertices is not trivial. However I
> used tess_vertconn.m from the BrainStorm toolbox to get the connectivity
> matrix that tells you who is a neighbor. This you can feed into
> timelockstats.
> >>>
> >>> Hope that helps,
> >>>
> >>> Stephan
> >>>
> >>> ________________________________________________________
> >>> Stephan Moratti, PhD
> >>>
> >>> see also: http://web.me.com/smoratti/
> >>>
> >>> Universidad Complutense de Madrid
> >>> Facultad de Psicolog?a
> >>> Departamento de Psicolog?a B?sica I
> >>> Campus de Somosaguas
> >>> 28223 Pozuelo de Alarc?n (Madrid)
> >>> Spain
> >>>
> >>> and
> >>>
> >>> Center for Biomedical Technology
> >>> Laboratory for Cognitive and Computational Neuroscience
> >>> Parque Cient?fico y Tecnol?gico de la Universidad Politecnica de Madrid
> >>> Campus Montegancedo
> >>> 28223 Pozuelo de Alarc?n (Madrid)
> >>> Spain
> >>>
> >>>
> >>> email: smoratti at psi.ucm.es
> >>> Tel.:    +34 679219982
> >>>
> >>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribi?:
> >>>
> >>>> Dear all,
> >>>>
> >>>> I have a question concerning the usage of ft_sourcegrandaverage and
> ft_sourcestatistics.
> >>>>
> >>>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal
> source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and
> 897 time points.
> >>>>
> >>>> Now I would like to use the cluster-based permutation test on my
> source reconstructed data. However it seems like ft_sourcegrandaverage and
> ft_sourcestatistics don't support source level time courses. E.g when I am
> using ft_sourcegrandaverage I am getting the following error:
> >>>>
> >>>> Error in ft_sourcegrandaverage (line 158)
> >>>>   dat(:,i) = tmp(:);
> >>>>
> >>>> Looking into the code:
> >>>>
> >>>>   for i=1:Nsubject
> >>>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter,
> varargin{i}));
> >>>>     dat(:,i) = tmp(:);
> >>>>     tmp = getsubfield(varargin{i}, 'inside');
> >>>>     inside(tmp,i) = 1;
> >>>>   end
> >>>>
> >>>> I see that "tmp" are getting the structure [N_sources x timepoints]
> from source.avg.pow for one subject, where "dat" requires the structure
> [N_sources x 1].
> >>>>
> >>>> I seached the mailing list for similar issues and found this thread:
> >>>>
> >>>>
> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
> >>>>
> >>>> Since I am interested in using the temporal dimension in my
> statistics, I would like to know if it is still not possible to use
> spatio-temporal source reconstructed data in ft_sourcestatistics and
> ft_sourcegrandaverage ?
> >>>>
> >>>> Or if any have succeeded in using the cluster-based permutation test
> on source level also including the temporal dimension ?
> >>>>
> >>>> Alternative I was thinking that I might could use
> ft_timelockstatistics, where I substituted the channels with sources, e.g
> instead of having 64 channels, I would now have 4050 "channels".
> >>>> If so I need to calculate a label structure and an appropriate
> neighbor structure, which I guess is possible as I have all the 3D
> coordinates for each source, e.g in leadfield.pos ?
> >>>> I know this is a work around solution, but have anyone tried or have
> any experience using such an approach ?
> >>>>
> >>>> Best,
> >>>>
> >>>> Nicolai
> >>>>
> >>>> _______________________________________________
> >>>> fieldtrip mailing list
> >>>> fieldtrip at donders.ru.nl
> >>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >>>
> >>> _______________________________________________
> >>> fieldtrip mailing list
> >>> fieldtrip at donders.ru.nl
> >>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >>
> >> Jan-Mathijs Schoffelen, MD PhD
> >>
> >> Donders Institute for Brain, Cognition and Behaviour,
> >> Centre for Cognitive Neuroimaging,
> >> Radboud University Nijmegen, The Netherlands
> >>
> >> Max Planck Institute for Psycholinguistics,
> >> Nijmegen, The Netherlands
> >>
> >> J.Schoffelen at donders.ru.nl
> >> Telephone: +31-24-3614793
> >>
> >> http://www.hettaligebrein.nl
> >>
> >> _______________________________________________
> >> fieldtrip mailing list
> >> fieldtrip at donders.ru.nl
> >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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>
> ------------------------------
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
> End of fieldtrip Digest, Vol 31, Issue 27
> *****************************************
>



-- 
Stephen Politzer-Ahles
University of Kansas
Linguistics Department
http://people.ku.edu/~sjpa/
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From a.stolk at fcdonders.ru.nl  Mon Jun 24 20:11:26 2013
From: a.stolk at fcdonders.ru.nl (Stolk, A.)
Date: Mon, 24 Jun 2013 20:11:26 +0200 (CEST)
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 27
In-Reply-To: <CAJT2k_-XpQZ0diLY+pYtyOmD0R1s_0rKKRNSzfT2Ac9iuWPEbA@mail.gmail.com>
Message-ID: <331233946.1725662.1372097486678.JavaMail.root@sculptor.zimbra.ru.nl>

Hi Steve, With respect to the cube vs. brain-shaped grid; this seems to be plotting-related? template_grid.inside in the snippet of code below selects only the grid points that have been determined as inside the brain, but with a negative inwardshift, hence it's also outside. ft_plot_mesh ( template_grid. pos ( template_grid. inside ,: ) ) ; % taken from the wiki Hopefully someone else has up-to-date knowledge to answer your question pertaining to the units (mm vs. cm) of the volume conductor and the source model. Best regards, Arjen ----- Oorspronkelijk bericht -----
> Van: "Stephen Politzer-Ahles" <politzerahless at gmail.com>
> Aan: fieldtrip at science.ru.nl
> Verzonden: Maandag 24 juni 2013 17:19:59
> Onderwerp: Re: [FieldTrip] fieldtrip Digest, Vol 31, Issue 27
> Hi everyone,
> I recently tried
> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space
> and noticed some inconsistencies between the example code and the
> results; I updated the code on the wiki but I wanted to send a message
> to the list to double-check whether my changes are ok. Firstly, I had
> to add a call to ft_convert_units, because otherwise the vol was
> expressed in mm and the grid in cm, causing the grid to be much
> smaller than the volume conductor (see http://i.imgur.com/gzct9Dm.png
> ). Is this change ok?
> The result I get is still not quite consistent with the examples shown
> on that page, though; in my result, the grid is a cube (
> http://i.imgur.com/NSgCFpg.png ), whereas in the example the grid is
> brain-shaped. I used the same Fieldtrip brain template and the same
> code from the example (except for the change above), so I'm not sure
> if the difference is due to different plot settings, a change in the
> Fieldtrip code since this example was made, or a change in the sample
> brain included in Fieldtrip since the example was made.
> Best,
> Steve
> On Thu, Jun 13, 2013 at 5:05 AM, < fieldtrip-request at science.ru.nl >
> wrote:
> >
> > Send fieldtrip mailing list submissions to
> > fieldtrip at science.ru.nl
> >
> > To subscribe or unsubscribe via the World Wide Web, visit
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > or, via email, send a message with subject or body 'help' to
> > fieldtrip-request at science.ru.nl
> >
> > You can reach the person managing the list at
> > fieldtrip-owner at science.ru.nl
> >
> > When replying, please edit your Subject line so it is more specific
> > than "Re: Contents of fieldtrip digest..."
> >
> >
> > Today's Topics:
> >
> > 1. Re: Source statistics on spatio-temporal source
> > reconstruction data (MNE) (Nicolai Mersebak)
> >
> >
> > ----------------------------------------------------------------------
> >
> > Message: 1
> > Date: Thu, 13 Jun 2013 12:04:34 +0200
> > From: Nicolai Mersebak < nicolai at mersebak.dk >
> > To: FieldTrip discussion list < fieldtrip at science.ru.nl >
> > Subject: Re: [FieldTrip] Source statistics on spatio-temporal source
> > reconstruction data (MNE)
> > Message-ID: < 6F3697BB-194F-422F-A1BF-EBBB132F805B at mersebak.dk >
> > Content-Type: text/plain; charset="iso-8859-1"
> >
> > Thanks to all of you for your comments and ideas - they are very
> > helpful!
> >
> > I ( off course :) ) have some follow up questions.
> >
> > I have created an ERP structure for my MNE source, so the only think
> > which I need and that is not straight forward is the neighbour
> > structure.
> >
> > I am using the standard bem template
> > (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head
> > model and use the following code to get a grid for all subjects as I
> > don't have any subject specific information regarding the anatomy.
> >
> > cfg = [];
> > cfg.grid.xgrid = -100:10:100;
> > cfg.grid.ygrid = -100:10:100;
> > cfg.grid.zgrid = -100:10:100;
> > cfg.grid.tight = 'yes';
> > cfg.grid.unit = hdm.unit; % unit: mm
> > cfg.vol = hdm;
> > grid = ft_prepare_sourcemodel(cfg);
> >
> >
> > @Jan-Mathijs and Stephan: I guess making a subject specific grid
> > based on a warped template requires anatomic information for each
> > subject, e.g. a MRI image like this tutorial shows:
> > http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
> >
> > The final grid output in the tutorial - does it have this 3D grid
> > which can be used as a neighbour structure ?
> >
> > I am not sure how to go from my cortical sheet [vertices x
> > coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour
> > structure ?
> >
> > A second thing I would like to know is, if any of you have tried to
> > use an atlas (e.g ALL template atlas) where the regions now are
> > channels in the permutation test? Going from source points to atlas
> > regions can be done through ft_sourcestatistics, but I am still
> > interested in keeping the temporal dimension. The reason to use
> > atlas regions instead of source points is to decrease the
> > computation time.
> >
> > Best,
> >
> > Nicolai
> >
> >
> On Thu, Jun 13, 2013 at 5:05 AM, < fieldtrip-request at science.ru.nl >
> wrote:
> > Send fieldtrip mailing list submissions to
> > fieldtrip at science.ru.nl
> > To subscribe or unsubscribe via the World Wide Web, visit
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > or, via email, send a message with subject or body 'help' to
> > fieldtrip-request at science.ru.nl
> > You can reach the person managing the list at
> > fieldtrip-owner at science.ru.nl
> > When replying, please edit your Subject line so it is more specific
> > than "Re: Contents of fieldtrip digest..."
> > Today's Topics:
> > 1. Re: Source statistics on spatio-temporal source
> > reconstruction data (MNE) (Nicolai Mersebak)
> > ----------------------------------------------------------------------
> > Message: 1
> > Date: Thu, 13 Jun 2013 12:04:34 +0200
> > From: Nicolai Mersebak < nicolai at mersebak.dk >
> > To: FieldTrip discussion list < fieldtrip at science.ru.nl >
> > Subject: Re: [FieldTrip] Source statistics on spatio-temporal source
> > reconstruction data (MNE)
> > Message-ID: < 6F3697BB-194F-422F-A1BF-EBBB132F805B at mersebak.dk >
> > Content-Type: text/plain; charset="iso-8859-1"
> > Thanks to all of you for your comments and ideas - they are very
> > helpful!
> > I ( off course :) ) have some follow up questions.
> > I have created an ERP structure for my MNE source, so the only think
> > which I need and that is not straight forward is the neighbour
> > structure.
> > I am using the standard bem template
> > (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head
> > model and use the following code to get a grid for all subjects as I
> > don't have any subject specific information regarding the anatomy.
> > cfg = [];
> > cfg.grid.xgrid = -100:10:100;
> > cfg.grid.ygrid = -100:10:100;
> > cfg.grid.zgrid = -100:10:100;
> > cfg.grid.tight = 'yes';
> > cfg.grid.unit = hdm.unit; % unit: mm
> > cfg.vol = hdm;
> > grid = ft_prepare_sourcemodel(cfg);
> > @Jan-Mathijs and Stephan: I guess making a subject specific grid
> > based
> > on a warped template requires anatomic information for each subject,
> > e.g. a MRI image like this tutorial shows:
> > http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
> > The final grid output in the tutorial - does it have this 3D grid
> > which can be used as a neighbour structure ?
> > I am not sure how to go from my cortical sheet [vertices x
> > coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour
> > structure ?
> > A second thing I would like to know is, if any of you have tried to
> > use an atlas (e.g ALL template atlas) where the regions now are
> > channels in the permutation test? Going from source points to atlas
> > regions can be done through ft_sourcestatistics, but I am still
> > interested in keeping the temporal dimension. The reason to use
> > atlas
> > regions instead of source points is to decrease the computation
> > time.
> > Best,
> > Nicolai
> > Den 12/06/2013 kl. 18.58 skrev " smoratti at psi.ucm.es " <
> > smoratti at psi.ucm.es >:
> > >
> > > I think Jan.Mathijs alternative suggestion is quite attractive.
> > > With
> > > the neighbors on a cortical sheet I also had the problems that
> > > sometimes the vertices do not have the same distance and then
> > > clustering may be biased to smaller or bigger clusters as the
> > > number
> > > of neighbors does not guarantee same cluster sizes. With the
> > > interpolation onto a 3D grid, you won't have that problem.
> > >
> > > best,
> > >
> > > Stephan
> > >
> > >
> > > ________________________________________________________
> > > Stephan Moratti, PhD
> > >
> > > see also: http://web.me.com/smoratti/
> > >
> > > Universidad Complutense de Madrid
> > > Facultad de Psicolog?a
> > > Departamento de Psicolog?a B?sica I
> > > Campus de Somosaguas
> > > 28223 Pozuelo de Alarc?n (Madrid)
> > > Spain
> > >
> > > and
> > >
> > > Center for Biomedical Technology
> > > Laboratory for Cognitive and Computational Neuroscience
> > > Parque Cient?fico y Tecnol?gico de la Universidad Politecnica de
> > > Madrid
> > > Campus Montegancedo
> > > 28223 Pozuelo de Alarc?n (Madrid)
> > > Spain
> > >
> > >
> > > email: smoratti at psi.ucm.es
> > > Tel.: +34 679219982
> > >
> > > El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribi?:
> > >
> > >> An alternative would be to interpolate the cortical sheet to a 3D
> > >> grid (where the grid is defined for each subject based on a
> > >> warped
> > >> template grid defined in a standard space), and then do
> > >> clustering
> > >> using a regular 3D spatial neighbourhood structure. The rationale
> > >> being that two vertices on the sheet may appear as disconnected
> > >> (e.g. being on two sides of a sulcus) whereas, given the poor
> > >> spatial resolution, they belong to the same spatial blob.
> > >>
> > >> Best,
> > >> Jan-Mathijs
> > >>
> > >> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
> > >>
> > >>> Dear Nicolai,
> > >>>
> > >>> Indeed I have used ft_timelockstatistics for minimum norm source
> > >>> data. The trick is to put the source level data into a ERF
> > >>> structure. Determining the neighbors of a source surface with
> > >>> vertices is not trivial. However I used tess_vertconn.m from the
> > >>> BrainStorm toolbox to get the connectivity matrix that tells you
> > >>> who is a neighbor. This you can feed into timelockstats.
> > >>>
> > >>> Hope that helps,
> > >>>
> > >>> Stephan
> > >>>
> > >>> ________________________________________________________
> > >>> Stephan Moratti, PhD
> > >>>
> > >>> see also: http://web.me.com/smoratti/
> > >>>
> > >>> Universidad Complutense de Madrid
> > >>> Facultad de Psicolog?a
> > >>> Departamento de Psicolog?a B?sica I
> > >>> Campus de Somosaguas
> > >>> 28223 Pozuelo de Alarc?n (Madrid)
> > >>> Spain
> > >>>
> > >>> and
> > >>>
> > >>> Center for Biomedical Technology
> > >>> Laboratory for Cognitive and Computational Neuroscience
> > >>> Parque Cient?fico y Tecnol?gico de la Universidad Politecnica de
> > >>> Madrid
> > >>> Campus Montegancedo
> > >>> 28223 Pozuelo de Alarc?n (Madrid)
> > >>> Spain
> > >>>
> > >>>
> > >>> email: smoratti at psi.ucm.es
> > >>> Tel.: +34 679219982
> > >>>
> > >>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribi?:
> > >>>
> > >>>> Dear all,
> > >>>>
> > >>>> I have a question concerning the usage of ft_sourcegrandaverage
> > >>>> and ft_sourcestatistics.
> > >>>>
> > >>>> After using ft_sourceanalysis (method: MNE), I get
> > >>>> spatio-temporal source reconstructed data in source.avg.pow
> > >>>> (4050
> > >>>> x 897): 4050 sources and 897 time points.
> > >>>>
> > >>>> Now I would like to use the cluster-based permutation test on
> > >>>> my
> > >>>> source reconstructed data. However it seems like
> > >>>> ft_sourcegrandaverage and ft_sourcestatistics don't support
> > >>>> source level time courses. E.g when I am using
> > >>>> ft_sourcegrandaverage I am getting the following error:
> > >>>>
> > >>>> Error in ft_sourcegrandaverage (line 158)
> > >>>> dat(:,i) = tmp(:);
> > >>>>
> > >>>> Looking into the code:
> > >>>>
> > >>>> for i=1:Nsubject
> > >>>> tmp = getsubfield(varargin{i},
> > >>>> parameterselection(cfg.parameter,
> > >>>> varargin{i}));
> > >>>> dat(:,i) = tmp(:);
> > >>>> tmp = getsubfield(varargin{i}, 'inside');
> > >>>> inside(tmp,i) = 1;
> > >>>> end
> > >>>>
> > >>>> I see that "tmp" are getting the structure [N_sources x
> > >>>> timepoints] from source.avg.pow for one subject, where "dat"
> > >>>> requires the structure [N_sources x 1].
> > >>>>
> > >>>> I seached the mailing list for similar issues and found this
> > >>>> thread:
> > >>>>
> > >>>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
> > >>>>
> > >>>> Since I am interested in using the temporal dimension in my
> > >>>> statistics, I would like to know if it is still not possible to
> > >>>> use spatio-temporal source reconstructed data in
> > >>>> ft_sourcestatistics and ft_sourcegrandaverage ?
> > >>>>
> > >>>> Or if any have succeeded in using the cluster-based permutation
> > >>>> test on source level also including the temporal dimension ?
> > >>>>
> > >>>> Alternative I was thinking that I might could use
> > >>>> ft_timelockstatistics, where I substituted the channels with
> > >>>> sources, e.g instead of having 64 channels, I would now have
> > >>>> 4050
> > >>>> "channels".
> > >>>> If so I need to calculate a label structure and an appropriate
> > >>>> neighbor structure, which I guess is possible as I have all the
> > >>>> 3D coordinates for each source, e.g in leadfield.pos ?
> > >>>> I know this is a work around solution, but have anyone tried or
> > >>>> have any experience using such an approach ?
> > >>>>
> > >>>> Best,
> > >>>>
> > >>>> Nicolai
> > >>>>
> > >>>> _______________________________________________
> > >>>> fieldtrip mailing list
> > >>>> fieldtrip at donders.ru.nl
> > >>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > >>>
> > >>> _______________________________________________
> > >>> fieldtrip mailing list
> > >>> fieldtrip at donders.ru.nl
> > >>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > >>
> > >> Jan-Mathijs Schoffelen, MD PhD
> > >>
> > >> Donders Institute for Brain, Cognition and Behaviour,
> > >> Centre for Cognitive Neuroimaging,
> > >> Radboud University Nijmegen, The Netherlands
> > >>
> > >> Max Planck Institute for Psycholinguistics,
> > >> Nijmegen, The Netherlands
> > >>
> > >> J.Schoffelen at donders.ru.nl
> > >> Telephone: +31-24-3614793
> > >>
> > >> http://www.hettaligebrein.nl
> > >>
> > >> _______________________________________________
> > >> fieldtrip mailing list
> > >> fieldtrip at donders.ru.nl
> > >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > >
> > > _______________________________________________
> > > fieldtrip mailing list
> > > fieldtrip at donders.ru.nl
> > > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
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> > >
> > ------------------------------
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > End of fieldtrip Digest, Vol 31, Issue 27
> > *****************************************
> --
> Stephen Politzer-Ahles
> University of Kansas
> Linguistics Department
> http://people.ku.edu/~sjpa/
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
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From politzerahless at gmail.com  Mon Jun 24 20:29:01 2013
From: politzerahless at gmail.com (Stephen Politzer-Ahles)
Date: Mon, 24 Jun 2013 13:29:01 -0500
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
Message-ID: <CAJT2k__aWw_68dy7K2MnGHkP2cEEyredBduU+VgoSVatx=_hYw@mail.gmail.com>

Hi Arjen,

Thanks, I also just tried that (after noticing that code in a later part of
the example) and can confirm that that change makes the plot come out like
the plot in the example. I updated the wiki accordingly.

Best,
Steve

> Message: 1
> Date: Mon, 24 Jun 2013 20:11:26 +0200 (CEST)
> From: "Stolk, A." <a.stolk at fcdonders.ru.nl>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] fieldtrip Digest, Vol 31, Issue 27
> Message-ID:
>         <
331233946.1725662.1372097486678.JavaMail.root at sculptor.zimbra.ru.nl>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Steve, With respect to the cube vs. brain-shaped grid; this seems to
be plotting-related? template_grid.inside in the snippet of code below
selects only the grid points that have been determined as inside the brain,
but with a negative inwardshift, hence it's also outside. ft_plot_mesh (
template_grid. pos ( template_grid. inside ,: ) ) ; % taken from the wiki
Hopefully someone else has up-to-date knowledge to answer your question
pertaining to the units (mm vs. cm) of the volume conductor and the source
model. Best regards, Arjen ----- Oorspronkelijk bericht -----
> > Van: "Stephen Politzer-Ahles" <politzerahless at gmail.com>
> > Aan: fieldtrip at science.ru.nl
> > Verzonden: Maandag 24 juni 2013 17:19:59
> > Onderwerp: Re: [FieldTrip] fieldtrip Digest, Vol 31, Issue 27
> > Hi everyone,
> > I recently tried
> >
http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space
> > and noticed some inconsistencies between the example code and the
> > results; I updated the code on the wiki but I wanted to send a message
> > to the list to double-check whether my changes are ok. Firstly, I had
> > to add a call to ft_convert_units, because otherwise the vol was
> > expressed in mm and the grid in cm, causing the grid to be much
> > smaller than the volume conductor (see http://i.imgur.com/gzct9Dm.png
> > ). Is this change ok?
> > The result I get is still not quite consistent with the examples shown
> > on that page, though; in my result, the grid is a cube (
> > http://i.imgur.com/NSgCFpg.png ), whereas in the example the grid is
> > brain-shaped. I used the same Fieldtrip brain template and the same
> > code from the example (except for the change above), so I'm not sure
> > if the difference is due to different plot settings, a change in the
> > Fieldtrip code since this example was made, or a change in the sample
> > brain included in Fieldtrip since the example was made.
> > Best,
> > Steve
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From joramvandriel at gmail.com  Tue Jun 25 09:17:27 2013
From: joramvandriel at gmail.com (Joram van Driel)
Date: Tue, 25 Jun 2013 09:17:27 +0200
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 27
In-Reply-To: <331233946.1725662.1372097486678.JavaMail.root@sculptor.zimbra.ru.nl>
References: <CAJT2k_-XpQZ0diLY+pYtyOmD0R1s_0rKKRNSzfT2Ac9iuWPEbA@mail.gmail.com>
	<331233946.1725662.1372097486678.JavaMail.root@sculptor.zimbra.ru.nl>
Message-ID: <CAKk__WW9+yaz6FwUSRQ-4SqSCy66-PbYsWxDkpe7TO=TvxH_mA@mail.gmail.com>

Hi Steve,
I had the same problem a while ago.

First of all, you need to take care of all the necessary ingredients to be
in cm before computing the volume conduction model and the leadfield
matrix, by using ft_convertunits.

Second, I also first had a brain-shaped grid, which was not a plot-related
problem; I noticed during the computation of the leadfield in the Matlab
command lines that it estimated 0 dipoles outside, and x-number of dipoles
inside the brain, which already made me suspicious. Check whether you get
this as well, then you know it's not a plotting problem.
In the end I managed to get a x inside and x outside number of dipoles, and
I think the difference was that I first used ft_prepare_singleshell (which
gave me the weird brain-shaped results with 0 dipoles outside), while I
think you should use ft_prepare_headmodel with cfg.method='singleshell'.
Maybe it doesn't matter at all, and the problem lies somewhere else, but
for me it worked and I got a nice cube-shaped grid in the end.

Hope this helps.
Best,
Joram


On Mon, Jun 24, 2013 at 8:11 PM, Stolk, A. <a.stolk at fcdonders.ru.nl> wrote:

> Hi Steve,
>
> With respect to the cube vs. brain-shaped grid; this seems to be
> plotting-related? template_grid.inside in the snippet of code below selects
> only the grid points that have been determined as inside the brain, but
> with a negative inwardshift, hence it's also outside.
>
> ft_plot_mesh(template_grid.pos(template_grid.inside,:)); % taken from the
> wiki
>
> Hopefully someone else has up-to-date knowledge to answer your question
> pertaining to the units (mm vs. cm) of the volume conductor and the source
> model.
>
> Best regards,
> Arjen
>
> ------------------------------
>
> *Van: *"Stephen Politzer-Ahles" <politzerahless at gmail.com>
> *Aan: *fieldtrip at science.ru.nl
> *Verzonden: *Maandag 24 juni 2013 17:19:59
> *Onderwerp: *Re: [FieldTrip] fieldtrip Digest, Vol 31, Issue 27
>
>
> Hi everyone,
>
> I recently tried
> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_spaceand noticed some inconsistencies between the example code and the results;
> I updated the code on the wiki but I wanted to send a message to the list
> to double-check whether my changes are ok. Firstly, I had to add a call to
> ft_convert_units, because otherwise the vol was expressed in mm and the
> grid in cm, causing the grid to be much smaller than the volume conductor
> (see http://i.imgur.com/gzct9Dm.png). Is this change ok?
>
> The result I get is still not quite consistent with the examples shown on
> that page, though; in my result, the grid is a cube (
> http://i.imgur.com/NSgCFpg.png), whereas in the example the grid is
> brain-shaped. I used the same Fieldtrip brain template and the same code
> from the example (except for the change above), so I'm not sure if the
> difference is due to different plot settings, a change in the Fieldtrip
> code since this example was made, or a change in the sample brain included
> in Fieldtrip since the example was made.
>
> Best,
> Steve
>
>
> On Thu, Jun 13, 2013 at 5:05 AM, <fieldtrip-request at science.ru.nl> wrote:
> >
> > Send fieldtrip mailing list submissions to
> >         fieldtrip at science.ru.nl
> >
> > To subscribe or unsubscribe via the World Wide Web, visit
> >         http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > or, via email, send a message with subject or body 'help' to
> >         fieldtrip-request at science.ru.nl
> >
> > You can reach the person managing the list at
> >         fieldtrip-owner at science.ru.nl
> >
> > When replying, please edit your Subject line so it is more specific
> > than "Re: Contents of fieldtrip digest..."
> >
> >
> > Today's Topics:
> >
> >    1. Re: Source statistics on spatio-temporal source
> >       reconstruction data (MNE) (Nicolai Mersebak)
> >
> >
> > ----------------------------------------------------------------------
> >
> > Message: 1
> > Date: Thu, 13 Jun 2013 12:04:34 +0200
> > From: Nicolai Mersebak <nicolai at mersebak.dk>
> > To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> > Subject: Re: [FieldTrip] Source statistics on spatio-temporal source
> >         reconstruction data (MNE)
> > Message-ID: <6F3697BB-194F-422F-A1BF-EBBB132F805B at mersebak.dk>
> > Content-Type: text/plain; charset="iso-8859-1"
> >
> > Thanks to all of you for your comments and ideas - they are very helpful!
> >
> > I ( off course :) ) have some follow up questions.
> >
> > I have created an ERP structure for my MNE source, so the only think
> which I need and that is not straight forward is the neighbour structure.
> >
> > I am using the standard bem template
> (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model
> and use the following code to get a grid for all subjects as I don't have
> any subject specific information regarding the anatomy.
> >
> > cfg = [];
> > cfg.grid.xgrid  = -100:10:100;
> > cfg.grid.ygrid  = -100:10:100;
> > cfg.grid.zgrid  = -100:10:100;
> > cfg.grid.tight  = 'yes';
> > cfg.grid.unit   = hdm.unit; % unit: mm
> > cfg.vol        = hdm;
> > grid  = ft_prepare_sourcemodel(cfg);
> >
> >
> > @Jan-Mathijs and Stephan: I guess making a subject specific grid based
> on a warped template requires anatomic information for each subject, e.g. a
> MRI image like this tutorial shows:
> >
> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
> >
> > The final grid output in the tutorial - does it have this 3D grid which
> can be used as a neighbour structure ?
> >
> > I am not sure how to go from my cortical sheet [vertices x
> coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
> >
> > A second thing I would like to know is, if any of you have tried to use
> an atlas (e.g ALL template atlas) where the regions now are channels in the
> permutation test? Going from source points to atlas regions can be done
> through ft_sourcestatistics, but I am still interested in keeping the
> temporal dimension. The reason to use atlas regions instead of source
> points is to decrease the computation time.
> >
> > Best,
> >
> > Nicolai
> >
> >
>
>
> On Thu, Jun 13, 2013 at 5:05 AM, <fieldtrip-request at science.ru.nl> wrote:
>
>> Send fieldtrip mailing list submissions to
>>         fieldtrip at science.ru.nl
>>
>> To subscribe or unsubscribe via the World Wide Web, visit
>>         http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> or, via email, send a message with subject or body 'help' to
>>         fieldtrip-request at science.ru.nl
>>
>> You can reach the person managing the list at
>>         fieldtrip-owner at science.ru.nl
>>
>> When replying, please edit your Subject line so it is more specific
>> than "Re: Contents of fieldtrip digest..."
>>
>>
>> Today's Topics:
>>
>>    1. Re: Source statistics on spatio-temporal source
>>       reconstruction data (MNE) (Nicolai Mersebak)
>>
>>
>> ----------------------------------------------------------------------
>>
>> Message: 1
>> Date: Thu, 13 Jun 2013 12:04:34 +0200
>> From: Nicolai Mersebak <nicolai at mersebak.dk>
>> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
>> Subject: Re: [FieldTrip] Source statistics on spatio-temporal source
>>         reconstruction data (MNE)
>> Message-ID: <6F3697BB-194F-422F-A1BF-EBBB132F805B at mersebak.dk>
>> Content-Type: text/plain; charset="iso-8859-1"
>>
>> Thanks to all of you for your comments and ideas - they are very helpful!
>>
>> I ( off course :) ) have some follow up questions.
>>
>> I have created an ERP structure for my MNE source, so the only think
>> which I need and that is not straight forward is the neighbour structure.
>>
>> I am using the standard bem template
>> (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model
>> and use the following code to get a grid for all subjects as I don't have
>> any subject specific information regarding the anatomy.
>>
>> cfg = [];
>> cfg.grid.xgrid  = -100:10:100;
>> cfg.grid.ygrid  = -100:10:100;
>> cfg.grid.zgrid  = -100:10:100;
>> cfg.grid.tight  = 'yes';
>> cfg.grid.unit   = hdm.unit; % unit: mm
>> cfg.vol        = hdm;
>> grid  = ft_prepare_sourcemodel(cfg);
>>
>>
>> @Jan-Mathijs and Stephan: I guess making a subject specific grid based on
>> a warped template requires anatomic information for each subject, e.g. a
>> MRI image like this tutorial shows:
>>
>> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
>>
>> The final grid output in the tutorial - does it have this 3D grid which
>> can be used as a neighbour structure ?
>>
>> I am not sure how to go from my cortical sheet [vertices x
>> coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
>>
>> A second thing I would like to know is, if any of you have tried to use
>> an atlas (e.g ALL template atlas) where the regions now are channels in the
>> permutation test? Going from source points to atlas regions can be done
>> through ft_sourcestatistics, but I am still interested in keeping the
>> temporal dimension. The reason to use atlas regions instead of source
>> points is to decrease the computation time.
>>
>> Best,
>>
>> Nicolai
>>
>>
>> Den 12/06/2013 kl. 18.58 skrev "smoratti at psi.ucm.es" <smoratti at psi.ucm.es
>> >:
>>
>> >
>> > I think Jan.Mathijs alternative suggestion is quite attractive. With
>> the neighbors on a cortical sheet I also had the problems that sometimes
>> the vertices do not have the same distance and then clustering may be
>> biased to smaller or bigger clusters as the number of neighbors does not
>> guarantee same cluster sizes. With the interpolation onto a 3D grid, you
>> won't have that problem.
>> >
>> > best,
>> >
>> > Stephan
>> >
>> >
>> > ________________________________________________________
>> > Stephan Moratti, PhD
>> >
>> > see also: http://web.me.com/smoratti/
>> >
>> > Universidad Complutense de Madrid
>> > Facultad de Psicolog?a
>> > Departamento de Psicolog?a B?sica I
>> > Campus de Somosaguas
>> > 28223 Pozuelo de Alarc?n (Madrid)
>> > Spain
>> >
>> > and
>> >
>> > Center for Biomedical Technology
>> > Laboratory for Cognitive and Computational Neuroscience
>> > Parque Cient?fico y Tecnol?gico de la Universidad Politecnica de Madrid
>> > Campus Montegancedo
>> > 28223 Pozuelo de Alarc?n (Madrid)
>> > Spain
>> >
>> >
>> > email: smoratti at psi.ucm.es
>> > Tel.:    +34 679219982
>> >
>> > El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribi?:
>> >
>> >> An alternative would be to interpolate the cortical sheet to a 3D grid
>> (where the grid is defined for each subject based on a warped template grid
>> defined in a standard space), and then do clustering using a regular 3D
>> spatial neighbourhood structure. The rationale being that two vertices on
>> the sheet may appear as disconnected  (e.g. being on two sides of a sulcus)
>> whereas, given the poor spatial resolution, they belong to the same spatial
>> blob.
>> >>
>> >> Best,
>> >> Jan-Mathijs
>> >>
>> >> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
>> >>
>> >>> Dear Nicolai,
>> >>>
>> >>> Indeed I have used ft_timelockstatistics for minimum norm source
>> data. The trick is to put the source level data into a ERF structure.
>> Determining the neighbors of a source surface with vertices is not trivial.
>> However I used tess_vertconn.m from the BrainStorm toolbox to get the
>> connectivity matrix that tells you who is a neighbor. This you can feed
>> into timelockstats.
>> >>>
>> >>> Hope that helps,
>> >>>
>> >>> Stephan
>> >>>
>> >>> ________________________________________________________
>> >>> Stephan Moratti, PhD
>> >>>
>> >>> see also: http://web.me.com/smoratti/
>> >>>
>> >>> Universidad Complutense de Madrid
>> >>> Facultad de Psicolog?a
>> >>> Departamento de Psicolog?a B?sica I
>> >>> Campus de Somosaguas
>> >>> 28223 Pozuelo de Alarc?n (Madrid)
>> >>> Spain
>> >>>
>> >>> and
>> >>>
>> >>> Center for Biomedical Technology
>> >>> Laboratory for Cognitive and Computational Neuroscience
>> >>> Parque Cient?fico y Tecnol?gico de la Universidad Politecnica de
>> Madrid
>> >>> Campus Montegancedo
>> >>> 28223 Pozuelo de Alarc?n (Madrid)
>> >>> Spain
>> >>>
>> >>>
>> >>> email: smoratti at psi.ucm.es
>> >>> Tel.:    +34 679219982
>> >>>
>> >>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribi?:
>> >>>
>> >>>> Dear all,
>> >>>>
>> >>>> I have a question concerning the usage of ft_sourcegrandaverage and
>> ft_sourcestatistics.
>> >>>>
>> >>>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal
>> source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and
>> 897 time points.
>> >>>>
>> >>>> Now I would like to use the cluster-based permutation test on my
>> source reconstructed data. However it seems like ft_sourcegrandaverage and
>> ft_sourcestatistics don't support source level time courses. E.g when I am
>> using ft_sourcegrandaverage I am getting the following error:
>> >>>>
>> >>>> Error in ft_sourcegrandaverage (line 158)
>> >>>>   dat(:,i) = tmp(:);
>> >>>>
>> >>>> Looking into the code:
>> >>>>
>> >>>>   for i=1:Nsubject
>> >>>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter,
>> varargin{i}));
>> >>>>     dat(:,i) = tmp(:);
>> >>>>     tmp = getsubfield(varargin{i}, 'inside');
>> >>>>     inside(tmp,i) = 1;
>> >>>>   end
>> >>>>
>> >>>> I see that "tmp" are getting the structure [N_sources x timepoints]
>> from source.avg.pow for one subject, where "dat" requires the structure
>> [N_sources x 1].
>> >>>>
>> >>>> I seached the mailing list for similar issues and found this thread:
>> >>>>
>> >>>>
>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>> >>>>
>> >>>> Since I am interested in using the temporal dimension in my
>> statistics, I would like to know if it is still not possible to use
>> spatio-temporal source reconstructed data in ft_sourcestatistics and
>> ft_sourcegrandaverage ?
>> >>>>
>> >>>> Or if any have succeeded in using the cluster-based permutation test
>> on source level also including the temporal dimension ?
>> >>>>
>> >>>> Alternative I was thinking that I might could use
>> ft_timelockstatistics, where I substituted the channels with sources, e.g
>> instead of having 64 channels, I would now have 4050 "channels".
>> >>>> If so I need to calculate a label structure and an appropriate
>> neighbor structure, which I guess is possible as I have all the 3D
>> coordinates for each source, e.g in leadfield.pos ?
>> >>>> I know this is a work around solution, but have anyone tried or have
>> any experience using such an approach ?
>> >>>>
>> >>>> Best,
>> >>>>
>> >>>> Nicolai
>> >>>>
>> >>>> _______________________________________________
>> >>>> fieldtrip mailing list
>> >>>> fieldtrip at donders.ru.nl
>> >>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> >>>
>> >>> _______________________________________________
>> >>> fieldtrip mailing list
>> >>> fieldtrip at donders.ru.nl
>> >>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> >>
>> >> Jan-Mathijs Schoffelen, MD PhD
>> >>
>> >> Donders Institute for Brain, Cognition and Behaviour,
>> >> Centre for Cognitive Neuroimaging,
>> >> Radboud University Nijmegen, The Netherlands
>> >>
>> >> Max Planck Institute for Psycholinguistics,
>> >> Nijmegen, The Netherlands
>> >>
>> >> J.Schoffelen at donders.ru.nl
>> >> Telephone: +31-24-3614793
>> >>
>> >> http://www.hettaligebrein.nl
>> >>
>> >> _______________________________________________
>> >> fieldtrip mailing list
>> >> fieldtrip at donders.ru.nl
>> >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> >
>> > _______________________________________________
>> > fieldtrip mailing list
>> > fieldtrip at donders.ru.nl
>> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>> -------------- next part --------------
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>> http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20130613/5974284f/attachment.html
>> >
>>
>> ------------------------------
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>> End of fieldtrip Digest, Vol 31, Issue 27
>> *****************************************
>>
>
>
>
> --
> Stephen Politzer-Ahles
> University of Kansas
> Linguistics Department
> http://people.ku.edu/~sjpa/
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
Joram van Driel, MSc.
PhD student at the University of Amsterdam
Department of Psychology, Brain & Cognition
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From mbj0310 at gmail.com  Tue Jun 25 13:04:15 2013
From: mbj0310 at gmail.com (Beom Jun Min)
Date: Tue, 25 Jun 2013 20:04:15 +0900
Subject: [FieldTrip] Decreased baseline level after using ICA in ERP data
In-Reply-To: <831995030.1708865.1372062324986.JavaMail.root@sculptor.zimbra.ru.nl>
References: <CA+v9jvKJnKAfsQDwoDhNVSPAKCmpOpwut8vdmFXa1akp_1WDGA@mail.gmail.com>
	<831995030.1708865.1372062324986.JavaMail.root@sculptor.zimbra.ru.nl>
Message-ID: <CA+v9jvLu5ox++Dt0AZnJrXtZ0COt_6421YquhOTUUHDbejsjTQ@mail.gmail.com>

Dear Diego,

Thank you for your kind answer.
The importance of 'quality' you mentioned and the references that you
attached could help me to understand the ICA algorithm further.
And I have an additional question about preprocessing before ICA. Is
detrending needed before the decomposition if there is a linear trend in
the segmented data?
Because I noticed one component showing linearly and consistently decreased
(or increased) activity during one segment in some trials after ICA, I
wondered why that happened.

Apart from that, I found the possible cause of the past problem. It looks
like the ft_rejectcomponent might remove the 'demean' effect.
After I used the function without any component removing, (cfg.component =
[];) the baseline level decreased again but the shape of the ERP does not
change.
However, I have not found the way to correct this decreased baseline yet.
The ft_preprocessing with demean pre-stimulus does not work.

Thanks.

BJ



2013/6/24 Lozano Soldevilla, D. (Diego) <d.lozanosoldevilla at fcdonders.ru.nl>

> Dear Beom Jun,
>
> I see multiple scenarios why this baseline activity decrease could happen.
> First of all, how the component you're rejecting look like (i.e. "blink
> component")? Do you see this activity decrease after the baseline period?
>
> The "quality" of the ICA decomposition, how well your artifact/component
> of interest has been isolated by algorithm in time (i.e. blink time
> courses) and space (marked frontal topography), will determine the activity
> that later on you'll reject/select. If your decomposition is not well
> suited, the rejection of a particular IC activity might have "extra"
> activity you don't want to reject (effect of interest), might be the
> algorithm is not able to isolate the components of interests (i.e.
> artifacts) or a combination of both.
>
> To evaluate the quality of your ICA decomposition you might have a look
> here (http://www.ncbi.nlm.nih.gov/pubmed/19162199). Basically, the
> authors find that the ICA decomposition improves significantly "increased
> by removing the mean EEG at each channel for each epoch of data rather than
> the mean EEG in a prestimulus baseline". In addition (see here:
> http://sccn.ucsd.edu/pipermail/eeglablist/2012/004925.html), high-pass
> filtering above ~1hz improve the results.
>
> It's very important to feed ICA as much relevant data as you can use. The
> more the data, the better the decomposition. There's a rule of thumb that
> says that for a reliable IC decomposition 20 time points per channel2  is
> needed (see here for a reference
> http://www.ncbi.nlm.nih.gov/pubmed/16904745)
>
> I hope that helps,
>
> Diego
> ------------------------------
>
> *From: *"Beom Jun Min" <mbj0310 at gmail.com>
> *To: *"FieldTrip discussion list" <fieldtrip at science.ru.nl>
> *Sent: *Monday, 24 June, 2013 6:27:47 AM
> *Subject: *[FieldTrip] Decreased baseline level after using ICA in ERP
> data
>
>
> Dear all,
>
> I have ERP data and now I am dealing with ICA to remove muscle and eye
> artifacts.
> However, I found that after ft_rejectcomponent, the baseline level of the
> segmented epoch decreased. (The baselinewindow is [-0.2 0].)
> The baseline level decreased even though I rejected only one component.
>
> My script is shown below.
>
> *%% Removing the Artifacts*
> *cfg = [];
> *
> *cfg.component = [ ]; % to be removed component(s)*
> *post_ICA_temp6 = ft_rejectcomponent(cfg, comp_detrand, data_raw);*
> *
> *
> *%% timelocking*
> *
> *
> *cfg = [];*
> *timelock_temp6 = ft_timelockanalysis(cfg, post_ICA_temp6);*
> *
> *
> *%% Plot*
> *
> *
> *figure;*
> *cfg = [];*
> *cfg.layout = lay;*
> *cfg.interactive = 'yes';*
> *cfg.channel = ['all', {'-EKG', '-EMG'}];*
> *ft_multiplotER(cfg, timelock_temp6)*
>
> Is there something that I missed?
>
> Thanks.
>
> BJ
>
> --
> BeomJun Min, M.D.
>
> Department of Medical System Engineering (DMSE)
> Gwangju Institute of Science and Technology (GIST)
> 261 Cheomdan-gwagiro(Oryong-dong), Buk-gu, Gwangju
> 500-712, Republic of Korea (South)
> Phone: +82-62-715-3266 / Fax: +82-62-715-3244
> E-mail: mbj0310 at gmail.com, http://bmssa.gist.ac.kr
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
>
> --
> PhD Student
> Neuronal Oscillations Group
> Donders Institute for Brain, Cognition and Behaviour
> Centre for Cognitive Neuroimaging
> Radboud University Nijmegen
> NL-6525 EN Nijmegen
> The Netherlands
> http://www.ru.nl/people/donders/lozano-soldevilla-d/
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
BeomJun Min, M.D.

Department of Medical System Engineering (DMSE)
Gwangju Institute of Science and Technology (GIST)
261 Cheomdan-gwagiro(Oryong-dong), Buk-gu, Gwangju
500-712, Republic of Korea (South)
Phone: +82-62-715-3266 / Fax: +82-62-715-3244
E-mail: mbj0310 at gmail.com, http://bmssa.gist.ac.kr
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From mengtongxiao at gmail.com  Tue Jun 25 15:29:41 2013
From: mengtongxiao at gmail.com (=?GB2312?B?s8LRqQ==?=)
Date: Tue, 25 Jun 2013 21:29:41 +0800
Subject: [FieldTrip] source reconstruction data (MNE .fif)
Message-ID: <CADiddyVSK6SqRU5BP1kNpSAR21f8heFkkZuOiAh1QKgCH+8xag@mail.gmail.com>

Dear all
 I have a .fif file and want to source  reconstruction .

I want use the template  sourcemodel in fieldtrip,but  I see there are two
different  coordinate system.
Shold I convert the fif coordinate to template coordinate?

thanks
best,
xiao
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From m.chait at ucl.ac.uk  Tue Jun 25 16:39:16 2013
From: m.chait at ucl.ac.uk (Chait, Maria)
Date: Tue, 25 Jun 2013 14:39:16 +0000
Subject: [FieldTrip] PhD studentship at the UCL Ear Institute
Message-ID: <3BA3DF582C0B7542AE0CB625F0119AB8378B0451@DB3PRD0111MB492.eurprd01.prod.exchangelabs.com>


Please forward to anyone who might be interested.

A 3 year PhD studentship in auditory cognitive neuroscience is available as part of a research collaboration between the UCL Ear Institute (London, UK) and NTT Communication Science Labs (Nippon Telegraph and Telephone corporation, Atsugi, Japan). The student will be based at the UCL Ear Institute and supervised by Dr. Maria Chait. They will also be working with Prof. Makio Kashino and Dr. Shigeto Furukawa (NTT).  The project will use psychophysics, eye tracking, autonomic response measures and MEG functional brain imaging to investigate which features of sound are perceptually salient. Namely, those sounds that automatically capture attention in a busy scene, even when listeners' initial perceptual focus is elsewhere.

The UCL Ear Institute provides state-of-the-art research facilities across a wide range of disciplines and is one of the foremost centres for hearing, speech and language-related research within Europe.

Key Requirements
The PhD start date would be September  2013.  Applicants should have a UK/EU nationality and a 1St class, or upper 2nd degree in a relevant discipline (e.g. Psychology, Neuroscience, Engineering). The PhD work would require good programming skills (e.g. in Matlab). Previous experience with auditory research, functional brain imaging, signal processing and/or acoustics is desirable.

For an informal discussion, or to submit an application please contact Dr. Maria Chait (m.chait at ucl.ac.uk<mailto:m.chait at ucl.ac.uk>). Applicants should submit a supporting statement, a CV, and the details of two academic referees.  The closing date for receipt of applications is July 15th, 2013.The studentship includes fees and a yearly stipend (about £16000;  tax free).


Maria Chait PhD
m.chait at ucl.ac.uk<mailto:m.chait at ucl.ac.uk>

Senior Lecturer
UCL Ear Institute
332 Gray's Inn Road
London WC1X 8EE

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From matt.craddock at uni-leipzig.de  Tue Jun 25 17:17:43 2013
From: matt.craddock at uni-leipzig.de (Matt Craddock)
Date: Tue, 25 Jun 2013 17:17:43 +0200
Subject: [FieldTrip] Decreased baseline level after using ICA in ERP data
In-Reply-To: <CA+v9jvLu5ox++Dt0AZnJrXtZ0COt_6421YquhOTUUHDbejsjTQ@mail.gmail.com>
References: <CA+v9jvKJnKAfsQDwoDhNVSPAKCmpOpwut8vdmFXa1akp_1WDGA@mail.gmail.com>
	<831995030.1708865.1372062324986.JavaMail.root@sculptor.zimbra.ru.nl>
	<CA+v9jvLu5ox++Dt0AZnJrXtZ0COt_6421YquhOTUUHDbejsjTQ@mail.gmail.com>
Message-ID: <51C9B497.7080105@uni-leipzig.de>

Dear Beom Jun,

Regarding detrending - ICA works better with relatively stationary data, 
which is why high-pass filtering - as Diego mentioned - is often 
performed. Both detrending and high-pass filtering remove/attenuate slow 
fluctuations in the signal, so I'd suggest using one or the other 
procedure before running ICA if you think such low frequency activity is 
affecting your decompositions.

Cheers,
Matt

On 25/06/2013 13:04, Beom Jun Min wrote:
> Dear Diego,
>
> Thank you for your kind answer.
> The importance of 'quality' you mentioned and the references that you
> attached could help me to understand the ICA algorithm further.
> And I have an additional question about preprocessing before ICA. Is
> detrending needed before the decomposition if there is a linear trend in
> the segmented data?
> Because I noticed one component showing linearly and consistently
> decreased (or increased) activity during one segment in some trials
> after ICA, I wondered why that happened.
> Apart from that, I found the possible cause of the past problem. It
> looks like the ft_rejectcomponent might remove the 'demean' effect.
> After I used the function without any component removing, (cfg.component
> = [];) the baseline level decreased again but the shape of the ERP does
> not change.
> However, I have not found the way to correct this decreased baseline
> yet. The ft_preprocessing with demean pre-stimulus does not work.
>
> Thanks.
>
> BJ



-- 
Dr. Matt Craddock

Post-doctoral researcher,
Institute of Psychology,
University of Leipzig,
Neumarkt 9-19,
04109 Leipzig, Germany
Phone: +49 341 973 95 44


From l.verhagen at fcdonders.ru.nl  Wed Jun 26 11:33:36 2013
From: l.verhagen at fcdonders.ru.nl (Verhagen, L. (Lennart))
Date: Wed, 26 Jun 2013 11:33:36 +0200 (CEST)
Subject: [FieldTrip] Brain Stimulation (TMS-tDCS-EEG) toolkit course at
	Donders, Nijmegen - registration is now open
Message-ID: <1380b01ce7250$3bba7a70$b32f6f50$@verhagen@fcdonders.ru.nl>

On September 2-4, 2013, we will host the “Toolkit of Cognitive Neuroscience: 
Transcranial Brain Stimulation” at the Donders Institute in Nijmegen.



This intensive three-day toolkit course will provide in-depth knowledge on 
transcranial magnetic stimulation (TMS) and transcranial current stimulation 
(tDCS/tACS). The course will cover both basic and advanced topics, 
discussing online and offline approaches of quantification, interference, 
and modulation of neural activity. We will specifically address multimodal 
applications of non-invasive brain stimulation, with an emphasis on 
concurrent electroencephalography (EEG).



The course involves a series of lectures and hands-on training of 
stimulation application, data acquisition and data analysis. These address 
fundamental paradigms, such as single-pulse TMS, repetitive TMS, tDCS and 
tACS, and advanced topics, such as paired-pulse TMS and concurrent 
TMS-tDCS-EEG. Keynote lectures will be given by Rogier Mars (Oxford), 
Jacinta O’Shea (Oxford), Alexander Sack (Maastricht), and Gregor Thut 
(Glasgow). Please see the program for more details.



The participation fee is €150 for (PhD) students and €300 for more senior 
researchers. This includes coffee/tea, Dutch sandwich lunches, and social 
diner and drinks on Monday and Tuesday. Because of space limitations the 
number of participants in the hands-on sessions is limited to 30; please 
indicate your preference to join these additional sessions when registering.



Location: Donders Institute for Brain, Cognition and Behaviour, Centre for 
Cognitive Neuroimaging, Kapittelweg 29, 6525 EN Nijmegen

Organizers: Lennart Verhagen (l.verhagen at donders.ru.nl) Til Ole Bergmann 
(t.bergmann at donders.ru.nl)

Registration: 
www.ru.nl/donders/course-information/2013courses/toolkit-cognitive-7



Best regards,

Lennart Verhagen and Til Ole Bergmann



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From graham at peyton.co.za  Wed Jun 26 12:13:58 2013
From: graham at peyton.co.za (Graham Peyton)
Date: Wed, 26 Jun 2013 12:13:58 +0200
Subject: [FieldTrip] QSUB toolbox on a multi-core computer
Message-ID: <CANOxK9E+ZCy9zFqYw1kR_aK7wnEpq0cF9efVj93wFxg5zJWmhQ@mail.gmail.com>

Dear FieldTrip community,

I am trying to carry out an MEG analysis using the qsub distributed
computing toolbox. I'm using a quad-core i7 computer, and was hoping that
I'd be able to distribute the workload over all four cores.

I have followed the tutorial below exactly:
http://fieldtrip.fcdonders.nl/tutorial/distributedcomputing

The problem I am having is this: I managed to run example 1 (with my own
dataset), but I am finding that when I use qsubcellfun, the function
ft_definetrial is executed *sequentially* (for each condition), *not* in *
parallel*. Is there a way I can correct this, so as to parallelize the
analysis? Or is the toolbox not designed for multi-core machines?

Many thanks,

Graham Peyton
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From m.vandenieuwenhuijzen at fcdonders.ru.nl  Wed Jun 26 15:07:02 2013
From: m.vandenieuwenhuijzen at fcdonders.ru.nl (Marieke van de Nieuwenhuijzen)
Date: Wed, 26 Jun 2013 15:07:02 +0200 (CEST)
Subject: [FieldTrip] ROI selection of beamformer grid points
Message-ID: <1483937264.1423478.1372252022737.JavaMail.root@draco.zimbra.ru.nl>

Dear Fieldtrippers,

I am running my analyses on time courses reconstructed in source space. Basically, that means that my working dataset is a matrix of grid point x time. What I want to do now is do some analyses on a subset of that dataset, a bit analogous to selecting some sensors to restrict analyses to. Therefore, what I would ideally want to do, is select a subset of grid points corresponding to a specific location (for example only the occipital grid points, or only the grid points corresponding to a specific atlas label).

Does anyone have any suggestions about how I should go about selecting specific grid points? Is there perhaps some grid based atlas, or is it possible to select grid points based on their corresponding mni coordinates which you get after running ft_sourceinterpolate and ft_volumenormalise (in other words, is it possible to reverse ft_volumenormalise and ft_sourceinterpolate to map the mni coordinates to the grid points instead of the grid points to mni representation).

Any pointers would be much appreciated.

Best,
Marieke


From jm.horschig at donders.ru.nl  Wed Jun 26 15:26:41 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Wed, 26 Jun 2013 15:26:41 +0200
Subject: [FieldTrip] ROI selection of beamformer grid points
In-Reply-To: <1483937264.1423478.1372252022737.JavaMail.root@draco.zimbra.ru.nl>
References: <1483937264.1423478.1372252022737.JavaMail.root@draco.zimbra.ru.nl>
Message-ID: <51CAEC11.10702@donders.ru.nl>

Hi Marieke,

I basically use two approaches (in the end, both failed, so any other 
hints are appreciated):

  (a) Select voxels purely based on anatomical labels, as found in an 
atlas or in literature.

  (b) Select voxels based on some local maxima or minima, e.g. power 
maximum or maximum difference of log-ratio


(a) should be pretty straight forward. In essence it involves getting 
MNI coordinates, inversely warping your grids to MNI space, getting 
closest voxel. If you have your region of interest not in MNI 
coordinates you need to transform them. I found some tal2mni functions 
on the web for this, but note that this is just an estimate. Of course, 
(a) is also applicable if you have a localizer task using fMRI and want 
to focus on some localized voxels.
(b) is a bit more tricky, because you might be faced with huge 
inter-subject variability. Best of course would be to have the 
subject-specific, fMRI localized voxel. What I done in the past is to 
define a rough region of interest, e.g. posterior neocortex (based on 
some quick&dirty coordinate thresholding), using ft_volumesmooth to 
apply a gaussian blur on single subject-activity and then select the 
voxel that suits me best (i.e. the one of maximum activity). Of course 
your ROI could also be based on the grand-average or what have you. I 
had the feeling that especially this latter approach (base ROI on GA +/- 
3 cm, smooth individual subject data, select most sensitive voxel) 
worked quite well, but I cannot tell for sure, because in the end my 
results were not reliable enough.

Oh and btw, if the question just aims on 'how' to select 
programming-wise: Match the coordinate with your template, store the 
index based on the template-grid and use this index on your 
subject-specific grid to get voxel of interest in subject-specific 
coordinates.

Good luck!
Best,
Jörn

On 6/26/2013 3:07 PM, Marieke van de Nieuwenhuijzen wrote:
> Dear Fieldtrippers,
>
> I am running my analyses on time courses reconstructed in source space. Basically, that means that my working dataset is a matrix of grid point x time. What I want to do now is do some analyses on a subset of that dataset, a bit analogous to selecting some sensors to restrict analyses to. Therefore, what I would ideally want to do, is select a subset of grid points corresponding to a specific location (for example only the occipital grid points, or only the grid points corresponding to a specific atlas label).
>
> Does anyone have any suggestions about how I should go about selecting specific grid points? Is there perhaps some grid based atlas, or is it possible to select grid points based on their corresponding mni coordinates which you get after running ft_sourceinterpolate and ft_volumenormalise (in other words, is it possible to reverse ft_volumenormalise and ft_sourceinterpolate to map the mni coordinates to the grid points instead of the grid points to mni representation).
>
> Any pointers would be much appreciated.
>
> Best,
> Marieke
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands



From andmib at gmail.com  Wed Jun 26 19:22:33 2013
From: andmib at gmail.com (Andrew Brooks)
Date: Wed, 26 Jun 2013 13:22:33 -0400
Subject: [FieldTrip] Siemens GUI Streamer Disconnecting
Message-ID: <CALJPz6_8Vrq9ebz3vj5N=FWwoTP9HuJiXd-=PV5nqDqSbiFZ5g@mail.gmail.com>

Hello all,

I have a protocol that includes three separate sequences. I start the
Siemens GUI streamer prior to the first sequence, and keep it open through
all three sequences. Only on the last sequence do I run
ft_omri_pipeline_nuisance. I've been running into a problem where the
Siemens GUI streamer disconnects as soon as the the third sequence starts
running (and the ft_omri_pipeline script is waiting for data). I have to
manually click 'connect' as soon as it disconnects, and then it works fine.

Any ideas as to why the streamer would disconnect like this?

Thanks!
Andrew
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From j.herring at fcdonders.ru.nl  Thu Jun 27 12:45:53 2013
From: j.herring at fcdonders.ru.nl (Herring, J.D. (Jim))
Date: Thu, 27 Jun 2013 12:45:53 +0200 (CEST)
Subject: [FieldTrip] QSUB toolbox on a multi-core computer
In-Reply-To: <CANOxK9E+ZCy9zFqYw1kR_aK7wnEpq0cF9efVj93wFxg5zJWmhQ@mail.gmail.com>
References: <CANOxK9E+ZCy9zFqYw1kR_aK7wnEpq0cF9efVj93wFxg5zJWmhQ@mail.gmail.com>
Message-ID: <004701ce7323$7fa9ff20$7efdfd60$@herring@fcdonders.ru.nl>

Dear Graham,

 

As stated in the tutorial the distributed computing functions are intended
to distribute workload over different computers running a Torque or SGE
batch system: "This tutorial covered how to distribute your
computations/workload over multiple computers in a cluster that uses the
Torque or SGE batch queue system". However, what you could do is make use
of Matlab's parallel processing tools. Matlab allows you to open a pool of
so-called 'workers' to distribute processing jobs to allowing you to run
multiple processes in parallel. Please see
http://www.mathworks.nl/help/distcomp/matlabpool.html and
http://www.mathworks.nl/help/matlab/ref/parfor.html.

 

Once you've opened a pool of workers using 'matlabpool', you can use
'parfor' in the same way as you would use 'for' to create a loop that runs
all processes in parallel over all four cores. 

 

Best,

Jim

From: fieldtrip-bounces at science.ru.nl
[mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of Graham Peyton
Sent: woensdag 26 juni 2013 12:14
To: fieldtrip at science.ru.nl
Subject: [FieldTrip] QSUB toolbox on a multi-core computer

 

Dear FieldTrip community,

I am trying to carry out an MEG analysis using the qsub distributed
computing toolbox. I'm using a quad-core i7 computer, and was hoping that
I'd be able to distribute the workload over all four cores. 

I have followed the tutorial below exactly:
http://fieldtrip.fcdonders.nl/tutorial/distributedcomputing

The problem I am having is this: I managed to run example 1 (with my own
dataset), but I am finding that when I use qsubcellfun, the function
ft_definetrial is executed sequentially (for each condition), not in
parallel. Is there a way I can correct this, so as to parallelize the
analysis? Or is the toolbox not designed for multi-core machines? 

 

Many thanks,

Graham Peyton

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From ana.hincapie at gmail.com  Fri Jun 28 09:31:24 2013
From: ana.hincapie at gmail.com (=?ISO-8859-1?Q?Ana_Sof=EDa_Hincapi=E9_Casas?=)
Date: Fri, 28 Jun 2013 09:31:24 +0200
Subject: [FieldTrip] In the forward problem,
 how are the points for the grid.inside and grid.outside defined?
Message-ID: <CAN+fi=zVBtweOXxwEWaHWnp1wKfDTXBXoUgeFgyoeVgQ=jCOxA@mail.gmail.com>

Hi,

I´am new in FieldTrip and I would like to what are the grid.inside and
grid.outside points and if I could used the whole grid to calculate the
leadfields.

Thanks in advance for the help you could bring me.

Regards,

-- 
Ana Hincapié
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From jm.horschig at donders.ru.nl  Fri Jun 28 10:42:03 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Fri, 28 Jun 2013 10:42:03 +0200
Subject: [FieldTrip] In the forward problem,
 how are the points for the grid.inside and grid.outside defined?
In-Reply-To: <CAN+fi=zVBtweOXxwEWaHWnp1wKfDTXBXoUgeFgyoeVgQ=jCOxA@mail.gmail.com>
References: <CAN+fi=zVBtweOXxwEWaHWnp1wKfDTXBXoUgeFgyoeVgQ=jCOxA@mail.gmail.com>
Message-ID: <51CD4C5B.5030909@donders.ru.nl>

Hi Ana,

inside and outside just describe whether the grid point is inside or 
outside the brain. You can plot this to see for yourself:
% plot only what is inside the brain
figure;
ft_plot_vol(vol, 'edgecolor', 'none'); alpha 0.4;
ft_plot_mesh(grid.pos(grid.inside,:));

% plot the whole grid
figure;
ft_plot_vol(vol, 'edgecolor', 'none'); alpha 0.4;
ft_plot_mesh(grid.pos(:,:));

FieldTrip will use that information automatically to only use grid 
points inside the brain, so yes, you can use the whole grid to compute 
the leadfield matrix. If you do not want that, you can modify 
grid.inside and grid.outside yourself.

Have fun fieldtrippin' :)
Jörn

On 6/28/2013 9:31 AM, Ana Sofía Hincapié Casas wrote:
> Hi,
>
> I´am new in FieldTrip and I would like to what are the grid.inside and 
> grid.outside points and if I could used the whole grid to calculate 
> the leadfields.
>
> Thanks in advance for the help you could bring me.
>
> Regards,
>
> -- 
> Ana Hincapié
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands

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From ggonesc at upo.es  Fri Jun 28 18:28:57 2013
From: ggonesc at upo.es (Gabriel Gonzalez Escamilla)
Date: Fri, 28 Jun 2013 18:28:57 +0200
Subject: [FieldTrip] problem appending data
Message-ID: <2350c7b9464ea50a.51cdd5e9@upo.es>

Dear Fieldtrip experts,

I'm working with restin-state EEG data, I'm looking for performing EEG coherence analysis between my normal EEG channels and a channel from the same subject but aquired with a different name

I did: data = ft_appenddata([], dataEEG_allchans, dataEEG_1chan)
and it did concatenate the one single channel at the end of the dataEEG_allchans, so now I have a matrix with Nchans+1, that looks perfect to me, then I did perform fourier transformations with a hanning window, and workded perfectly, but if I set 
cfg.method='coh'
cfg.complex='imag'
cfg.channelcbm={'all', 'ref-P7'}
icohe=ft_connectovityanalysis(cfg,)

I always get the following error:
???? attempted to access siz(4); index out of bounds because numel(siz=3)
Error in ==> ft_checkdata>fixcsd at 798

I have also tried something like:
cfg.channelcbm={{1x40cell}, 'ref-P7'}
where {1x40 cell} is a cell matrix containing the names of all my sensors

but it didn't worked.

Any help will be appreciated

Many thanks in advanced,
Gabriel

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From manuel.mercier at einstein.yu.edu  Fri Jun 28 22:43:54 2013
From: manuel.mercier at einstein.yu.edu (Manuel  Mercier)
Date: Fri, 28 Jun 2013 20:43:54 +0000
Subject: [FieldTrip] PLV formula
Message-ID: <D0B70B31DE8EC849948A63FAED36B67D2A14420D@AEWEXCPM21.yuad.uds.yu.edu>

Dear Fieldtripers
Sometime ago I wrote for myself a function that was computing PLV and some related non parametric statistics.
(Phase Locking Value as define as the mean across trials of the phase angle difference recorded at two loci ; based on Lachaux et al., 1999, HBM).
I implemented PLV in matlab using the following formula:
plv = squeeze(abs(mean(exp(1i*(angle(data.fourierspctrm(:,cmb(1),:,:)) ...
                                                -angle(data.fourierspctrm(:,cmb(2),:,:)))),1)));
with cmb(1) and cmb(2) being the indices of the electrodes of interest (between which PLV is computed).
I compared my results with the ft_connectivityanalysis function from Fieldtrip and the results were exactly the same.
So far so good.

But I recently went back to my code, and I was a little bit confused.
Since I was dealing with angles, I though that the best way to do the subtraction should be done in the complex plane
Like:
plv = squeeze(abs(mean(exp(1i*(angle(exp(1i*(angle(data.fourierspctrm(:,cmb(1),:,:)))) ...
                                                        - exp(1i*(angle(data.fourierspctrm(:,cmb(2),:,:))))))),1)));
(for instance if the two angles: pi/2 and -pi/2 the direct subtraction will give pi,
whereas in the complex plan it will be pi/2 - with the norm x2).

The result I got with this code is obviously different from the previous one, and what I got from Fieldtrip.
I went back to the archive of the mailing list but didn't find a clear answer to my point. Does anyone can enlighten me ?
Thanks !

Manuel


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From ebrahimi_nia at yahoo.com  Sat Jun  1 06:52:43 2013
From: ebrahimi_nia at yahoo.com (Fatemeh Ebrahimi nia)
Date: Fri, 31 May 2013 21:52:43 -0700 (PDT)
Subject: [FieldTrip] loreta2fieldtrip function error
In-Reply-To: <1370015815.5183.YahooMailNeo@web122402.mail.ne1.yahoo.com>
References: <1369934092.15336.YahooMailNeo@web122405.mail.ne1.yahoo.com>
	<51A78CC1.6030906@berkeley.edu>
	<1370015815.5183.YahooMailNeo@web122402.mail.ne1.yahoo.com>
Message-ID: <1370062363.83888.YahooMailNeo@web122406.mail.ne1.yahoo.com>



Hi Dear all,
Can any one give me information about the output structure of "loreta2fieldtrip" function (What do the matrixes refer to?) or advise a reference to study about that please? 

Best,
Fatemeh



________________________________
 From: Ingrid Nieuwenhuis <inieuwenhuis at berkeley.edu>
To: fieldtrip at science.ru.nl 
Sent: Thursday, May 30, 2013 10:30 AM
Subject: Re: [FieldTrip] loreta2fieldtrip function error
 


Hi Fatemeh,

I had the same error recently when I did the same. I filed the bug,
    see http://bugzilla.fcdonders.nl/show_bug.cgi?id=2144

I did create a work around. In the LORETA program, you can export
    the source data as a text file. You can read that text file in with
    loreta2fieldtrip.m. It's a bit of a patch, but it worked for me. 

Hope this helps,
Ingrid


On 5/30/2013 10:14 AM, Fatemeh Ebrahimi nia wrote:

Hi dear all,
>
>
>I am analyzing EEG data. I have computed sLORETA (.slor) from ERP data. Now I want to read and convert LORETA source reconstruction into a
>MATLAB data structure using "loreta2fieldtrip" function, But I have gotten the bellow error.
>
>
>**** Error using fread
>
>Invalid precision.
>Error in loreta2fieldtrip (line 85)
>activity = fread(fid, [voxnumber Ntime], 'float = >single'); ***
>
>
>Can someone give me a help?
>
>
>
>Best regards,
>Fatemeh
>
>
>
>
>_______________________________________________
fieldtrip mailing list fieldtrip at donders.ru.nl http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

-- 
Ingrid Nieuwenhuis PhD
Postdoctoral Fellow
Sleep and Neuroimaging Laboratory
Department of Psychology
University of California, Berkeley
California 94720-1650
Tolman Hall, room 5305 
_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl
http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl
http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
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From politzerahless at gmail.com  Sat Jun  1 20:44:04 2013
From: politzerahless at gmail.com (Stephen Politzer-Ahles)
Date: Sat, 1 Jun 2013 13:44:04 -0500
Subject: [FieldTrip] Question about minimum norm estimate pipeline
Message-ID: <CAJT2k_-Qba_X4uqQeR54LFApDSe31xkWCkCAwO-DnR5=zXxWpQ@mail.gmail.com>

Hi Arjen,

Thanks for your message. I did align the mri to Talairach; as you can see
from http://i.imgur.com/26nyHYZ.png, the volume conduction model and
sourcespace are both expressed in the same coordinate system (i.e.,
everything's pointing in the same direction) but they're just not sitting
on top of one another. If anyone has any ideas on where that problem was
introduced (or how to re-align them now), I would greatly appreciate it.
Below I have some more details about how I processed that data, if it helps.

I'm trying to go through the data one step at a time and track where the
problem might have happened. When I compare the sourcespace before having
applied any transformation (i.e., the headshape from
<subject>-oct-6-src.fif) to the original mri (orig-nomask.mgz), they look
ok (I don't know how to plot them together, but see
http://i.imgur.com/LGW7YnJ.png and http://i.imgur.com/JUoTxc9.png -- things
at least look like they're on more or less the same plane). Then I
re-register the mri to CTF (
http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate#source_modelco-registration_of_the_source_space_to_the_sensor-based_head_coordinate_system);
after that, in mri_nom_ctf, the axes are all going in the right direction
but the whole head is tilted forward and the origin of the axes is no
longer at the anterior commisure (see http://i.imgur.com/CTZNOTk.png for
the realigned MRI).  Applying the transformation matrix T to the
sourcespace also seems to tilt it like that (http://i.imgur.com/bcNIpf3.png),
although as can be seen from the first image in this message it doesn't
quite line up with the volume conduction model in the end. As for the
volume conduction model, here is what it looks like at first (
http://i.imgur.com/ZX3m38b.png) and here is what it looks like after
applying the transformation matrix (http://i.imgur.com/vXa3Cnc.png).
Obviously the transformation matrix is doing something, but it's not
getting the sourcespace and volume conduction model lined up; since it's
the same transformation matrix, all I can guess is that there was some
pre-existing difference between the source mesh (the .fif file) and the
anatomical mri (orig-nomask.mgz), but I'm not sure when that came in.

Another minor issue: when I first compared the volume conduction model and
the sourcespace, they were expressed in different units even though I
followed the code in the tutorial. See http://i.imgur.com/orwgcTJ.png: the
sourcespace looks 10x smaller than the volume conduction model, which I
assume is because it is expressed in cm whereas the volume conduction model
is expressed in mm. To get the figure linked at the very beginning of this
message, I had to convert the units of the volume conduction model to cm,
even though that's not in the tutorial.

I notice that the tutorial on the wiki hasn't been edited since October
2012 (other than a few edits I made this month which were just correcting
typos in the prose). Is it possible that what's on the wiki is out of date?
(Also cc'ing Lilla on this.)

Thanks,
Steve



> Message: 1
> Date: Fri, 31 May 2013 08:11:23 +0200 (CEST)
> From: "Stolk, A." <a.stolk at fcdonders.ru.nl>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] Question about minimum norm estimate pipeline
> Message-ID:
>         <
1914237354.1292588.1369980683984.JavaMail.root at sculptor.zimbra.ru.nl>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Steve, A quick guess; did you correctly align your resliced mri to
Talairach space by indicating the commissures (
http://imaging.mrc-cbu.cam.ac.uk/imaging/FindingCommissures ) and, if I'm
correct, a point in the same place, e.g. between the hemispheres? This
should update the transformation matrix. Best regards, Arjen -----
Oorspronkelijk bericht -----
> > Van: "Stephen Politzer-Ahles" <politzerahless at gmail.com>
> > Aan: fieldtrip at science.ru.nl
> > Verzonden: Vrijdag 31 mei 2013 05:53:45
> > Onderwerp: [FieldTrip] Question about minimum norm estimate pipeline
> > Hello all,
> > I have not yet gotten a response to my question below, but in the
> > meantime I have another question about the minimum norm estimate
> > workflow--specifically, about the coordinate system for the
> > skull-stripped anatomy in the step described at
> >
http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate#preprocessing_of_the_anatomical_mrisave_to_disk
> > . I'm confused by the following bit of code:
> > % ensure that the skull-stripped anatomy is expressed in the same
> > coordinate system as the anatomy
> > seg.transform = mri_tal.transform;
> > In my data, mri_tal.coordsys is 'spm' (I presume this is the result of
> > re-aligning to Talairach in the previous step?) whereas seg.coordsys
> > is 'ctf' (as a result of re-aligning to CTF several steps earlier).
> > (But mri_tal also has a field mri_tal.transformorig, which seg does
> > not have.) So should I really be using the same transform for both, as
> > shown in the tutorial?
> > Apologies if this question is pretty basic; I'm just trying to
> > pinpoint where the mis-alignment described in my message below
> > occurred, so I want to make sure I understand each step of the
> > workflow correctly
> > Best,
> > Steve
> > > Message: 1
> > > Date: Sat, 25 May 2013 08:11:18 -0500
> > > From: Stephen Politzer-Ahles < politzerahless at gmail.com >
> > > To: fieldtrip at donders.ru.nl
> > > Subject: [FieldTrip] Sourcespace and volume conductor misaligned
> > > Message-ID:
> > > <CAJT2k_9-hd_sM=hp4P-CUu+=aduSOMyZV7XPG0= fFk0ouR0wzA at mail.gmail.com
> > > >
> > > Content-Type: text/plain; charset="utf-8"
> > >
> > > Hello all,
> > >
> > > I am going through the workflow at
> > > http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate . After
> > > making
> > > the volume conduction model using ft_prepare_headmodel(), I noticed
> > > that
> > > although the volume conduction model and sourcespace have the same
> > > orientation and overall size/shape (after I converted the volume
> > > conduction
> > > model to cm, which wasn't in the tutorial but my original model came
> > > out in
> > > mm), they don't quite line up, as you can see in this figure:
> > >
> > > http://i.imgur.com/mGEtLOa.png
> > >
> > > I did interactively re-align the data to CTF (twice--in step 2 of
> > > "Preprocessing of the anatomical MRI" and in step 4 of "Source
> > > model")
> > > using fiducials, and to Talairach (step 5 of "Preprocessing of the
> > > anatomical data"), so I'm not sure how it ended up this way. The
> > > code I've
> > > used at each step is basically the same as that in the tutorial.
> > >
> > > Is there any way to line up my volume conduction model and
> > > sourcespace now,
> > > without going back and re-running most of the workflow?
> > >
> > > Best,
> > > Steve
> > >
> > > --
> > > Stephen Politzer-Ahles
> > > University of Kansas
> > > Linguistics Department
> > > http://people.ku.edu/~sjpa/
> > On Sat, May 25, 2013 at 1:56 PM, < fieldtrip-request at science.ru.nl >
> > wrote:
> > >
> > > Send fieldtrip mailing list submissions to
> > > fieldtrip at science.ru.nl
> > >
> > > To subscribe or unsubscribe via the World Wide Web, visit
> > > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > > or, via email, send a message with subject or body 'help' to
> > > fieldtrip-request at science.ru.nl
> > >
> > > You can reach the person managing the list at
> > > fieldtrip-owner at science.ru.nl
> > >
> > > When replying, please edit your Subject line so it is more specific
> > > than "Re: Contents of fieldtrip digest..."
> > >
> > >
> > > Today's Topics:
> > >
> > > 1. Sourcespace and volume conductor misaligned
> > > (Stephen Politzer-Ahles)
> > > 2. Re: fieldtrip Digest, Vol 30, Issue 31 (Johanna Zumer)
> > >
> > >
> > > ----------------------------------------------------------------------
> > >
> > > Message: 1
> > > Date: Sat, 25 May 2013 08:11:18 -0500
> > > From: Stephen Politzer-Ahles < politzerahless at gmail.com >
> > > To: fieldtrip at donders.ru.nl
> > > Subject: [FieldTrip] Sourcespace and volume conductor misaligned
> > > Message-ID:
> > > <CAJT2k_9-hd_sM=hp4P-CUu+=aduSOMyZV7XPG0= fFk0ouR0wzA at mail.gmail.com
> > > >
> > > Content-Type: text/plain; charset="utf-8"
> > >
> > > Hello all,
> > >
> > > I am going through the workflow at
> > > http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate . After
> > > making
> > > the volume conduction model using ft_prepare_headmodel(), I noticed
> > > that
> > > although the volume conduction model and sourcespace have the same
> > > orientation and overall size/shape (after I converted the volume
> > > conduction
> > > model to cm, which wasn't in the tutorial but my original model came
> > > out in
> > > mm), they don't quite line up, as you can see in this figure:
> > >
> > > http://i.imgur.com/mGEtLOa.png
> > >
> > > I did interactively re-align the data to CTF (twice--in step 2 of
> > > "Preprocessing of the anatomical MRI" and in step 4 of "Source
> > > model")
> > > using fiducials, and to Talairach (step 5 of "Preprocessing of the
> > > anatomical data"), so I'm not sure how it ended up this way. The
> > > code I've
> > > used at each step is basically the same as that in the tutorial.
> > >
> > > Is there any way to line up my volume conduction model and
> > > sourcespace now,
> > > without going back and re-running most of the workflow?
> > >
> > > Best,
> > > Steve
> > >
> > > --
> > > Stephen Politzer-Ahles
> > > University of Kansas
> > > Linguistics Department
> > > http://people.ku.edu/~sjpa/
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From Lilla.Magyari at mpi.nl  Sat Jun  1 23:22:34 2013
From: Lilla.Magyari at mpi.nl (Lilla.Magyari at mpi.nl)
Date: Sat, 1 Jun 2013 23:22:34 +0200 (CEST)
Subject: [FieldTrip] Question about minimum norm estimate pipeline
In-Reply-To: <CAJT2k_-Qba_X4uqQeR54LFApDSe31xkWCkCAwO-DnR5=zXxWpQ@mail.gmail.com>
References: <CAJT2k_-Qba_X4uqQeR54LFApDSe31xkWCkCAwO-DnR5=zXxWpQ@mail.gmail.com>
Message-ID: <2765.87.78.47.204.1370121754.squirrel@87.78.47.204>

hi Steve,

yes, it is possible that the tutorial is slightly out of the date. I can
look at your problem and the tutorial around the end of the next week.
Thanks a lot for the detailed email!

Lilla



> Hi Arjen,
>
> Thanks for your message. I did align the mri to Talairach; as you can see
> from http://i.imgur.com/26nyHYZ.png, the volume conduction model and
> sourcespace are both expressed in the same coordinate system (i.e.,
> everything's pointing in the same direction) but they're just not sitting
> on top of one another. If anyone has any ideas on where that problem was
> introduced (or how to re-align them now), I would greatly appreciate it.
> Below I have some more details about how I processed that data, if it
> helps.
>
> I'm trying to go through the data one step at a time and track where the
> problem might have happened. When I compare the sourcespace before having
> applied any transformation (i.e., the headshape from
> <subject>-oct-6-src.fif) to the original mri (orig-nomask.mgz), they look
> ok (I don't know how to plot them together, but see
> http://i.imgur.com/LGW7YnJ.png and http://i.imgur.com/JUoTxc9.png --
> things
> at least look like they're on more or less the same plane). Then I
> re-register the mri to CTF (
> http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate#source_modelco-registration_of_the_source_space_to_the_sensor-based_head_coordinate_system);
> after that, in mri_nom_ctf, the axes are all going in the right direction
> but the whole head is tilted forward and the origin of the axes is no
> longer at the anterior commisure (see http://i.imgur.com/CTZNOTk.png for
> the realigned MRI).  Applying the transformation matrix T to the
> sourcespace also seems to tilt it like that
> (http://i.imgur.com/bcNIpf3.png),
> although as can be seen from the first image in this message it doesn't
> quite line up with the volume conduction model in the end. As for the
> volume conduction model, here is what it looks like at first (
> http://i.imgur.com/ZX3m38b.png) and here is what it looks like after
> applying the transformation matrix (http://i.imgur.com/vXa3Cnc.png).
> Obviously the transformation matrix is doing something, but it's not
> getting the sourcespace and volume conduction model lined up; since it's
> the same transformation matrix, all I can guess is that there was some
> pre-existing difference between the source mesh (the .fif file) and the
> anatomical mri (orig-nomask.mgz), but I'm not sure when that came in.
>
> Another minor issue: when I first compared the volume conduction model and
> the sourcespace, they were expressed in different units even though I
> followed the code in the tutorial. See http://i.imgur.com/orwgcTJ.png: the
> sourcespace looks 10x smaller than the volume conduction model, which I
> assume is because it is expressed in cm whereas the volume conduction
> model
> is expressed in mm. To get the figure linked at the very beginning of this
> message, I had to convert the units of the volume conduction model to cm,
> even though that's not in the tutorial.
>
> I notice that the tutorial on the wiki hasn't been edited since October
> 2012 (other than a few edits I made this month which were just correcting
> typos in the prose). Is it possible that what's on the wiki is out of
> date?
> (Also cc'ing Lilla on this.)
>
> Thanks,
> Steve
>
>
>
>> Message: 1
>> Date: Fri, 31 May 2013 08:11:23 +0200 (CEST)
>> From: "Stolk, A." <a.stolk at fcdonders.ru.nl>
>> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
>> Subject: Re: [FieldTrip] Question about minimum norm estimate pipeline
>> Message-ID:
>>         <
> 1914237354.1292588.1369980683984.JavaMail.root at sculptor.zimbra.ru.nl>
>> Content-Type: text/plain; charset="utf-8"
>>
>> Hi Steve, A quick guess; did you correctly align your resliced mri to
> Talairach space by indicating the commissures (
> http://imaging.mrc-cbu.cam.ac.uk/imaging/FindingCommissures ) and, if I'm
> correct, a point in the same place, e.g. between the hemispheres? This
> should update the transformation matrix. Best regards, Arjen -----
> Oorspronkelijk bericht -----
>> > Van: "Stephen Politzer-Ahles" <politzerahless at gmail.com>
>> > Aan: fieldtrip at science.ru.nl
>> > Verzonden: Vrijdag 31 mei 2013 05:53:45
>> > Onderwerp: [FieldTrip] Question about minimum norm estimate pipeline
>> > Hello all,
>> > I have not yet gotten a response to my question below, but in the
>> > meantime I have another question about the minimum norm estimate
>> > workflow--specifically, about the coordinate system for the
>> > skull-stripped anatomy in the step described at
>> >
> http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate#preprocessing_of_the_anatomical_mrisave_to_disk
>> > . I'm confused by the following bit of code:
>> > % ensure that the skull-stripped anatomy is expressed in the same
>> > coordinate system as the anatomy
>> > seg.transform = mri_tal.transform;
>> > In my data, mri_tal.coordsys is 'spm' (I presume this is the result of
>> > re-aligning to Talairach in the previous step?) whereas seg.coordsys
>> > is 'ctf' (as a result of re-aligning to CTF several steps earlier).
>> > (But mri_tal also has a field mri_tal.transformorig, which seg does
>> > not have.) So should I really be using the same transform for both, as
>> > shown in the tutorial?
>> > Apologies if this question is pretty basic; I'm just trying to
>> > pinpoint where the mis-alignment described in my message below
>> > occurred, so I want to make sure I understand each step of the
>> > workflow correctly
>> > Best,
>> > Steve
>> > > Message: 1
>> > > Date: Sat, 25 May 2013 08:11:18 -0500
>> > > From: Stephen Politzer-Ahles < politzerahless at gmail.com >
>> > > To: fieldtrip at donders.ru.nl
>> > > Subject: [FieldTrip] Sourcespace and volume conductor misaligned
>> > > Message-ID:
>> > > <CAJT2k_9-hd_sM=hp4P-CUu+=aduSOMyZV7XPG0= fFk0ouR0wzA at mail.gmail.com
>> > > >
>> > > Content-Type: text/plain; charset="utf-8"
>> > >
>> > > Hello all,
>> > >
>> > > I am going through the workflow at
>> > > http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate . After
>> > > making
>> > > the volume conduction model using ft_prepare_headmodel(), I noticed
>> > > that
>> > > although the volume conduction model and sourcespace have the same
>> > > orientation and overall size/shape (after I converted the volume
>> > > conduction
>> > > model to cm, which wasn't in the tutorial but my original model came
>> > > out in
>> > > mm), they don't quite line up, as you can see in this figure:
>> > >
>> > > http://i.imgur.com/mGEtLOa.png
>> > >
>> > > I did interactively re-align the data to CTF (twice--in step 2 of
>> > > "Preprocessing of the anatomical MRI" and in step 4 of "Source
>> > > model")
>> > > using fiducials, and to Talairach (step 5 of "Preprocessing of the
>> > > anatomical data"), so I'm not sure how it ended up this way. The
>> > > code I've
>> > > used at each step is basically the same as that in the tutorial.
>> > >
>> > > Is there any way to line up my volume conduction model and
>> > > sourcespace now,
>> > > without going back and re-running most of the workflow?
>> > >
>> > > Best,
>> > > Steve
>> > >
>> > > --
>> > > Stephen Politzer-Ahles
>> > > University of Kansas
>> > > Linguistics Department
>> > > http://people.ku.edu/~sjpa/
>> > On Sat, May 25, 2013 at 1:56 PM, < fieldtrip-request at science.ru.nl >
>> > wrote:
>> > >
>> > > Send fieldtrip mailing list submissions to
>> > > fieldtrip at science.ru.nl
>> > >
>> > > To subscribe or unsubscribe via the World Wide Web, visit
>> > > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> > > or, via email, send a message with subject or body 'help' to
>> > > fieldtrip-request at science.ru.nl
>> > >
>> > > You can reach the person managing the list at
>> > > fieldtrip-owner at science.ru.nl
>> > >
>> > > When replying, please edit your Subject line so it is more specific
>> > > than "Re: Contents of fieldtrip digest..."
>> > >
>> > >
>> > > Today's Topics:
>> > >
>> > > 1. Sourcespace and volume conductor misaligned
>> > > (Stephen Politzer-Ahles)
>> > > 2. Re: fieldtrip Digest, Vol 30, Issue 31 (Johanna Zumer)
>> > >
>> > >
>> > > ----------------------------------------------------------------------
>> > >
>> > > Message: 1
>> > > Date: Sat, 25 May 2013 08:11:18 -0500
>> > > From: Stephen Politzer-Ahles < politzerahless at gmail.com >
>> > > To: fieldtrip at donders.ru.nl
>> > > Subject: [FieldTrip] Sourcespace and volume conductor misaligned
>> > > Message-ID:
>> > > <CAJT2k_9-hd_sM=hp4P-CUu+=aduSOMyZV7XPG0= fFk0ouR0wzA at mail.gmail.com
>> > > >
>> > > Content-Type: text/plain; charset="utf-8"
>> > >
>> > > Hello all,
>> > >
>> > > I am going through the workflow at
>> > > http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate . After
>> > > making
>> > > the volume conduction model using ft_prepare_headmodel(), I noticed
>> > > that
>> > > although the volume conduction model and sourcespace have the same
>> > > orientation and overall size/shape (after I converted the volume
>> > > conduction
>> > > model to cm, which wasn't in the tutorial but my original model came
>> > > out in
>> > > mm), they don't quite line up, as you can see in this figure:
>> > >
>> > > http://i.imgur.com/mGEtLOa.png
>> > >
>> > > I did interactively re-align the data to CTF (twice--in step 2 of
>> > > "Preprocessing of the anatomical MRI" and in step 4 of "Source
>> > > model")
>> > > using fiducials, and to Talairach (step 5 of "Preprocessing of the
>> > > anatomical data"), so I'm not sure how it ended up this way. The
>> > > code I've
>> > > used at each step is basically the same as that in the tutorial.
>> > >
>> > > Is there any way to line up my volume conduction model and
>> > > sourcespace now,
>> > > without going back and re-running most of the workflow?
>> > >
>> > > Best,
>> > > Steve
>> > >
>> > > --
>> > > Stephen Politzer-Ahles
>> > > University of Kansas
>> > > Linguistics Department
>> > > http://people.ku.edu/~sjpa/
>




From frank.ye.mei at gmail.com  Sun Jun  2 03:58:29 2013
From: frank.ye.mei at gmail.com (Frank Mei)
Date: Sat, 1 Jun 2013 21:58:29 -0400
Subject: [FieldTrip] error when using ctf2grad (Lozano Soldevilla,
	D. (Diego))
Message-ID: <CAF0J_Mts3imCMYaVE8QppR=oT8j0h9ceLKm=ANtW6JNyAxoPcA@mail.gmail.com>

Hello Diego,

Thank you for the reply. I was using fieldtrip20120822.

I found the bug in the fieldtrip20120822 file -ft_read_header.m.
In line 446 of the file:

-------
if any(~cellfun(@isempty,strfind(coeftype, 'G1AR')))
-------

should be:

-------
if any(~cellfun(@isempty,strfind(coeftype, 'G3AR')))
-------


The bug is corrected in the latest version of fieldtrip, and it runs
correctly now.

Now, grad.balance has 'G1BR','G2BR','G3BR''G3AR' in it.

The ctf sytem I use is ctf151.

Regards,
Ye
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From vitoria.piai at gmail.com  Sun Jun  2 11:17:25 2013
From: vitoria.piai at gmail.com (=?ISO-8859-1?Q?Vit=F3ria_Magalh=E3es_Piai?=)
Date: Sun, 02 Jun 2013 11:17:25 +0200
Subject: [FieldTrip] how to use ft_stratify?
Message-ID: <51AB0DA5.10805@gmail.com>

Hi all,

I'm trying to use ft_stratify for the first time, but (it could be just 
me) I don't find the help info helpful enough :)
What I want to achieve in the end is TFRs of two conditions for which 
the histogram of the reaction time over trials for each condition is 
matched.

If I understood ft_stratify correctly (and I doubt that), I could use 
this function to select the trials for each condition such that the 
histograms of the RTs match. Then knowing which trials to keep, I run 
ft_freqanalysis on those specifically.
So question number 1, is that how I should proceed? 'Cause as far as I 
can tell, ft_stratify will not take a whole raw data structure: The help 
says "each input is a Nchan X Nobs matrix". So I have to go for the RTs 
then.

Assuming my approach is correct (ft_stratify on RTs of two conditions, 
then move on with only those trials), I've made a matrix Nchan x 
N_trials for each condition.
% input1 = 265 sensors x 95 RT_trials;
% input2 = 265 sensors x 100 RT_trials;

         cfgst = [];
         cfgst.method      = 'histogram';
         cfgst.equalbinavg = 'no';
         cfgst.numbin      = 4;
         cfgst.numiter     = 2000; % default
         [output,bin] = ft_stratify(cfgst, input1, input2);

I then get an error in line 127:
linearhisto = zeros(ncond, cfg.numbin.^nchan);
??? Error using ==> zeros
Maximum variable size allowed by the program is exceeded.

Apparently, zeros(2, 4^265) is something matlab doesn't want to calculate!
Am I doing something wrong here? Has anyone worked with this function 
before (with such a number of sensors)?

Any help is greatly appreciated!
Cheers, Vitória


From a.stolk at fcdonders.ru.nl  Sun Jun  2 11:46:03 2013
From: a.stolk at fcdonders.ru.nl (Stolk, A.)
Date: Sun, 2 Jun 2013 11:46:03 +0200 (CEST)
Subject: [FieldTrip] how to use ft_stratify?
In-Reply-To: <51AB0DA5.10805@gmail.com>
Message-ID: <1910615072.1312606.1370166363974.JavaMail.root@sculptor.zimbra.ru.nl>

Hi Vitoria,

There is a wikipage that may help you get started, and answer your questions:
http://fieldtrip.fcdonders.nl/example/stratify

Best wishes,
Arjen  

----- Oorspronkelijk bericht -----
> Van: "Vitória Magalhães Piai" <vitoria.piai at gmail.com>
> Aan: fieldtrip at donders.ru.nl
> Verzonden: Zondag 2 juni 2013 11:17:25
> Onderwerp: [FieldTrip] how to use ft_stratify?
> Hi all,
> 
> I'm trying to use ft_stratify for the first time, but (it could be
> just
> me) I don't find the help info helpful enough :)
> What I want to achieve in the end is TFRs of two conditions for which
> the histogram of the reaction time over trials for each condition is
> matched.
> 
> If I understood ft_stratify correctly (and I doubt that), I could use
> this function to select the trials for each condition such that the
> histograms of the RTs match. Then knowing which trials to keep, I run
> ft_freqanalysis on those specifically.
> So question number 1, is that how I should proceed? 'Cause as far as I
> can tell, ft_stratify will not take a whole raw data structure: The
> help
> says "each input is a Nchan X Nobs matrix". So I have to go for the
> RTs
> then.
> 
> Assuming my approach is correct (ft_stratify on RTs of two conditions,
> then move on with only those trials), I've made a matrix Nchan x
> N_trials for each condition.
> % input1 = 265 sensors x 95 RT_trials;
> % input2 = 265 sensors x 100 RT_trials;
> 
> cfgst = [];
> cfgst.method = 'histogram';
> cfgst.equalbinavg = 'no';
> cfgst.numbin = 4;
> cfgst.numiter = 2000; % default
> [output,bin] = ft_stratify(cfgst, input1, input2);
> 
> I then get an error in line 127:
> linearhisto = zeros(ncond, cfg.numbin.^nchan);
> ??? Error using ==> zeros
> Maximum variable size allowed by the program is exceeded.
> 
> Apparently, zeros(2, 4^265) is something matlab doesn't want to
> calculate!
> Am I doing something wrong here? Has anyone worked with this function
> before (with such a number of sensors)?
> 
> Any help is greatly appreciated!
> Cheers, Vitória
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip



From vitoria.piai at gmail.com  Sun Jun  2 17:09:34 2013
From: vitoria.piai at gmail.com (=?ISO-8859-1?Q?Vit=F3ria_Magalh=E3es_Piai?=)
Date: Sun, 02 Jun 2013 17:09:34 +0200
Subject: [FieldTrip] how to use ft_stratify?
In-Reply-To: <mailman.11.1370167205.25821.fieldtrip@science.ru.nl>
References: <mailman.11.1370167205.25821.fieldtrip@science.ru.nl>
Message-ID: <51AB602E.8020609@gmail.com>

Thanx, Arjen!
Shame on me, I should have known that there would be a wikipage on that :)

And for the sake of archiving, in case someone else ever bumps into this 
thread because they're making the same mistake as me when using this 
function, here's what I was doing wrong:
The input Nchan x N_trials for each condition, Nchan should be 1 'cause 
my data are the RTs
So:

% input1 = RT_trials_cond1' ; % size = 1 x 95
% input2 = RT_trials_cond2' ;  % size = 1 x 100
cfgst = [];
cfgst.method = 'histogram';
output = ft_stratify(cfgst, input1, input2);

Now it will run and it won't even complain they are of different sizes 
either!

Hope this will help anyone in the future making the same mistake!
Cheers, Vitória



On 6/2/2013 12:00 PM, fieldtrip-request at science.ru.nl wrote:
> Message: 2
> Date: Sun, 02 Jun 2013 11:17:25 +0200
> From: Vit?ria Magalh?es Piai<vitoria.piai at gmail.com>
> To:fieldtrip at donders.ru.nl
> Subject: [FieldTrip] how to use ft_stratify?
> Message-ID:<51AB0DA5.10805 at gmail.com>
> Content-Type: text/plain; charset=ISO-8859-1; format=flowed
>
> Hi all,
>
> I'm trying to use ft_stratify for the first time, but (it could be just
> me) I don't find the help info helpful enough:)
> What I want to achieve in the end is TFRs of two conditions for which
> the histogram of the reaction time over trials for each condition is
> matched.
>
> If I understood ft_stratify correctly (and I doubt that), I could use
> this function to select the trials for each condition such that the
> histograms of the RTs match. Then knowing which trials to keep, I run
> ft_freqanalysis on those specifically.
> So question number 1, is that how I should proceed? 'Cause as far as I
> can tell, ft_stratify will not take a whole raw data structure: The help
> says "each input is a Nchan X Nobs matrix". So I have to go for the RTs
> then.
>
> Assuming my approach is correct (ft_stratify on RTs of two conditions,
> then move on with only those trials), I've made a matrix Nchan x
> N_trials for each condition.
> % input1 = 265 sensors x 95 RT_trials;
> % input2 = 265 sensors x 100 RT_trials;
>
>           cfgst = [];
>           cfgst.method      = 'histogram';
>           cfgst.equalbinavg = 'no';
>           cfgst.numbin      = 4;
>           cfgst.numiter     = 2000; % default
>           [output,bin] = ft_stratify(cfgst, input1, input2);
>
> I then get an error in line 127:
> linearhisto = zeros(ncond, cfg.numbin.^nchan);
> ??? Error using ==> zeros
> Maximum variable size allowed by the program is exceeded.
>
> Apparently, zeros(2, 4^265) is something matlab doesn't want to calculate!
> Am I doing something wrong here? Has anyone worked with this function
> before (with such a number of sensors)?
>
> Any help is greatly appreciated!
> Cheers, Vit?ria
>
>
> ------------------------------
>
> Message: 3
> Date: Sun, 2 Jun 2013 11:46:03 +0200 (CEST)
> From: "Stolk, A."<a.stolk at fcdonders.ru.nl>
> To: FieldTrip discussion list<fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] how to use ft_stratify?
> Message-ID:
> 	<1910615072.1312606.1370166363974.JavaMail.root at sculptor.zimbra.ru.nl>
> Content-Type: text/plain; charset=utf-8
>
> Hi Vitoria,
>
> There is a wikipage that may help you get started, and answer your questions:
> http://fieldtrip.fcdonders.nl/example/stratify
>
> Best wishes,
> Arjen

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From d.stoffers at gmail.com  Mon Jun  3 10:12:17 2013
From: d.stoffers at gmail.com (Diederick Stoffers)
Date: Mon, 3 Jun 2013 10:12:17 +0200
Subject: [FieldTrip] Postdoc positions available at the Netherlands
	Institute for Neuroscience in Amsterdam
In-Reply-To: <21E5F1A0-241E-43B6-957B-18A7767A7B51@gmail.com>
References: <21E5F1A0-241E-43B6-957B-18A7767A7B51@gmail.com>
Message-ID: <8B956BE9-4168-4ED4-B0E9-47FE260EAEE4@gmail.com>

Dear all,

Please find attached a description of postdoc positions available at the Netherlands Institute for Neuroscience in Amsterdam, which I am posting on behalf of my group leader Eus van Someren (cc). 

Relevant keywords for these positions are sleep, emotion, arousal, high-density EEG, fMRI, TMS, insomnia, internet assessment, database, latent class and latent trait analysis. 

Cheers,

Diederick


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From d.stoffers at gmail.com  Mon Jun  3 10:20:20 2013
From: d.stoffers at gmail.com (Diederick Stoffers)
Date: Mon, 3 Jun 2013 10:20:20 +0200
Subject: [FieldTrip] Postdoc positions available at the Netherlands
	Institute for Neuroscience in Amsterdam
In-Reply-To: <8B956BE9-4168-4ED4-B0E9-47FE260EAEE4@gmail.com>
References: <21E5F1A0-241E-43B6-957B-18A7767A7B51@gmail.com>
	<8B956BE9-4168-4ED4-B0E9-47FE260EAEE4@gmail.com>
Message-ID: <6DACABEC-925B-4E71-A7A2-FB8C7B2A60D1@gmail.com>

Dear all,

Please find attached a description of postdoc positions available at the Netherlands Institute for Neuroscience in Amsterdam, which I am posting on behalf of my group leader Eus van Someren (cc). 

Relevant keywords for these positions are sleep, emotion, arousal, high-density EEG, fMRI, TMS, insomnia, internet assessment, database, latent class and latent trait analysis. 

Cheers,

Diederick

NB Apologies if you receive this message twice, the initial message was rejected by some servers because it exceeded maximum message size.


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From jm.horschig at donders.ru.nl  Mon Jun  3 10:59:49 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Mon, 03 Jun 2013 10:59:49 +0200
Subject: [FieldTrip] channel combination problems
In-Reply-To: <27E5CAD9145EEC41BB9B34C01716A1983046156B@UM-EXCDAG-A01.um.gwdg.de>
References: <27E5CAD9145EEC41BB9B34C01716A1983046156B@UM-EXCDAG-A01.um.gwdg.de>
Message-ID: <51AC5B05.2020409@donders.ru.nl>

Hi Thomas,

that is indeed a bug that we are currently working on, see also here:
http://bugzilla.fcdonders.nl/show_bug.cgi?id=2148

A workaround for the moment is to call this:

   coh.dimord = 'chancmb_freq';
   coh = ft_checkdata(coh, 'cmbrepresentation', 'full');


As you asked what the difference between the two is:
Connectivity measures are define between two signals, or channels. So, 
for example you compute coherence between channel1 and channel2. In 
FieldTrip there are two ways to represent this: Either by a 3D NxMxF 
matrix or by a 2D (NxM)xF matrix, where F denotes the frequency 
dimension and N and M are the in- or output channels (coherence is a 
symmetric measure, so N=M). In other words, we can either represent it 
as a three dimensional matrix, where the first dimension denotes the 
input and the second the output channels, or we represent it as a two 
dimensional matrix, where the first dimension denotes the relation 
between in- and output channels. The latter is what we call a 
channelcombination (chancmb). It can be channel1->channel2 (meaning, 
influence from channel1 to channel 2). The same in a three dimensional 
matrix would be channel1 for dimension 1 and channel 2 for dimension 2. 
The workaround above converts from one to the other convention. If your 
data is in 'cmbrepresentation;, you will have 'labelcmb' which is a 2D 
cell-matrix, and your data dimensions (dimord) will be 'chancmb_XXX', 
where a single dimension respective to labelcmb defines the channel 
combination. If your data is not in 'cmbrepresentation', you will have a 
1D 'label' field and your data dimension (dimord) will be 
'chan_chan_XXX', this a 2D channel combinations that explains the 
channel combination.

Btw, I am not aware that you can define cfg.labelcmb in any function, 
imho it is always cfg.channelcmb.

Best,
Jörn


On 5/31/2013 11:42 AM, Wunderle, Thomas wrote:
>
> Hi all,
>
> I'm new in fieldtrip and I try to get the cfg.channelcmb to work, 
> because I want to plot the connectivity between the channels of 
> different laminar electrodes,
>
> let's say the connectivity between channel 1:24 and 25:38
>
> I tried the following:
>
> cfg           = [];
>
> cfg.method    = 'mtmfft';
>
> cfg.taper     = 'dpss';
>
> cfg.output    = 'fourier';
>
> cfg.tapsmofrq = 1;
>
> freq          = ft_freqanalysis(cfg, data)
>
> The output is:
>
> >> freq
>
> freq =
>
>             label: {3x1 cell}
>
>            dimord: 'rpttap_chan_freq'
>
>             freq: [1x101 double]
>
>             fourierspctrm: [500x3x101 double]
>
>             cumsumcnt: [500x1 double]
>
>             cumtapcnt: [500x1 double]
>
>              cfg: [1x1 struct]
>
> I then run
>
> cfg = [];
>
> cfg.method = 'coh';
>
> cfg.channelcmb = {freq.label{1} freq.label{2};freq.label{2} 
> freq.label{1}};
>
> coh= ft_connectivityanalysis(cfg, freq);
>
> And the output here is:
>
> >> coh
>
> coh =
>
>        labelcmb: {2x2 cell}
>
>        dimord: 'chan_freq'
>
>        cohspctrm: [2x101 double]
>
>         freq: [1x101 double]
>
>         dof: 500
>
>         cfg: [1x1 struct]
>
> As you can seen, the output of dimord is 'chan_freq' so in the 
> subsequent call of ft_connectivityplot I get an error message:
>
> cfg           = [];
>
> cfg.parameter = 'cohspctrm';
>
> ft_connectivityplot(cfg, coh);
>
> ??? Error using ==> ft_connectivityplot at 99
>
> the data should have a dimord of chan_chan_freq or chancmb_freq
>
> If I use in ft_freqanalysis the cfg.method = 'powandcsd', 
> cfg.channelcmb seems to have no effect at all,
>
> the coherence is computed for all possible pairs.
>
> I also don't understand the difference between "cfg.channelcmb" and 
> "cfg.labelcmb"
>
> Can you help me in how I should correctly use the cannelcmb and 
> labelcmb options?
>
> Thanks for your help,
>
> Thomas
>
> -----
>
> Dr. Thomas Wunderle
>
> Ernst Strüngmann Institute (ESI) for Neuroscience 
> <http://www.ncbi.nlm.nih.gov/feed/rss.cgi?ChanKey=PubMedNews>
>
> in Cooperation with Max Planck Society 
> <http://www.ncbi.nlm.nih.gov/feed/rss.cgi?ChanKey=PubMedNews>
>
> Deutschordenstrasse 46
>
> 60528 Frankfurt am Main, Germany
>
> www.esi-frankfurt.de <http://www.esi-frankfurt.de/>
>
> thomas.wunderle at esi-frankfurt.de <mailto:thomas.wunderle at esi-frankfurt.de>
>
> Tel: +49 69 96769 519
>
> Fax: +49 69 96769 555
>
> Sitz der Gesellschaft: Frankfurt am Main
>
> Registergericht: Amtsgericht Frankfurt - HRB 84266
>
> Geschäftsführer: Prof. Dr. Pascal Fries
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands

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From jm.horschig at donders.ru.nl  Mon Jun  3 11:30:34 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Mon, 03 Jun 2013 11:30:34 +0200
Subject: [FieldTrip] some of the requested samples occur twice
In-Reply-To: <CALsWBNOxcuA=LCMONaGWObU4fdZ3+vskGGFcKdTZE4jGRoW47Q@mail.gmail.com>
References: <CALsWBNOxcuA=LCMONaGWObU4fdZ3+vskGGFcKdTZE4jGRoW47Q@mail.gmail.com>
Message-ID: <51AC623A.1080207@donders.ru.nl>

Hi Robin,

it's not a bug that ft_fetch_data is not allowing for overlap. The 
function needs to be generic and eventually allow for fetching data 
extending over several trial segments. However, what should be the way 
to fetch  data that occurs twice, i.e. at the end of one trial and the 
beginning of another? If you have data with overlapping samples, it is 
not straight forward to define data from one trial as to be fetched and 
ignore the other. Since preprocessing options like filters are applied 
per trial segment, data will differ between trial segments if it 
overlaps. As there are a multitude of possibilities to deal with this 
and none of them is perfect (imho neither of them can even be called 
good), we decided to not allow for that.

For your problem, however, imho you can define negative trial padding in 
the function call to ft_artifact_zvalue, which should effectively pad. 
Have you tried this rather than padding manually?

Best,
Jörn

On 5/31/2013 6:14 PM, Robin wrote:
> I have a problem in preprocessing where I am getting this error:
>
> """
> some of the requested samples occur twice in the data
>
> Error in ft_artifact_zvalue (line 262)
>        dat{trlop} = ft_fetch_data(data,        'header', hdr, 'begsample',
>        trl(trlop,1)-fltpadding, 'endsample', trl(trlop,2)+fltpadding,
>        'chanindx', sgnind, 'checkboundary', strcmp(cfg.continuous,'no
> Error in ft_artifact_muscle (line 158)
>      [tmpcfg, artifact] = ft_artifact_zvalue(tmpcfg, data);
> """
>
> I think this is because I am manually adding some extra padding to the
> trials so that the artifact filtering can use that padding (I am doing
> the artifact filtering on data in memory which is output from
> ft_denoise_pca). So in this case it is not a problem if consecutive
> trials overlap a bit.
>
> I would therefore like to disable this error and wondered what is the
> best way to do it. I am a bit confused because ft_artifact_zvalue
> calls ft_fetch data with a "checkboundary" option which looks like it
> might be what I want (and set correctly), but ft_fetch_data doesn't
> seem to use that option. Instead it has an allowoverlap option.
>
> So for now I will manually add the allowoverlap option to the call in
> ft_artifact_zvalue, but I wondered what checkboundary doesn't appear
> in ft_fetch_data or if this might be a bug.
>
> Cheers
>
> Robin
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands



From julian.keil at gmail.com  Mon Jun  3 17:14:08 2013
From: julian.keil at gmail.com (Julian Keil)
Date: Mon, 3 Jun 2013 17:14:08 +0200
Subject: [FieldTrip] Polhemus Patriot
Message-ID: <67D8C434-4D28-40C3-94A6-A95C86BD6B78@gmail.com>

Dear FieldTrip-Users,

I have a not really FieldTrip-related question, but maybe one of you can help me anyways.
In our lab, we have a Polhemus Patriot 3D tracking system to acquire electrode positions.
Unfortunately, the recordings are severely distorted in the Z-axis (up-down).
After contacting the Polhemus Support, I got the information, that this is due to metal in the surroundings of the source which distorts the magnetic field.
I tried to get as far away from any metal as possible in our lab (~1.5 m to the walls and floor) but to no avail.

Now to my question: Has anyone any experience dealing with this? I'm quite puzzled by this as I know plenty of labs use Polhemus trackers, and I'm not sure if our lab is especially metal prone or if I'm missing something.

Thanks a lot for any help.

Julian

********************
Dr. Julian Keil

AG Multisensorische Integration
Psychiatrische Universitätsklinik
der Charité im St. Hedwig-Krankenhaus
Große Hamburger Straße 5-11, Raum E 307
10115 Berlin

Telefon: +49-30-2311-1879
Fax:        +49-30-2311-2209 
http://psy-ccm.charite.de/forschung/bildgebung/ag_multisensorische_integration

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From inieuwenhuis at berkeley.edu  Mon Jun  3 17:52:14 2013
From: inieuwenhuis at berkeley.edu (Ingrid Nieuwenhuis)
Date: Mon, 03 Jun 2013 08:52:14 -0700
Subject: [FieldTrip] loreta2fieldtrip function error
In-Reply-To: <1370015815.5183.YahooMailNeo@web122402.mail.ne1.yahoo.com>
References: <1369934092.15336.YahooMailNeo@web122405.mail.ne1.yahoo.com>
	<51A78CC1.6030906@berkeley.edu>
	<1370015815.5183.YahooMailNeo@web122402.mail.ne1.yahoo.com>
Message-ID: <51ACBBAE.4070508@berkeley.edu>

Hi Fatameh,

- In the LORETA program, you go to main utilities > Format converter.
- There you select: input binary file (sLORETA)
- It does not matter which format for output you choose, I coded it 
robust, it'll figure it out. As it says, rows are time points, columns 
are the volume-gridpoints (called voxels)
- After using loreta2fieldtrip the data is in normal FieldTrip volume 
format, see here: http://fieldtrip.fcdonders.nl/reference/ft_datatype_volume

To get familiar with FieldTrip source plotting etc, see the tutorials, 
for instance: http://fieldtrip.fcdonders.nl/tutorial/plotting
- The following steps are:
1) create a template: template = ft_read_mri([cur_path_FT, 
'\external\spm8\templates\T1.nii']);
2) interpolate your volume on the MNI template: [interp_mean] = 
ft_sourceinterpolate(cfg, GA_mean, template);
3) plot it using ft_sourceplot

Hope it helps,
Ingrid

On 5/31/2013 8:56 AM, Fatemeh Ebrahimi nia wrote:
> Dear respondent,
>
> Thank you for your advices.
> I have used the function that you have updated. It works out. Can you 
> give me information about the output structure (What do the matrixes 
> refer to?) or advise a reference to study about that please?
>
> Best,
> Fatemeh
>
>
> ------------------------------------------------------------------------
> *From:* Ingrid Nieuwenhuis <inieuwenhuis at berkeley.edu>
> *To:* fieldtrip at science.ru.nl
> *Sent:* Thursday, May 30, 2013 10:30 AM
> *Subject:* Re: [FieldTrip] loreta2fieldtrip function error
>
> Hi Fatemeh,
>
> I had the same error recently when I did the same. I filed the bug, 
> see http://bugzilla.fcdonders.nl/show_bug.cgi?id=2144
>
> I did create a work around. In the LORETA program, you can export the 
> source data as a text file. You can read that text file in with 
> loreta2fieldtrip.m. It's a bit of a patch, but it worked for me.
>
> Hope this helps,
> Ingrid
>
> On 5/30/2013 10:14 AM, Fatemeh Ebrahimi nia wrote:
>> Hi dear all,
>>
>> I am analyzing EEG data. I have computed sLORETA (.slor) from ERP 
>> data. Now I want to read and convert LORETA source reconstruction into a
>> MATLAB data structure using "loreta2fieldtrip" function, But I have 
>> gotten the bellow error.
>>
>> **** Error using fread
>> Invalid precision.
>> Error in loreta2fieldtrip (line 85)
>> activity = fread(fid, [voxnumber Ntime], 'float = >single'); ***
>>
>> Can someone give me a help?
>>
>> Best regards,
>> Fatemeh
>>
>>
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl  <mailto:fieldtrip at donders.ru.nl>
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
> -- 
> Ingrid Nieuwenhuis PhD
> Postdoctoral Fellow
> Sleep and Neuroimaging Laboratory
> Department of Psychology
> University of California, Berkeley
> California 94720-1650
> Tolman Hall, room 5305
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl <mailto:fieldtrip at donders.ru.nl>
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

-- 
Ingrid Nieuwenhuis PhD
Postdoctoral Fellow
Sleep and Neuroimaging Laboratory
Department of Psychology
University of California, Berkeley
California 94720-1650
Tolman Hall, room 5305

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From smoratti at psi.ucm.es  Mon Jun  3 18:07:40 2013
From: smoratti at psi.ucm.es (smoratti at psi.ucm.es)
Date: Mon, 3 Jun 2013 18:07:40 +0200
Subject: [FieldTrip] Polhemus Patriot
In-Reply-To: <67D8C434-4D28-40C3-94A6-A95C86BD6B78@gmail.com>
References: <67D8C434-4D28-40C3-94A6-A95C86BD6B78@gmail.com>
Message-ID: <C92FAB98-3619-4953-9C1D-DFD3186EFD40@psi.ucm.es>

Dear Julian,

Maybe a stupid answer and probably you have taken care of this already, but does the chair have any metal? We use an IKEA wooden garden chair.

Best,

Stephan

________________________________________________________
Stephan Moratti, PhD

see also: http://web.me.com/smoratti/

Universidad Complutense de Madrid
Facultad de Psicología
Departamento de Psicología Básica I
Campus de Somosaguas
28223 Pozuelo de Alarcón (Madrid)
Spain

and

Center for Biomedical Technology
Laboratory for Cognitive and Computational Neuroscience
Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
Campus Montegancedo
28223 Pozuelo de Alarcón (Madrid)
Spain


email: smoratti at psi.ucm.es
Tel.:    +34 679219982

El 03/06/2013, a las 17:14, Julian Keil escribió:

> Dear FieldTrip-Users,
> 
> I have a not really FieldTrip-related question, but maybe one of you can help me anyways.
> In our lab, we have a Polhemus Patriot 3D tracking system to acquire electrode positions.
> Unfortunately, the recordings are severely distorted in the Z-axis (up-down).
> After contacting the Polhemus Support, I got the information, that this is due to metal in the surroundings of the source which distorts the magnetic field.
> I tried to get as far away from any metal as possible in our lab (~1.5 m to the walls and floor) but to no avail.
> 
> Now to my question: Has anyone any experience dealing with this? I'm quite puzzled by this as I know plenty of labs use Polhemus trackers, and I'm not sure if our lab is especially metal prone or if I'm missing something.
> 
> Thanks a lot for any help.
> 
> Julian
> 
> ********************
> Dr. Julian Keil
> 
> AG Multisensorische Integration
> Psychiatrische Universitätsklinik
> der Charité im St. Hedwig-Krankenhaus
> Große Hamburger Straße 5-11, Raum E 307
> 10115 Berlin
> 
> Telefon: +49-30-2311-1879
> Fax:        +49-30-2311-2209 
> http://psy-ccm.charite.de/forschung/bildgebung/ag_multisensorische_integration
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From sarang.dalal at uni-konstanz.de  Mon Jun  3 18:16:02 2013
From: sarang.dalal at uni-konstanz.de (Sarang S. Dalal)
Date: Mon, 3 Jun 2013 09:16:02 -0700
Subject: [FieldTrip] Polhemus Patriot
In-Reply-To: <mailman.159.1370275680.1298.fieldtrip@science.ru.nl>
References: <mailman.159.1370275680.1298.fieldtrip@science.ru.nl>
Message-ID: <27A129F9-9570-4D6B-BBF9-48080801F980@uni-konstanz.de>

Dear Julian,

At UCSF, we were unable to use a Polhemus (an older model, not sure which) in the shielded room of the MEG, so we performed the digitization just outside the room before moving the subject inside. Perhaps if you have a nicely shielded EEG booth you have the same problem...

Sarang


On Jun 3, 2013, at 9:08 AM, fieldtrip-request at science.ru.nl wrote:
> Date: Mon, 3 Jun 2013 17:14:08 +0200
> From: Julian Keil <julian.keil at gmail.com>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: [FieldTrip] Polhemus Patriot
> Message-ID: <67D8C434-4D28-40C3-94A6-A95C86BD6B78 at gmail.com>
> Content-Type: text/plain; charset="iso-8859-1"
> 
> Dear FieldTrip-Users,
> 
> I have a not really FieldTrip-related question, but maybe one of you can help me anyways.
> In our lab, we have a Polhemus Patriot 3D tracking system to acquire electrode positions.
> Unfortunately, the recordings are severely distorted in the Z-axis (up-down).
> After contacting the Polhemus Support, I got the information, that this is due to metal in the surroundings of the source which distorts the magnetic field.
> I tried to get as far away from any metal as possible in our lab (~1.5 m to the walls and floor) but to no avail.
> 
> Now to my question: Has anyone any experience dealing with this? I'm quite puzzled by this as I know plenty of labs use Polhemus trackers, and I'm not sure if our lab is especially metal prone or if I'm missing something.
> 
> Thanks a lot for any help.
> 
> Julian
> 
> ********************
> Dr. Julian Keil
> 
> AG Multisensorische Integration
> Psychiatrische Universit?tsklinik
> der Charit? im St. Hedwig-Krankenhaus
> Gro?e Hamburger Stra?e 5-11, Raum E 307
> 10115 Berlin
> 
> Telefon: +49-30-2311-1879
> Fax:        +49-30-2311-2209 
> http://psy-ccm.charite.de/forschung/bildgebung/ag_multisensorische_integration




From inieuwenhuis at berkeley.edu  Mon Jun  3 18:25:47 2013
From: inieuwenhuis at berkeley.edu (Ingrid Nieuwenhuis)
Date: Mon, 03 Jun 2013 09:25:47 -0700
Subject: [FieldTrip] format conversion
In-Reply-To: <1369986505.7865.YahooMailNeo@web192306.mail.sg3.yahoo.com>
References: <1369986505.7865.YahooMailNeo@web192306.mail.sg3.yahoo.com>
Message-ID: <51ACC38B.9080802@berkeley.edu>

Hi Bahar,

I've added more info on the FieldTrip wiki about this for you and other. 
See here:
http://fieldtrip.fcdonders.nl/integrating_with_loreta

Hope it helps,
Ingrid


On 5/31/2013 12:48 AM, Bahar Bahar wrote:
> Hi dear all,
>
> I have a technical question about format converter module via sLORETA 
> software (.slor file to .txt one). Can any one give me some 
> information about the conversion procedure (and the meaning of the 
> column and row of the output file)?
>
> Thanks,
> bahar
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

-- 
Ingrid Nieuwenhuis PhD
Postdoctoral Fellow
Sleep and Neuroimaging Laboratory
Department of Psychology
University of California, Berkeley
California 94720-1650
Tolman Hall, room 5305

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From andmib at gmail.com  Mon Jun  3 22:15:49 2013
From: andmib at gmail.com (Andrew Brooks)
Date: Mon, 3 Jun 2013 16:15:49 -0400
Subject: [FieldTrip] Private function problems
Message-ID: <CALJPz69S8R+n+vWMYsmqC_Rqo63FbfECL+UStC0HcjQA3m8w2w@mail.gmail.com>

Hello all,

I followed the instructions on properly adding FieldTrip to the Matlab path
file. However, I continue to run into errors involving private functions.
In this case, I get the error 'undefined function 'hom2six' for input
arguments of type 'double''.

Does anybody have a suggestion as to why this is occurring?

Thanks!
Andrew
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From d.lozanosoldevilla at fcdonders.ru.nl  Mon Jun  3 22:53:41 2013
From: d.lozanosoldevilla at fcdonders.ru.nl (Lozano Soldevilla, D. (Diego))
Date: Mon, 3 Jun 2013 22:53:41 +0200 (CEST)
Subject: [FieldTrip] Private function problems
In-Reply-To: <CALJPz69S8R+n+vWMYsmqC_Rqo63FbfECL+UStC0HcjQA3m8w2w@mail.gmail.com>
Message-ID: <481032685.1338448.1370292821035.JavaMail.root@sculptor.zimbra.ru.nl>

Hi Andrew, Did you type the following? >> restoredefaultpath >> addpath /fieldtripxxxx >> ft_defaults What's the ft_* function you invoke to get the error 'undefined function 'hom2six'? And what's the fieldtrip version you're using? best, Diego ----- Original Message -----
> From: "Andrew Brooks" <andmib at gmail.com>
> To: "FieldTrip discussion list" <fieldtrip at science.ru.nl>
> Sent: Monday, 3 June, 2013 10:15:49 PM
> Subject: [FieldTrip] Private function problems
> Hello all,
> I followed the instructions on properly adding FieldTrip to the Matlab
> path file. However, I continue to run into errors involving private
> functions. In this case, I get the error 'undefined function 'hom2six'
> for input arguments of type 'double''.
> Does anybody have a suggestion as to why this is occurring?
> Thanks!
> Andrew
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
-- PhD Student Neuronal Oscillations Group Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Trigon, room 0.83 Kapittelweg 29 Radboud University Nijmegen NL-6525 EN Nijmegen The Netherlands E-Mail: d.lozanosoldevilla at fcdonders.ru.nl Tel: +31-(0)24-36-66274 Web: http://www.neuosc.com/ 
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From 13681530640 at 139.com  Tue Jun  4 04:16:18 2013
From: 13681530640 at 139.com (WangJing)
Date: Tue, 4 Jun 2013 10:16:18 +0800 (CST)
Subject: [FieldTrip] Question about Head Model
References: <mailman.159.1370275680.1298.fieldtrip@science.ru.nl>
Message-ID: <2af951ad49e020a-0000c.Richmail.00026806626265132618@139.com>


HI everyone,


 


    When I build head model,I encount some questions.


    1.for two Functions ft_volumereslice and ft_volumerealign,which should be run firstly?


    2. when surfaces are created at the boarders of the different tissue-types by the ft_prepare_mesh function. how to determine the parameter cfg.numvertices?


    3.when I build the head model,using the following codes:


     cfg        = [];
     cfg.method ='dipoli';
     cfg.cond =[0.3300 0.004125 0.3300];
     vol        = ft_prepare_headmodel(cfg, bnd);


     


the error message is:


 


??? Error using ==> surface_nesting at 26
the compartment nesting cannot be determined


Error in ==> ft_headmodel_dipoli at 84
order = surface_nesting(vol.bnd, 'outsidefirst');


Error in ==> ft_prepare_headmodel at 226
      vol = ft_headmodel_dipoli(geometry,'conductivity',cfg.conductivity,'isolatedsource',cfg.isolatedsource);


Error in ==> Myheadmodel at 5
vol        = ft_prepare_headmodel(cfg, bnd);


 


   I don't know where is wrong.who can help me? Thank you!


 


Best Regards,


Jing Wang


 


 






 
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From sauer.mpih at googlemail.com  Tue Jun  4 11:42:13 2013
From: sauer.mpih at googlemail.com (Andreas Sauer)
Date: Tue, 4 Jun 2013 11:42:13 +0200
Subject: [FieldTrip] NaNs as output of ft_sourceanalysis (DICS)
Message-ID: <CAHLSopU-XWo6-t=MW78POK-6CvN1hRoFcc74aRxEuXZXhiSjUQ@mail.gmail.com>

Dear all,

I would like to analyze sources with the beamforming approach using the
DICS method. I followed the steps in the tutorial and everything works
well. However, the output of ft_sourceanalysis contains only NaNs.

I checked the TF data that I calculated in the step before but that looks
fine, so I assume the error happens somewhere during ft_sourceanalysis.

That's how I calculate the TFRs:

        cfg = [];
        cfg.toilim = [-0.5 -0.3]; % baseline activity
        eval(['dataPre =
ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
        cfg.toilim = [0.1 1.0]; % task-related activity
        eval(['dataPost =
ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);

        % Combine the two datasets...
        data = appenddata(cfg, dataPre, dataPost);
        trialdesign = [ones(1,length(dataPost.trial))
ones(1,length(dataPre.trial))*2];

        % ... and compute the CSD matrices...
        cfg = [];
        cfg.output     = 'powandcsd';
        cfg.channel    = Channel.meg;
        cfg.method     = 'mtmfft';
        cfg.taper      = 'dpss';
        cfg.foilim     = [75 75];
        cfg.tapsmofrq  = 15; % amount of spectral smoothing = +/- 15 Hz
        cfg.channelcmb = {Channel.meg Channel.meg};

        % ... for the baseline and task part separately...
        eval(['freqPre.Cond_',num2str(cond(j)), ' =
ft_freqanalysis(cfg,dataPre);']);
        eval(['freqPost.Cond_',num2str(cond(j)), ' =
ft_freqanalysis(cfg,dataPost);']);

        % ... and for the whole trial
        eval(['freqAll.Cond_',num2str(cond(j)), ' =
ft_freqanalysis(cfg,data);']);
        eval(['freqAll.Cond_',num2str(cond(j)), '.trialdesign =
trialdesign;']); % pre and post info

And that's how I calculate the sources:

        cfg               = [];
        cfg.frequency     = 75;
        cfg.method        = 'dics';
        cfg.grid          = grid; % Here it gives .pos, .inside, .outside
to the structure
        cfg.vol           = vol;
        cfg.dim           = template_grid.dim; % Here I give the dimension
of the template grid
        cfg.grad          = Cond_101.hdr.grad;
        cfg.lambda        = '5%';
        cfg.reducerank    = 'no';
        cfg.projectnoise  = 'yes';
        cfg.realfilter    = 'yes';
        cfg.keepfilter    = 'yes'; % the output saves the computed inverse
filter

        eval(['SourceAll = ft_sourceanalysis(cfg,
freqAll.Cond_',num2str(cond(k)),');'])

        % use the common filter here
        cfg.grid.filter = SourceAll.avg.filter;
        eval(['sourcePre_con = ft_sourceanalysis(cfg,
freqPre.Cond_',num2str(cond(k)),');'])
        eval(['sourcePost_con = ft_sourceanalysis(cfg,
freqPost.Cond_',num2str(cond(k)),');'])



I would really appreciate any help with that! Thanks a lot!

Best,

Andreas

-- 
Andreas Sauer
Max Planck Institute for Brain Research
Deutschordenstr. 46
60528 Frankfurt am Main
Germany

T: +49 69 96769 278
F: +49 69 96769 327
Email: andreas.sauer at brain.mpg.de
www.brain.mpg.de
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From sauer.mpih at googlemail.com  Tue Jun  4 11:52:24 2013
From: sauer.mpih at googlemail.com (Andreas Sauer)
Date: Tue, 4 Jun 2013 11:52:24 +0200
Subject: [FieldTrip] NaNs as outpout of ft_sourceanalysis (DICS)
Message-ID: <CAHLSopUvv47POq0cHQD8iZfYnOvp+oz6VyCLcW4CsNhjJAvBVw@mail.gmail.com>

Dear all,

I would like to analyze sources with the beamforming approach using the
DICS method. I followed the steps in the tutorial and everything works
well. However, the output of ft_sourceanalysis contains only NaNs.

I checked the TF data that I calculated in the step before but that looks
fine, so I assume the error happens somewhere during ft_sourceanalysis.

That's how I calculate the TFRs:

        cfg = [];
        cfg.toilim = [-0.5 -0.3]; % baseline activity
        eval(['dataPre =
ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
        cfg.toilim = [0.1 1.0]; % task-related activity
        eval(['dataPost =
ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);

        % Combine the two datasets...
        data = appenddata(cfg, dataPre, dataPost);
        trialdesign = [ones(1,length(dataPost.trial))
ones(1,length(dataPre.trial))*2];

        % ... and compute the CSD matrices...
        cfg = [];
        cfg.output     = 'powandcsd';
        cfg.channel    = Channel.meg;
        cfg.method     = 'mtmfft';
        cfg.taper      = 'dpss';
        cfg.foilim     = [75 75];
        cfg.tapsmofrq  = 15; % amount of spectral smoothing = +/- 15 Hz
        cfg.channelcmb = {Channel.meg Channel.meg};

        % ... for the baseline and task part separately...
        eval(['freqPre.Cond_',num2str(cond(j)), ' =
ft_freqanalysis(cfg,dataPre);']);
        eval(['freqPost.Cond_',num2str(cond(j)), ' =
ft_freqanalysis(cfg,dataPost);']);

        % ... and for the whole trial
        eval(['freqAll.Cond_',num2str(cond(j)), ' =
ft_freqanalysis(cfg,data);']);
        eval(['freqAll.Cond_',num2str(cond(j)), '.trialdesign =
trialdesign;']); % pre and post info

And that's how I calculate the sources:

        cfg               = [];
        cfg.frequency     = 75;
        cfg.method        = 'dics';
        cfg.grid          = grid; % Here it gives .pos, .inside, .outside
to the structure
        cfg.vol           = vol;
        cfg.dim           = template_grid.dim; % Here I give the dimension
of the template grid
        cfg.grad          = Cond_101.hdr.grad;
        cfg.lambda        = '5%';
        cfg.reducerank    = 'no';
        cfg.projectnoise  = 'yes';
        cfg.realfilter    = 'yes';
        cfg.keepfilter    = 'yes'; % the output saves the computed inverse
filter

        eval(['SourceAll = ft_sourceanalysis(cfg,
freqAll.Cond_',num2str(cond(k)),');'])

        % use the common filter here
        cfg.grid.filter = SourceAll.avg.filter;
        eval(['sourcePre_con = ft_sourceanalysis(cfg,
freqPre.Cond_',num2str(cond(k)),');'])
        eval(['sourcePost_con = ft_sourceanalysis(cfg,
freqPost.Cond_',num2str(cond(k)),');'])



I would really appreciate any help with that! Thanks a lot!

Best,

Andreas


-- 
Andreas Sauer
Max Planck Institute for Brain Research
Deutschordenstr. 46
60528 Frankfurt am Main
Germany

T: +49 69 96769 278
F: +49 69 96769 327
Email: andreas.sauer at brain.mpg.de <sauer.mpih at gmail.com>
www.brain.mpg.de
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From eelke.spaak at donders.ru.nl  Tue Jun  4 11:54:51 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Tue, 4 Jun 2013 11:54:51 +0200
Subject: [FieldTrip] NaNs as output of ft_sourceanalysis (DICS)
In-Reply-To: <CAHLSopU-XWo6-t=MW78POK-6CvN1hRoFcc74aRxEuXZXhiSjUQ@mail.gmail.com>
References: <CAHLSopU-XWo6-t=MW78POK-6CvN1hRoFcc74aRxEuXZXhiSjUQ@mail.gmail.com>
Message-ID: <CABPNLUoRezPPHDCNMJqvw3T3-dOqnC32VP_ihdmDqqpXQF0aNQ@mail.gmail.com>

Dear Andreas,

How many NaNs do you get exactly and in which field? If it is some
NaNs in source.avg.pow, then it is quite normal: the estimates for
dipole locations which were flagged as outside the brain are always
NaN, as they are not scanned. The following should hold:

sum(isnan(source.avg.pow)) == numel(source.outside)
&&
sum(~isnan(source.avg.pow)) == numel(source.inside)

Best,
Eelke

On 4 June 2013 11:42, Andreas Sauer <sauer.mpih at googlemail.com> wrote:
> Dear all,
>
> I would like to analyze sources with the beamforming approach using the DICS
> method. I followed the steps in the tutorial and everything works well.
> However, the output of ft_sourceanalysis contains only NaNs.
>
> I checked the TF data that I calculated in the step before but that looks
> fine, so I assume the error happens somewhere during ft_sourceanalysis.
>
> That's how I calculate the TFRs:
>
>         cfg = [];
>         cfg.toilim = [-0.5 -0.3]; % baseline activity
>         eval(['dataPre =
> ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
>         cfg.toilim = [0.1 1.0]; % task-related activity
>         eval(['dataPost =
> ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
>
>         % Combine the two datasets...
>         data = appenddata(cfg, dataPre, dataPost);
>         trialdesign = [ones(1,length(dataPost.trial))
> ones(1,length(dataPre.trial))*2];
>
>         % ... and compute the CSD matrices...
>         cfg = [];
>         cfg.output     = 'powandcsd';
>         cfg.channel    = Channel.meg;
>         cfg.method     = 'mtmfft';
>         cfg.taper      = 'dpss';
>         cfg.foilim     = [75 75];
>         cfg.tapsmofrq  = 15; % amount of spectral smoothing = +/- 15 Hz
>         cfg.channelcmb = {Channel.meg Channel.meg};
>
>         % ... for the baseline and task part separately...
>         eval(['freqPre.Cond_',num2str(cond(j)), ' =
> ft_freqanalysis(cfg,dataPre);']);
>         eval(['freqPost.Cond_',num2str(cond(j)), ' =
> ft_freqanalysis(cfg,dataPost);']);
>
>         % ... and for the whole trial
>         eval(['freqAll.Cond_',num2str(cond(j)), ' =
> ft_freqanalysis(cfg,data);']);
>         eval(['freqAll.Cond_',num2str(cond(j)), '.trialdesign =
> trialdesign;']); % pre and post info
>
> And that's how I calculate the sources:
>
>         cfg               = [];
>         cfg.frequency     = 75;
>         cfg.method        = 'dics';
>         cfg.grid          = grid; % Here it gives .pos, .inside, .outside to
> the structure
>         cfg.vol           = vol;
>         cfg.dim           = template_grid.dim; % Here I give the dimension
> of the template grid
>         cfg.grad          = Cond_101.hdr.grad;
>         cfg.lambda        = '5%';
>         cfg.reducerank    = 'no';
>         cfg.projectnoise  = 'yes';
>         cfg.realfilter    = 'yes';
>         cfg.keepfilter    = 'yes'; % the output saves the computed inverse
> filter
>
>         eval(['SourceAll = ft_sourceanalysis(cfg,
> freqAll.Cond_',num2str(cond(k)),');'])
>
>         % use the common filter here
>         cfg.grid.filter = SourceAll.avg.filter;
>         eval(['sourcePre_con = ft_sourceanalysis(cfg,
> freqPre.Cond_',num2str(cond(k)),');'])
>         eval(['sourcePost_con = ft_sourceanalysis(cfg,
> freqPost.Cond_',num2str(cond(k)),');'])
>
>
>
> I would really appreciate any help with that! Thanks a lot!
>
> Best,
>
> Andreas
>
> --
> Andreas Sauer
> Max Planck Institute for Brain Research
> Deutschordenstr. 46
> 60528 Frankfurt am Main
> Germany
>
> T: +49 69 96769 278
> F: +49 69 96769 327
> Email: andreas.sauer at brain.mpg.de
> www.brain.mpg.de
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From jm.horschig at donders.ru.nl  Tue Jun  4 12:17:37 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Tue, 04 Jun 2013 12:17:37 +0200
Subject: [FieldTrip] NaNs as output of ft_sourceanalysis (DICS)
In-Reply-To: <CABPNLUoRezPPHDCNMJqvw3T3-dOqnC32VP_ihdmDqqpXQF0aNQ@mail.gmail.com>
References: <CAHLSopU-XWo6-t=MW78POK-6CvN1hRoFcc74aRxEuXZXhiSjUQ@mail.gmail.com>
	<CABPNLUoRezPPHDCNMJqvw3T3-dOqnC32VP_ihdmDqqpXQF0aNQ@mail.gmail.com>
Message-ID: <51ADBEC1.5060204@donders.ru.nl>

Hi Andreas,

could it be related to the fact that you redefine your trials and when 
estimating the frequency content, there is no exact 75Hz bin, thus 
ft_sourceanalysis cannot beam the frequency you specify? Since you cut 
out the pre- and poststimulus periods with different lengths, the 
frequency resolution will be strongly different, thus an estimate of 
75Hz will effectively be somewhere around 75Hz, but not exactly 75Hz. 
You could try to set 
cfg.frequency=freqAll.Cond_(yourNumberedCondition).freq instead of 
cfg.frequency=75. Note that in this case, sourceAll might have non-nans, 
but sourcePre and sourcePost will probably still have nans due to the 
resolution issue
If that's not the case, then I agree also with Eelke that more 
information is needed to help you, e.g. in which of the three source 
structures are nans? How many nans are there (try 
all(isnan(source.avg.pow(:))))?

Best,
Jörn

On 6/4/2013 11:54 AM, Eelke Spaak wrote:
> Dear Andreas,
>
> How many NaNs do you get exactly and in which field? If it is some
> NaNs in source.avg.pow, then it is quite normal: the estimates for
> dipole locations which were flagged as outside the brain are always
> NaN, as they are not scanned. The following should hold:
>
> sum(isnan(source.avg.pow)) == numel(source.outside)
> &&
> sum(~isnan(source.avg.pow)) == numel(source.inside)
>
> Best,
> Eelke
>
> On 4 June 2013 11:42, Andreas Sauer <sauer.mpih at googlemail.com> wrote:
>> Dear all,
>>
>> I would like to analyze sources with the beamforming approach using the DICS
>> method. I followed the steps in the tutorial and everything works well.
>> However, the output of ft_sourceanalysis contains only NaNs.
>>
>> I checked the TF data that I calculated in the step before but that looks
>> fine, so I assume the error happens somewhere during ft_sourceanalysis.
>>
>> That's how I calculate the TFRs:
>>
>>          cfg = [];
>>          cfg.toilim = [-0.5 -0.3]; % baseline activity
>>          eval(['dataPre =
>> ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
>>          cfg.toilim = [0.1 1.0]; % task-related activity
>>          eval(['dataPost =
>> ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
>>
>>          % Combine the two datasets...
>>          data = appenddata(cfg, dataPre, dataPost);
>>          trialdesign = [ones(1,length(dataPost.trial))
>> ones(1,length(dataPre.trial))*2];
>>
>>          % ... and compute the CSD matrices...
>>          cfg = [];
>>          cfg.output     = 'powandcsd';
>>          cfg.channel    = Channel.meg;
>>          cfg.method     = 'mtmfft';
>>          cfg.taper      = 'dpss';
>>          cfg.foilim     = [75 75];
>>          cfg.tapsmofrq  = 15; % amount of spectral smoothing = +/- 15 Hz
>>          cfg.channelcmb = {Channel.meg Channel.meg};
>>
>>          % ... for the baseline and task part separately...
>>          eval(['freqPre.Cond_',num2str(cond(j)), ' =
>> ft_freqanalysis(cfg,dataPre);']);
>>          eval(['freqPost.Cond_',num2str(cond(j)), ' =
>> ft_freqanalysis(cfg,dataPost);']);
>>
>>          % ... and for the whole trial
>>          eval(['freqAll.Cond_',num2str(cond(j)), ' =
>> ft_freqanalysis(cfg,data);']);
>>          eval(['freqAll.Cond_',num2str(cond(j)), '.trialdesign =
>> trialdesign;']); % pre and post info
>>
>> And that's how I calculate the sources:
>>
>>          cfg               = [];
>>          cfg.frequency     = 75;
>>          cfg.method        = 'dics';
>>          cfg.grid          = grid; % Here it gives .pos, .inside, .outside to
>> the structure
>>          cfg.vol           = vol;
>>          cfg.dim           = template_grid.dim; % Here I give the dimension
>> of the template grid
>>          cfg.grad          = Cond_101.hdr.grad;
>>          cfg.lambda        = '5%';
>>          cfg.reducerank    = 'no';
>>          cfg.projectnoise  = 'yes';
>>          cfg.realfilter    = 'yes';
>>          cfg.keepfilter    = 'yes'; % the output saves the computed inverse
>> filter
>>
>>          eval(['SourceAll = ft_sourceanalysis(cfg,
>> freqAll.Cond_',num2str(cond(k)),');'])
>>
>>          % use the common filter here
>>          cfg.grid.filter = SourceAll.avg.filter;
>>          eval(['sourcePre_con = ft_sourceanalysis(cfg,
>> freqPre.Cond_',num2str(cond(k)),');'])
>>          eval(['sourcePost_con = ft_sourceanalysis(cfg,
>> freqPost.Cond_',num2str(cond(k)),');'])
>>
>>
>>
>> I would really appreciate any help with that! Thanks a lot!
>>
>> Best,
>>
>> Andreas
>>
>> --
>> Andreas Sauer
>> Max Planck Institute for Brain Research
>> Deutschordenstr. 46
>> 60528 Frankfurt am Main
>> Germany
>>
>> T: +49 69 96769 278
>> F: +49 69 96769 327
>> Email: andreas.sauer at brain.mpg.de
>> www.brain.mpg.de
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands



From sauer.mpih at googlemail.com  Tue Jun  4 12:31:32 2013
From: sauer.mpih at googlemail.com (Andreas Sauer)
Date: Tue, 4 Jun 2013 12:31:32 +0200
Subject: [FieldTrip] NaNs as output of ft_sourceanalysis (DICS)
In-Reply-To: <CABPNLUoRezPPHDCNMJqvw3T3-dOqnC32VP_ihdmDqqpXQF0aNQ@mail.gmail.com>
References: <CAHLSopU-XWo6-t=MW78POK-6CvN1hRoFcc74aRxEuXZXhiSjUQ@mail.gmail.com>
	<CABPNLUoRezPPHDCNMJqvw3T3-dOqnC32VP_ihdmDqqpXQF0aNQ@mail.gmail.com>
Message-ID: <CAHLSopUkz1XxH+2VoLH9FYOE_97ouFDCxV8Qvy8fO2oP-vU6iw@mail.gmail.com>

Dear Eelke and Jörn,

thanks for the super quick responses! And sorry for the double post...

I tried Eelke's suggestion and that holds. So, I have only NaNs in the
fields for the dipole locations outside the brain.
However, if I continue and calculate the contrast between pre and post and
plot it I don't see any activation.

I will try your suggestion, Jörn, as well and see whether it has to do with
the re-definition.

Thanks again for your suggestions!

Best,

Andreas


2013/6/4 Eelke Spaak <eelke.spaak at donders.ru.nl>

> Dear Andreas,
>
> How many NaNs do you get exactly and in which field? If it is some
> NaNs in source.avg.pow, then it is quite normal: the estimates for
> dipole locations which were flagged as outside the brain are always
> NaN, as they are not scanned. The following should hold:
>
> sum(isnan(source.avg.pow)) == numel(source.outside)
> &&
> sum(~isnan(source.avg.pow)) == numel(source.inside)
>
> Best,
> Eelke
>
> On 4 June 2013 11:42, Andreas Sauer <sauer.mpih at googlemail.com> wrote:
> > Dear all,
> >
> > I would like to analyze sources with the beamforming approach using the
> DICS
> > method. I followed the steps in the tutorial and everything works well.
> > However, the output of ft_sourceanalysis contains only NaNs.
> >
> > I checked the TF data that I calculated in the step before but that looks
> > fine, so I assume the error happens somewhere during ft_sourceanalysis.
> >
> > That's how I calculate the TFRs:
> >
> >         cfg = [];
> >         cfg.toilim = [-0.5 -0.3]; % baseline activity
> >         eval(['dataPre =
> > ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
> >         cfg.toilim = [0.1 1.0]; % task-related activity
> >         eval(['dataPost =
> > ft_redefinetrial(cfg,Cond_',num2str(cond(j)),');']);
> >
> >         % Combine the two datasets...
> >         data = appenddata(cfg, dataPre, dataPost);
> >         trialdesign = [ones(1,length(dataPost.trial))
> > ones(1,length(dataPre.trial))*2];
> >
> >         % ... and compute the CSD matrices...
> >         cfg = [];
> >         cfg.output     = 'powandcsd';
> >         cfg.channel    = Channel.meg;
> >         cfg.method     = 'mtmfft';
> >         cfg.taper      = 'dpss';
> >         cfg.foilim     = [75 75];
> >         cfg.tapsmofrq  = 15; % amount of spectral smoothing = +/- 15 Hz
> >         cfg.channelcmb = {Channel.meg Channel.meg};
> >
> >         % ... for the baseline and task part separately...
> >         eval(['freqPre.Cond_',num2str(cond(j)), ' =
> > ft_freqanalysis(cfg,dataPre);']);
> >         eval(['freqPost.Cond_',num2str(cond(j)), ' =
> > ft_freqanalysis(cfg,dataPost);']);
> >
> >         % ... and for the whole trial
> >         eval(['freqAll.Cond_',num2str(cond(j)), ' =
> > ft_freqanalysis(cfg,data);']);
> >         eval(['freqAll.Cond_',num2str(cond(j)), '.trialdesign =
> > trialdesign;']); % pre and post info
> >
> > And that's how I calculate the sources:
> >
> >         cfg               = [];
> >         cfg.frequency     = 75;
> >         cfg.method        = 'dics';
> >         cfg.grid          = grid; % Here it gives .pos, .inside,
> .outside to
> > the structure
> >         cfg.vol           = vol;
> >         cfg.dim           = template_grid.dim; % Here I give the
> dimension
> > of the template grid
> >         cfg.grad          = Cond_101.hdr.grad;
> >         cfg.lambda        = '5%';
> >         cfg.reducerank    = 'no';
> >         cfg.projectnoise  = 'yes';
> >         cfg.realfilter    = 'yes';
> >         cfg.keepfilter    = 'yes'; % the output saves the computed
> inverse
> > filter
> >
> >         eval(['SourceAll = ft_sourceanalysis(cfg,
> > freqAll.Cond_',num2str(cond(k)),');'])
> >
> >         % use the common filter here
> >         cfg.grid.filter = SourceAll.avg.filter;
> >         eval(['sourcePre_con = ft_sourceanalysis(cfg,
> > freqPre.Cond_',num2str(cond(k)),');'])
> >         eval(['sourcePost_con = ft_sourceanalysis(cfg,
> > freqPost.Cond_',num2str(cond(k)),');'])
> >
> >
> >
> > I would really appreciate any help with that! Thanks a lot!
> >
> > Best,
> >
> > Andreas
> >
> > --
> > Andreas Sauer
> > Max Planck Institute for Brain Research
> > Deutschordenstr. 46
> > 60528 Frankfurt am Main
> > Germany
> >
> > T: +49 69 96769 278
> > F: +49 69 96769 327
> > Email: andreas.sauer at brain.mpg.de
> > www.brain.mpg.de
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
Dipl.-Psych. Andreas Sauer
Max Planck Institute for Brain Research
Deutschordenstraße 46
60528 Frankfurt am Main
Germany

T: +49 69 96769 278
F: +49 69 96769 327
Email: sauer.mpih at gmail.com
www.brain.mpg.de
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From r.cox at uva.nl  Tue Jun  4 14:31:06 2013
From: r.cox at uva.nl (Roy Cox)
Date: Tue, 4 Jun 2013 14:31:06 +0200
Subject: [FieldTrip] ft_freqstatistics & ft_clusterplot
Message-ID: <CABafTZd5GXvBG=Xa=252EGwEsQysX1zaCnn+iuRH575F6byo7Q@mail.gmail.com>

Dear all,

I recently joined your trip and I want to make use of fieldtrip's cluster
correction capabilities. But I can't seem to get it to work. Perhaps some
of you can clarify some things I can't figure out easily from the tutorials
or functions themselves.

A potentially important thing to know is that I performed all
single-subject tf analyes using custom scripts, and now I want to have
fieldtrip perform the overall statistics (8 subjects, 2 within-subj
conditions).

ft_freqstatistics works. However, I wonder: does it matter for the
statistics what latency and frequency range you choose and/or whether you
average across time/freq bins? I tried a number of variants, but the
command window output "found [] positive/negative clusters in observed
data" is always identical. Which confuses me.

is it possible to call ft_freqstatistics and neither average over time nor
frequency bins? or am I supposed to average across at least one to end up
with less-dimensional data for ft_clusterplot?

regardless of how I call ft_freqstatistics, ft_clusterplot crashes like
this:

 Assignment has more non-singleton rhs dimensions than non-singleton
subscripts

Error in ==> ft_clusterplot at 179
    sigposCLM(:,:,iPos) = (posCLM == sigpos(iPos));

here, my posCLM is a 126(chan)x35(freqs)x301(time) array, which indeed does
not fit the left-hand side.

If anyone has any ideas/suggestions I'd be happy to hear them.

Roy

-- 
Roy Cox, M.Sc. | Brain & Cognition Group | Department of Psychology |
University of Amsterdam | Weesperplein 4 | 1018 XA Amsterdam | the
Netherlands | room 3.21 | phone: +31 20 525 6847 | email: r.cox at uva.nl
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From andmib at gmail.com  Tue Jun  4 17:01:43 2013
From: andmib at gmail.com (Andrew Brooks)
Date: Tue, 4 Jun 2013 11:01:43 -0400
Subject: [FieldTrip] Private function problems
In-Reply-To: <481032685.1338448.1370292821035.JavaMail.root@sculptor.zimbra.ru.nl>
References: <CALJPz69S8R+n+vWMYsmqC_Rqo63FbfECL+UStC0HcjQA3m8w2w@mail.gmail.com>
	<481032685.1338448.1370292821035.JavaMail.root@sculptor.zimbra.ru.nl>
Message-ID: <CALJPz69LZ_35=Z6YR5E6yRymDcZ3bBjaOpXOMyz3+CTWDjDNcw@mail.gmail.com>

Hello Diego,

I am using the example pipeline script from an earlier version of FieldTrip
(ft_omri_pipeline_nuisance). The exact code that is throwing the
error: curSixDof = hom2six(M).

I did run the three lines of code to reset the default paths, add
fieldtrip, and then ran ft_defaults. The version of FieldTrip I am using is
20130602.

Thanks,
Andrew






On Mon, Jun 3, 2013 at 4:53 PM, Lozano Soldevilla, D. (Diego) <
d.lozanosoldevilla at fcdonders.ru.nl> wrote:

> Hi Andrew,
>
> Did you type the following?
>
> >> restoredefaultpath
> >> addpath /fieldtripxxxx
> >> ft_defaults
>
> What's the ft_* function you invoke to get the error 'undefined function
> 'hom2six'? And what's the fieldtrip version you're using?
>
> best,
>
> Diego
>
> ------------------------------
>
> *From: *"Andrew Brooks" <andmib at gmail.com>
> *To: *"FieldTrip discussion list" <fieldtrip at science.ru.nl>
> *Sent: *Monday, 3 June, 2013 10:15:49 PM
> *Subject: *[FieldTrip] Private function problems
>
>
> Hello all,
>
> I followed the instructions on properly adding FieldTrip to the Matlab
> path file. However, I continue to run into errors involving private
> functions. In this case, I get the error 'undefined function 'hom2six' for
> input arguments of type 'double''.
>
> Does anybody have a suggestion as to why this is occurring?
>
> Thanks!
> Andrew
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
>
> --
> PhD Student
> Neuronal Oscillations Group
> Donders Institute for Brain, Cognition and Behaviour
> Centre for Cognitive Neuroimaging
> Trigon, room 0.83
> Kapittelweg 29
> Radboud University Nijmegen
> NL-6525 EN Nijmegen
> The Netherlands
> E-Mail: d.lozanosoldevilla at fcdonders.ru.nl
> Tel:     +31-(0)24-36-66274
> Web:   http://www.neuosc.com/
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From frank.ye.mei at gmail.com  Tue Jun  4 22:47:08 2013
From: frank.ye.mei at gmail.com (Frank Mei)
Date: Tue, 4 Jun 2013 16:47:08 -0400
Subject: [FieldTrip] How to set a small window when doing source
	localization?
Message-ID: <CAF0J_Mu4csTxGVM=3UQajwDQFbM3igEyjLUUMwvW9GBVcZpW7w@mail.gmail.com>

Hello all,

I want to be more precise in time, when doing source localization. So I
tried to set a small cfg.toilim, before the 'ft_redefinetrial'.   But if it
is set smaller than 0.3(corresponding to 300ms), an error will pop up.

How to solve that problem?

thanks ahead,
Ye Mei
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From d.lozanosoldevilla at fcdonders.ru.nl  Wed Jun  5 15:39:14 2013
From: d.lozanosoldevilla at fcdonders.ru.nl (Lozano Soldevilla, D. (Diego))
Date: Wed, 5 Jun 2013 15:39:14 +0200 (CEST)
Subject: [FieldTrip] Private function problems
In-Reply-To: <CALJPz69LZ_35=Z6YR5E6yRymDcZ3bBjaOpXOMyz3+CTWDjDNcw@mail.gmail.com>
Message-ID: <2127428772.1387542.1370439554352.JavaMail.root@sculptor.zimbra.ru.nl>

Hi Andrew, Could you please check inside your matlab path there's the realtime/mri directory where ft_omri_pipeline_nuisance.m function is located? Mine looks like this: '/home/electromag/dieloz/matlab/ fieldtrip-dev/realtime/online_mri/ ' If it's there, you shouldn't have the private folder problem. Otherwise, add from the command window and tell me. best, Diego ----- Original Message -----
> From: "Andrew Brooks" <andmib at gmail.com>
> To: "Diego Lozano" <diego.lozanosoldevilla at fcdonders.ru.nl>,
> "FieldTrip discussion list" <fieldtrip at science.ru.nl>
> Sent: Tuesday, 4 June, 2013 5:01:43 PM
> Subject: Re: [FieldTrip] Private function problems
> Hello Diego,
> I am using the example pipeline script from an earlier version of
> FieldTrip (ft_omri_pipeline_nuisance). The exact code that is throwing
> the error: curSixDof = hom2six(M).
> I did run the three lines of code to reset the default paths, add
> fieldtrip, and then ran ft_defaults. The version of FieldTrip I am
> using is 20130602.
> Thanks,
> Andrew
> On Mon, Jun 3, 2013 at 4:53 PM, Lozano Soldevilla, D. (Diego) <
> d.lozanosoldevilla at fcdonders.ru.nl > wrote:
> > Hi Andrew,
> > Did you type the following?
> > >> restoredefaultpath
> > >> addpath /fieldtripxxxx
> > >> ft_defaults
> > What's the ft_* function you invoke to get the error 'undefined
> > function 'hom2six'? And what's the fieldtrip version you're using?
> > best,
> > Diego
> > > From: "Andrew Brooks" < andmib at gmail.com >
> > > To: "FieldTrip discussion list" < fieldtrip at science.ru.nl >
> > > Sent: Monday, 3 June, 2013 10:15:49 PM
> > > Subject: [FieldTrip] Private function problems
> > > Hello all,
> > > I followed the instructions on properly adding FieldTrip to the
> > > Matlab
> > > path file. However, I continue to run into errors involving
> > > private
> > > functions. In this case, I get the error 'undefined function
> > > 'hom2six'
> > > for input arguments of type 'double''.
> > > Does anybody have a suggestion as to why this is occurring?
> > > Thanks!
> > > Andrew
> > > _______________________________________________
> > > fieldtrip mailing list
> > > fieldtrip at donders.ru.nl
> > > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > --
> > PhD Student
> > Neuronal Oscillations Group
> > Donders Institute for Brain, Cognition and Behaviour
> > Centre for Cognitive Neuroimaging
> > Trigon, room 0.83
> > Kapittelweg 29
> > Radboud University Nijmegen
> > NL-6525 EN Nijmegen
> > The Netherlands
> > E-Mail: d.lozanosoldevilla at fcdonders.ru.nl
> > Tel: +31-(0)24-36-66274
> > Web: http://www.neuosc.com/
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
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From elizabeth.bock at mcgill.ca  Wed Jun  5 17:53:36 2013
From: elizabeth.bock at mcgill.ca (Elizabeth Anne Bock, Ms)
Date: Wed, 5 Jun 2013 15:53:36 +0000
Subject: [FieldTrip] Polhemus Patriot
In-Reply-To: <67D8C434-4D28-40C3-94A6-A95C86BD6B78@gmail.com>
References: <67D8C434-4D28-40C3-94A6-A95C86BD6B78@gmail.com>
Message-ID: <86D86365C4E767468A79EB52DFBFB46F051E242F@exmbx2010-8.campus.MCGILL.CA>

Hi Julian,
We have experienced this problem as well.  We solved it using the following guidelines:

No metal near the polhemus or any of the receivers/transmitters - you will need to move the setup around the room to find the perfect spot.
Use a wooden or plastic chair
Use plastic or cloth glasses/holder to attach the receiver to the subject

My system is sensitive to the proximity of the transmitter and the receiver.  I use two receivers, #1 is the stylus and #2 is secured to plastic glasses that the subject wears.  The transmitter is taped to the back of the chair.  If #2 and the transmitter are too close to each other (i.e. a short person or child), then the measurement are inaccurate.  You would have to experiment with different distances that give good results.

Hope this helps!
Beth


------------------------------------------------------------------------------------------

Elizabeth Bock / MEG System Engineer

McConnell Brain Imaging Centre / Montreal Neurological Institute

McGill University / 3801 University St. / Montreal, QC H3A 2B4


Office: 514.398.3706

MEG Lab: 514.398.6056

Mobile: 514.718.6342

________________________________
From: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl] on behalf of Julian Keil [julian.keil at gmail.com]
Sent: Monday, June 03, 2013 11:14 AM
To: FieldTrip discussion list
Subject: [FieldTrip] Polhemus Patriot

Dear FieldTrip-Users,

I have a not really FieldTrip-related question, but maybe one of you can help me anyways.
In our lab, we have a Polhemus Patriot 3D tracking system to acquire electrode positions.
Unfortunately, the recordings are severely distorted in the Z-axis (up-down).
After contacting the Polhemus Support, I got the information, that this is due to metal in the surroundings of the source which distorts the magnetic field.
I tried to get as far away from any metal as possible in our lab (~1.5 m to the walls and floor) but to no avail.

Now to my question: Has anyone any experience dealing with this? I'm quite puzzled by this as I know plenty of labs use Polhemus trackers, and I'm not sure if our lab is especially metal prone or if I'm missing something.

Thanks a lot for any help.

Julian

********************
Dr. Julian Keil

AG Multisensorische Integration
Psychiatrische Universitätsklinik
der Charité im St. Hedwig-Krankenhaus
Große Hamburger Straße 5-11, Raum E 307
10115 Berlin

Telefon: +49-30-2311-1879
Fax:        +49-30-2311-2209
http://psy-ccm.charite.de/forschung/bildgebung/ag_multisensorische_integration

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From julian.keil at gmail.com  Wed Jun  5 18:02:55 2013
From: julian.keil at gmail.com (Julian Keil)
Date: Wed, 5 Jun 2013 18:02:55 +0200
Subject: [FieldTrip] Polhemus Patriot
In-Reply-To: <86D86365C4E767468A79EB52DFBFB46F051E242F@exmbx2010-8.campus.MCGILL.CA>
References: <67D8C434-4D28-40C3-94A6-A95C86BD6B78@gmail.com>
	<86D86365C4E767468A79EB52DFBFB46F051E242F@exmbx2010-8.campus.MCGILL.CA>
Message-ID: <CC0BDDFC-CF83-47BE-8B49-C18B3D1EC701@gmail.com>

Dear all,

thank you very much for your input.
I'll have to experiment a bit more with the distance to the walls (which probably contain metal) and the chair.
Thank you also for the idea with the second sensor, I hadn't tried this before.

Best,

Julian

Am 05.06.2013 um 17:53 schrieb Elizabeth Anne Bock, Ms:

> Hi Julian,
> We have experienced this problem as well.  We solved it using the following guidelines:
> 
> No metal near the polhemus or any of the receivers/transmitters - you will need to move the setup around the room to find the perfect spot.
> Use a wooden or plastic chair
> Use plastic or cloth glasses/holder to attach the receiver to the subject
> 
> My system is sensitive to the proximity of the transmitter and the receiver.  I use two receivers, #1 is the stylus and #2 is secured to plastic glasses that the subject wears.  The transmitter is taped to the back of the chair.  If #2 and the transmitter are too close to each other (i.e. a short person or child), then the measurement are inaccurate.  You would have to experiment with different distances that give good results.
> 
> Hope this helps!
> Beth
> 
> ------------------------------------------------------------------------------------------
> Elizabeth Bock / MEG System Engineer
> McConnell Brain Imaging Centre / Montreal Neurological Institute
> McGill University / 3801 University St. / Montreal, QC H3A 2B4
> 
> Office: 514.398.3706 
> MEG Lab: 514.398.6056
> Mobile: 514.718.6342
> From: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl] on behalf of Julian Keil [julian.keil at gmail.com]
> Sent: Monday, June 03, 2013 11:14 AM
> To: FieldTrip discussion list
> Subject: [FieldTrip] Polhemus Patriot
> 
> Dear FieldTrip-Users,
> 
> I have a not really FieldTrip-related question, but maybe one of you can help me anyways.
> In our lab, we have a Polhemus Patriot 3D tracking system to acquire electrode positions.
> Unfortunately, the recordings are severely distorted in the Z-axis (up-down).
> After contacting the Polhemus Support, I got the information, that this is due to metal in the surroundings of the source which distorts the magnetic field.
> I tried to get as far away from any metal as possible in our lab (~1.5 m to the walls and floor) but to no avail.
> 
> Now to my question: Has anyone any experience dealing with this? I'm quite puzzled by this as I know plenty of labs use Polhemus trackers, and I'm not sure if our lab is especially metal prone or if I'm missing something.
> 
> Thanks a lot for any help.
> 
> Julian
> 
> ********************
> Dr. Julian Keil
> 
> AG Multisensorische Integration
> Psychiatrische Universitätsklinik
> der Charité im St. Hedwig-Krankenhaus
> Große Hamburger Straße 5-11, Raum E 307
> 10115 Berlin
> 
> Telefon: +49-30-2311-1879
> Fax:        +49-30-2311-2209 
> http://psy-ccm.charite.de/forschung/bildgebung/ag_multisensorische_integration
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From mje.mads at gmail.com  Thu Jun  6 09:16:01 2013
From: mje.mads at gmail.com (Mads Jensen)
Date: Thu, 06 Jun 2013 09:16:01 +0200
Subject: [FieldTrip] Extracting the time of a cluster
Message-ID: <51B03731.2080303@gmail.com>

Dear all,

I have made a statistics analysis on ERP data using 
ft_timelockstatistics and got a significant cluster I would like to know 
the time course of this cluster(i.e. when it starts and ends being 
significant) , is that possible?

I take to the cirange that is computed in the output for the cluster 
from ft_timelockstatistics be the upper and lower limit of the 
confidence interval, so the cluster.prop +/- the cirange gives the 
95%confidence intervals. Is that correct?

best wishes,
Mads


From jm.horschig at donders.ru.nl  Thu Jun  6 10:17:50 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Thu, 06 Jun 2013 10:17:50 +0200
Subject: [FieldTrip] Extracting the time of a cluster
In-Reply-To: <51B03731.2080303@gmail.com>
References: <51B03731.2080303@gmail.com>
Message-ID: <51B045AE.3010305@donders.ru.nl>

Hi Mads,

there is a stats.posclusterlabelmat and stats.negclusterlabelmat field, 
which contain the indices of all your clusters. You can use these 
indices and to index the period where your test shows some significant 
effect(e.g. for timelock.avg or timelock.time). See here for an example, 
which does not quite do what you want, but gets close
http://fieldtrip.fcdonders.nl/tutorial/cluster_permutation_timelock#plotting_the_results

And, yes, cirange defines the range of the confidence interval for that 
particular cluster, so pvalue - cirange gives the lower bound and pvalue 
+ cirange the upper bound. If your upper bound extends beyond the 
critical alpha-value, I would advise to use more randomizations.

Best,
Jörn

On 6/6/2013 9:16 AM, Mads Jensen wrote:
> Dear all,
>
> I have made a statistics analysis on ERP data using 
> ft_timelockstatistics and got a significant cluster I would like to 
> know the time course of this cluster(i.e. when it starts and ends 
> being significant) , is that possible?
>
> I take to the cirange that is computed in the output for the cluster 
> from ft_timelockstatistics be the upper and lower limit of the 
> confidence interval, so the cluster.prop +/- the cirange gives the 
> 95%confidence intervals. Is that correct?
>
> best wishes,
> Mads
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands



From mje.mads at gmail.com  Thu Jun  6 12:48:02 2013
From: mje.mads at gmail.com (Mads Jensen)
Date: Thu, 06 Jun 2013 12:48:02 +0200
Subject: [FieldTrip] Extracting the time of a cluster
In-Reply-To: <51B045AE.3010305@donders.ru.nl>
References: <51B03731.2080303@gmail.com> <51B045AE.3010305@donders.ru.nl>
Message-ID: <51B068E2.3010500@gmail.com>

Hi Jörn,

thanks for the swift and very useful reply.

best,
mads

On 06/06/13 10:17, "Jörn M. Horschig" wrote:
> Hi Mads,
>
> there is a stats.posclusterlabelmat and stats.negclusterlabelmat field,
> which contain the indices of all your clusters. You can use these
> indices and to index the period where your test shows some significant
> effect(e.g. for timelock.avg or timelock.time). See here for an example,
> which does not quite do what you want, but gets close
> http://fieldtrip.fcdonders.nl/tutorial/cluster_permutation_timelock#plotting_the_results
>
>
> And, yes, cirange defines the range of the confidence interval for that
> particular cluster, so pvalue - cirange gives the lower bound and pvalue
> + cirange the upper bound. If your upper bound extends beyond the
> critical alpha-value, I would advise to use more randomizations.
>
> Best,
> Jörn
>
> On 6/6/2013 9:16 AM, Mads Jensen wrote:
>> Dear all,
>>
>> I have made a statistics analysis on ERP data using
>> ft_timelockstatistics and got a significant cluster I would like to
>> know the time course of this cluster(i.e. when it starts and ends
>> being significant) , is that possible?
>>
>> I take to the cirange that is computed in the output for the cluster
>> from ft_timelockstatistics be the upper and lower limit of the
>> confidence interval, so the cluster.prop +/- the cirange gives the
>> 95%confidence intervals. Is that correct?
>>
>> best wishes,
>> Mads
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>


From antony.passaro at gmail.com  Thu Jun  6 15:59:22 2013
From: antony.passaro at gmail.com (Antony Passaro)
Date: Thu, 6 Jun 2013 09:59:22 -0400
Subject: [FieldTrip] Statistics for correlation across subjects using
	cluster analysis
Message-ID: <CAB8wAYRKGor5kv1KYB4z-z92AGyyFFgqTkpUgkZTYQVHefeVyw@mail.gmail.com>

Hi,

I came across an email in the mailing list archives from this time last
year when a user ( Ingrid ) was asking about using a statistical model with
a cluster analysis to correct for multiple comparisons based on performing
a correlation across trials (and/or subjects). Jan-mathijs replied saying
he had a copy of statfun_corr and statfun_glm but I don't see a copy of
either of those functions in the latest fieldtrip release. Would anyone be
so kind as to point my in the right directions to tackle this problem?

Thank you,
-Tony
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From andmib at gmail.com  Thu Jun  6 17:06:25 2013
From: andmib at gmail.com (Andrew Brooks)
Date: Thu, 6 Jun 2013 11:06:25 -0400
Subject: [FieldTrip] Private function problems
In-Reply-To: <2127428772.1387542.1370439554352.JavaMail.root@sculptor.zimbra.ru.nl>
References: <CALJPz69LZ_35=Z6YR5E6yRymDcZ3bBjaOpXOMyz3+CTWDjDNcw@mail.gmail.com>
	<2127428772.1387542.1370439554352.JavaMail.root@sculptor.zimbra.ru.nl>
Message-ID: <CALJPz68nhn6pRVcDaKSazaic76pw+OsZaowVtWsBmhkWora_kg@mail.gmail.com>

Diego,

Thank you, that was indeed the problem. I had moved the ft_omri_pipeline
script out of the /realtime/online_mri directory, which caused the problems.

Thanks,
Andrew


On Wed, Jun 5, 2013 at 9:39 AM, Lozano Soldevilla, D. (Diego) <
d.lozanosoldevilla at fcdonders.ru.nl> wrote:

> Hi Andrew,
>
> Could you please check inside your matlab path there's the realtime/mri
> directory where ft_omri_pipeline_nuisance.m function is located?
>
> Mine looks like this:
>
> '/home/electromag/dieloz/matlab/*fieldtrip-dev/realtime/online_mri/*'
>
> If it's there, you shouldn't have the private folder problem. Otherwise,
> add from the command window and tell me.
>
> best,
>
> Diego
>
> ------------------------------
>
> *From: *"Andrew Brooks" <andmib at gmail.com>
> *To: *"Diego Lozano" <diego.lozanosoldevilla at fcdonders.ru.nl>, "FieldTrip
> discussion list" <fieldtrip at science.ru.nl>
> *Sent: *Tuesday, 4 June, 2013 5:01:43 PM
> *Subject: *Re: [FieldTrip] Private function problems
>
>
> Hello Diego,
>
> I am using the example pipeline script from an earlier version of
> FieldTrip (ft_omri_pipeline_nuisance). The exact code that is throwing the
> error: curSixDof = hom2six(M).
>
> I did run the three lines of code to reset the default paths, add
> fieldtrip, and then ran ft_defaults. The version of FieldTrip I am using is
> 20130602.
>
> Thanks,
> Andrew
>
>
>
>
>
>
> On Mon, Jun 3, 2013 at 4:53 PM, Lozano Soldevilla, D. (Diego) <
> d.lozanosoldevilla at fcdonders.ru.nl> wrote:
>
>> Hi Andrew,
>>
>> Did you type the following?
>>
>> >> restoredefaultpath
>> >> addpath /fieldtripxxxx
>> >> ft_defaults
>>
>> What's the ft_* function you invoke to get the error 'undefined function
>> 'hom2six'? And what's the fieldtrip version you're using?
>>
>> best,
>>
>> Diego
>>
>> ------------------------------
>>
>> *From: *"Andrew Brooks" <andmib at gmail.com>
>> *To: *"FieldTrip discussion list" <fieldtrip at science.ru.nl>
>> *Sent: *Monday, 3 June, 2013 10:15:49 PM
>> *Subject: *[FieldTrip] Private function problems
>>
>>
>> Hello all,
>>
>> I followed the instructions on properly adding FieldTrip to the Matlab
>> path file. However, I continue to run into errors involving private
>> functions. In this case, I get the error 'undefined function 'hom2six' for
>> input arguments of type 'double''.
>>
>> Does anybody have a suggestion as to why this is occurring?
>>
>> Thanks!
>> Andrew
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>>
>>
>>
>> --
>> PhD Student
>> Neuronal Oscillations Group
>> Donders Institute for Brain, Cognition and Behaviour
>> Centre for Cognitive Neuroimaging
>> Trigon, room 0.83
>> Kapittelweg 29
>> Radboud University Nijmegen
>> NL-6525 EN Nijmegen
>> The Netherlands
>> E-Mail: d.lozanosoldevilla at fcdonders.ru.nl
>> Tel:     +31-(0)24-36-66274
>> Web:   http://www.neuosc.com/
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From jkamienk at gmail.com  Thu Jun  6 17:49:27 2013
From: jkamienk at gmail.com (Juan Kamienkowski)
Date: Thu, 6 Jun 2013 12:49:27 -0300
Subject: [FieldTrip] Oscillatory power normalization
In-Reply-To: <CAJB8axm9J3=ktKM16bVhjFiToBOcD1RrVbn+1xxD4HiiqP1_WA@mail.gmail.com>
References: <CAJB8axm9J3=ktKM16bVhjFiToBOcD1RrVbn+1xxD4HiiqP1_WA@mail.gmail.com>
Message-ID: <CAARjoQSOKzcBL8qF6LYLd4CYzCOfzOhYiSQbfwhVDBB16bu2dg@mail.gmail.com>

Hi everybody,

More than one year later we come up with the same questions. Does anybody
have suggestions on this topic?

Thanks a lot!

Best,

juan


On Fri, Mar 9, 2012 at 4:16 PM, Matt Mollison <matt.mollison at gmail.com>wrote:

> My questions essentially boil down to: what do people do for power
> normalization when assessing statistical differences?
>
> It gets more detailed below regarding examining event-related power
> changes relative to a baseline (within-subjects, comparing two conditions,
> stimulus onset = 0 ms). I didn't find much discussion of this on the list
> or the wiki. Any references for these issues would also be appreciated.
>
> (1) Does power data need to be baseline normalized for statistical tests
> comparing conditions? Normalization would put power on equal footing across
> all subjects, conditions, sensors, times, frequencies, etc., but it will
> surely affect power during the stimulus period in a particular way. If so,
> do the two (or more) conditions need to use the same baseline condition, or
> can each trial be normalized to its own pre-stim baseline period (a la
> ft_freqbaseline)? For either, it seems like you'd always need
> keeptrials='yes' in ft_freqanalysis. However, it does not seem to get
> normalized in the cluster_permutation_freq tutorial (within-subjects)---am
> I missing something?
>
> If we should normalize:
> (2) I've read a number of papers that Z-transform stimulus period power
> relative to pre-stim activity (subtract mean, divide by std) before doing
> statistics. I've also read a lot that don't mention baselines, or e.g. do a
> decibel [dB] transform. ft_freqbaseline does not have a Z-transform option.
> There is ft_preproc_standardize, but this seems to operate at a lower level
> than is usually recommended. Z-transforming seems like a good option, but
> how can I use it in the FT pipeline for within-subjects analyses
> (especially with keeptrials='no')? Alternatively, when should one use
> 'absolute', 'relative', or 'relchange'?
>
> Regarding choosing the baseline period:
> (3) It seems that the baseline period needs to precede stimulus onset by a
> sufficient amount of time so that the stimulus period doesn't bleed into
> the baseline; this time would be specific to both the frequency and either
> wavelet width or taper window length. For example, at 4 Hz with wavelet
> width=6 or a taper with 6 cycles per time window (t_ftimwin) the
> wavelet/window would be 1500 ms long, and the end of the baseline must
> precede stimulus onset by at least half this to keep them separate. At
> lower frequencies this could get quite unruly (e.g., 1 Hz would require
> ending 3000 ms before stimulus). Is this correct? Maybe that's why it's
> better to have a single separate baseline condition. Anyway, the
> timefrequencyanalysis tutorial seems to disregard this separation of
> baseline and stimulus activity (as have many papers I've read), so maybe
> I'm wrong about this being necessary.
>
> Thanks for your time,
> Matt Mollison
>
> --
> Univ. of Colorado at Boulder
> Dept. of Psychology and Neuroscience
> matthew.mollison at colorado.edu
> http://psych.colorado.edu/~mollison/
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
Juan E Kamienkowski
Laboratorio de Neurociencia Integrativa
Departamento de Fisica, FCEN-UBA
Ciudad Universitaria, Pabellon I
(1428) Buenos Aires, Argentina
Phone: (54-11) 4576 3300 (282)
Fax: (54-11) 4576 3357
http://www.neurociencia.df.uba.ar/
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From S.J.Johnston at swansea.ac.uk  Fri Jun  7 11:23:20 2013
From: S.J.Johnston at swansea.ac.uk (Steve Johnston)
Date: Fri, 7 Jun 2013 10:23:20 +0100
Subject: [FieldTrip] Bad channel correction problems and ICA
Message-ID: <55D211F2-5D76-43EE-B41A-EA05C8FFCE6F@swansea.ac.uk>

Dear fters

I've just started using ft and, although being able to run through a test run of eye movement data just fine, I'm now getting into the more detailed stuff and I'm hitting a snag that I hope you can help me with.

Specifically I'm struggling to get any real ICA results after using ft_channelrepair but not if I go through without it. 

Data was recorded on a biosemi 128 system and the trials are just eye movements that I want to identify via ICA (simple test). 

If I just run through the procedure of importing data, set markers, remove gross artifacts (keeping all channels, including 3 bad ones) and then run the ICA - I get lovely eye movement components appearing. However, now I want to do it 'properly' and replace the bad channels. Currently I do the following … (sorry, for completeness I included everything to be on the safe side).

%%
% Standard cfg for import
 
cfg                         = [];
cfg.trialdef.prestim        = .2;
cfg.trialdef.poststim       = 2;
cfg.trialdef.eventtype      = 'STATUS';
 
%%
%Load each dataset and examine for channels that are bad - starting with EOG Localiser.
 
cfg.dataset                 = [subjectdata.dir filesep subjectdata.artifactfile];
cfg.trialdef.eventvalue     = markers.artifact;
cfg                         = ft_definetrial(cfg);
 
cfg.demean                  = 'yes';
data                        = ft_preprocessing(cfg);
 
% After the above, run ChannelRepair after identifying bad channels.
%%
% Channel Replace - get nearest neighbours
cfg                      = [];
cfg.method               = 'distance'
cfg.layout               = 'biosemi128.lay';
cfg.neighbourdist        = 0.13;
[neighbours]             = ft_prepare_neighbours(cfg,data)
 
%% Interpolate and put into new data structure
cfg                      = [];
cfg.badchannel           = replace_channels;
cfg.layout               = 'biosemi128.lay';
cfg.method               = 'nearest';
cfg.neighbours           = neighbours;
cfg.neighbourdist        = 0.13;
artifact_cleandata       = ft_channelrepair(cfg,data)

% Visualise data for and mark uncorrectable artifacts.
cfg.viewmode                = 'vertical';
cfg.continuous              = 'yes';
cfg.blocksize               = 12;
cfg                         = ft_databrowser(cfg,artifact_cleandata)
 
%%
% Do artifact rejection (also redefine settings lost during re-cfg in artefact rejection) 
cfg.trialdef.prestim        = .2;
cfg.trialdef.poststim       = 2;
cfg.trialdef.eventtype      = 'STATUS';
cfg.artifact.reject         = 'complete';
cfg.channel                 = 'EEG';
cfg                         = ft_rejectartifact(cfg, artifact_cleandata);
trialdata                   = ft_preprocessing(cfg, artifact_cleandata);
 
%%
cfg                         = [];
comp                        = ft_componentanalysis(cfg, trialdata); 
cfg                         = [];
cfg.component               = [1:20]
cfg.layout                  = 'biosemi128.lay'
cfg.comment                 = 'no'
ft_topoplotIC(cfg,comp)

So, the big question is - why do I get nothing after doing the channel repair. I've been through it several times and that seems to be the step where everything goes wrong. I've looked at the data post re-interpolation and it looks good - for now I'm assuming I've missed something.

Thanks for any help

Steve 
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From jm.horschig at donders.ru.nl  Fri Jun  7 11:47:11 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Fri, 07 Jun 2013 11:47:11 +0200
Subject: [FieldTrip] Bad channel correction problems and ICA
In-Reply-To: <55D211F2-5D76-43EE-B41A-EA05C8FFCE6F@swansea.ac.uk>
References: <55D211F2-5D76-43EE-B41A-EA05C8FFCE6F@swansea.ac.uk>
Message-ID: <51B1AC1F.1010008@donders.ru.nl>

Hi Steve,

I'm not quite sure what you mean with getting nothing (nothing like, 
empty? or an error?) or not getting real ICA results (real in contrast 
to complex?). My hunge is that you need to take the rank of your data 
into account. Interpolating missing channels is done by combining 
already existing information, i.e. channels, to reconstruct a 
time-course at another spatial location, i.e. another channel. Since you 
do not add any new information by this (it's just a linear combination 
of your existing data matrix), you can leave that step out prior to 
doing ICA. Otherwise, you can set something like ica_cfg.XXXica.pca = 
rank(data.trial{1}), then afaik ft_componentanalysis will perform a PCA 
and essentially identify that the interpolated channels are a linear 
combination of other channels (ICA is then done of the PCA components). 
Both methods are equivalent, so you might as well just drop the 
interpolation and remove bad channels completely.

Best,
Jörn


On 6/7/2013 11:23 AM, Steve Johnston wrote:
> Dear fters
>
> I've just started using ft and, although being able to run through a 
> test run of eye movement data just fine, I'm now getting into the more 
> detailed stuff and I'm hitting a snag that I hope you can help me with.
>
> Specifically I'm struggling to get any real ICA results after using 
> ft_channelrepair but not if I go through without it.
>
> Data was recorded on a biosemi 128 system and the trials are just eye 
> movements that I want to identify via ICA (simple test).
>
> If I just run through the procedure of importing data, set markers, 
> remove gross artifacts (keeping all channels, including 3 bad ones) 
> and then run the ICA - I get lovely eye movement components appearing. 
> However, now I want to do it 'properly' and replace the bad channels. 
> Currently I do the following ... (sorry, for completeness I included 
> everything to be on the safe side).
>
> %%
> % Standard cfg for import
>
> cfg                         = [];
> cfg.trialdef.prestim       = .2;
> cfg.trialdef.poststim       = 2;
> cfg.trialdef.eventtype     = 'STATUS';
>
> %%
> %Load each dataset and examine for channels that are bad - starting 
> with EOG Localiser.
>
> cfg.dataset                 = [subjectdata.dir filesep 
> subjectdata.artifactfile];
> cfg.trialdef.eventvalue     = markers.artifact;
> cfg                         = ft_definetrial(cfg);
>
> cfg.demean                 = 'yes';
> data                       = ft_preprocessing(cfg);
>
> % After the above, run ChannelRepair after identifying bad channels.
> %%
> % Channel Replace - get nearest neighbours
> cfg                      = [];
> cfg.method               = 'distance'
> cfg.layout               = 'biosemi128.lay';
> cfg.neighbourdist        = 0.13;
> [neighbours]             = ft_prepare_neighbours(cfg,data)
>
> %% Interpolate and put into new data structure
> cfg                      = [];
> cfg.badchannel           = replace_channels;
> cfg.layout               = 'biosemi128.lay';
> cfg.method               = 'nearest';
> cfg.neighbours           = neighbours;
> cfg.neighbourdist        = 0.13;
> artifact_cleandata       = ft_channelrepair(cfg,data)
>
> % Visualise data for and mark uncorrectable artifacts.
> cfg.viewmode                = 'vertical';
> cfg.continuous              = 'yes';
> cfg.blocksize               = 12;
> cfg                         = ft_databrowser(cfg,artifact_cleandata)
>
> %%
> % Do artifact rejection (also redefine settings lost during re-cfg in 
> artefact rejection)
> cfg.trialdef.prestim        = .2;
> cfg.trialdef.poststim       = 2;
> cfg.trialdef.eventtype      = 'STATUS';
> cfg.artifact.reject         = 'complete';
> cfg.channel                 = 'EEG';
> cfg                         = ft_rejectartifact(cfg, artifact_cleandata);
> trialdata                   = ft_preprocessing(cfg, artifact_cleandata);
>
> %%
> cfg                         = [];
> comp                        = ft_componentanalysis(cfg, trialdata);
> cfg                         = [];
> cfg.component               = [1:20]
> cfg.layout                  = 'biosemi128.lay'
> cfg.comment                 = 'no'
> ft_topoplotIC(cfg,comp)
>
> So, the big question is - why do I get nothing after doing the channel 
> repair. I've been through it several times and that seems to be the 
> step where everything goes wrong. I've looked at the data post 
> re-interpolation and it looks good - for now I'm assuming I've missed 
> something.
>
> Thanks for any help
>
> Steve
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands

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From S.J.Johnston at swansea.ac.uk  Fri Jun  7 11:59:10 2013
From: S.J.Johnston at swansea.ac.uk (Steve Johnston)
Date: Fri, 7 Jun 2013 10:59:10 +0100
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 15
In-Reply-To: <mailman.405.1370598433.1298.fieldtrip@science.ru.nl>
References: <mailman.405.1370598433.1298.fieldtrip@science.ru.nl>
Message-ID: <49AE80C3-1CA6-402B-8819-3140FCFF7DC3@swansea.ac.uk>

Thanks, and sorry, that was a pretty poor description of the results by me. Yes, I am getting a result, but the error/warning is 

'Warning: Matrix is close to singular or badly scaled.
Results may be inaccurate. RCOND = 1.376132e-17. '

I figured that matrix singularity may have been the problem, although I hadn't appreciated that replacing only three channels could lead to it -  I was expecting that to result from more channel replacements or using a lot of electrodes to interpolate with.

Thanks a lot for the help, will try as you suggest

Steve



> 
> 
> ----------------------------------------------------------------------
> 
> Message: 1
> Date: Fri, 7 Jun 2013 10:23:20 +0100
> From: Steve Johnston <S.J.Johnston at swansea.ac.uk>
> To: "fieldtrip at science.ru.nl" <fieldtrip at science.ru.nl>
> Subject: [FieldTrip] Bad channel correction problems and ICA
> Message-ID: <55D211F2-5D76-43EE-B41A-EA05C8FFCE6F at swansea.ac.uk>
> Content-Type: text/plain; charset="windows-1252"
> 
> Dear fters
> 
> I've just started using ft and, although being able to run through a test run of eye movement data just fine, I'm now getting into the more detailed stuff and I'm hitting a snag that I hope you can help me with.
> 
> Specifically I'm struggling to get any real ICA results after using ft_channelrepair but not if I go through without it. 
> 
> Data was recorded on a biosemi 128 system and the trials are just eye movements that I want to identify via ICA (simple test). 
> 
> If I just run through the procedure of importing data, set markers, remove gross artifacts (keeping all channels, including 3 bad ones) and then run the ICA - I get lovely eye movement components appearing. However, now I want to do it 'properly' and replace the bad channels. Currently I do the following ? (sorry, for completeness I included everything to be on the safe side).
> 
> %%
> % Standard cfg for import
> 
> cfg                         = [];
> cfg.trialdef.prestim        = .2;
> cfg.trialdef.poststim       = 2;
> cfg.trialdef.eventtype      = 'STATUS';
> 
> %%
> %Load each dataset and examine for channels that are bad - starting with EOG Localiser.
> 
> cfg.dataset                 = [subjectdata.dir filesep subjectdata.artifactfile];
> cfg.trialdef.eventvalue     = markers.artifact;
> cfg                         = ft_definetrial(cfg);
> 
> cfg.demean                  = 'yes';
> data                        = ft_preprocessing(cfg);
> 
> % After the above, run ChannelRepair after identifying bad channels.
> %%
> % Channel Replace - get nearest neighbours
> cfg                      = [];
> cfg.method               = 'distance'
> cfg.layout               = 'biosemi128.lay';
> cfg.neighbourdist        = 0.13;
> [neighbours]             = ft_prepare_neighbours(cfg,data)
> 
> %% Interpolate and put into new data structure
> cfg                      = [];
> cfg.badchannel           = replace_channels;
> cfg.layout               = 'biosemi128.lay';
> cfg.method               = 'nearest';
> cfg.neighbours           = neighbours;
> cfg.neighbourdist        = 0.13;
> artifact_cleandata       = ft_channelrepair(cfg,data)
> 
> % Visualise data for and mark uncorrectable artifacts.
> cfg.viewmode                = 'vertical';
> cfg.continuous              = 'yes';
> cfg.blocksize               = 12;
> cfg                         = ft_databrowser(cfg,artifact_cleandata)
> 
> %%
> % Do artifact rejection (also redefine settings lost during re-cfg in artefact rejection) 
> cfg.trialdef.prestim        = .2;
> cfg.trialdef.poststim       = 2;
> cfg.trialdef.eventtype      = 'STATUS';
> cfg.artifact.reject         = 'complete';
> cfg.channel                 = 'EEG';
> cfg                         = ft_rejectartifact(cfg, artifact_cleandata);
> trialdata                   = ft_preprocessing(cfg, artifact_cleandata);
> 
> %%
> cfg                         = [];
> comp                        = ft_componentanalysis(cfg, trialdata); 
> cfg                         = [];
> cfg.component               = [1:20]
> cfg.layout                  = 'biosemi128.lay'
> cfg.comment                 = 'no'
> ft_topoplotIC(cfg,comp)
> 
> So, the big question is - why do I get nothing after doing the channel repair. I've been through it several times and that seems to be the step where everything goes wrong. I've looked at the data post re-interpolation and it looks good - for now I'm assuming I've missed something.
> 
> Thanks for any help
> 
> Steve 
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> 
> ------------------------------
> 
> Message: 2
> Date: Fri, 07 Jun 2013 11:47:11 +0200
> From: "J?rn M. Horschig" <jm.horschig at donders.ru.nl>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] Bad channel correction problems and ICA
> Message-ID: <51B1AC1F.1010008 at donders.ru.nl>
> Content-Type: text/plain; charset="iso-8859-1"; Format="flowed"
> 
> Hi Steve,
> 
> I'm not quite sure what you mean with getting nothing (nothing like, 
> empty? or an error?) or not getting real ICA results (real in contrast 
> to complex?). My hunge is that you need to take the rank of your data 
> into account. Interpolating missing channels is done by combining 
> already existing information, i.e. channels, to reconstruct a 
> time-course at another spatial location, i.e. another channel. Since you 
> do not add any new information by this (it's just a linear combination 
> of your existing data matrix), you can leave that step out prior to 
> doing ICA. Otherwise, you can set something like ica_cfg.XXXica.pca = 
> rank(data.trial{1}), then afaik ft_componentanalysis will perform a PCA 
> and essentially identify that the interpolated channels are a linear 
> combination of other channels (ICA is then done of the PCA components). 
> Both methods are equivalent, so you might as well just drop the 
> interpolation and remove bad channels completely.
> 
> Best,
> J?rn
> 
> 
> On 6/7/2013 11:23 AM, Steve Johnston wrote:
>> Dear fters
>> 
>> I've just started using ft and, although being able to run through a 
>> test run of eye movement data just fine, I'm now getting into the more 
>> detailed stuff and I'm hitting a snag that I hope you can help me with.
>> 
>> Specifically I'm struggling to get any real ICA results after using 
>> ft_channelrepair but not if I go through without it.
>> 
>> Data was recorded on a biosemi 128 system and the trials are just eye 
>> movements that I want to identify via ICA (simple test).
>> 
>> If I just run through the procedure of importing data, set markers, 
>> remove gross artifacts (keeping all channels, including 3 bad ones) 
>> and then run the ICA - I get lovely eye movement components appearing. 
>> However, now I want to do it 'properly' and replace the bad channels. 
>> Currently I do the following ... (sorry, for completeness I included 
>> everything to be on the safe side).
>> 
>> %%
>> % Standard cfg for import
>> 
>> cfg                         = [];
>> cfg.trialdef.prestim       = .2;
>> cfg.trialdef.poststim       = 2;
>> cfg.trialdef.eventtype     = 'STATUS';
>> 
>> %%
>> %Load each dataset and examine for channels that are bad - starting 
>> with EOG Localiser.
>> 
>> cfg.dataset                 = [subjectdata.dir filesep 
>> subjectdata.artifactfile];
>> cfg.trialdef.eventvalue     = markers.artifact;
>> cfg                         = ft_definetrial(cfg);
>> 
>> cfg.demean                 = 'yes';
>> data                       = ft_preprocessing(cfg);
>> 
>> % After the above, run ChannelRepair after identifying bad channels.
>> %%
>> % Channel Replace - get nearest neighbours
>> cfg                      = [];
>> cfg.method               = 'distance'
>> cfg.layout               = 'biosemi128.lay';
>> cfg.neighbourdist        = 0.13;
>> [neighbours]             = ft_prepare_neighbours(cfg,data)
>> 
>> %% Interpolate and put into new data structure
>> cfg                      = [];
>> cfg.badchannel           = replace_channels;
>> cfg.layout               = 'biosemi128.lay';
>> cfg.method               = 'nearest';
>> cfg.neighbours           = neighbours;
>> cfg.neighbourdist        = 0.13;
>> artifact_cleandata       = ft_channelrepair(cfg,data)
>> 
>> % Visualise data for and mark uncorrectable artifacts.
>> cfg.viewmode                = 'vertical';
>> cfg.continuous              = 'yes';
>> cfg.blocksize               = 12;
>> cfg                         = ft_databrowser(cfg,artifact_cleandata)
>> 
>> %%
>> % Do artifact rejection (also redefine settings lost during re-cfg in 
>> artefact rejection)
>> cfg.trialdef.prestim        = .2;
>> cfg.trialdef.poststim       = 2;
>> cfg.trialdef.eventtype      = 'STATUS';
>> cfg.artifact.reject         = 'complete';
>> cfg.channel                 = 'EEG';
>> cfg                         = ft_rejectartifact(cfg, artifact_cleandata);
>> trialdata                   = ft_preprocessing(cfg, artifact_cleandata);
>> 
>> %%
>> cfg                         = [];
>> comp                        = ft_componentanalysis(cfg, trialdata);
>> cfg                         = [];
>> cfg.component               = [1:20]
>> cfg.layout                  = 'biosemi128.lay'
>> cfg.comment                 = 'no'
>> ft_topoplotIC(cfg,comp)
>> 
>> So, the big question is - why do I get nothing after doing the channel 
>> repair. I've been through it several times and that seems to be the 
>> step where everything goes wrong. I've looked at the data post 
>> re-interpolation and it looks good - for now I'm assuming I've missed 
>> something.
>> 
>> Thanks for any help
>> 
>> Steve
>> 
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> 
> -- 
> J?rn M. Horschig
> PhD Student
> Donders Institute for Brain, Cognition and Behaviour
> Centre for Cognitive Neuroimaging
> Radboud University Nijmegen
> Neuronal Oscillations Group
> FieldTrip Development Team
> 
> P.O. Box 9101
> NL-6500 HB Nijmegen
> The Netherlands
> 
> Contact:
> E-Mail: jm.horschig at donders.ru.nl
> Tel:    +31-(0)24-36-68493
> Web: http://www.ru.nl/donders
> 
> Visiting address:
> Trigon, room 2.30
> Kapittelweg 29
> NL-6525 EN Nijmegen
> The Netherlands
> 
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> 
> ------------------------------
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> End of fieldtrip Digest, Vol 31, Issue 15
> *****************************************




From robince at gmail.com  Fri Jun  7 17:03:21 2013
From: robince at gmail.com (Robin)
Date: Fri, 7 Jun 2013 16:03:21 +0100
Subject: [FieldTrip] some of the requested samples occur twice
In-Reply-To: <51AC623A.1080207@donders.ru.nl>
References: <CALsWBNOxcuA=LCMONaGWObU4fdZ3+vskGGFcKdTZE4jGRoW47Q@mail.gmail.com>
	<51AC623A.1080207@donders.ru.nl>
Message-ID: <CALsWBNOe7BiBuBcHGeLOSAf0diPUzGdLg0E+M3wq9MnZ21t6FA@mail.gmail.com>

Hi Jörn,

Thanks.

I am already using negative trlpadding.

In this case I am trying to do the artifact detection on in memory trial
data, because I want to do it after denoise_pca. I am not sure if this is
correct but it seemed to me that denoise_pca is to correct physical
aquisition artifacts so it would be better to do it before trying to
identify biological artifacts that are a part of the recorded signal.

The code I am using is below. If you could point out how to add padding for
the ft*artifact* section so that it can work on in memory data it would be
great.

Thanks,

Robin

%% Automatic artifact rejection
% for each run
run_data = cell(1,length(sub.blocks));
trl_idx = 0;
for ri=1:length(sub.blocks)
    % extra data to allow padding in artifact detection
    filterpad = 0.2;
    prestim = 0.5;
    poststim = 0.6;
    % extract trials
    cfg = [];
    cfg.dataset = fullfile(sub.megDataPath, num2str(sub.blocks(ri)), 'c,rfDC');
    cfg.trialdef.eventtype  = 'TRIGGER';
    cfg.trialdef.eventvalue = 192;
    cfg.trialdef.prestim    = prestim + filterpad;
    cfg.trialdef.poststim   = poststim + filterpad;
    cfg.trialfun = 'ft_trialfun_general';
    cfg.continuous = 'yes';

    cfg = ft_definetrial(cfg);
    % overwrite unnecessary constant eventvalue
    % with trial number within this block
    cfg.trl(:,4) = (1:size(cfg.trl,1)) + trl_idx;
    trl_idx = trl_idx + size(cfg.trl,1);

    % remove jump artifact trials
    trlidx = ismember(cfg.trl(:,4), good_trials);
    cfg.trl = cfg.trl(trlidx, :);

    % load
    cfg.detrend = 'yes';
    % long padding for line noise removal
    cfg.dftfilter = 'yes';
    cfg.padding = 10;
    run_raw = ft_preprocessing(cfg);

    % apply denoise_pca
    cfg = [];
    if isfield(sub,'posthoc_badchannels')
        remove_chans = sub.posthoc_badchannels;
    else
        remove_chans = {};
    end
    cfg.channel = ft_channelselection([{'all'} remove_chans],
good_meg_channels);
    cfg.trials = find(ismember(run_raw.trialinfo, good_trials));
    run_clean = ft_denoise_pca(cfg, run_raw);

    % artifact detection
    cfg = [];
    cfg.continuous = 'no'; % some trials are excluded
    cfg.trl = run_clean.sampleinfo;
    cfg.artfctdef.muscle.trlpadding = -filterpad;
    cfg.artfctdef.muscle.cutoff     = 20;
    [cfg, artifact] = ft_artifact_muscle(cfg, run_clean);

    cfg.artfctdef.eog.trlpadding = -filterpad;
    cfg.artfctdef.eog.channel    = {'A150' 'A124'};
    cfg.artfctdef.eog.cutoff     = 5;
    [cfg, artifact] = ft_artifact_eog(cfg, run_clean);

    % reject artifacts
    cfg.artfctdef.reject = 'complete';
    run_artfree = ft_rejectartifact(cfg, run_clean);

    % reduce to the original window
    cfg = [];
    cfg.toilim = [-prestim poststim];
    run_artfree = ft_redefinetrial(cfg, run_artfree);

    run_data{ri} = run_artfree;end

On Mon, Jun 3, 2013 at 10:30 AM, "Jörn M. Horschig" <
jm.horschig at donders.ru.nl> wrote:

Hi Robin,
>
> it's not a bug that ft_fetch_data is not allowing for overlap. The
> function needs to be generic and eventually allow for fetching data
> extending over several trial segments. However, what should be the way to
> fetch  data that occurs twice, i.e. at the end of one trial and the
> beginning of another? If you have data with overlapping samples, it is not
> straight forward to define data from one trial as to be fetched and ignore
> the other. Since preprocessing options like filters are applied per trial
> segment, data will differ between trial segments if it overlaps. As there
> are a multitude of possibilities to deal with this and none of them is
> perfect (imho neither of them can even be called good), we decided to not
> allow for that.
>
> For your problem, however, imho you can define negative trial padding in
> the function call to ft_artifact_zvalue, which should effectively pad. Have
> you tried this rather than padding manually?
>
> Best,
> Jörn
>
>
> On 5/31/2013 6:14 PM, Robin wrote:
>
>> I have a problem in preprocessing where I am getting this error:
>>
>> """
>> some of the requested samples occur twice in the data
>>
>> Error in ft_artifact_zvalue (line 262)
>>        dat{trlop} = ft_fetch_data(data,        'header', hdr, 'begsample',
>>        trl(trlop,1)-fltpadding, 'endsample', trl(trlop,2)+fltpadding,
>>        'chanindx', sgnind, 'checkboundary', strcmp(cfg.continuous,'no
>> Error in ft_artifact_muscle (line 158)
>>      [tmpcfg, artifact] = ft_artifact_zvalue(tmpcfg, data);
>> """
>>
>> I think this is because I am manually adding some extra padding to the
>> trials so that the artifact filtering can use that padding (I am doing
>> the artifact filtering on data in memory which is output from
>> ft_denoise_pca). So in this case it is not a problem if consecutive
>> trials overlap a bit.
>>
>> I would therefore like to disable this error and wondered what is the
>> best way to do it. I am a bit confused because ft_artifact_zvalue
>> calls ft_fetch data with a "checkboundary" option which looks like it
>> might be what I want (and set correctly), but ft_fetch_data doesn't
>> seem to use that option. Instead it has an allowoverlap option.
>>
>> So for now I will manually add the allowoverlap option to the call in
>> ft_artifact_zvalue, but I wondered what checkboundary doesn't appear
>> in ft_fetch_data or if this might be a bug.
>>
>> Cheers
>>
>> Robin
>> ______________________________**_________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/**mailman/listinfo/fieldtrip<http://mailman.science.ru.nl/mailman/listinfo/fieldtrip>
>>
>
>
> --
> Jörn M. Horschig
> PhD Student
> Donders Institute for Brain, Cognition and Behaviour
> Centre for Cognitive Neuroimaging
> Radboud University Nijmegen
> Neuronal Oscillations Group
> FieldTrip Development Team
>
> P.O. Box 9101
> NL-6500 HB Nijmegen
> The Netherlands
>
> Contact:
> E-Mail: jm.horschig at donders.ru.nl
> Tel:    +31-(0)24-36-68493
> Web: http://www.ru.nl/donders
>
> Visiting address:
> Trigon, room 2.30
> Kapittelweg 29
> NL-6525 EN Nijmegen
> The Netherlands
>
> ______________________________**_________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/**mailman/listinfo/fieldtrip<http://mailman.science.ru.nl/mailman/listinfo/fieldtrip>
>
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From jkamienk at gmail.com  Fri Jun  7 19:02:22 2013
From: jkamienk at gmail.com (Juan Kamienkowski)
Date: Fri, 7 Jun 2013 14:02:22 -0300
Subject: [FieldTrip] Cluster-based permutation tests on single channel
Message-ID: <CAARjoQQ-HQ7ML+2krPKvVePZo_ckfZQ8iy=4M4P7M2bvVCr_bA@mail.gmail.com>

Hi,

I wanted to perform a Cluster-based permutation tests on time-frequency
data, on a single channel (one Independent Component). But the
ft_freqstatistics() function ask me for the "neighbours" field in the "cfg"
structure, although I set the cfg.minnbchan to 0. Is there a way to run
this analysis in a single channel?

Thanks a lot in advance!

Best,

Juan

-- 
Juan E Kamienkowski
Laboratorio de Neurociencia Integrativa
Departamento de Fisica, FCEN-UBA
Ciudad Universitaria, Pabellon I
(1428) Buenos Aires, Argentina
Phone: (54-11) 4576 3300 (282)
Fax: (54-11) 4576 3357
http://www.neurociencia.df.uba.ar/
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From Don.Rojas at ucdenver.edu  Fri Jun  7 23:37:10 2013
From: Don.Rojas at ucdenver.edu (Rojas, Don)
Date: Fri, 7 Jun 2013 15:37:10 -0600
Subject: [FieldTrip] Cluster-based permutation tests on single channel
In-Reply-To: <CAARjoQQ-HQ7ML+2krPKvVePZo_ckfZQ8iy=4M4P7M2bvVCr_bA@mail.gmail.com>
References: <CAARjoQQ-HQ7ML+2krPKvVePZo_ckfZQ8iy=4M4P7M2bvVCr_bA@mail.gmail.com>
Message-ID: <E59258AC-98B2-40CB-8986-D047C55F2BB2@ucdenver.edu>

Juan,

The neighbours field is for defining adjacent channels for multi-channel multiple comparison correction. I'm not sure if you've gotten a response on this yet, but you simply set the cfg.neighbours field to be empty in your call to ft_freqstatistics for using cluster based corrections within time-frequency space for single channels.

cfg.neighbours = [];

Best,

Don

On Jun 7, 2013, at 11:02 AM, Juan Kamienkowski <jkamienk at gmail.com<mailto:jkamienk at gmail.com>> wrote:

Hi,

I wanted to perform a Cluster-based permutation tests on time-frequency data, on a single channel (one Independent Component). But the ft_freqstatistics() function ask me for the "neighbours" field in the "cfg" structure, although I set the cfg.minnbchan to 0. Is there a way to run this analysis in a single channel?

Thanks a lot in advance!

Best,

Juan

--
Juan E Kamienkowski
Laboratorio de Neurociencia Integrativa
Departamento de Fisica, FCEN-UBA
Ciudad Universitaria, Pabellon I
(1428) Buenos Aires, Argentina
Phone: (54-11) 4576 3300 (282)
Fax: (54-11) 4576 3357
http://www.neurociencia.df.uba.ar/
_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From Don.Rojas at ucdenver.edu  Fri Jun  7 23:37:10 2013
From: Don.Rojas at ucdenver.edu (Rojas, Don)
Date: Fri, 7 Jun 2013 15:37:10 -0600
Subject: [FieldTrip] Cluster-based permutation tests on single channel
In-Reply-To: <CAARjoQQ-HQ7ML+2krPKvVePZo_ckfZQ8iy=4M4P7M2bvVCr_bA@mail.gmail.com>
References: <CAARjoQQ-HQ7ML+2krPKvVePZo_ckfZQ8iy=4M4P7M2bvVCr_bA@mail.gmail.com>
Message-ID: <E59258AC-98B2-40CB-8986-D047C55F2BB2@ucdenver.edu>

Juan,

The neighbours field is for defining adjacent channels for multi-channel multiple comparison correction. I'm not sure if you've gotten a response on this yet, but you simply set the cfg.neighbours field to be empty in your call to ft_freqstatistics for using cluster based corrections within time-frequency space for single channels.

cfg.neighbours = [];

Best,

Don

On Jun 7, 2013, at 11:02 AM, Juan Kamienkowski <jkamienk at gmail.com<mailto:jkamienk at gmail.com>> wrote:

Hi,

I wanted to perform a Cluster-based permutation tests on time-frequency data, on a single channel (one Independent Component). But the ft_freqstatistics() function ask me for the "neighbours" field in the "cfg" structure, although I set the cfg.minnbchan to 0. Is there a way to run this analysis in a single channel?

Thanks a lot in advance!

Best,

Juan

--
Juan E Kamienkowski
Laboratorio de Neurociencia Integrativa
Departamento de Fisica, FCEN-UBA
Ciudad Universitaria, Pabellon I
(1428) Buenos Aires, Argentina
Phone: (54-11) 4576 3300 (282)
Fax: (54-11) 4576 3357
http://www.neurociencia.df.uba.ar/
_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From haristz at gmail.com  Sat Jun  8 00:25:03 2013
From: haristz at gmail.com (Charidimos Tzagarakis)
Date: Fri, 7 Jun 2013 17:25:03 -0500
Subject: [FieldTrip] Using ft_rejectcomponent after PCA reduction
Message-ID: <CAFN2X+fGYE6maW7X6_eyGrbt7+wvWggv4xXvu6PhebXPgSpq5A@mail.gmail.com>

Dear Fieldtripverse,
I have been experimenting with using ICA for artifact correction and have
the following question:
Because of the relatively large number of channels vs samples I have, I use
the option to first reduce the dimensionality of the data with PCA (I have
248 MEG channels and I select, say 100 components, using the <for
cfg.method="runica"> cfg.numcomponent=100 and cfg.runica.pca=100 in the
call to ft_componentanalysis ).
So the "topo" matrix in the component output structure has dimensions
248x100 and the unmixing matrix has dimensions 100x248. I then use
something like "data = ft_rejectcomponent(cfg, comp,data)" to say reject 2
components cfg.component=[30 40] that contain ECG signal. Note: data here
is the original data I fed in the ft_componentanalysis function.
This is all pretty straightforward and as described in the Fieldtrip
tutorial (minus the PCA part) . I am however a bit worried by the
message:"removing 2 components
keeping 246 components" I get in the end. Should it not be "removing 2
components
keeping 98 components"? When I look in the code for ft_rejectcomponent, I
can see that if "hasdata" is True the message is calculated based on the
number of channels : fprintf('keeping %d components\n',
nchans-length(cfg.component));
On the other hand (as far as I can tell, not being an ICA expert) the
actual calculation for the removal of the desired components seems to
correctly use the components selected for removal :
  mixing = comp.topo(selcomp,:);
  unmixing = comp.unmixing(:,selcomp);
  tra = eye(length(selcomp)) - mixing(:, cfg.component)*unmixing(cfg.
component, :);
(I do note the comment under that snippet!:
 %I am not sure about this, but it gives comparable results to the ~hasdata
case
  %when comp contains non-orthogonal (=ica) topographies, and contains a
complete decomposition)

Further down the function code there are however more operations (eg remove
unused channels, remove unused components ) where I am less able to follow
things to make sure it is robust to non-square mixing and unmixing
matrices.

In summary, I wanted to ask if it is OK to use ft_rejectcomponent in this
way (ie without decomposing to the full number of ICA's and then using it
on the original data).
With Thanks and Best Wishes,
Haris

Charidimos [Haris] Tzagarakis MD, PhD, MRCPsych
University of Minnesota Dept of Neuroscience and Brain Sciences Center
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From mengtongxiao at gmail.com  Sun Jun  9 03:31:56 2013
From: mengtongxiao at gmail.com (=?GB2312?B?s8LRqQ==?=)
Date: Sun, 9 Jun 2013 09:31:56 +0800
Subject: [FieldTrip] what is the MNI-template be use to constructed
	sourcemodel , MNI125 or colin27?
Message-ID: <CADiddyX5sgXN2qhoVPCmDsm9sbjSCkUGp=sv6PKBy1UBF_+arw@mail.gmail.com>

Dear all
I use the model ( fieldtrip/template/sourcemodel )  doing source
reconstruction with beamformer .
I want to know  the template is matching  MNI125 or colin27 .

thanks.
best ,
xiao
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From nomeserio at gmail.com  Mon Jun 10 10:29:21 2013
From: nomeserio at gmail.com (Michele Barsotti)
Date: Mon, 10 Jun 2013 10:29:21 +0200
Subject: [FieldTrip] Downloading FieldTrip
Message-ID: <CAGZjeH4vNQBHOYe7kp6jQXjtcnRD=Wvic99OkjARq57h=hm1Vg@mail.gmail.com>

Dear FieldTrip users and staff,

  I'm dealing with the download of fieldtrip but everytime I try a download
error occurs with this message:
"...fieldtrip-aaaammgg.zip could not be saved, because the source file
could not be read. Try again later, or contact the server administrator."

Can someone help me?

Thank in advance

-- 
        -Michele-
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From joramvandriel at gmail.com  Mon Jun 10 16:09:25 2013
From: joramvandriel at gmail.com (Joram van Driel)
Date: Mon, 10 Jun 2013 16:09:25 +0200
Subject: [FieldTrip] BEM for MEG data
Message-ID: <CAKk__WVoQL5s4NwxPFpLJm7WRgFzwX1CxQk4k4WtRToormTEhA@mail.gmail.com>

Dear Fieldtrip users and developers,

I've been struggling quite some time now with the following problem.

We want to do source localization of MEG data from an experiment with 10
subjects. We collected MRIs using a Phillips scanner (UvA), and MEG data
using the Neuromag Elekta scanner (VUmc).

Using Neuromag software in Linux (seglab, xfit), I've created BEM forward
models based on coregistered MRIs (coregistration also done using the
Neuromag package), which result in .fif files (extension *bem-sol.fif).

Using these models we want to continue computing the leadfields and doing
source reconstruction in Matlab. For the latter, we have our own customized
codes; to get the leadfield, we need some step in between. I'm trying to
use fieldtrip functions for this but I get stuck. Here's what I do:

- Import the bem fif files using the mne toolbox (function:
mne_read_bem_surfaces).
- Attach the imported boundary data to a vol structure as follows:

[bem] = mne_read_bem_surfaces(bemfilz(subno).name);
vol                 = [];
vol.bnd.pnt         = bem.rr;
vol.bnd.tri         = double(bem.tris);
vol.unit            = 'mm';
vol.cfg.sourceunits = 'mm';
vol.type            = 'bemcp';
vol.cfg.numvertices = bem.np;

- Import the sensor locations using ft_read_sens and convert to mm using
ft_convert_units.
- Check whether the resulting structures are OK for leadfield computation
using ft_prepare_vol_sens. This results in an error "Unsupported volume
conductor model for MEG".

I also tried ft_read_vol, but for Neuromag this needs the meg-pd toolbox
which doesn't run on Windows (the Linux we use for the Neuromag software,
in turn, is a virtual machine and doesn't have Matlab).

Is there a way around this? Using BEM models for MEG data should in
principle be possible, but not using Fieldtrip?

Any suggestions would be much appreciated!
Thanks in advance,

Joram


-- 
Joram van Driel, MSc.
PhD student at the University of Amsterdam
Department of Psychology, Brain & Cognition
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From aaron.schurger at gmail.com  Mon Jun 10 18:11:23 2013
From: aaron.schurger at gmail.com (Aaron Schurger)
Date: Mon, 10 Jun 2013 18:11:23 +0200
Subject: [FieldTrip] What are the units output by ft_freqanalysis_tfr?
Message-ID: <CALeeyAQiEs-GM+40MU-O4QJQq29iO4XaK97_6utb2dLjpCqW_Q@mail.gmail.com>

Hi,
I am preparing figures for a paper, one of which is a time-frequency
plot of the output from ft_freqanalysis (using the tfr method). The
units of the data going in were on the order of 10e-11 or smaller (MEG
data), but the units on the color (power) axis of the plot are on the
order of 10e-1. Are the units normalized by default when you use
ft_freqanalysis? If not then what are the units? The help on these
functions was short on this kind of detail.
Thanks!
Aaron Schurger

--
Aaron Schurger, PhD
Post-doctoral researcher
INSERM U992 / NeuroSpin
CEA - Saclay, France
+33-1-69-08-66-47
aaron.schurger at gmail.com
http://www.unicog.org


From ivan.skelin at uleth.ca  Tue Jun 11 03:57:55 2013
From: ivan.skelin at uleth.ca (Skelin, Ivan)
Date: Mon, 10 Jun 2013 18:57:55 -0700
Subject: [FieldTrip] ncs file downsampling and further processing
Message-ID: <CA+pymnfq-RTSQuP_LQvZLGACQPetbdWeaT_zY81_cwA+hKATPw@mail.gmail.com>

Hi,

I am recording from the anesthetized rats using the two NeuroNexus silicone
probes with 8 tetrodes (32 channels) each and Neuralynx Cheetah system at
32556 Hz sampling frequency. I choose to analyze the .ncs files from 1/4 of
the channels or 1 channel per tetrode. Since the recordings took about 150
mins, the .ncs files are too bulky (0.5 GB) for the standard procedure that
the FieldTrip recommends for discontinuous data recorded using Neuralynx
system. More precisely, when I preprocess the channels separately and
subsequently run the ft_read_neuralynx_interp on them, I get the "out of
memory" error message (even when running it on only two .ncs files at the
time).

My question is if I can first downsample all the .csc files that I want to
analyze using the ft_spikedownsample, before I run the ft_read_neuralynx_interp
on them?



Thank you very much,

Ivan


-- 
Ivan Skelin, MD, PhD
Postdoctoral Fellow
Polaris Brain Dynamics Research Group
Canadian Centre for Behavioural Neuroscience
The University of Lethbridge
4401 University Dr W
Lethbridge, AB, T1K 3M4
Canada
http://lethbridgebraindynamics.com
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From explena at gmail.com  Tue Jun 11 09:48:34 2013
From: explena at gmail.com (Shen-Mou Hsu)
Date: Tue, 11 Jun 2013 15:48:34 +0800
Subject: [FieldTrip] ROC_based permutation test
Message-ID: <CAFg6g2eKEb-EmYa=BkWTwUVx20+oP92rs6u06w9m+Ehz5ni8qg@mail.gmail.com>

Dear all,

I was trying to perform signle-trial ROC-based permutation tests using the
statfun_roc. However I encountered two questions and wondered if anyone
could kindly shed some light on the issues. First, is it necessary to
perform baseline normalization for each trial before the tests? Second, an
error message returned stating "Error using roc. Too many input arguments.
Error using ft_statistics_montecarlo (line 223) could not determine the
parametric critical value for clustering", after running the following
script:

load (['t_RF_EpoRejDePow']); load (['t_RN_EpoRejDePow']);

cfg = [];
cfg.channel     = 'MEG';
cfg.latency     = [-0.35 0.55];
cfg.frequency   = [8 12];
cfg.parameter   = 'powspctrm';
cfg.method      = 'montecarlo';
cfg.statistic   = 'roc';
cfg.alpha       = 0.025;
cfg.tail = 0;
cfg.correctm    = 'cluster';
cfg.clusteralpha = 0.05;
% cfg.correcttail = 'prob';
cfg.clustertail = 0;
cfg.numrandomization = 1000;
cfg.minnbchan        = 2;
cfg_neighb.method    = 'distance';
cfg.neighbours       = ft_prepare_neighbours(cfg_neighb, t_RN_EpoRejDePow);
cfg.logtransform = 'yes';

design = [1*ones(1,size(t_RF_EpoRejDePow.powspctrm,1))
2*ones(1,size(t_RN_EpoRejDePow.powspctrm,1))]; % the first dimension of
these variable is the trial number.
cfg.design  = design;

P_ROC_t_RFvsRN = ft_freqstatistics(cfg,t_RF_EpoRejDePow,t_RN_EpoRejDePow);


Any help is greatly appreciated.

Best regards,

Shen-Mou Hsu
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From eelke.spaak at donders.ru.nl  Tue Jun 11 09:58:58 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Tue, 11 Jun 2013 09:58:58 +0200
Subject: [FieldTrip] What are the units output by ft_freqanalysis_tfr?
In-Reply-To: <CALeeyAQiEs-GM+40MU-O4QJQq29iO4XaK97_6utb2dLjpCqW_Q@mail.gmail.com>
References: <CALeeyAQiEs-GM+40MU-O4QJQq29iO4XaK97_6utb2dLjpCqW_Q@mail.gmail.com>
Message-ID: <CABPNLUrhOFUV30iN8SWGEbR_613nYXVa6=gFaE8toDB+rNwTwA@mail.gmail.com>

Hi Aaron,

How are you plotting the data? If you are using
ft_single/multi/topoplotTFR, did you use baseline correction
(cfg.baseline = 'yes' or [begin end])? If you use cfg.baselinetype =
'relative' or cfg.baselinetype = 'relchange', data plotted will
typically be on the order of 10e-1. It represents ratio vs baseline
('relative') or relative change vs baseline ('relchange').

If you did not specify baseline correction, then there is something
else going on. In any case, ft_freqanalysis does not explicitly
transform/normalize units; it does not care about them.

Best,
Eelke

On 10 June 2013 18:11, Aaron Schurger <aaron.schurger at gmail.com> wrote:
> Hi,
> I am preparing figures for a paper, one of which is a time-frequency
> plot of the output from ft_freqanalysis (using the tfr method). The
> units of the data going in were on the order of 10e-11 or smaller (MEG
> data), but the units on the color (power) axis of the plot are on the
> order of 10e-1. Are the units normalized by default when you use
> ft_freqanalysis? If not then what are the units? The help on these
> functions was short on this kind of detail.
> Thanks!
> Aaron Schurger
>
> --
> Aaron Schurger, PhD
> Post-doctoral researcher
> INSERM U992 / NeuroSpin
> CEA - Saclay, France
> +33-1-69-08-66-47
> aaron.schurger at gmail.com
> http://www.unicog.org
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From eelke.spaak at donders.ru.nl  Tue Jun 11 10:18:09 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Tue, 11 Jun 2013 10:18:09 +0200
Subject: [FieldTrip] ROC_based permutation test
In-Reply-To: <CAFg6g2eKEb-EmYa=BkWTwUVx20+oP92rs6u06w9m+Ehz5ni8qg@mail.gmail.com>
References: <CAFg6g2eKEb-EmYa=BkWTwUVx20+oP92rs6u06w9m+Ehz5ni8qg@mail.gmail.com>
Message-ID: <CABPNLUpB9DHCQCszf7WuujVgKT4g9Dp3GPNd19-O65b160y8NQ@mail.gmail.com>

Dear Shen-Mou Hsu,

With regards to your first question, I do not know the answer, so
someone else might help you there.

In response to your second question, regarding the error "could not
determine the parametric critical value for clustering", this is
caused by the value of cfg.clusterthreshold used. The default value
there is 'parametric', meaning that the statistics routine will ask
your 'statfun' to compute a parametric threshold for considering a
(time/frequency/channel)-voxel a cluster-member candidate. This can be
done by e.g. depsamplesT or indepsamplesT, as it is possible to
analytically compute a T value corresponding to p < 0.05. However, in
the case of the ROC statistic, no such parametric estimate can be
computed (or perhaps it can be in some way, I don't know, but at least
I know the FT implementation does not).

Fortunately, the statistics routines also allow you to use a
nonparametric threshold for cluster-member candidates, based on the
generated distribution of the test statistic under the null
hypothesis. To use this, simply specify cfg.clusterthreshold =
'nonparametric_individual' or cfg.clusterthreshold =
'nonparametric_common'. The difference between the two is that the
former computes a threshold per voxel, and the latter uses the same
threshold for all voxels. Which one is appropriate for you I don't
know. (Good reasons for using 'nonparametric_individual' might be a
strong variation of your test statistic with frequency. I know for a
fact this is the case with certain quantifications of phase-amplitude
coupling; these show much higher values in the low frequencies even
when computed on noise.)

Hope this helps.

Best,
Eelke

On 11 June 2013 09:48, Shen-Mou Hsu <explena at gmail.com> wrote:
> Dear all,
>
> I was trying to perform signle-trial ROC-based permutation tests using the
> statfun_roc. However I encountered two questions and wondered if anyone
> could kindly shed some light on the issues. First, is it necessary to
> perform baseline normalization for each trial before the tests? Second, an
> error message returned stating "Error using roc. Too many input arguments.
> Error using ft_statistics_montecarlo (line 223) could not determine the
> parametric critical value for clustering", after running the following
> script:
>
> load (['t_RF_EpoRejDePow']); load (['t_RN_EpoRejDePow']);
>
> cfg = [];
> cfg.channel     = 'MEG';
> cfg.latency     = [-0.35 0.55];
> cfg.frequency   = [8 12];
> cfg.parameter   = 'powspctrm';
> cfg.method      = 'montecarlo';
> cfg.statistic   = 'roc';
> cfg.alpha       = 0.025;
> cfg.tail = 0;
> cfg.correctm    = 'cluster';
> cfg.clusteralpha = 0.05;
> % cfg.correcttail = 'prob';
> cfg.clustertail = 0;
> cfg.numrandomization = 1000;
> cfg.minnbchan        = 2;
> cfg_neighb.method    = 'distance';
> cfg.neighbours       = ft_prepare_neighbours(cfg_neighb, t_RN_EpoRejDePow);
> cfg.logtransform = 'yes';
>
> design = [1*ones(1,size(t_RF_EpoRejDePow.powspctrm,1))
> 2*ones(1,size(t_RN_EpoRejDePow.powspctrm,1))]; % the first dimension of
> these variable is the trial number.
> cfg.design  = design;
>
> P_ROC_t_RFvsRN = ft_freqstatistics(cfg,t_RF_EpoRejDePow,t_RN_EpoRejDePow);
>
>
> Any help is greatly appreciated.
>
> Best regards,
>
> Shen-Mou Hsu
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From aaron.schurger at gmail.com  Tue Jun 11 11:00:03 2013
From: aaron.schurger at gmail.com (Aaron Schurger)
Date: Tue, 11 Jun 2013 11:00:03 +0200
Subject: [FieldTrip] What are the units output by ft_freqanalysis_tfr?
In-Reply-To: <CABPNLUrhOFUV30iN8SWGEbR_613nYXVa6=gFaE8toDB+rNwTwA@mail.gmail.com>
References: <CALeeyAQiEs-GM+40MU-O4QJQq29iO4XaK97_6utb2dLjpCqW_Q@mail.gmail.com>
	<CABPNLUrhOFUV30iN8SWGEbR_613nYXVa6=gFaE8toDB+rNwTwA@mail.gmail.com>
Message-ID: <CALeeyAS=CgYuqCh0cve-euKptDk2AGNyS8vLXZtQ987244zAaQ@mail.gmail.com>

Hi, Eelke,
Thanks for your reply. I think that might explain it. When I step
through my code, I see that the units are as expected for MEG in the
output from ft_freqanalysis, so it must be something after that stage
that is changing.
Thanks for the tip!
Best wishes,
Aaron

On Tue, Jun 11, 2013 at 9:58 AM, Eelke Spaak <eelke.spaak at donders.ru.nl> wrote:
> Hi Aaron,
>
> How are you plotting the data? If you are using
> ft_single/multi/topoplotTFR, did you use baseline correction
> (cfg.baseline = 'yes' or [begin end])? If you use cfg.baselinetype =
> 'relative' or cfg.baselinetype = 'relchange', data plotted will
> typically be on the order of 10e-1. It represents ratio vs baseline
> ('relative') or relative change vs baseline ('relchange').
>
> If you did not specify baseline correction, then there is something
> else going on. In any case, ft_freqanalysis does not explicitly
> transform/normalize units; it does not care about them.
>
> Best,
> Eelke
>
> On 10 June 2013 18:11, Aaron Schurger <aaron.schurger at gmail.com> wrote:
>> Hi,
>> I am preparing figures for a paper, one of which is a time-frequency
>> plot of the output from ft_freqanalysis (using the tfr method). The
>> units of the data going in were on the order of 10e-11 or smaller (MEG
>> data), but the units on the color (power) axis of the plot are on the
>> order of 10e-1. Are the units normalized by default when you use
>> ft_freqanalysis? If not then what are the units? The help on these
>> functions was short on this kind of detail.
>> Thanks!
>> Aaron Schurger
>>
>> --
>> Aaron Schurger, PhD
>> Post-doctoral researcher
>> INSERM U992 / NeuroSpin
>> CEA - Saclay, France
>> +33-1-69-08-66-47
>> aaron.schurger at gmail.com
>> http://www.unicog.org
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip



-- 
Aaron Schurger, PhD
Post-doctoral researcher
INSERM U992 / NeuroSpin
CEA - Saclay, France
+33-1-69-08-66-47
aaron.schurger at gmail.com
http://www.unicog.org


From nicolai at mersebak.dk  Wed Jun 12 15:44:00 2013
From: nicolai at mersebak.dk (Nicolai Mersebak)
Date: Wed, 12 Jun 2013 15:44:00 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
Message-ID: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>

Dear all,

I have a question concerning the usage of ft_sourcegrandaverage and
ft_sourcestatistics.

After using ft_sourceanalysis (method: MNE), I get spatio-temporal source
reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897
time points.

Now I would like to use the cluster-based permutation test on my source
reconstructed data. However it seems like ft_sourcegrandaverage and
ft_sourcestatistics
don't support source level time courses. E.g when I am using
ft_sourcegrandaverage
I am getting the following error:

Error in ft_sourcegrandaverage (line 158)
  dat(:,i) = tmp(:);

Looking into the code:

  for i=1:Nsubject

    tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter,
varargin{i}));

    dat(:,i) = tmp(:);

    tmp = getsubfield(varargin{i}, 'inside');

    inside(tmp,i) = 1;

  end

I see that "tmp" are getting the structure [N_sources x timepoints] from
source.avg.pow for one subject, where "dat" requires the structure
[N_sources x 1].

I seached the mailing list for similar issues and found this thread:

http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html

Since I am interested in using the temporal dimension in my statistics, I
would like to know if it is still not possible to use spatio-temporal
source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?

Or if any have succeeded in using the cluster-based permutation test on
source level also including the temporal dimension ?

Alternative I was thinking that I might could use ft_timelockstatistics,
where I substituted the channels with sources, e.g instead of having 64
channels, I would now have 4050 "channels".
If so I need to calculate a label structure and an appropriate neighbor
structure, which I guess is possible as I have all the 3D coordinates for
each source, e.g in leadfield.pos ?
I know this is a work around solution, but have anyone tried or have any
experience using such an approach ?

Best,

Nicolai
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From johanna.zumer at donders.ru.nl  Wed Jun 12 16:03:16 2013
From: johanna.zumer at donders.ru.nl (Johanna Zumer)
Date: Wed, 12 Jun 2013 16:03:16 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
 reconstruction data (MNE)
In-Reply-To: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
Message-ID: <CAL4kA6dpzj6xWWs0kXOeQ60WKVixowZtF6N4Kse0ubeoA=4vLQ@mail.gmail.com>

Dear Nicolai,

Good timing, I have just last week filed a 'bug' for this code modification
request:  http://bugzilla.fcdonders.nl/show_bug.cgi?id=2185
You may add yourself to the CC list if you wish to receive updates on the
bug progress.

I would be interested to hear if anyone else has thoughts on your
suggestion to 'hack' it as a timelock structure with channels.

Best,
Johanna


2013/6/12 Nicolai Mersebak <nicolai at mersebak.dk>

> Dear all,
>
> I have a question concerning the usage of ft_sourcegrandaverage and
> ft_sourcestatistics.
>
> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source
> reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897
> time points.
>
> Now I would like to use the cluster-based permutation test on my source
> reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics
> don't support source level time courses. E.g when I am using ft_sourcegrandaverage
> I am getting the following error:
>
> Error in ft_sourcegrandaverage (line 158)
>   dat(:,i) = tmp(:);
>
> Looking into the code:
>
>   for i=1:Nsubject
>
>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter,
> varargin{i}));
>
>     dat(:,i) = tmp(:);
>
>     tmp = getsubfield(varargin{i}, 'inside');
>
>     inside(tmp,i) = 1;
>
>   end
>
> I see that "tmp" are getting the structure [N_sources x timepoints] from
> source.avg.pow for one subject, where "dat" requires the structure
> [N_sources x 1].
>
> I seached the mailing list for similar issues and found this thread:
>
> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>
> Since I am interested in using the temporal dimension in my statistics, I
> would like to know if it is still not possible to use spatio-temporal
> source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
>
> Or if any have succeeded in using the cluster-based permutation test on
> source level also including the temporal dimension ?
>
> Alternative I was thinking that I might could use ft_timelockstatistics,
> where I substituted the channels with sources, e.g instead of having 64
> channels, I would now have 4050 "channels".
> If so I need to calculate a label structure and an appropriate neighbor
> structure, which I guess is possible as I have all the 3D coordinates for
> each source, e.g in leadfield.pos ?
> I know this is a work around solution, but have anyone tried or have any
> experience using such an approach ?
>
> Best,
>
> Nicolai
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From jm.horschig at donders.ru.nl  Wed Jun 12 16:20:29 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Wed, 12 Jun 2013 16:20:29 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
 reconstruction data (MNE)
In-Reply-To: <CAL4kA6dpzj6xWWs0kXOeQ60WKVixowZtF6N4Kse0ubeoA=4vLQ@mail.gmail.com>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
	<CAL4kA6dpzj6xWWs0kXOeQ60WKVixowZtF6N4Kse0ubeoA=4vLQ@mail.gmail.com>
Message-ID: <51B883AD.8020707@donders.ru.nl>

Heyho,

it might be a good way, at least I am doing it that way :) But think 
about defining neighbouring voxels beforehands (easily doable for a 
decent programmer, hard for a not-so-experienced programmer). In the 
upcoming months/years there will be something changing on the 
source-front anyway, so maybe it is best to use the temporary solution 
with ft_timelockXXX until then. Note that my personal opinion does not 
necessarily reflect the opinion of the core dev team ;)

Best,
Jörn

On 6/12/2013 4:03 PM, Johanna Zumer wrote:
> Dear Nicolai,
>
> Good timing, I have just last week filed a 'bug' for this code 
> modification request: http://bugzilla.fcdonders.nl/show_bug.cgi?id=2185
> You may add yourself to the CC list if you wish to receive updates on 
> the bug progress.
>
> I would be interested to hear if anyone else has thoughts on your 
> suggestion to 'hack' it as a timelock structure with channels.
>
> Best,
> Johanna
>
>
> 2013/6/12 Nicolai Mersebak <nicolai at mersebak.dk 
> <mailto:nicolai at mersebak.dk>>
>
>     Dear all,
>
>     I have a question concerning the usage of ft_sourcegrandaverage
>     and ft_sourcestatistics.
>
>     After using ft_sourceanalysis (method: MNE), I get spatio-temporal
>     source reconstructed data in source.avg.pow (4050 x 897): 4050
>     sources and 897 time points.
>
>     Now I would like to use the cluster-based permutation test on my
>     source reconstructed data. However it seems like
>     ft_sourcegrandaverage and ft_sourcestatistics don't support source
>     level time courses. E.g when I am using ft_sourcegrandaverage I am
>     getting the following error:
>
>     Error in ft_sourcegrandaverage (line 158)
>       dat(:,i) = tmp(:);
>
>     Looking into the code:
>
>     for i=1:Nsubject
>
>       tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter,
>     varargin{i}));
>
>       dat(:,i) = tmp(:);
>
>       tmp = getsubfield(varargin{i}, 'inside');
>
>       inside(tmp,i) = 1;
>
>     end
>
>
>     I see that "tmp" are getting the structure [N_sources x
>     timepoints] from source.avg.pow for one subject, where "dat"
>     requires the structure [N_sources x 1].
>
>     I seached the mailing list for similar issues and found this thread:
>
>     http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>
>     Since I am interested in using the temporal dimension in my
>     statistics, I would like to know if it is still not possible to
>     use spatio-temporal source reconstructed data in
>     ft_sourcestatistics and ft_sourcegrandaverage ?
>
>     Or if any have succeeded in using the cluster-based permutation
>     test on source level also including the temporal dimension ?
>
>     Alternative I was thinking that I might could use
>     ft_timelockstatistics, where I substituted the channels with
>     sources, e.g instead of having 64 channels, I would now have 4050
>     "channels".
>     If so I need to calculate a label structure and an appropriate
>     neighbor structure, which I guess is possible as I have all the 3D
>     coordinates for each source, e.g in leadfield.pos ?
>     I know this is a work around solution, but have anyone tried or
>     have any experience using such an approach ?
>
>     Best,
>
>     Nicolai
>
>
>     _______________________________________________
>     fieldtrip mailing list
>     fieldtrip at donders.ru.nl <mailto:fieldtrip at donders.ru.nl>
>     http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands

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From smoratti at psi.ucm.es  Wed Jun 12 17:44:59 2013
From: smoratti at psi.ucm.es (smoratti at psi.ucm.es)
Date: Wed, 12 Jun 2013 17:44:59 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
In-Reply-To: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
Message-ID: <05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>

Dear Nicolai,

Indeed I have used ft_timelockstatistics for minimum norm source data. The trick is to put the source level data into a ERF structure. Determining the neighbors of a source surface with vertices is not trivial. However I used tess_vertconn.m from the BrainStorm toolbox to get the connectivity matrix that tells you who is a neighbor. This you can feed into timelockstats.

Hope that helps,

Stephan

________________________________________________________
Stephan Moratti, PhD

see also: http://web.me.com/smoratti/

Universidad Complutense de Madrid
Facultad de Psicología
Departamento de Psicología Básica I
Campus de Somosaguas
28223 Pozuelo de Alarcón (Madrid)
Spain

and

Center for Biomedical Technology
Laboratory for Cognitive and Computational Neuroscience
Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
Campus Montegancedo
28223 Pozuelo de Alarcón (Madrid)
Spain


email: smoratti at psi.ucm.es
Tel.:    +34 679219982

El 12/06/2013, a las 15:44, Nicolai Mersebak escribió:

> Dear all,
> 
> I have a question concerning the usage of ft_sourcegrandaverage and ft_sourcestatistics. 
> 
> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897 time points. 
> 
> Now I would like to use the cluster-based permutation test on my source reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics don't support source level time courses. E.g when I am using ft_sourcegrandaverage I am getting the following error:
> 
> Error in ft_sourcegrandaverage (line 158)
>   dat(:,i) = tmp(:);
> 
> Looking into the code:
> 
>   for i=1:Nsubject
>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter, varargin{i}));
>     dat(:,i) = tmp(:);
>     tmp = getsubfield(varargin{i}, 'inside');
>     inside(tmp,i) = 1;
>   end
> 
> I see that "tmp" are getting the structure [N_sources x timepoints] from source.avg.pow for one subject, where "dat" requires the structure [N_sources x 1]. 
> 
> I seached the mailing list for similar issues and found this thread:
> 
> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
> 
> Since I am interested in using the temporal dimension in my statistics, I would like to know if it is still not possible to use spatio-temporal source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
> 
> Or if any have succeeded in using the cluster-based permutation test on source level also including the temporal dimension ? 
> 
> Alternative I was thinking that I might could use ft_timelockstatistics, where I substituted the channels with sources, e.g instead of having 64 channels, I would now have 4050 "channels". 
> If so I need to calculate a label structure and an appropriate neighbor structure, which I guess is possible as I have all the 3D coordinates for each source, e.g in leadfield.pos ?
> I know this is a work around solution, but have anyone tried or have any experience using such an approach ? 
> 
> Best,
> 
> Nicolai
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From jan.schoffelen at donders.ru.nl  Wed Jun 12 18:00:46 2013
From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen)
Date: Wed, 12 Jun 2013 18:00:46 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
In-Reply-To: <05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
	<05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>
Message-ID: <683ABC6E-9FC6-420A-9DCF-E54D6FC6A27E@donders.ru.nl>

An alternative would be to interpolate the cortical sheet to a 3D grid (where the grid is defined for each subject based on a warped template grid defined in a standard space), and then do clustering using a regular 3D spatial neighbourhood structure. The rationale being that two vertices on the sheet may appear as disconnected  (e.g. being on two sides of a sulcus) whereas, given the poor spatial resolution, they belong to the same spatial blob.

Best,
Jan-Mathijs

On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:

> Dear Nicolai,
> 
> Indeed I have used ft_timelockstatistics for minimum norm source data. The trick is to put the source level data into a ERF structure. Determining the neighbors of a source surface with vertices is not trivial. However I used tess_vertconn.m from the BrainStorm toolbox to get the connectivity matrix that tells you who is a neighbor. This you can feed into timelockstats.
> 
> Hope that helps,
> 
> Stephan
> 
> ________________________________________________________
> Stephan Moratti, PhD
> 
> see also: http://web.me.com/smoratti/
> 
> Universidad Complutense de Madrid
> Facultad de Psicología
> Departamento de Psicología Básica I
> Campus de Somosaguas
> 28223 Pozuelo de Alarcón (Madrid)
> Spain
> 
> and
> 
> Center for Biomedical Technology
> Laboratory for Cognitive and Computational Neuroscience
> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
> Campus Montegancedo
> 28223 Pozuelo de Alarcón (Madrid)
> Spain
> 
> 
> email: smoratti at psi.ucm.es
> Tel.:    +34 679219982
> 
> El 12/06/2013, a las 15:44, Nicolai Mersebak escribió:
> 
>> Dear all,
>> 
>> I have a question concerning the usage of ft_sourcegrandaverage and ft_sourcestatistics. 
>> 
>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897 time points. 
>> 
>> Now I would like to use the cluster-based permutation test on my source reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics don't support source level time courses. E.g when I am using ft_sourcegrandaverage I am getting the following error:
>> 
>> Error in ft_sourcegrandaverage (line 158)
>>   dat(:,i) = tmp(:);
>> 
>> Looking into the code:
>> 
>>   for i=1:Nsubject
>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter, varargin{i}));
>>     dat(:,i) = tmp(:);
>>     tmp = getsubfield(varargin{i}, 'inside');
>>     inside(tmp,i) = 1;
>>   end
>> 
>> I see that "tmp" are getting the structure [N_sources x timepoints] from source.avg.pow for one subject, where "dat" requires the structure [N_sources x 1]. 
>> 
>> I seached the mailing list for similar issues and found this thread:
>> 
>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>> 
>> Since I am interested in using the temporal dimension in my statistics, I would like to know if it is still not possible to use spatio-temporal source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
>> 
>> Or if any have succeeded in using the cluster-based permutation test on source level also including the temporal dimension ? 
>> 
>> Alternative I was thinking that I might could use ft_timelockstatistics, where I substituted the channels with sources, e.g instead of having 64 channels, I would now have 4050 "channels". 
>> If so I need to calculate a label structure and an appropriate neighbor structure, which I guess is possible as I have all the 3D coordinates for each source, e.g in leadfield.pos ?
>> I know this is a work around solution, but have anyone tried or have any experience using such an approach ? 
>> 
>> Best,
>> 
>> Nicolai
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

Jan-Mathijs Schoffelen, MD PhD 

Donders Institute for Brain, Cognition and Behaviour, 
Centre for Cognitive Neuroimaging,
Radboud University Nijmegen, The Netherlands

Max Planck Institute for Psycholinguistics,
Nijmegen, The Netherlands

J.Schoffelen at donders.ru.nl
Telephone: +31-24-3614793

http://www.hettaligebrein.nl

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From smoratti at psi.ucm.es  Wed Jun 12 18:58:40 2013
From: smoratti at psi.ucm.es (smoratti at psi.ucm.es)
Date: Wed, 12 Jun 2013 18:58:40 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
In-Reply-To: <683ABC6E-9FC6-420A-9DCF-E54D6FC6A27E@donders.ru.nl>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
	<05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>
	<683ABC6E-9FC6-420A-9DCF-E54D6FC6A27E@donders.ru.nl>
Message-ID: <8D369E00-7FF3-4CC7-8B91-A55AD9ECE385@psi.ucm.es>


I think Jan.Mathijs alternative suggestion is quite attractive. With the neighbors on a cortical sheet I also had the problems that sometimes the vertices do not have the same distance and then clustering may be biased to smaller or bigger clusters as the number of neighbors does not guarantee same cluster sizes. With the interpolation onto a 3D grid, you won't have that problem.

best,

Stephan


________________________________________________________
Stephan Moratti, PhD

see also: http://web.me.com/smoratti/

Universidad Complutense de Madrid
Facultad de Psicología
Departamento de Psicología Básica I
Campus de Somosaguas
28223 Pozuelo de Alarcón (Madrid)
Spain

and

Center for Biomedical Technology
Laboratory for Cognitive and Computational Neuroscience
Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
Campus Montegancedo
28223 Pozuelo de Alarcón (Madrid)
Spain


email: smoratti at psi.ucm.es
Tel.:    +34 679219982

El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribió:

> An alternative would be to interpolate the cortical sheet to a 3D grid (where the grid is defined for each subject based on a warped template grid defined in a standard space), and then do clustering using a regular 3D spatial neighbourhood structure. The rationale being that two vertices on the sheet may appear as disconnected  (e.g. being on two sides of a sulcus) whereas, given the poor spatial resolution, they belong to the same spatial blob.
> 
> Best,
> Jan-Mathijs
> 
> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
> 
>> Dear Nicolai,
>> 
>> Indeed I have used ft_timelockstatistics for minimum norm source data. The trick is to put the source level data into a ERF structure. Determining the neighbors of a source surface with vertices is not trivial. However I used tess_vertconn.m from the BrainStorm toolbox to get the connectivity matrix that tells you who is a neighbor. This you can feed into timelockstats.
>> 
>> Hope that helps,
>> 
>> Stephan
>> 
>> ________________________________________________________
>> Stephan Moratti, PhD
>> 
>> see also: http://web.me.com/smoratti/
>> 
>> Universidad Complutense de Madrid
>> Facultad de Psicología
>> Departamento de Psicología Básica I
>> Campus de Somosaguas
>> 28223 Pozuelo de Alarcón (Madrid)
>> Spain
>> 
>> and
>> 
>> Center for Biomedical Technology
>> Laboratory for Cognitive and Computational Neuroscience
>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>> Campus Montegancedo
>> 28223 Pozuelo de Alarcón (Madrid)
>> Spain
>> 
>> 
>> email: smoratti at psi.ucm.es
>> Tel.:    +34 679219982
>> 
>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribió:
>> 
>>> Dear all,
>>> 
>>> I have a question concerning the usage of ft_sourcegrandaverage and ft_sourcestatistics. 
>>> 
>>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897 time points. 
>>> 
>>> Now I would like to use the cluster-based permutation test on my source reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics don't support source level time courses. E.g when I am using ft_sourcegrandaverage I am getting the following error:
>>> 
>>> Error in ft_sourcegrandaverage (line 158)
>>>   dat(:,i) = tmp(:);
>>> 
>>> Looking into the code:
>>> 
>>>   for i=1:Nsubject
>>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter, varargin{i}));
>>>     dat(:,i) = tmp(:);
>>>     tmp = getsubfield(varargin{i}, 'inside');
>>>     inside(tmp,i) = 1;
>>>   end
>>> 
>>> I see that "tmp" are getting the structure [N_sources x timepoints] from source.avg.pow for one subject, where "dat" requires the structure [N_sources x 1]. 
>>> 
>>> I seached the mailing list for similar issues and found this thread:
>>> 
>>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>>> 
>>> Since I am interested in using the temporal dimension in my statistics, I would like to know if it is still not possible to use spatio-temporal source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
>>> 
>>> Or if any have succeeded in using the cluster-based permutation test on source level also including the temporal dimension ? 
>>> 
>>> Alternative I was thinking that I might could use ft_timelockstatistics, where I substituted the channels with sources, e.g instead of having 64 channels, I would now have 4050 "channels". 
>>> If so I need to calculate a label structure and an appropriate neighbor structure, which I guess is possible as I have all the 3D coordinates for each source, e.g in leadfield.pos ?
>>> I know this is a work around solution, but have anyone tried or have any experience using such an approach ? 
>>> 
>>> Best,
>>> 
>>> Nicolai
>>> 
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> Jan-Mathijs Schoffelen, MD PhD 
> 
> Donders Institute for Brain, Cognition and Behaviour, 
> Centre for Cognitive Neuroimaging,
> Radboud University Nijmegen, The Netherlands
> 
> Max Planck Institute for Psycholinguistics,
> Nijmegen, The Netherlands
> 
> J.Schoffelen at donders.ru.nl
> Telephone: +31-24-3614793
> 
> http://www.hettaligebrein.nl
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From mengtongxiao at gmail.com  Thu Jun 13 10:10:14 2013
From: mengtongxiao at gmail.com (=?GB2312?B?s8LRqQ==?=)
Date: Thu, 13 Jun 2013 16:10:14 +0800
Subject: [FieldTrip] PDC
Message-ID: <CADiddyUvconnj1o5n+=RYKyDE0LsFsH7_Eg0re0+a5D-2oz9Xw@mail.gmail.com>

Dear  all

I want to use compute  PDC,
I want to  Konw   when I got the chan*chan*freq，
Dose the information flow from row (chan) to column(chan)?

best,
xiao

   
   
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From jan.schoffelen at donders.ru.nl  Thu Jun 13 10:20:48 2013
From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen)
Date: Thu, 13 Jun 2013 10:20:48 +0200
Subject: [FieldTrip] PDC
In-Reply-To: <CADiddyUvconnj1o5n+=RYKyDE0LsFsH7_Eg0re0+a5D-2oz9Xw@mail.gmail.com>
References: <CADiddyUvconnj1o5n+=RYKyDE0LsFsH7_Eg0re0+a5D-2oz9Xw@mail.gmail.com>
Message-ID: <756060F3-17D2-420B-B55F-FFE7671B067B@donders.ru.nl>

Hi Xiao,

this would be from row to column.

Best,
Jan-Mathijs

On Jun 13, 2013, at 10:10 AM, 陈雪 wrote:

> Dear  all
> 
> I want to use compute  PDC,
> I want to  Konw   when I got the chan*chan*freq，
> Dose the information flow from row (chan) to column(chan)?
> 
> best,
> xiao 
> 	
> 	
> 	
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

Jan-Mathijs Schoffelen, MD PhD 

Donders Institute for Brain, Cognition and Behaviour, 
Centre for Cognitive Neuroimaging,
Radboud University Nijmegen, The Netherlands

Max Planck Institute for Psycholinguistics,
Nijmegen, The Netherlands

J.Schoffelen at donders.ru.nl
Telephone: +31-24-3614793

http://www.hettaligebrein.nl

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From explena at gmail.com  Thu Jun 13 11:15:11 2013
From: explena at gmail.com (Shen-Mou Hsu)
Date: Thu, 13 Jun 2013 17:15:11 +0800
Subject: [FieldTrip] ROC_based permutation test
In-Reply-To: <CABPNLUpB9DHCQCszf7WuujVgKT4g9Dp3GPNd19-O65b160y8NQ@mail.gmail.com>
References: <CAFg6g2eKEb-EmYa=BkWTwUVx20+oP92rs6u06w9m+Ehz5ni8qg@mail.gmail.com>
	<CABPNLUpB9DHCQCszf7WuujVgKT4g9Dp3GPNd19-O65b160y8NQ@mail.gmail.com>
Message-ID: <CAFg6g2ewK2N54R0coEbShh1AxUrCkcL6gAgnEskEA5_sAa=h-A@mail.gmail.com>

Dear Eelke,

Many thanks for your helpful and detailed answers. I think that there is an
error in the documentation about the configuration option for performing
ROC analysis. The correct one should be cfg.statistic = 'ft_statfun_roc'.
Otherwise, it will call the matlab built-in ROC function.

Meanwhile, just to clarify my concept about the ROC_based permutation
tests. In the initial stage, does the test calculate whether for every
sample, the area under ROC curve is significant from 0.5. In this sense,
should I specify cfg.clusteralpha = 0.5?

Best regards,

Shen-Mou Hsu


On Tue, Jun 11, 2013 at 4:18 PM, Eelke Spaak <eelke.spaak at donders.ru.nl>wrote:

> Dear Shen-Mou Hsu,
>
> With regards to your first question, I do not know the answer, so
> someone else might help you there.
>
> In response to your second question, regarding the error "could not
> determine the parametric critical value for clustering", this is
> caused by the value of cfg.clusterthreshold used. The default value
> there is 'parametric', meaning that the statistics routine will ask
> your 'statfun' to compute a parametric threshold for considering a
> (time/frequency/channel)-voxel a cluster-member candidate. This can be
> done by e.g. depsamplesT or indepsamplesT, as it is possible to
> analytically compute a T value corresponding to p < 0.05. However, in
> the case of the ROC statistic, no such parametric estimate can be
> computed (or perhaps it can be in some way, I don't know, but at least
> I know the FT implementation does not).
>
> Fortunately, the statistics routines also allow you to use a
> nonparametric threshold for cluster-member candidates, based on the
> generated distribution of the test statistic under the null
> hypothesis. To use this, simply specify cfg.clusterthreshold =
> 'nonparametric_individual' or cfg.clusterthreshold =
> 'nonparametric_common'. The difference between the two is that the
> former computes a threshold per voxel, and the latter uses the same
> threshold for all voxels. Which one is appropriate for you I don't
> know. (Good reasons for using 'nonparametric_individual' might be a
> strong variation of your test statistic with frequency. I know for a
> fact this is the case with certain quantifications of phase-amplitude
> coupling; these show much higher values in the low frequencies even
> when computed on noise.)
>
> Hope this helps.
>
> Best,
> Eelke
>
> On 11 June 2013 09:48, Shen-Mou Hsu <explena at gmail.com> wrote:
> > Dear all,
> >
> > I was trying to perform signle-trial ROC-based permutation tests using
> the
> > statfun_roc. However I encountered two questions and wondered if anyone
> > could kindly shed some light on the issues. First, is it necessary to
> > perform baseline normalization for each trial before the tests? Second,
> an
> > error message returned stating "Error using roc. Too many input
> arguments.
> > Error using ft_statistics_montecarlo (line 223) could not determine the
> > parametric critical value for clustering", after running the following
> > script:
> >
> > load (['t_RF_EpoRejDePow']); load (['t_RN_EpoRejDePow']);
> >
> > cfg = [];
> > cfg.channel     = 'MEG';
> > cfg.latency     = [-0.35 0.55];
> > cfg.frequency   = [8 12];
> > cfg.parameter   = 'powspctrm';
> > cfg.method      = 'montecarlo';
> > cfg.statistic   = 'roc';
> > cfg.alpha       = 0.025;
> > cfg.tail = 0;
> > cfg.correctm    = 'cluster';
> > cfg.clusteralpha = 0.05;
> > % cfg.correcttail = 'prob';
> > cfg.clustertail = 0;
> > cfg.numrandomization = 1000;
> > cfg.minnbchan        = 2;
> > cfg_neighb.method    = 'distance';
> > cfg.neighbours       = ft_prepare_neighbours(cfg_neighb,
> t_RN_EpoRejDePow);
> > cfg.logtransform = 'yes';
> >
> > design = [1*ones(1,size(t_RF_EpoRejDePow.powspctrm,1))
> > 2*ones(1,size(t_RN_EpoRejDePow.powspctrm,1))]; % the first dimension of
> > these variable is the trial number.
> > cfg.design  = design;
> >
> > P_ROC_t_RFvsRN =
> ft_freqstatistics(cfg,t_RF_EpoRejDePow,t_RN_EpoRejDePow);
> >
> >
> > Any help is greatly appreciated.
> >
> > Best regards,
> >
> > Shen-Mou Hsu
> >
> >
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From nicolai at mersebak.dk  Thu Jun 13 12:04:34 2013
From: nicolai at mersebak.dk (Nicolai Mersebak)
Date: Thu, 13 Jun 2013 12:04:34 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
In-Reply-To: <8D369E00-7FF3-4CC7-8B91-A55AD9ECE385@psi.ucm.es>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
	<05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>
	<683ABC6E-9FC6-420A-9DCF-E54D6FC6A27E@donders.ru.nl>
	<8D369E00-7FF3-4CC7-8B91-A55AD9ECE385@psi.ucm.es>
Message-ID: <6F3697BB-194F-422F-A1BF-EBBB132F805B@mersebak.dk>

Thanks to all of you for your comments and ideas - they are very helpful! 

I ( off course :) ) have some follow up questions. 

I have created an ERP structure for my MNE source, so the only think which I need and that is not straight forward is the neighbour structure. 

I am using the standard bem template (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model and use the following code to get a grid for all subjects as I don't have any subject specific information regarding the anatomy. 

cfg = [];
cfg.grid.xgrid  = -100:10:100;
cfg.grid.ygrid  = -100:10:100;
cfg.grid.zgrid  = -100:10:100;
cfg.grid.tight  = 'yes';
cfg.grid.unit   = hdm.unit; % unit: mm
cfg.vol        = hdm;
grid  = ft_prepare_sourcemodel(cfg);


@Jan-Mathijs and Stephan: I guess making a subject specific grid based on a warped template requires anatomic information for each subject, e.g. a MRI image like this tutorial shows:
http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B

The final grid output in the tutorial - does it have this 3D grid which can be used as a neighbour structure ? 

I am not sure how to go from my cortical sheet [vertices x coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
 
A second thing I would like to know is, if any of you have tried to use an atlas (e.g ALL template atlas) where the regions now are channels in the permutation test? Going from source points to atlas regions can be done through ft_sourcestatistics, but I am still interested in keeping the temporal dimension. The reason to use atlas regions instead of source points is to decrease the computation time. 

Best,

Nicolai


Den 12/06/2013 kl. 18.58 skrev "smoratti at psi.ucm.es" <smoratti at psi.ucm.es>:

> 
> I think Jan.Mathijs alternative suggestion is quite attractive. With the neighbors on a cortical sheet I also had the problems that sometimes the vertices do not have the same distance and then clustering may be biased to smaller or bigger clusters as the number of neighbors does not guarantee same cluster sizes. With the interpolation onto a 3D grid, you won't have that problem.
> 
> best,
> 
> Stephan
> 
> 
> ________________________________________________________
> Stephan Moratti, PhD
> 
> see also: http://web.me.com/smoratti/
> 
> Universidad Complutense de Madrid
> Facultad de Psicología
> Departamento de Psicología Básica I
> Campus de Somosaguas
> 28223 Pozuelo de Alarcón (Madrid)
> Spain
> 
> and
> 
> Center for Biomedical Technology
> Laboratory for Cognitive and Computational Neuroscience
> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
> Campus Montegancedo
> 28223 Pozuelo de Alarcón (Madrid)
> Spain
> 
> 
> email: smoratti at psi.ucm.es
> Tel.:    +34 679219982
> 
> El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribió:
> 
>> An alternative would be to interpolate the cortical sheet to a 3D grid (where the grid is defined for each subject based on a warped template grid defined in a standard space), and then do clustering using a regular 3D spatial neighbourhood structure. The rationale being that two vertices on the sheet may appear as disconnected  (e.g. being on two sides of a sulcus) whereas, given the poor spatial resolution, they belong to the same spatial blob.
>> 
>> Best,
>> Jan-Mathijs
>> 
>> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
>> 
>>> Dear Nicolai,
>>> 
>>> Indeed I have used ft_timelockstatistics for minimum norm source data. The trick is to put the source level data into a ERF structure. Determining the neighbors of a source surface with vertices is not trivial. However I used tess_vertconn.m from the BrainStorm toolbox to get the connectivity matrix that tells you who is a neighbor. This you can feed into timelockstats.
>>> 
>>> Hope that helps,
>>> 
>>> Stephan
>>> 
>>> ________________________________________________________
>>> Stephan Moratti, PhD
>>> 
>>> see also: http://web.me.com/smoratti/
>>> 
>>> Universidad Complutense de Madrid
>>> Facultad de Psicología
>>> Departamento de Psicología Básica I
>>> Campus de Somosaguas
>>> 28223 Pozuelo de Alarcón (Madrid)
>>> Spain
>>> 
>>> and
>>> 
>>> Center for Biomedical Technology
>>> Laboratory for Cognitive and Computational Neuroscience
>>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>>> Campus Montegancedo
>>> 28223 Pozuelo de Alarcón (Madrid)
>>> Spain
>>> 
>>> 
>>> email: smoratti at psi.ucm.es
>>> Tel.:    +34 679219982
>>> 
>>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribió:
>>> 
>>>> Dear all,
>>>> 
>>>> I have a question concerning the usage of ft_sourcegrandaverage and ft_sourcestatistics. 
>>>> 
>>>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897 time points. 
>>>> 
>>>> Now I would like to use the cluster-based permutation test on my source reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics don't support source level time courses. E.g when I am using ft_sourcegrandaverage I am getting the following error:
>>>> 
>>>> Error in ft_sourcegrandaverage (line 158)
>>>>   dat(:,i) = tmp(:);
>>>> 
>>>> Looking into the code:
>>>> 
>>>>   for i=1:Nsubject
>>>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter, varargin{i}));
>>>>     dat(:,i) = tmp(:);
>>>>     tmp = getsubfield(varargin{i}, 'inside');
>>>>     inside(tmp,i) = 1;
>>>>   end
>>>> 
>>>> I see that "tmp" are getting the structure [N_sources x timepoints] from source.avg.pow for one subject, where "dat" requires the structure [N_sources x 1]. 
>>>> 
>>>> I seached the mailing list for similar issues and found this thread:
>>>> 
>>>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>>>> 
>>>> Since I am interested in using the temporal dimension in my statistics, I would like to know if it is still not possible to use spatio-temporal source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
>>>> 
>>>> Or if any have succeeded in using the cluster-based permutation test on source level also including the temporal dimension ? 
>>>> 
>>>> Alternative I was thinking that I might could use ft_timelockstatistics, where I substituted the channels with sources, e.g instead of having 64 channels, I would now have 4050 "channels". 
>>>> If so I need to calculate a label structure and an appropriate neighbor structure, which I guess is possible as I have all the 3D coordinates for each source, e.g in leadfield.pos ?
>>>> I know this is a work around solution, but have anyone tried or have any experience using such an approach ? 
>>>> 
>>>> Best,
>>>> 
>>>> Nicolai
>>>> 
>>>> _______________________________________________
>>>> fieldtrip mailing list
>>>> fieldtrip at donders.ru.nl
>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>> 
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> 
>> Jan-Mathijs Schoffelen, MD PhD 
>> 
>> Donders Institute for Brain, Cognition and Behaviour, 
>> Centre for Cognitive Neuroimaging,
>> Radboud University Nijmegen, The Netherlands
>> 
>> Max Planck Institute for Psycholinguistics,
>> Nijmegen, The Netherlands
>> 
>> J.Schoffelen at donders.ru.nl
>> Telephone: +31-24-3614793
>> 
>> http://www.hettaligebrein.nl
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From smoratti at psi.ucm.es  Thu Jun 13 15:50:30 2013
From: smoratti at psi.ucm.es (smoratti at psi.ucm.es)
Date: Thu, 13 Jun 2013 15:50:30 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
In-Reply-To: <6F3697BB-194F-422F-A1BF-EBBB132F805B@mersebak.dk>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
	<05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>
	<683ABC6E-9FC6-420A-9DCF-E54D6FC6A27E@donders.ru.nl>
	<8D369E00-7FF3-4CC7-8B91-A55AD9ECE385@psi.ucm.es>
	<6F3697BB-194F-422F-A1BF-EBBB132F805B@mersebak.dk>
Message-ID: <4755A6E7-44B5-4E98-B536-A19F544ED284@psi.ucm.es>

Dear Nikolai,

In ft_sourceplot there is the possibility of projecting grid data to surface data. However, I am not sure if the other way round is implemented in field trip.

With respect to the other (maybe less accurate solution) of providing a neighbor matrix of the vertices of your brain surface:

if you do " channeigbststructmat = your_neighbor_matrix" in clusterstat.m should work.

Best,

Stephan



________________________________________________________
Stephan Moratti, PhD

see also: http://web.me.com/smoratti/

Universidad Complutense de Madrid
Facultad de Psicología
Departamento de Psicología Básica I
Campus de Somosaguas
28223 Pozuelo de Alarcón (Madrid)
Spain

and

Center for Biomedical Technology
Laboratory for Cognitive and Computational Neuroscience
Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
Campus Montegancedo
28223 Pozuelo de Alarcón (Madrid)
Spain


email: smoratti at psi.ucm.es
Tel.:    +34 679219982

El 13/06/2013, a las 12:04, Nicolai Mersebak escribió:

> Thanks to all of you for your comments and ideas - they are very helpful! 
> 
> I ( off course :) ) have some follow up questions. 
> 
> I have created an ERP structure for my MNE source, so the only think which I need and that is not straight forward is the neighbour structure. 
> 
> I am using the standard bem template (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model and use the following code to get a grid for all subjects as I don't have any subject specific information regarding the anatomy. 
> 
> cfg = [];
> cfg.grid.xgrid  = -100:10:100;
> cfg.grid.ygrid  = -100:10:100;
> cfg.grid.zgrid  = -100:10:100;
> cfg.grid.tight  = 'yes';
> cfg.grid.unit   = hdm.unit; % unit: mm
> cfg.vol        = hdm;
> grid  = ft_prepare_sourcemodel(cfg);
> 
> 
> @Jan-Mathijs and Stephan: I guess making a subject specific grid based on a warped template requires anatomic information for each subject, e.g. a MRI image like this tutorial shows:
> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
> 
> The final grid output in the tutorial - does it have this 3D grid which can be used as a neighbour structure ? 
> 
> I am not sure how to go from my cortical sheet [vertices x coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
>  
> A second thing I would like to know is, if any of you have tried to use an atlas (e.g ALL template atlas) where the regions now are channels in the permutation test? Going from source points to atlas regions can be done through ft_sourcestatistics, but I am still interested in keeping the temporal dimension. The reason to use atlas regions instead of source points is to decrease the computation time. 
> 
> Best,
> 
> Nicolai
> 
> 
> Den 12/06/2013 kl. 18.58 skrev "smoratti at psi.ucm.es" <smoratti at psi.ucm.es>:
> 
>> 
>> I think Jan.Mathijs alternative suggestion is quite attractive. With the neighbors on a cortical sheet I also had the problems that sometimes the vertices do not have the same distance and then clustering may be biased to smaller or bigger clusters as the number of neighbors does not guarantee same cluster sizes. With the interpolation onto a 3D grid, you won't have that problem.
>> 
>> best,
>> 
>> Stephan
>> 
>> 
>> ________________________________________________________
>> Stephan Moratti, PhD
>> 
>> see also: http://web.me.com/smoratti/
>> 
>> Universidad Complutense de Madrid
>> Facultad de Psicología
>> Departamento de Psicología Básica I
>> Campus de Somosaguas
>> 28223 Pozuelo de Alarcón (Madrid)
>> Spain
>> 
>> and
>> 
>> Center for Biomedical Technology
>> Laboratory for Cognitive and Computational Neuroscience
>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>> Campus Montegancedo
>> 28223 Pozuelo de Alarcón (Madrid)
>> Spain
>> 
>> 
>> email: smoratti at psi.ucm.es
>> Tel.:    +34 679219982
>> 
>> El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribió:
>> 
>>> An alternative would be to interpolate the cortical sheet to a 3D grid (where the grid is defined for each subject based on a warped template grid defined in a standard space), and then do clustering using a regular 3D spatial neighbourhood structure. The rationale being that two vertices on the sheet may appear as disconnected  (e.g. being on two sides of a sulcus) whereas, given the poor spatial resolution, they belong to the same spatial blob.
>>> 
>>> Best,
>>> Jan-Mathijs
>>> 
>>> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
>>> 
>>>> Dear Nicolai,
>>>> 
>>>> Indeed I have used ft_timelockstatistics for minimum norm source data. The trick is to put the source level data into a ERF structure. Determining the neighbors of a source surface with vertices is not trivial. However I used tess_vertconn.m from the BrainStorm toolbox to get the connectivity matrix that tells you who is a neighbor. This you can feed into timelockstats.
>>>> 
>>>> Hope that helps,
>>>> 
>>>> Stephan
>>>> 
>>>> ________________________________________________________
>>>> Stephan Moratti, PhD
>>>> 
>>>> see also: http://web.me.com/smoratti/
>>>> 
>>>> Universidad Complutense de Madrid
>>>> Facultad de Psicología
>>>> Departamento de Psicología Básica I
>>>> Campus de Somosaguas
>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>> Spain
>>>> 
>>>> and
>>>> 
>>>> Center for Biomedical Technology
>>>> Laboratory for Cognitive and Computational Neuroscience
>>>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>>>> Campus Montegancedo
>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>> Spain
>>>> 
>>>> 
>>>> email: smoratti at psi.ucm.es
>>>> Tel.:    +34 679219982
>>>> 
>>>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribió:
>>>> 
>>>>> Dear all,
>>>>> 
>>>>> I have a question concerning the usage of ft_sourcegrandaverage and ft_sourcestatistics. 
>>>>> 
>>>>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897 time points. 
>>>>> 
>>>>> Now I would like to use the cluster-based permutation test on my source reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics don't support source level time courses. E.g when I am using ft_sourcegrandaverage I am getting the following error:
>>>>> 
>>>>> Error in ft_sourcegrandaverage (line 158)
>>>>>   dat(:,i) = tmp(:);
>>>>> 
>>>>> Looking into the code:
>>>>> 
>>>>>   for i=1:Nsubject
>>>>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter, varargin{i}));
>>>>>     dat(:,i) = tmp(:);
>>>>>     tmp = getsubfield(varargin{i}, 'inside');
>>>>>     inside(tmp,i) = 1;
>>>>>   end
>>>>> 
>>>>> I see that "tmp" are getting the structure [N_sources x timepoints] from source.avg.pow for one subject, where "dat" requires the structure [N_sources x 1]. 
>>>>> 
>>>>> I seached the mailing list for similar issues and found this thread:
>>>>> 
>>>>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>>>>> 
>>>>> Since I am interested in using the temporal dimension in my statistics, I would like to know if it is still not possible to use spatio-temporal source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
>>>>> 
>>>>> Or if any have succeeded in using the cluster-based permutation test on source level also including the temporal dimension ? 
>>>>> 
>>>>> Alternative I was thinking that I might could use ft_timelockstatistics, where I substituted the channels with sources, e.g instead of having 64 channels, I would now have 4050 "channels". 
>>>>> If so I need to calculate a label structure and an appropriate neighbor structure, which I guess is possible as I have all the 3D coordinates for each source, e.g in leadfield.pos ?
>>>>> I know this is a work around solution, but have anyone tried or have any experience using such an approach ? 
>>>>> 
>>>>> Best,
>>>>> 
>>>>> Nicolai
>>>>> 
>>>>> _______________________________________________
>>>>> fieldtrip mailing list
>>>>> fieldtrip at donders.ru.nl
>>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>> 
>>>> _______________________________________________
>>>> fieldtrip mailing list
>>>> fieldtrip at donders.ru.nl
>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>> 
>>> Jan-Mathijs Schoffelen, MD PhD 
>>> 
>>> Donders Institute for Brain, Cognition and Behaviour, 
>>> Centre for Cognitive Neuroimaging,
>>> Radboud University Nijmegen, The Netherlands
>>> 
>>> Max Planck Institute for Psycholinguistics,
>>> Nijmegen, The Netherlands
>>> 
>>> J.Schoffelen at donders.ru.nl
>>> Telephone: +31-24-3614793
>>> 
>>> http://www.hettaligebrein.nl
>>> 
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From jan.schoffelen at donders.ru.nl  Thu Jun 13 15:58:47 2013
From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen)
Date: Thu, 13 Jun 2013 15:58:47 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
In-Reply-To: <4755A6E7-44B5-4E98-B536-A19F544ED284@psi.ucm.es>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
	<05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>
	<683ABC6E-9FC6-420A-9DCF-E54D6FC6A27E@donders.ru.nl>
	<8D369E00-7FF3-4CC7-8B91-A55AD9ECE385@psi.ucm.es>
	<6F3697BB-194F-422F-A1BF-EBBB132F805B@mersebak.dk>
	<4755A6E7-44B5-4E98-B536-A19F544ED284@psi.ucm.es>
Message-ID: <944F6EF6-C03A-46F4-BFF4-3D9EC324E602@donders.ru.nl>

Hi all,

ft_sourceinterpolate can interpolate from between arbitrary point clouds, so also between a set of points defined on the cortical sheet, and a more or less regular 3D grid.

JM

On Jun 13, 2013, at 3:50 PM, smoratti at psi.ucm.es wrote:

> Dear Nikolai,
> 
> In ft_sourceplot there is the possibility of projecting grid data to surface data. However, I am not sure if the other way round is implemented in field trip.
> 
> With respect to the other (maybe less accurate solution) of providing a neighbor matrix of the vertices of your brain surface:
> 
> if you do " channeigbststructmat = your_neighbor_matrix" in clusterstat.m should work.
> 
> Best,
> 
> Stephan
> 
> 
> 
> ________________________________________________________
> Stephan Moratti, PhD
> 
> see also: http://web.me.com/smoratti/
> 
> Universidad Complutense de Madrid
> Facultad de Psicología
> Departamento de Psicología Básica I
> Campus de Somosaguas
> 28223 Pozuelo de Alarcón (Madrid)
> Spain
> 
> and
> 
> Center for Biomedical Technology
> Laboratory for Cognitive and Computational Neuroscience
> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
> Campus Montegancedo
> 28223 Pozuelo de Alarcón (Madrid)
> Spain
> 
> 
> email: smoratti at psi.ucm.es
> Tel.:    +34 679219982
> 
> El 13/06/2013, a las 12:04, Nicolai Mersebak escribió:
> 
>> Thanks to all of you for your comments and ideas - they are very helpful! 
>> 
>> I ( off course :) ) have some follow up questions. 
>> 
>> I have created an ERP structure for my MNE source, so the only think which I need and that is not straight forward is the neighbour structure. 
>> 
>> I am using the standard bem template (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model and use the following code to get a grid for all subjects as I don't have any subject specific information regarding the anatomy. 
>> 
>> cfg = [];
>> cfg.grid.xgrid  = -100:10:100;
>> cfg.grid.ygrid  = -100:10:100;
>> cfg.grid.zgrid  = -100:10:100;
>> cfg.grid.tight  = 'yes';
>> cfg.grid.unit   = hdm.unit; % unit: mm
>> cfg.vol        = hdm;
>> grid  = ft_prepare_sourcemodel(cfg);
>> 
>> 
>> @Jan-Mathijs and Stephan: I guess making a subject specific grid based on a warped template requires anatomic information for each subject, e.g. a MRI image like this tutorial shows:
>> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
>> 
>> The final grid output in the tutorial - does it have this 3D grid which can be used as a neighbour structure ? 
>> 
>> I am not sure how to go from my cortical sheet [vertices x coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
>>  
>> A second thing I would like to know is, if any of you have tried to use an atlas (e.g ALL template atlas) where the regions now are channels in the permutation test? Going from source points to atlas regions can be done through ft_sourcestatistics, but I am still interested in keeping the temporal dimension. The reason to use atlas regions instead of source points is to decrease the computation time. 
>> 
>> Best,
>> 
>> Nicolai
>> 
>> 
>> Den 12/06/2013 kl. 18.58 skrev "smoratti at psi.ucm.es" <smoratti at psi.ucm.es>:
>> 
>>> 
>>> I think Jan.Mathijs alternative suggestion is quite attractive. With the neighbors on a cortical sheet I also had the problems that sometimes the vertices do not have the same distance and then clustering may be biased to smaller or bigger clusters as the number of neighbors does not guarantee same cluster sizes. With the interpolation onto a 3D grid, you won't have that problem.
>>> 
>>> best,
>>> 
>>> Stephan
>>> 
>>> 
>>> ________________________________________________________
>>> Stephan Moratti, PhD
>>> 
>>> see also: http://web.me.com/smoratti/
>>> 
>>> Universidad Complutense de Madrid
>>> Facultad de Psicología
>>> Departamento de Psicología Básica I
>>> Campus de Somosaguas
>>> 28223 Pozuelo de Alarcón (Madrid)
>>> Spain
>>> 
>>> and
>>> 
>>> Center for Biomedical Technology
>>> Laboratory for Cognitive and Computational Neuroscience
>>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>>> Campus Montegancedo
>>> 28223 Pozuelo de Alarcón (Madrid)
>>> Spain
>>> 
>>> 
>>> email: smoratti at psi.ucm.es
>>> Tel.:    +34 679219982
>>> 
>>> El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribió:
>>> 
>>>> An alternative would be to interpolate the cortical sheet to a 3D grid (where the grid is defined for each subject based on a warped template grid defined in a standard space), and then do clustering using a regular 3D spatial neighbourhood structure. The rationale being that two vertices on the sheet may appear as disconnected  (e.g. being on two sides of a sulcus) whereas, given the poor spatial resolution, they belong to the same spatial blob.
>>>> 
>>>> Best,
>>>> Jan-Mathijs
>>>> 
>>>> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
>>>> 
>>>>> Dear Nicolai,
>>>>> 
>>>>> Indeed I have used ft_timelockstatistics for minimum norm source data. The trick is to put the source level data into a ERF structure. Determining the neighbors of a source surface with vertices is not trivial. However I used tess_vertconn.m from the BrainStorm toolbox to get the connectivity matrix that tells you who is a neighbor. This you can feed into timelockstats.
>>>>> 
>>>>> Hope that helps,
>>>>> 
>>>>> Stephan
>>>>> 
>>>>> ________________________________________________________
>>>>> Stephan Moratti, PhD
>>>>> 
>>>>> see also: http://web.me.com/smoratti/
>>>>> 
>>>>> Universidad Complutense de Madrid
>>>>> Facultad de Psicología
>>>>> Departamento de Psicología Básica I
>>>>> Campus de Somosaguas
>>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>>> Spain
>>>>> 
>>>>> and
>>>>> 
>>>>> Center for Biomedical Technology
>>>>> Laboratory for Cognitive and Computational Neuroscience
>>>>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>>>>> Campus Montegancedo
>>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>>> Spain
>>>>> 
>>>>> 
>>>>> email: smoratti at psi.ucm.es
>>>>> Tel.:    +34 679219982
>>>>> 
>>>>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribió:
>>>>> 
>>>>>> Dear all,
>>>>>> 
>>>>>> I have a question concerning the usage of ft_sourcegrandaverage and ft_sourcestatistics. 
>>>>>> 
>>>>>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897 time points. 
>>>>>> 
>>>>>> Now I would like to use the cluster-based permutation test on my source reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics don't support source level time courses. E.g when I am using ft_sourcegrandaverage I am getting the following error:
>>>>>> 
>>>>>> Error in ft_sourcegrandaverage (line 158)
>>>>>>   dat(:,i) = tmp(:);
>>>>>> 
>>>>>> Looking into the code:
>>>>>> 
>>>>>>   for i=1:Nsubject
>>>>>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter, varargin{i}));
>>>>>>     dat(:,i) = tmp(:);
>>>>>>     tmp = getsubfield(varargin{i}, 'inside');
>>>>>>     inside(tmp,i) = 1;
>>>>>>   end
>>>>>> 
>>>>>> I see that "tmp" are getting the structure [N_sources x timepoints] from source.avg.pow for one subject, where "dat" requires the structure [N_sources x 1]. 
>>>>>> 
>>>>>> I seached the mailing list for similar issues and found this thread:
>>>>>> 
>>>>>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>>>>>> 
>>>>>> Since I am interested in using the temporal dimension in my statistics, I would like to know if it is still not possible to use spatio-temporal source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
>>>>>> 
>>>>>> Or if any have succeeded in using the cluster-based permutation test on source level also including the temporal dimension ? 
>>>>>> 
>>>>>> Alternative I was thinking that I might could use ft_timelockstatistics, where I substituted the channels with sources, e.g instead of having 64 channels, I would now have 4050 "channels". 
>>>>>> If so I need to calculate a label structure and an appropriate neighbor structure, which I guess is possible as I have all the 3D coordinates for each source, e.g in leadfield.pos ?
>>>>>> I know this is a work around solution, but have anyone tried or have any experience using such an approach ? 
>>>>>> 
>>>>>> Best,
>>>>>> 
>>>>>> Nicolai
>>>>>> 
>>>>>> _______________________________________________
>>>>>> fieldtrip mailing list
>>>>>> fieldtrip at donders.ru.nl
>>>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>> 
>>>>> _______________________________________________
>>>>> fieldtrip mailing list
>>>>> fieldtrip at donders.ru.nl
>>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>> 
>>>> Jan-Mathijs Schoffelen, MD PhD 
>>>> 
>>>> Donders Institute for Brain, Cognition and Behaviour, 
>>>> Centre for Cognitive Neuroimaging,
>>>> Radboud University Nijmegen, The Netherlands
>>>> 
>>>> Max Planck Institute for Psycholinguistics,
>>>> Nijmegen, The Netherlands
>>>> 
>>>> J.Schoffelen at donders.ru.nl
>>>> Telephone: +31-24-3614793
>>>> 
>>>> http://www.hettaligebrein.nl
>>>> 
>>>> _______________________________________________
>>>> fieldtrip mailing list
>>>> fieldtrip at donders.ru.nl
>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>> 
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

Jan-Mathijs Schoffelen, MD PhD 

Donders Institute for Brain, Cognition and Behaviour, 
Centre for Cognitive Neuroimaging,
Radboud University Nijmegen, The Netherlands

Max Planck Institute for Psycholinguistics,
Nijmegen, The Netherlands

J.Schoffelen at donders.ru.nl
Telephone: +31-24-3614793

http://www.hettaligebrein.nl

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From jan.schoffelen at donders.ru.nl  Thu Jun 13 16:12:26 2013
From: jan.schoffelen at donders.ru.nl (jan-mathijs schoffelen)
Date: Thu, 13 Jun 2013 16:12:26 +0200
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
In-Reply-To: <944F6EF6-C03A-46F4-BFF4-3D9EC324E602@donders.ru.nl>
References: <CAP1F31k24w0cEo=-04VKX+0dxrcyg5PxCBSdG-ug4r_a-nsYAg@mail.gmail.com>
	<05B1DB8A-163B-40C0-B303-5B7D2A5434BD@psi.ucm.es>
	<683ABC6E-9FC6-420A-9DCF-E54D6FC6A27E@donders.ru.nl>
	<8D369E00-7FF3-4CC7-8B91-A55AD9ECE385@psi.ucm.es>
	<6F3697BB-194F-422F-A1BF-EBBB132F805B@mersebak.dk>
	<4755A6E7-44B5-4E98-B536-A19F544ED284@psi.ucm.es>
	<944F6EF6-C03A-46F4-BFF4-3D9EC324E602@donders.ru.nl>
Message-ID: <C58208AA-1DC3-40CD-9E55-F1B3ADD3CCD4@donders.ru.nl>

Hi all,

As a follow up to my previous message: it is intended in the future to remove the functionality in ft_sourceplot, doing the interpolation on the fly when cfg.method='surface' but when the input contains data defined on a 3D grid, and to request the user to go through ft_sourceinterpolate before visualization. Stay tuned...

JM

On Jun 13, 2013, at 3:58 PM, jan-mathijs schoffelen wrote:

> Hi all,
> 
> ft_sourceinterpolate can interpolate from between arbitrary point clouds, so also between a set of points defined on the cortical sheet, and a more or less regular 3D grid.
> 
> JM
> 
> On Jun 13, 2013, at 3:50 PM, smoratti at psi.ucm.es wrote:
> 
>> Dear Nikolai,
>> 
>> In ft_sourceplot there is the possibility of projecting grid data to surface data. However, I am not sure if the other way round is implemented in field trip.
>> 
>> With respect to the other (maybe less accurate solution) of providing a neighbor matrix of the vertices of your brain surface:
>> 
>> if you do " channeigbststructmat = your_neighbor_matrix" in clusterstat.m should work.
>> 
>> Best,
>> 
>> Stephan
>> 
>> 
>> 
>> ________________________________________________________
>> Stephan Moratti, PhD
>> 
>> see also: http://web.me.com/smoratti/
>> 
>> Universidad Complutense de Madrid
>> Facultad de Psicología
>> Departamento de Psicología Básica I
>> Campus de Somosaguas
>> 28223 Pozuelo de Alarcón (Madrid)
>> Spain
>> 
>> and
>> 
>> Center for Biomedical Technology
>> Laboratory for Cognitive and Computational Neuroscience
>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>> Campus Montegancedo
>> 28223 Pozuelo de Alarcón (Madrid)
>> Spain
>> 
>> 
>> email: smoratti at psi.ucm.es
>> Tel.:    +34 679219982
>> 
>> El 13/06/2013, a las 12:04, Nicolai Mersebak escribió:
>> 
>>> Thanks to all of you for your comments and ideas - they are very helpful! 
>>> 
>>> I ( off course :) ) have some follow up questions. 
>>> 
>>> I have created an ERP structure for my MNE source, so the only think which I need and that is not straight forward is the neighbour structure. 
>>> 
>>> I am using the standard bem template (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model and use the following code to get a grid for all subjects as I don't have any subject specific information regarding the anatomy. 
>>> 
>>> cfg = [];
>>> cfg.grid.xgrid  = -100:10:100;
>>> cfg.grid.ygrid  = -100:10:100;
>>> cfg.grid.zgrid  = -100:10:100;
>>> cfg.grid.tight  = 'yes';
>>> cfg.grid.unit   = hdm.unit; % unit: mm
>>> cfg.vol        = hdm;
>>> grid  = ft_prepare_sourcemodel(cfg);
>>> 
>>> 
>>> @Jan-Mathijs and Stephan: I guess making a subject specific grid based on a warped template requires anatomic information for each subject, e.g. a MRI image like this tutorial shows:
>>> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
>>> 
>>> The final grid output in the tutorial - does it have this 3D grid which can be used as a neighbour structure ? 
>>> 
>>> I am not sure how to go from my cortical sheet [vertices x coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
>>>  
>>> A second thing I would like to know is, if any of you have tried to use an atlas (e.g ALL template atlas) where the regions now are channels in the permutation test? Going from source points to atlas regions can be done through ft_sourcestatistics, but I am still interested in keeping the temporal dimension. The reason to use atlas regions instead of source points is to decrease the computation time. 
>>> 
>>> Best,
>>> 
>>> Nicolai
>>> 
>>> 
>>> Den 12/06/2013 kl. 18.58 skrev "smoratti at psi.ucm.es" <smoratti at psi.ucm.es>:
>>> 
>>>> 
>>>> I think Jan.Mathijs alternative suggestion is quite attractive. With the neighbors on a cortical sheet I also had the problems that sometimes the vertices do not have the same distance and then clustering may be biased to smaller or bigger clusters as the number of neighbors does not guarantee same cluster sizes. With the interpolation onto a 3D grid, you won't have that problem.
>>>> 
>>>> best,
>>>> 
>>>> Stephan
>>>> 
>>>> 
>>>> ________________________________________________________
>>>> Stephan Moratti, PhD
>>>> 
>>>> see also: http://web.me.com/smoratti/
>>>> 
>>>> Universidad Complutense de Madrid
>>>> Facultad de Psicología
>>>> Departamento de Psicología Básica I
>>>> Campus de Somosaguas
>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>> Spain
>>>> 
>>>> and
>>>> 
>>>> Center for Biomedical Technology
>>>> Laboratory for Cognitive and Computational Neuroscience
>>>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>>>> Campus Montegancedo
>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>> Spain
>>>> 
>>>> 
>>>> email: smoratti at psi.ucm.es
>>>> Tel.:    +34 679219982
>>>> 
>>>> El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribió:
>>>> 
>>>>> An alternative would be to interpolate the cortical sheet to a 3D grid (where the grid is defined for each subject based on a warped template grid defined in a standard space), and then do clustering using a regular 3D spatial neighbourhood structure. The rationale being that two vertices on the sheet may appear as disconnected  (e.g. being on two sides of a sulcus) whereas, given the poor spatial resolution, they belong to the same spatial blob.
>>>>> 
>>>>> Best,
>>>>> Jan-Mathijs
>>>>> 
>>>>> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
>>>>> 
>>>>>> Dear Nicolai,
>>>>>> 
>>>>>> Indeed I have used ft_timelockstatistics for minimum norm source data. The trick is to put the source level data into a ERF structure. Determining the neighbors of a source surface with vertices is not trivial. However I used tess_vertconn.m from the BrainStorm toolbox to get the connectivity matrix that tells you who is a neighbor. This you can feed into timelockstats.
>>>>>> 
>>>>>> Hope that helps,
>>>>>> 
>>>>>> Stephan
>>>>>> 
>>>>>> ________________________________________________________
>>>>>> Stephan Moratti, PhD
>>>>>> 
>>>>>> see also: http://web.me.com/smoratti/
>>>>>> 
>>>>>> Universidad Complutense de Madrid
>>>>>> Facultad de Psicología
>>>>>> Departamento de Psicología Básica I
>>>>>> Campus de Somosaguas
>>>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>>>> Spain
>>>>>> 
>>>>>> and
>>>>>> 
>>>>>> Center for Biomedical Technology
>>>>>> Laboratory for Cognitive and Computational Neuroscience
>>>>>> Parque Científico y Tecnológico de la Universidad Politecnica de Madrid
>>>>>> Campus Montegancedo
>>>>>> 28223 Pozuelo de Alarcón (Madrid)
>>>>>> Spain
>>>>>> 
>>>>>> 
>>>>>> email: smoratti at psi.ucm.es
>>>>>> Tel.:    +34 679219982
>>>>>> 
>>>>>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribió:
>>>>>> 
>>>>>>> Dear all,
>>>>>>> 
>>>>>>> I have a question concerning the usage of ft_sourcegrandaverage and ft_sourcestatistics. 
>>>>>>> 
>>>>>>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and 897 time points. 
>>>>>>> 
>>>>>>> Now I would like to use the cluster-based permutation test on my source reconstructed data. However it seems like ft_sourcegrandaverage and ft_sourcestatistics don't support source level time courses. E.g when I am using ft_sourcegrandaverage I am getting the following error:
>>>>>>> 
>>>>>>> Error in ft_sourcegrandaverage (line 158)
>>>>>>>   dat(:,i) = tmp(:);
>>>>>>> 
>>>>>>> Looking into the code:
>>>>>>> 
>>>>>>>   for i=1:Nsubject
>>>>>>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter, varargin{i}));
>>>>>>>     dat(:,i) = tmp(:);
>>>>>>>     tmp = getsubfield(varargin{i}, 'inside');
>>>>>>>     inside(tmp,i) = 1;
>>>>>>>   end
>>>>>>> 
>>>>>>> I see that "tmp" are getting the structure [N_sources x timepoints] from source.avg.pow for one subject, where "dat" requires the structure [N_sources x 1]. 
>>>>>>> 
>>>>>>> I seached the mailing list for similar issues and found this thread:
>>>>>>> 
>>>>>>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>>>>>>> 
>>>>>>> Since I am interested in using the temporal dimension in my statistics, I would like to know if it is still not possible to use spatio-temporal source reconstructed data in ft_sourcestatistics and ft_sourcegrandaverage ?
>>>>>>> 
>>>>>>> Or if any have succeeded in using the cluster-based permutation test on source level also including the temporal dimension ? 
>>>>>>> 
>>>>>>> Alternative I was thinking that I might could use ft_timelockstatistics, where I substituted the channels with sources, e.g instead of having 64 channels, I would now have 4050 "channels". 
>>>>>>> If so I need to calculate a label structure and an appropriate neighbor structure, which I guess is possible as I have all the 3D coordinates for each source, e.g in leadfield.pos ?
>>>>>>> I know this is a work around solution, but have anyone tried or have any experience using such an approach ? 
>>>>>>> 
>>>>>>> Best,
>>>>>>> 
>>>>>>> Nicolai
>>>>>>> 
>>>>>>> _______________________________________________
>>>>>>> fieldtrip mailing list
>>>>>>> fieldtrip at donders.ru.nl
>>>>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>>> 
>>>>>> _______________________________________________
>>>>>> fieldtrip mailing list
>>>>>> fieldtrip at donders.ru.nl
>>>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>> 
>>>>> Jan-Mathijs Schoffelen, MD PhD 
>>>>> 
>>>>> Donders Institute for Brain, Cognition and Behaviour, 
>>>>> Centre for Cognitive Neuroimaging,
>>>>> Radboud University Nijmegen, The Netherlands
>>>>> 
>>>>> Max Planck Institute for Psycholinguistics,
>>>>> Nijmegen, The Netherlands
>>>>> 
>>>>> J.Schoffelen at donders.ru.nl
>>>>> Telephone: +31-24-3614793
>>>>> 
>>>>> http://www.hettaligebrein.nl
>>>>> 
>>>>> _______________________________________________
>>>>> fieldtrip mailing list
>>>>> fieldtrip at donders.ru.nl
>>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>> 
>>>> _______________________________________________
>>>> fieldtrip mailing list
>>>> fieldtrip at donders.ru.nl
>>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>> 
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> Jan-Mathijs Schoffelen, MD PhD 
> 
> Donders Institute for Brain, Cognition and Behaviour, 
> Centre for Cognitive Neuroimaging,
> Radboud University Nijmegen, The Netherlands
> 
> Max Planck Institute for Psycholinguistics,
> Nijmegen, The Netherlands
> 
> J.Schoffelen at donders.ru.nl
> Telephone: +31-24-3614793
> 
> http://www.hettaligebrein.nl
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip

Jan-Mathijs Schoffelen, MD PhD 

Donders Institute for Brain, Cognition and Behaviour, 
Centre for Cognitive Neuroimaging,
Radboud University Nijmegen, The Netherlands

Max Planck Institute for Psycholinguistics,
Nijmegen, The Netherlands

J.Schoffelen at donders.ru.nl
Telephone: +31-24-3614793

http://www.hettaligebrein.nl

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From gopalar.ccf at gmail.com  Fri Jun 14 17:37:54 2013
From: gopalar.ccf at gmail.com (Raghavan Gopalakrishnan)
Date: Fri, 14 Jun 2013 11:37:54 -0400
Subject: [FieldTrip] Butter command
Message-ID: <CAHz=SkUHMvCSLf+uZ=rJiEOvxJJGCJAiPq0RHtc0G34u7ToZhA@mail.gmail.com>

I noticed that 'butter' command in the fieldtrip toolbox
'/fieldtrip-20130609/external/signal/butter.m'
is interfering with the 'butter' command in the Matlab signal processing
toolbox. Can the name be changed?
There are probably more commands in fieldtrip that has same names as
regular matlab commands.
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From eelke.spaak at donders.ru.nl  Fri Jun 14 20:56:17 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Fri, 14 Jun 2013 20:56:17 +0200
Subject: [FieldTrip] Butter command
In-Reply-To: <CAHz=SkUHMvCSLf+uZ=rJiEOvxJJGCJAiPq0RHtc0G34u7ToZhA@mail.gmail.com>
References: <CAHz=SkUHMvCSLf+uZ=rJiEOvxJJGCJAiPq0RHtc0G34u7ToZhA@mail.gmail.com>
Message-ID: <CABPNLUo2=TjM0dqE41syJLtqAcmTEN2mAYsMmA045SGNabvRnQ@mail.gmail.com>

Dear Raghavan,

The /external/signal/ functions are meant as drop-in replacements for
functions in the MATLAB Signal Processing Toolbox, so they should
behave exactly the same as the functions they are shadowing. They are
included in the FieldTrip release for people who do not have Signal
Processing Toolbox licenses, or who would prefer not to use those
licenses just for tapering or filter coefficient functions.

Best,
Eelke

On 14 June 2013 17:37, Raghavan Gopalakrishnan <gopalar.ccf at gmail.com> wrote:
>
> I noticed that 'butter' command in the fieldtrip toolbox
> '/fieldtrip-20130609/external/signal/butter.m'
> is interfering with the 'butter' command in the Matlab signal processing
> toolbox. Can the name be changed?
> There are probably more commands in fieldtrip that has same names as regular
> matlab commands.
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From karenschuil at gmail.com  Mon Jun 17 13:56:09 2013
From: karenschuil at gmail.com (Karen Schuil)
Date: Mon, 17 Jun 2013 13:56:09 +0200
Subject: [FieldTrip] ERP average Brain Vision is different from ERP average
	FieldTrip
Message-ID: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>

Dear Fieldtrip Users,

I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision Analyser
are different from the ERPS of FieldTrip. It seems that in Fieldtrip a slow
negative drift is added and peaks are more/less pronounced than in BVA
(attached is a picture of the two different plots).

An expert FieldTrip User and I could not find a solution for this problem.
I hope one of you has a suggestion for this problem.

The individual trial data was exported from BVA (version 2.02.5859) with
the following settings:
File extension: .seg
Write header file: yes
Write marker file: yes
Format: BINARY
Orientation: MULTIPLEXED
Line Delimiter: CRLF (PC style)
Binary format: 16-Bit signed integer format
Set resolution manually: no
Individually optimized resolution for each channel: yes
Convert to big-endian order: no
Export all channels: no
Export the following channels:
AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5
CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5
FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5
P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8
Created Using Component Version 2.0.2.5827

We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
tried a version from 2011).

The scripts we used are read_analyzer_data and timelockanalysis. This is
the code we used for calling the scripts:
% read data into fieldtrip
cfg = [];

cfg.inputfile = 'pp10_A';
cfg.triggercode = 'S 20';
cfg.triggertype = 'Stimulus';
cfg.prestim = 1.2;
cfg.poststim = 1.7;

pp10_l = read_analyzer_data(cfg);

% check: compute ERP
%
cfg = [];
pp10_ERP = timelockanalysis(cfg, pp10_l);

%plot ERP

cfg = [];
cfg.layout = 'elec1010.lay';
cfg.xlim = [-0.15 1.7];
cfg.ylim = [-12.25 12.25];
% cfg.baseline = 'yes';
% cfg.baselinetype = 'absolute';
cfg.showlabels = 'yes';
cfg.interactive = 'yes';

multiplotER(cfg, pp10_ERP);


I hope you can help!

Kind regards,
Karen
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From j.herring at fcdonders.ru.nl  Mon Jun 17 14:23:13 2013
From: j.herring at fcdonders.ru.nl (Herring, J.D. (Jim))
Date: Mon, 17 Jun 2013 14:23:13 +0200 (CEST)
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
	average	FieldTrip
In-Reply-To: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
References: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
Message-ID: <001901ce6b55$6fcf4590$4f6dd0b0$@herring@fcdonders.ru.nl>

Dear Karen,

 

Comparing the BVA and Fieldtrip images it seems that the trials in BVA
have been filtered using at least a high-pass filter. I can see from the
BVA image that you have applied filters prior to averaging your trials.
>From the Fieldtrip code you've posted I cannot see any filtering applied.
If you could find out what filters were applied to the trials in BVA and
apply the same filters to the trials in FieldTrip using ft_preprocessing
your results will most likely be the same.

 

Best,

 

Jim

 

From: fieldtrip-bounces at science.ru.nl
[mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of Karen Schuil
Sent: maandag 17 juni 2013 13:56
To: fieldtrip at science.ru.nl
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
average FieldTrip

 

Dear Fieldtrip Users,

 

I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision Analyser
are different from the ERPS of FieldTrip. It seems that in Fieldtrip a
slow negative drift is added and peaks are more/less pronounced than in
BVA (attached is a picture of the two different plots). 

 

An expert FieldTrip User and I could not find a solution for this problem.
I hope one of you has a suggestion for this problem.

 

The individual trial data was exported from BVA (version 2.02.5859) with
the following settings:

File extension: .seg
Write header file: yes
Write marker file: yes
Format: BINARY
Orientation: MULTIPLEXED
Line Delimiter: CRLF (PC style)
Binary format: 16-Bit signed integer format
Set resolution manually: no
Individually optimized resolution for each channel: yes
Convert to big-endian order: no
Export all channels: no
Export the following channels:
AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5 
CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5 
FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5 
P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8

Created Using Component Version 2.0.2.5827

 

We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
tried a version from 2011).

 

The scripts we used are read_analyzer_data and timelockanalysis. This is
the code we used for calling the scripts:

% read data into fieldtrip

cfg = [];

 

cfg.inputfile = 'pp10_A';

cfg.triggercode = 'S 20';

cfg.triggertype = 'Stimulus';

cfg.prestim = 1.2;

cfg.poststim = 1.7;

 

pp10_l = read_analyzer_data(cfg);

 

% check: compute ERP

% 

cfg = [];

pp10_ERP = timelockanalysis(cfg, pp10_l);

 

%plot ERP

 

cfg = [];

cfg.layout = 'elec1010.lay';

cfg.xlim = [-0.15 1.7];

cfg.ylim = [-12.25 12.25];

% cfg.baseline = 'yes';

% cfg.baselinetype = 'absolute';

cfg.showlabels = 'yes';

cfg.interactive = 'yes';

 

multiplotER(cfg, pp10_ERP);

 

 

I hope you can help! 

 

Kind regards,

Karen

 

 

 

 

 

 

 

 

 

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From aaron.schurger at gmail.com  Mon Jun 17 14:25:25 2013
From: aaron.schurger at gmail.com (Aaron Schurger)
Date: Mon, 17 Jun 2013 14:25:25 +0200
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
 average FieldTrip
In-Reply-To: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
References: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
Message-ID: <CALeeyASM1BMtZu5GUUQfDocnPq+S=bdJyUrx0AYhB2_ON95ODA@mail.gmail.com>

To me it really looks like BVA is applying a high-pass filter at some
stage. When you export the data, the high-pass filter has probably
already been applied. It is typical in EEG (though not a good idea in
my opinion) to apply a high-pass filter with a cutoff at around 0.05
or 0.1 Hz. There should be a setting somewhere in BVA to turn off the
high-pass filter. Anyway, that's my guess just from looking at the
figure you attached.
Cheers,
Aaron

On Mon, Jun 17, 2013 at 1:56 PM, Karen Schuil <karenschuil at gmail.com> wrote:
> Dear Fieldtrip Users,
>
> I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision Analyser
> are different from the ERPS of FieldTrip. It seems that in Fieldtrip a slow
> negative drift is added and peaks are more/less pronounced than in BVA
> (attached is a picture of the two different plots).
>
> An expert FieldTrip User and I could not find a solution for this problem. I
> hope one of you has a suggestion for this problem.
>
> The individual trial data was exported from BVA (version 2.02.5859) with the
> following settings:
> File extension: .seg
> Write header file: yes
> Write marker file: yes
> Format: BINARY
> Orientation: MULTIPLEXED
> Line Delimiter: CRLF (PC style)
> Binary format: 16-Bit signed integer format
> Set resolution manually: no
> Individually optimized resolution for each channel: yes
> Convert to big-endian order: no
> Export all channels: no
> Export the following channels:
> AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5
> CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5
> FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5
> P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8
> Created Using Component Version 2.0.2.5827
>
> We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
> tried a version from 2011).
>
> The scripts we used are read_analyzer_data and timelockanalysis. This is the
> code we used for calling the scripts:
> % read data into fieldtrip
> cfg = [];
>
> cfg.inputfile = 'pp10_A';
> cfg.triggercode = 'S 20';
> cfg.triggertype = 'Stimulus';
> cfg.prestim = 1.2;
> cfg.poststim = 1.7;
>
> pp10_l = read_analyzer_data(cfg);
>
> % check: compute ERP
> %
> cfg = [];
> pp10_ERP = timelockanalysis(cfg, pp10_l);
>
> %plot ERP
>
> cfg = [];
> cfg.layout = 'elec1010.lay';
> cfg.xlim = [-0.15 1.7];
> cfg.ylim = [-12.25 12.25];
> % cfg.baseline = 'yes';
> % cfg.baselinetype = 'absolute';
> cfg.showlabels = 'yes';
> cfg.interactive = 'yes';
>
> multiplotER(cfg, pp10_ERP);
>
>
> I hope you can help!
>
> Kind regards,
> Karen
>
>
>
>
>
>
>
>
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip



-- 
Aaron Schurger, PhD
Post-doctoral researcher
INSERM U992 / NeuroSpin
CEA - Saclay, France
+33-1-69-08-66-47
aaron.schurger at gmail.com
http://www.unicog.org


From r.vandermeij at donders.ru.nl  Mon Jun 17 14:48:18 2013
From: r.vandermeij at donders.ru.nl (Roemer van der Meij)
Date: Mon, 17 Jun 2013 14:48:18 +0200
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
 average FieldTrip
In-Reply-To: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
References: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
Message-ID: <CA+WpQ345PZtMY27cMXWTsJNantCXJUd_E5ZUi86gFUNUpGREeg@mail.gmail.com>

Hi Karen,

In case the data wasn't exported with the filtering applied in BVA (see
email Jim) then that looks like a probable cause.
In case the data was exported with the filterings, I noticed in the BVA
part of the attached image that it says AF7 - ref, where I see no such
thing in your exported channel list (and thus not in the fieldtrip image).
What the AF7 - ref is referring to I don't know, it seems like a uncommon
place in the pipeline to do rereferencing, but maybe I'm missing something
obvious. Nevertheless, it might lead you somewhere.

All the best,
Roemer


On Mon, Jun 17, 2013 at 1:56 PM, Karen Schuil <karenschuil at gmail.com> wrote:

> Dear Fieldtrip Users,
>
> I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision Analyser
> are different from the ERPS of FieldTrip. It seems that in Fieldtrip a slow
> negative drift is added and peaks are more/less pronounced than in BVA
> (attached is a picture of the two different plots).
>
> An expert FieldTrip User and I could not find a solution for this problem.
> I hope one of you has a suggestion for this problem.
>
> The individual trial data was exported from BVA (version 2.02.5859) with
> the following settings:
> File extension: .seg
> Write header file: yes
> Write marker file: yes
> Format: BINARY
> Orientation: MULTIPLEXED
> Line Delimiter: CRLF (PC style)
> Binary format: 16-Bit signed integer format
> Set resolution manually: no
> Individually optimized resolution for each channel: yes
> Convert to big-endian order: no
> Export all channels: no
> Export the following channels:
> AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5
> CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5
> FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5
> P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8
> Created Using Component Version 2.0.2.5827
>
>  We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
> tried a version from 2011).
>
> The scripts we used are read_analyzer_data and timelockanalysis. This is
> the code we used for calling the scripts:
> % read data into fieldtrip
> cfg = [];
>
> cfg.inputfile = 'pp10_A';
> cfg.triggercode = 'S 20';
> cfg.triggertype = 'Stimulus';
> cfg.prestim = 1.2;
> cfg.poststim = 1.7;
>
> pp10_l = read_analyzer_data(cfg);
>
> % check: compute ERP
> %
> cfg = [];
> pp10_ERP = timelockanalysis(cfg, pp10_l);
>
> %plot ERP
>
> cfg = [];
> cfg.layout = 'elec1010.lay';
> cfg.xlim = [-0.15 1.7];
> cfg.ylim = [-12.25 12.25];
> % cfg.baseline = 'yes';
> % cfg.baselinetype = 'absolute';
> cfg.showlabels = 'yes';
> cfg.interactive = 'yes';
>
> multiplotER(cfg, pp10_ERP);
>
>
> I hope you can help!
>
> Kind regards,
> Karen
>
>
>
>
>
>
>
>
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
Roemer van der Meij M.Sc.
PhD Candidate
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognition
P.O. Box 9104
6500 HE Nijmegen
The Netherlands
Tel: +31(0)24 3655932
E-mail: r.vandermeij at donders.ru.nl
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From t.grent-tjong at donders.ru.nl  Mon Jun 17 14:55:43 2013
From: t.grent-tjong at donders.ru.nl (Tineke Grent-'t-Jong)
Date: Mon, 17 Jun 2013 14:55:43 +0200
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 32
References: <mailman.55.1371470195.980.fieldtrip@science.ru.nl>
Message-ID: <5819595A0394409287071472F2D6352A@socrates>

Hi Karen,

To me it looks like the only thing you need to do is subtract the baseline, 
like you have done in BVA (specifying the same window with cfg.baseline = 
[xmin xmax], not 'yes'). The average ERP that you are plotting in BVA has 
already been baselined, but the single trials that go into the 
ft_timelockanalysis function are not, hence the need for baselining later, 
like in your case at the level of plotting.

Hope this helps,

Tineke


----- Original Message ----- 
From: <fieldtrip-request at science.ru.nl>
To: <fieldtrip at science.ru.nl>
Sent: Monday, June 17, 2013 1:56 PM
Subject: fieldtrip Digest, Vol 31, Issue 32


> Send fieldtrip mailing list submissions to
> fieldtrip at science.ru.nl
>
> To subscribe or unsubscribe via the World Wide Web, visit
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> or, via email, send a message with subject or body 'help' to
> fieldtrip-request at science.ru.nl
>
> You can reach the person managing the list at
> fieldtrip-owner at science.ru.nl
>
> When replying, please edit your Subject line so it is more specific
> than "Re: Contents of fieldtrip digest..."
>


--------------------------------------------------------------------------------


> Today's Topics:
>
>   1. ERP average Brain Vision is different from ERP average
>      FieldTrip (Karen Schuil)
>


--------------------------------------------------------------------------------


> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip 



From aaron.schurger at gmail.com  Mon Jun 17 15:08:25 2013
From: aaron.schurger at gmail.com (Aaron Schurger)
Date: Mon, 17 Jun 2013 15:08:25 +0200
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 32
In-Reply-To: <5819595A0394409287071472F2D6352A@socrates>
References: <mailman.55.1371470195.980.fieldtrip@science.ru.nl>
	<5819595A0394409287071472F2D6352A@socrates>
Message-ID: <CALeeyASpsHCvVHZ_dYVt-aJt6F7vsuzLvb4wsmsDeYWCYJDphQ@mail.gmail.com>

Hi, Karen, Tineke,
To me it looks like more than just a baseline shift. It looks like
either linear de-trending or high-pass filtering was applied to the
BVA data. I don't see how a baseline shift could get rid of the low
frequency component that is clearly visible in the FT plot, but not
the BVA plot.
Cheers,
Aaron

On Mon, Jun 17, 2013 at 2:55 PM, Tineke Grent-'t-Jong
<t.grent-tjong at donders.ru.nl> wrote:
> Hi Karen,
>
> To me it looks like the only thing you need to do is subtract the baseline,
> like you have done in BVA (specifying the same window with cfg.baseline =
> [xmin xmax], not 'yes'). The average ERP that you are plotting in BVA has
> already been baselined, but the single trials that go into the
> ft_timelockanalysis function are not, hence the need for baselining later,
> like in your case at the level of plotting.
>
> Hope this helps,
>
> Tineke
>
>
> ----- Original Message ----- From: <fieldtrip-request at science.ru.nl>
> To: <fieldtrip at science.ru.nl>
> Sent: Monday, June 17, 2013 1:56 PM
> Subject: fieldtrip Digest, Vol 31, Issue 32
>
>
>> Send fieldtrip mailing list submissions to
>> fieldtrip at science.ru.nl
>>
>> To subscribe or unsubscribe via the World Wide Web, visit
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> or, via email, send a message with subject or body 'help' to
>> fieldtrip-request at science.ru.nl
>>
>> You can reach the person managing the list at
>> fieldtrip-owner at science.ru.nl
>>
>> When replying, please edit your Subject line so it is more specific
>> than "Re: Contents of fieldtrip digest..."
>>
>
>
> --------------------------------------------------------------------------------
>
>
>> Today's Topics:
>>
>>   1. ERP average Brain Vision is different from ERP average
>>      FieldTrip (Karen Schuil)
>>
>
>
> --------------------------------------------------------------------------------
>
>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip



-- 
Aaron Schurger, PhD
Post-doctoral researcher
INSERM U992 / NeuroSpin
CEA - Saclay, France
+33-1-69-08-66-47
aaron.schurger at gmail.com
http://www.unicog.org


From schuil at fsw.eur.nl  Mon Jun 17 15:22:22 2013
From: schuil at fsw.eur.nl (Karen Schuil)
Date: Mon, 17 Jun 2013 15:22:22 +0200
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
 average FieldTrip
In-Reply-To: <CALeeyASM1BMtZu5GUUQfDocnPq+S=bdJyUrx0AYhB2_ON95ODA@mail.gmail.com>
References: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
	<CALeeyASM1BMtZu5GUUQfDocnPq+S=bdJyUrx0AYhB2_ON95ODA@mail.gmail.com>
Message-ID: <CAGnbK6gqEqLBXuATfXHzh2M7ofohp_z7=i8x=WQtX4RxPEMx6A@mail.gmail.com>

Dear Jim, Aaron, Roemer and Tineke,

Thanks for your quick response and suggestions! The whole preprocessing
(including the filters) was done in BVA. After segmentatation of the
conditions, we exported the data to Fieldtrip. The only steps we did in
Fieldtrip was averaging, creating and plotting an ERP. Therefore it can't
be the filters, right? Unless, the averaging step in BVA applies filters as
well.

The ref in AF7-ref is added by BVA and refers to the channels being linked
to the mastoids.

We have also tried it with subtracting a baseline, but this unfortunately
did not help.

Do you have any other suggestions?

Cheers, Karen




On Mon, Jun 17, 2013 at 2:25 PM, Aaron Schurger <aaron.schurger at gmail.com>wrote:

> To me it really looks like BVA is applying a high-pass filter at some
> stage. When you export the data, the high-pass filter has probably
> already been applied. It is typical in EEG (though not a good idea in
> my opinion) to apply a high-pass filter with a cutoff at around 0.05
> or 0.1 Hz. There should be a setting somewhere in BVA to turn off the
> high-pass filter. Anyway, that's my guess just from looking at the
> figure you attached.
> Cheers,
> Aaron
>
> On Mon, Jun 17, 2013 at 1:56 PM, Karen Schuil <karenschuil at gmail.com>
> wrote:
> > Dear Fieldtrip Users,
> >
> > I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision Analyser
> > are different from the ERPS of FieldTrip. It seems that in Fieldtrip a
> slow
> > negative drift is added and peaks are more/less pronounced than in BVA
> > (attached is a picture of the two different plots).
> >
> > An expert FieldTrip User and I could not find a solution for this
> problem. I
> > hope one of you has a suggestion for this problem.
> >
> > The individual trial data was exported from BVA (version 2.02.5859) with
> the
> > following settings:
> > File extension: .seg
> > Write header file: yes
> > Write marker file: yes
> > Format: BINARY
> > Orientation: MULTIPLEXED
> > Line Delimiter: CRLF (PC style)
> > Binary format: 16-Bit signed integer format
> > Set resolution manually: no
> > Individually optimized resolution for each channel: yes
> > Convert to big-endian order: no
> > Export all channels: no
> > Export the following channels:
> > AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5
> > CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5
> > FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5
> > P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8
> > Created Using Component Version 2.0.2.5827
> >
> > We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
> > tried a version from 2011).
> >
> > The scripts we used are read_analyzer_data and timelockanalysis. This is
> the
> > code we used for calling the scripts:
> > % read data into fieldtrip
> > cfg = [];
> >
> > cfg.inputfile = 'pp10_A';
> > cfg.triggercode = 'S 20';
> > cfg.triggertype = 'Stimulus';
> > cfg.prestim = 1.2;
> > cfg.poststim = 1.7;
> >
> > pp10_l = read_analyzer_data(cfg);
> >
> > % check: compute ERP
> > %
> > cfg = [];
> > pp10_ERP = timelockanalysis(cfg, pp10_l);
> >
> > %plot ERP
> >
> > cfg = [];
> > cfg.layout = 'elec1010.lay';
> > cfg.xlim = [-0.15 1.7];
> > cfg.ylim = [-12.25 12.25];
> > % cfg.baseline = 'yes';
> > % cfg.baselinetype = 'absolute';
> > cfg.showlabels = 'yes';
> > cfg.interactive = 'yes';
> >
> > multiplotER(cfg, pp10_ERP);
> >
> >
> > I hope you can help!
> >
> > Kind regards,
> > Karen
> >
> >
> >
> >
> >
> >
> >
> >
> >
> >
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
> --
> Aaron Schurger, PhD
> Post-doctoral researcher
> INSERM U992 / NeuroSpin
> CEA - Saclay, France
> +33-1-69-08-66-47
> aaron.schurger at gmail.com
> http://www.unicog.org
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
-------------------
Karen Schuil
PhD student

Erasmus University Rotterdam
Institute of Psychology, T 13-09
Burgemeester Oudlaan 50
P.O. Box 1738
3000 DR Rotterdam
The Netherlands
Phone: +31 (0) 10 408 2293
Email:  schuil at fsw.eur.nl
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From t.grent-tjong at donders.ru.nl  Mon Jun 17 15:39:30 2013
From: t.grent-tjong at donders.ru.nl (Tineke Grent-'t-Jong)
Date: Mon, 17 Jun 2013 15:39:30 +0200
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 32
References: <mailman.55.1371470195.980.fieldtrip@science.ru.nl><5819595A0394409287071472F2D6352A@socrates>
	<CALeeyASpsHCvVHZ_dYVt-aJt6F7vsuzLvb4wsmsDeYWCYJDphQ@mail.gmail.com>
Message-ID: <0840040570ED4FE896ED4FAE33DE1355@socrates>

Hi Karen,

Aaron is right that it could be an effect of de-trending or high-pass 
filtering. You could try running the ft_timelockanalyis step again with 
option cfg.removemean = 'no' ('yes' is the default option!). If this
solves the problem then it indeed was some kind of de-trending problem.

Cheers,
Tineke



----- Original Message ----- 
From: "Aaron Schurger" <aaron.schurger at gmail.com>
To: "Tineke Grent-'t-Jong" <t.grent-tjong at donders.ru.nl>; "FieldTrip 
discussion list" <fieldtrip at science.ru.nl>
Sent: Monday, June 17, 2013 3:08 PM
Subject: Re: [FieldTrip] fieldtrip Digest, Vol 31, Issue 32


> Hi, Karen, Tineke,
> To me it looks like more than just a baseline shift. It looks like
> either linear de-trending or high-pass filtering was applied to the
> BVA data. I don't see how a baseline shift could get rid of the low
> frequency component that is clearly visible in the FT plot, but not
> the BVA plot.
> Cheers,
> Aaron
>
> On Mon, Jun 17, 2013 at 2:55 PM, Tineke Grent-'t-Jong
> <t.grent-tjong at donders.ru.nl> wrote:
>> Hi Karen,
>>
>> To me it looks like the only thing you need to do is subtract the 
>> baseline,
>> like you have done in BVA (specifying the same window with cfg.baseline =
>> [xmin xmax], not 'yes'). The average ERP that you are plotting in BVA has
>> already been baselined, but the single trials that go into the
>> ft_timelockanalysis function are not, hence the need for baselining 
>> later,
>> like in your case at the level of plotting.
>>
>> Hope this helps,
>>
>> Tineke
>>
>>
>> ----- Original Message ----- From: <fieldtrip-request at science.ru.nl>
>> To: <fieldtrip at science.ru.nl>
>> Sent: Monday, June 17, 2013 1:56 PM
>> Subject: fieldtrip Digest, Vol 31, Issue 32
>>
>>
>>> Send fieldtrip mailing list submissions to
>>> fieldtrip at science.ru.nl
>>>
>>> To subscribe or unsubscribe via the World Wide Web, visit
>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>> or, via email, send a message with subject or body 'help' to
>>> fieldtrip-request at science.ru.nl
>>>
>>> You can reach the person managing the list at
>>> fieldtrip-owner at science.ru.nl
>>>
>>> When replying, please edit your Subject line so it is more specific
>>> than "Re: Contents of fieldtrip digest..."
>>>
>>
>>
>> --------------------------------------------------------------------------------
>>
>>
>>> Today's Topics:
>>>
>>>   1. ERP average Brain Vision is different from ERP average
>>>      FieldTrip (Karen Schuil)
>>>
>>
>>
>> --------------------------------------------------------------------------------
>>
>>
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
> -- 
> Aaron Schurger, PhD
> Post-doctoral researcher
> INSERM U992 / NeuroSpin
> CEA - Saclay, France
> +33-1-69-08-66-47
> aaron.schurger at gmail.com
> http://www.unicog.org
> 



From berryv.dberg at gmail.com  Mon Jun 17 15:40:14 2013
From: berryv.dberg at gmail.com (berry van den berg)
Date: Mon, 17 Jun 2013 09:40:14 -0400
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
 average FieldTrip
In-Reply-To: <CAGnbK6gqEqLBXuATfXHzh2M7ofohp_z7=i8x=WQtX4RxPEMx6A@mail.gmail.com>
References: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
	<CALeeyASM1BMtZu5GUUQfDocnPq+S=bdJyUrx0AYhB2_ON95ODA@mail.gmail.com>
	<CAGnbK6gqEqLBXuATfXHzh2M7ofohp_z7=i8x=WQtX4RxPEMx6A@mail.gmail.com>
Message-ID: <CAL-qV4JzQmdy=-JNvpm1HwEEvVuLrjQ02sAzjdDffbCV+Ys0ew@mail.gmail.com>

I dont know BVA but it looks like the ERPs are a bit more different (for
example at timepoint 100ms) then I would expect just based on high pass
filtering.... Suggesting that there is different data going into averaging.
Maybe brain vision just detects trials with artifacts and does not throw
out the trials until the averaging step (similar to ERPlab). Can you check
the number of trials?

Cheers,

Berry van den Berg



On 17 June 2013 09:22, Karen Schuil <schuil at fsw.eur.nl> wrote:

> Dear Jim, Aaron, Roemer and Tineke,
>
> Thanks for your quick response and suggestions! The whole preprocessing
> (including the filters) was done in BVA. After segmentatation of the
> conditions, we exported the data to Fieldtrip. The only steps we did in
> Fieldtrip was averaging, creating and plotting an ERP. Therefore it can't
> be the filters, right? Unless, the averaging step in BVA applies filters as
> well.
>
> The ref in AF7-ref is added by BVA and refers to the channels being linked
> to the mastoids.
>
> We have also tried it with subtracting a baseline, but this unfortunately
> did not help.
>
> Do you have any other suggestions?
>
> Cheers, Karen
>
>
>
>
> On Mon, Jun 17, 2013 at 2:25 PM, Aaron Schurger <aaron.schurger at gmail.com>wrote:
>
>> To me it really looks like BVA is applying a high-pass filter at some
>> stage. When you export the data, the high-pass filter has probably
>> already been applied. It is typical in EEG (though not a good idea in
>> my opinion) to apply a high-pass filter with a cutoff at around 0.05
>> or 0.1 Hz. There should be a setting somewhere in BVA to turn off the
>> high-pass filter. Anyway, that's my guess just from looking at the
>> figure you attached.
>> Cheers,
>> Aaron
>>
>> On Mon, Jun 17, 2013 at 1:56 PM, Karen Schuil <karenschuil at gmail.com>
>> wrote:
>> > Dear Fieldtrip Users,
>> >
>> > I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision
>> Analyser
>> > are different from the ERPS of FieldTrip. It seems that in Fieldtrip a
>> slow
>> > negative drift is added and peaks are more/less pronounced than in BVA
>> > (attached is a picture of the two different plots).
>> >
>> > An expert FieldTrip User and I could not find a solution for this
>> problem. I
>> > hope one of you has a suggestion for this problem.
>> >
>> > The individual trial data was exported from BVA (version 2.02.5859)
>> with the
>> > following settings:
>> > File extension: .seg
>> > Write header file: yes
>> > Write marker file: yes
>> > Format: BINARY
>> > Orientation: MULTIPLEXED
>> > Line Delimiter: CRLF (PC style)
>> > Binary format: 16-Bit signed integer format
>> > Set resolution manually: no
>> > Individually optimized resolution for each channel: yes
>> > Convert to big-endian order: no
>> > Export all channels: no
>> > Export the following channels:
>> > AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5
>> > CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5
>> > FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5
>> > P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8
>> > Created Using Component Version 2.0.2.5827
>> >
>> > We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
>> > tried a version from 2011).
>> >
>> > The scripts we used are read_analyzer_data and timelockanalysis. This
>> is the
>> > code we used for calling the scripts:
>> > % read data into fieldtrip
>> > cfg = [];
>> >
>> > cfg.inputfile = 'pp10_A';
>> > cfg.triggercode = 'S 20';
>> > cfg.triggertype = 'Stimulus';
>> > cfg.prestim = 1.2;
>> > cfg.poststim = 1.7;
>> >
>> > pp10_l = read_analyzer_data(cfg);
>> >
>> > % check: compute ERP
>> > %
>> > cfg = [];
>> > pp10_ERP = timelockanalysis(cfg, pp10_l);
>> >
>> > %plot ERP
>> >
>> > cfg = [];
>> > cfg.layout = 'elec1010.lay';
>> > cfg.xlim = [-0.15 1.7];
>> > cfg.ylim = [-12.25 12.25];
>> > % cfg.baseline = 'yes';
>> > % cfg.baselinetype = 'absolute';
>> > cfg.showlabels = 'yes';
>> > cfg.interactive = 'yes';
>> >
>> > multiplotER(cfg, pp10_ERP);
>> >
>> >
>> > I hope you can help!
>> >
>> > Kind regards,
>> > Karen
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> > _______________________________________________
>> > fieldtrip mailing list
>> > fieldtrip at donders.ru.nl
>> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>>
>>
>> --
>> Aaron Schurger, PhD
>> Post-doctoral researcher
>> INSERM U992 / NeuroSpin
>> CEA - Saclay, France
>> +33-1-69-08-66-47
>> aaron.schurger at gmail.com
>> http://www.unicog.org
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>
>
>
> --
> -------------------
> Karen Schuil
> PhD student
>
> Erasmus University Rotterdam
> Institute of Psychology, T 13-09
> Burgemeester Oudlaan 50
> P.O. Box 1738
> 3000 DR Rotterdam
> The Netherlands
> Phone: +31 (0) 10 408 2293
> Email:  schuil at fsw.eur.nl
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
Berry van den Berg
berryv.dberg at gmail.com
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From aaron.schurger at gmail.com  Mon Jun 17 15:44:05 2013
From: aaron.schurger at gmail.com (Aaron Schurger)
Date: Mon, 17 Jun 2013 15:44:05 +0200
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
 average FieldTrip
In-Reply-To: <CAGnbK6gqEqLBXuATfXHzh2M7ofohp_z7=i8x=WQtX4RxPEMx6A@mail.gmail.com>
References: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
	<CALeeyASM1BMtZu5GUUQfDocnPq+S=bdJyUrx0AYhB2_ON95ODA@mail.gmail.com>
	<CAGnbK6gqEqLBXuATfXHzh2M7ofohp_z7=i8x=WQtX4RxPEMx6A@mail.gmail.com>
Message-ID: <CALeeyASwKFoiJ-YL_q1Me+QvFTCtsFvyWpM5i3J4FjgiC8Tuww@mail.gmail.com>

Hi, Karen,
Yes, you're right - it would have to be the case that the averaging
step in BVA applies the filters. That would be where I would check. If
nothing there then it really is mysterious!
Aaron

On Mon, Jun 17, 2013 at 3:22 PM, Karen Schuil <schuil at fsw.eur.nl> wrote:
> Dear Jim, Aaron, Roemer and Tineke,
>
> Thanks for your quick response and suggestions! The whole preprocessing
> (including the filters) was done in BVA. After segmentatation of the
> conditions, we exported the data to Fieldtrip. The only steps we did in
> Fieldtrip was averaging, creating and plotting an ERP. Therefore it can't be
> the filters, right? Unless, the averaging step in BVA applies filters as
> well.
>
> The ref in AF7-ref is added by BVA and refers to the channels being linked
> to the mastoids.
>
> We have also tried it with subtracting a baseline, but this unfortunately
> did not help.
>
> Do you have any other suggestions?
>
> Cheers, Karen
>
>
>
>
> On Mon, Jun 17, 2013 at 2:25 PM, Aaron Schurger <aaron.schurger at gmail.com>
> wrote:
>>
>> To me it really looks like BVA is applying a high-pass filter at some
>> stage. When you export the data, the high-pass filter has probably
>> already been applied. It is typical in EEG (though not a good idea in
>> my opinion) to apply a high-pass filter with a cutoff at around 0.05
>> or 0.1 Hz. There should be a setting somewhere in BVA to turn off the
>> high-pass filter. Anyway, that's my guess just from looking at the
>> figure you attached.
>> Cheers,
>> Aaron
>>
>> On Mon, Jun 17, 2013 at 1:56 PM, Karen Schuil <karenschuil at gmail.com>
>> wrote:
>> > Dear Fieldtrip Users,
>> >
>> > I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision
>> > Analyser
>> > are different from the ERPS of FieldTrip. It seems that in Fieldtrip a
>> > slow
>> > negative drift is added and peaks are more/less pronounced than in BVA
>> > (attached is a picture of the two different plots).
>> >
>> > An expert FieldTrip User and I could not find a solution for this
>> > problem. I
>> > hope one of you has a suggestion for this problem.
>> >
>> > The individual trial data was exported from BVA (version 2.02.5859) with
>> > the
>> > following settings:
>> > File extension: .seg
>> > Write header file: yes
>> > Write marker file: yes
>> > Format: BINARY
>> > Orientation: MULTIPLEXED
>> > Line Delimiter: CRLF (PC style)
>> > Binary format: 16-Bit signed integer format
>> > Set resolution manually: no
>> > Individually optimized resolution for each channel: yes
>> > Convert to big-endian order: no
>> > Export all channels: no
>> > Export the following channels:
>> > AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5
>> > CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5
>> > FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5
>> > P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8
>> > Created Using Component Version 2.0.2.5827
>> >
>> > We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
>> > tried a version from 2011).
>> >
>> > The scripts we used are read_analyzer_data and timelockanalysis. This is
>> > the
>> > code we used for calling the scripts:
>> > % read data into fieldtrip
>> > cfg = [];
>> >
>> > cfg.inputfile = 'pp10_A';
>> > cfg.triggercode = 'S 20';
>> > cfg.triggertype = 'Stimulus';
>> > cfg.prestim = 1.2;
>> > cfg.poststim = 1.7;
>> >
>> > pp10_l = read_analyzer_data(cfg);
>> >
>> > % check: compute ERP
>> > %
>> > cfg = [];
>> > pp10_ERP = timelockanalysis(cfg, pp10_l);
>> >
>> > %plot ERP
>> >
>> > cfg = [];
>> > cfg.layout = 'elec1010.lay';
>> > cfg.xlim = [-0.15 1.7];
>> > cfg.ylim = [-12.25 12.25];
>> > % cfg.baseline = 'yes';
>> > % cfg.baselinetype = 'absolute';
>> > cfg.showlabels = 'yes';
>> > cfg.interactive = 'yes';
>> >
>> > multiplotER(cfg, pp10_ERP);
>> >
>> >
>> > I hope you can help!
>> >
>> > Kind regards,
>> > Karen
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> > _______________________________________________
>> > fieldtrip mailing list
>> > fieldtrip at donders.ru.nl
>> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>>
>>
>> --
>> Aaron Schurger, PhD
>> Post-doctoral researcher
>> INSERM U992 / NeuroSpin
>> CEA - Saclay, France
>> +33-1-69-08-66-47
>> aaron.schurger at gmail.com
>> http://www.unicog.org
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
>
> --
> -------------------
> Karen Schuil
> PhD student
>
> Erasmus University Rotterdam
> Institute of Psychology, T 13-09
> Burgemeester Oudlaan 50
> P.O. Box 1738
> 3000 DR Rotterdam
> The Netherlands
> Phone: +31 (0) 10 408 2293
> Email:  schuil at fsw.eur.nl
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip



-- 
Aaron Schurger, PhD
Post-doctoral researcher
INSERM U992 / NeuroSpin
CEA - Saclay, France
+33-1-69-08-66-47
aaron.schurger at gmail.com
http://www.unicog.org


From eelke.spaak at donders.ru.nl  Tue Jun 18 10:29:34 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Tue, 18 Jun 2013 10:29:34 +0200
Subject: [FieldTrip] ERP average Brain Vision is different from ERP
 average FieldTrip
In-Reply-To: <CAGnbK6gqEqLBXuATfXHzh2M7ofohp_z7=i8x=WQtX4RxPEMx6A@mail.gmail.com>
References: <CAGnbK6gQXxiz5YF-EkKi1pX-KVewJCRQikqAG-2K9k6tY5+btQ@mail.gmail.com>
	<CALeeyASM1BMtZu5GUUQfDocnPq+S=bdJyUrx0AYhB2_ON95ODA@mail.gmail.com>
	<CAGnbK6gqEqLBXuATfXHzh2M7ofohp_z7=i8x=WQtX4RxPEMx6A@mail.gmail.com>
Message-ID: <CABPNLUomcmtO7B9phMmV9-aGAfJqURGjyxt-RV0v+z_RS_p4aA@mail.gmail.com>

Dear Karen,

It seems likely (as the other responses also indicate) that
BrainVision Analyzer is doing something to the data that FieldTrip is
not; in other words, the FieldTrip ERP is probably more 'pure'.
Therefore, perhaps it might be worth asking around on the BVA mailing
list if the people there know what BVA is doing to the data prior to
computing and displaying the average?

It is easy to check whether FieldTrip is doing something unexpected to
the data, by computing and plotting the average yourself:

erp = mean(cat(3, pp10_l.trial{:}), 3);
chanind = strmatch('AF7', pp10_l.label);
plot(pp10_l.time{1}, erp(chanind,:));

This only works if all trials have identical time axes, but judging
from your script I think they do. It the above steps give a different
plot than the FT functions, something is possibly (/probably) wrong in
the FT code.

Best,
Eelke

On 17 June 2013 15:22, Karen Schuil <schuil at fsw.eur.nl> wrote:
> Dear Jim, Aaron, Roemer and Tineke,
>
> Thanks for your quick response and suggestions! The whole preprocessing
> (including the filters) was done in BVA. After segmentatation of the
> conditions, we exported the data to Fieldtrip. The only steps we did in
> Fieldtrip was averaging, creating and plotting an ERP. Therefore it can't be
> the filters, right? Unless, the averaging step in BVA applies filters as
> well.
>
> The ref in AF7-ref is added by BVA and refers to the channels being linked
> to the mastoids.
>
> We have also tried it with subtracting a baseline, but this unfortunately
> did not help.
>
> Do you have any other suggestions?
>
> Cheers, Karen
>
>
>
>
> On Mon, Jun 17, 2013 at 2:25 PM, Aaron Schurger <aaron.schurger at gmail.com>
> wrote:
>>
>> To me it really looks like BVA is applying a high-pass filter at some
>> stage. When you export the data, the high-pass filter has probably
>> already been applied. It is typical in EEG (though not a good idea in
>> my opinion) to apply a high-pass filter with a cutoff at around 0.05
>> or 0.1 Hz. There should be a setting somewhere in BVA to turn off the
>> high-pass filter. Anyway, that's my guess just from looking at the
>> figure you attached.
>> Cheers,
>> Aaron
>>
>> On Mon, Jun 17, 2013 at 1:56 PM, Karen Schuil <karenschuil at gmail.com>
>> wrote:
>> > Dear Fieldtrip Users,
>> >
>> > I have a BVA-Fieldtrip problem. The average ERPs of Brain Vision
>> > Analyser
>> > are different from the ERPS of FieldTrip. It seems that in Fieldtrip a
>> > slow
>> > negative drift is added and peaks are more/less pronounced than in BVA
>> > (attached is a picture of the two different plots).
>> >
>> > An expert FieldTrip User and I could not find a solution for this
>> > problem. I
>> > hope one of you has a suggestion for this problem.
>> >
>> > The individual trial data was exported from BVA (version 2.02.5859) with
>> > the
>> > following settings:
>> > File extension: .seg
>> > Write header file: yes
>> > Write marker file: yes
>> > Format: BINARY
>> > Orientation: MULTIPLEXED
>> > Line Delimiter: CRLF (PC style)
>> > Binary format: 16-Bit signed integer format
>> > Set resolution manually: no
>> > Individually optimized resolution for each channel: yes
>> > Convert to big-endian order: no
>> > Export all channels: no
>> > Export the following channels:
>> > AF3 AF4 AF7 AF8 AFz C1 C2 C3 C4 C5 C6 CP1 CP2 CP3 CP4 CP5
>> > CP6 CPz Cz F1 F2 F3 F4 F5 F6 F7 F8 FC1 FC2 FC3 FC4 FC5
>> > FC6 FCz Fpz FT7 FT8 Fz Iz O1 O2 Oz P1 P10 P2 P3 P4 P5
>> > P6 P7 P8 P9 PO3 PO4 PO7 PO8 POz Pz T7 T8 TP7 TP8
>> > Created Using Component Version 2.0.2.5827
>> >
>> > We used Matlab version 7.10.0 R2, and fieldtrip version 13-06-2013 (and
>> > tried a version from 2011).
>> >
>> > The scripts we used are read_analyzer_data and timelockanalysis. This is
>> > the
>> > code we used for calling the scripts:
>> > % read data into fieldtrip
>> > cfg = [];
>> >
>> > cfg.inputfile = 'pp10_A';
>> > cfg.triggercode = 'S 20';
>> > cfg.triggertype = 'Stimulus';
>> > cfg.prestim = 1.2;
>> > cfg.poststim = 1.7;
>> >
>> > pp10_l = read_analyzer_data(cfg);
>> >
>> > % check: compute ERP
>> > %
>> > cfg = [];
>> > pp10_ERP = timelockanalysis(cfg, pp10_l);
>> >
>> > %plot ERP
>> >
>> > cfg = [];
>> > cfg.layout = 'elec1010.lay';
>> > cfg.xlim = [-0.15 1.7];
>> > cfg.ylim = [-12.25 12.25];
>> > % cfg.baseline = 'yes';
>> > % cfg.baselinetype = 'absolute';
>> > cfg.showlabels = 'yes';
>> > cfg.interactive = 'yes';
>> >
>> > multiplotER(cfg, pp10_ERP);
>> >
>> >
>> > I hope you can help!
>> >
>> > Kind regards,
>> > Karen
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> >
>> > _______________________________________________
>> > fieldtrip mailing list
>> > fieldtrip at donders.ru.nl
>> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>>
>>
>> --
>> Aaron Schurger, PhD
>> Post-doctoral researcher
>> INSERM U992 / NeuroSpin
>> CEA - Saclay, France
>> +33-1-69-08-66-47
>> aaron.schurger at gmail.com
>> http://www.unicog.org
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
>
> --
> -------------------
> Karen Schuil
> PhD student
>
> Erasmus University Rotterdam
> Institute of Psychology, T 13-09
> Burgemeester Oudlaan 50
> P.O. Box 1738
> 3000 DR Rotterdam
> The Netherlands
> Phone: +31 (0) 10 408 2293
> Email:  schuil at fsw.eur.nl
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From mje.mads at gmail.com  Tue Jun 18 10:44:01 2013
From: mje.mads at gmail.com (Mads Jensen)
Date: Tue, 18 Jun 2013 10:44:01 +0200
Subject: [FieldTrip] select trial by previous trigger code
Message-ID: <51C01DD1.5070005@gmail.com>

Hi all,

I would like to know if it is possible select a trail based on the 
previous trigger code?

I got a dataset (MEG, neuromeg) where sometimes the subject just press a 
button and sometimes a cue is shown and they then press the button, the 
button presses are coded "1" and the cue "2". So, what I would like is 
to datasets one with trials where there has been no cue and one dataset 
where the trials that have cue is. Is that possible to do automatically 
or do I have to do a "by hand"?

best wishes,
mads


From s.vanpelt at fcdonders.ru.nl  Tue Jun 18 11:11:06 2013
From: s.vanpelt at fcdonders.ru.nl (Stan van Pelt)
Date: Tue, 18 Jun 2013 11:11:06 +0200 (CEST)
Subject: [FieldTrip] select trial by previous trigger code
References: <51C01DD1.5070005@gmail.com> 
Message-ID: <03cc01ce6c03$c403fb20$4c0bf160$@vanpelt@fcdonders.ru.nl>

Dear Mads,

It is not possible to do this automatically. However, by writing your own
'trialfun', you should be able to program this in a relative
straightforward manner. You can enter this trialfun-name in the
cfg.trialfun configuration option when subsequently calling
ft_definetrial.
See
http://fieldtrip.fcdonders.nl/example/making_your_own_trialfun_for_conditi
onal_trial_definition

Best,
Stan

Stan van Pelt, PhD
Donders Institute for Brain, Cognition and Behaviour Centre for Cognition
Montessorilaan 3, B.01.19
6525 HR Nijmegen
tel: 024-3616288


-----Original Message-----
From: fieldtrip-bounces at science.ru.nl
[mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of Mads Jensen
Sent: dinsdag 18 juni 2013 10:44
To: FieldTrip discussion list
Subject: [FieldTrip] select trial by previous trigger code

Hi all,

I would like to know if it is possible select a trail based on the
previous trigger code?

I got a dataset (MEG, neuromeg) where sometimes the subject just press a
button and sometimes a cue is shown and they then press the button, the
button presses are coded "1" and the cue "2". So, what I would like is to
datasets one with trials where there has been no cue and one dataset where
the trials that have cue is. Is that possible to do automatically or do I
have to do a "by hand"?

best wishes,
mads
_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl
http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From jm.horschig at donders.ru.nl  Tue Jun 18 11:11:50 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Tue, 18 Jun 2013 11:11:50 +0200
Subject: [FieldTrip] select trial by previous trigger code
In-Reply-To: <51C01DD1.5070005@gmail.com>
References: <51C01DD1.5070005@gmail.com>
Message-ID: <51C02456.2000800@donders.ru.nl>

Hi Mads,

such things are possible if you write your own trial function. 
Basically, you need to read in the events (i.e. trigger values) and then 
make a selection based on that, see also here:
http://fieldtrip.fcdonders.nl/example/making_your_own_trialfun_for_conditional_trial_definition?s[]=trialfun
http://fieldtrip.fcdonders.nl/faq/what_is_the_relation_between_events_such_as_triggers_and_trials?s[]=trialfun

Hope that helps!
Best,
Jörn

On 6/18/2013 10:44 AM, Mads Jensen wrote:
> Hi all,
>
> I would like to know if it is possible select a trail based on the 
> previous trigger code?
>
> I got a dataset (MEG, neuromeg) where sometimes the subject just press 
> a button and sometimes a cue is shown and they then press the button, 
> the button presses are coded "1" and the cue "2". So, what I would 
> like is to datasets one with trials where there has been no cue and 
> one dataset where the trials that have cue is. Is that possible to do 
> automatically or do I have to do a "by hand"?
>
> best wishes,
> mads
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands



From yuvharpaz at gmail.com  Tue Jun 18 14:58:15 2013
From: yuvharpaz at gmail.com (Yuval Harpaz)
Date: Tue, 18 Jun 2013 15:58:15 +0300
Subject: [FieldTrip] fixed dipole orientation for MNE
Message-ID: <CAGQZS_m+RSW6LDOmbYc9MDtwf1dUM==a4c3Nc9BRA5WYneTp6w@mail.gmail.com>

Dear group
I would like to ask again (
http://mailman.science.ru.nl/pipermail/fieldtrip/2011-February/003456.html)
about head model with fixed dipole orientation (obtained from freesurfer),
as I saw no reply to the previous message.

I understand that there is no civilized way, currently, to tell MNE or
beamforming to use fixed orientation, or am I wrong?

applying 'sam' I managed to set dipole orinetation by making a dip.mom
field in addition to dip.pos and by
gain = lf;
instead of the existing
gain = lf * UnitMDip';
note that here lf is a vector (no 3 columns).

However this is patchy and not thorough. So can you please tell me if there
is a way to do it with regular ft functions?
thank you
Yuval




Dr .Harpaz

BIU MEG lab <http://faculty.biu.ac.il/~goldsa/index.html>
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From eelke.spaak at donders.ru.nl  Tue Jun 18 15:16:41 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Tue, 18 Jun 2013 15:16:41 +0200
Subject: [FieldTrip] fixed dipole orientation for MNE
In-Reply-To: <CAGQZS_m+RSW6LDOmbYc9MDtwf1dUM==a4c3Nc9BRA5WYneTp6w@mail.gmail.com>
References: <CAGQZS_m+RSW6LDOmbYc9MDtwf1dUM==a4c3Nc9BRA5WYneTp6w@mail.gmail.com>
Message-ID: <CABPNLUpqBxHFfrw=9mvesB2RXirhnyQH_-Mt5+icKA5HMcrkXQ@mail.gmail.com>

Dear Yuval,

The LCMV and DICS beamforming implementations in FieldTrip support
cfg.<method>.fixedori = 'yes', where <method> is either 'lcmv' or
'dics'. This will compute a filter which constrains each dipole to
point in the strongest orientation. For SAM I think this is not
implemented, and for MNE I have no clue.

Does this answer your question? Or are you lookling for another type
of fixed orientation, maybe based on anatomy or so?

Best,
Eelke

On 18 June 2013 14:58, Yuval Harpaz <yuvharpaz at gmail.com> wrote:
> Dear group
> I would like to ask again
> (http://mailman.science.ru.nl/pipermail/fieldtrip/2011-February/003456.html)
> about head model with fixed dipole orientation (obtained from freesurfer),
> as I saw no reply to the previous message.
>
> I understand that there is no civilized way, currently, to tell MNE or
> beamforming to use fixed orientation, or am I wrong?
>
> applying 'sam' I managed to set dipole orinetation by making a dip.mom field
> in addition to dip.pos and by
> gain = lf;
> instead of the existing
> gain = lf * UnitMDip';
> note that here lf is a vector (no 3 columns).
>
> However this is patchy and not thorough. So can you please tell me if there
> is a way to do it with regular ft functions?
> thank you
> Yuval
>
>
>
>
> Dr .Harpaz
>
> BIU MEG lab
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From yuvharpaz at gmail.com  Tue Jun 18 19:01:40 2013
From: yuvharpaz at gmail.com (Yuval Harpaz)
Date: Tue, 18 Jun 2013 20:01:40 +0300
Subject: [FieldTrip] fixed dipole orientation for MNE
In-Reply-To: <CABPNLUpqBxHFfrw=9mvesB2RXirhnyQH_-Mt5+icKA5HMcrkXQ@mail.gmail.com>
References: <CAGQZS_m+RSW6LDOmbYc9MDtwf1dUM==a4c3Nc9BRA5WYneTp6w@mail.gmail.com>
	<CABPNLUpqBxHFfrw=9mvesB2RXirhnyQH_-Mt5+icKA5HMcrkXQ@mail.gmail.com>
Message-ID: <CAGQZS_=G15YJw-Cc+aQrHhwSXq9pXC8P5qrCpbU8LAkqkMCBUg@mail.gmail.com>

Well, it uses fixed orientation but it calculates the orientation based on
the signal, not on the anatomy. I am trying to reduce leakage problems by
limiting orientation according to structure. you CAN specify dip.mom but
this is really buggy.
thanks


On 18 June 2013 16:16, Eelke Spaak <eelke.spaak at donders.ru.nl> wrote:

> Dear Yuval,
>
> The LCMV and DICS beamforming implementations in FieldTrip support
> cfg.<method>.fixedori = 'yes', where <method> is either 'lcmv' or
> 'dics'. This will compute a filter which constrains each dipole to
> point in the strongest orientation. For SAM I think this is not
> implemented, and for MNE I have no clue.
>
> Does this answer your question? Or are you lookling for another type
> of fixed orientation, maybe based on anatomy or so?
>
> Best,
> Eelke
>
> On 18 June 2013 14:58, Yuval Harpaz <yuvharpaz at gmail.com> wrote:
> > Dear group
> > I would like to ask again
> > (
> http://mailman.science.ru.nl/pipermail/fieldtrip/2011-February/003456.html
> )
> > about head model with fixed dipole orientation (obtained from
> freesurfer),
> > as I saw no reply to the previous message.
> >
> > I understand that there is no civilized way, currently, to tell MNE or
> > beamforming to use fixed orientation, or am I wrong?
> >
> > applying 'sam' I managed to set dipole orinetation by making a dip.mom
> field
> > in addition to dip.pos and by
> > gain = lf;
> > instead of the existing
> > gain = lf * UnitMDip';
> > note that here lf is a vector (no 3 columns).
> >
> > However this is patchy and not thorough. So can you please tell me if
> there
> > is a way to do it with regular ft functions?
> > thank you
> > Yuval
> >
> >
> >
> >
> > Dr .Harpaz
> >
> > BIU MEG lab
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
Yuval




Dr .Harpaz

BIU MEG lab <http://faculty.biu.ac.il/~goldsa/index.html>
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From mje.mads at gmail.com  Tue Jun 18 23:52:02 2013
From: mje.mads at gmail.com (Mads Jensen)
Date: Tue, 18 Jun 2013 23:52:02 +0200
Subject: [FieldTrip] select trial by previous trigger code
In-Reply-To: <51C02456.2000800@donders.ru.nl>
References: <51C01DD1.5070005@gmail.com> <51C02456.2000800@donders.ru.nl>
Message-ID: <51C0D682.7070008@gmail.com>

HI Jörn & Stan,

Thanks for your replies and advises. It worked.

thanks, best
mads



On 06/18/2013 11:11 AM, "Jörn M. Horschig" wrote:
> Hi Mads,
>
> such things are possible if you write your own trial function.
> Basically, you need to read in the events (i.e. trigger values) and then
> make a selection based on that, see also here:
> http://fieldtrip.fcdonders.nl/example/making_your_own_trialfun_for_conditional_trial_definition?s[]=trialfun
>
> http://fieldtrip.fcdonders.nl/faq/what_is_the_relation_between_events_such_as_triggers_and_trials?s[]=trialfun
>
>
> Hope that helps!
> Best,
> Jörn
>
> On 6/18/2013 10:44 AM, Mads Jensen wrote:
>> Hi all,
>>
>> I would like to know if it is possible select a trail based on the
>> previous trigger code?
>>
>> I got a dataset (MEG, neuromeg) where sometimes the subject just press
>> a button and sometimes a cue is shown and they then press the button,
>> the button presses are coded "1" and the cue "2". So, what I would
>> like is to datasets one with trials where there has been no cue and
>> one dataset where the trials that have cue is. Is that possible to do
>> automatically or do I have to do a "by hand"?
>>
>> best wishes,
>> mads
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>


From marco.porta88 at gmail.com  Wed Jun 19 16:41:47 2013
From: marco.porta88 at gmail.com (Marco Porta)
Date: Wed, 19 Jun 2013 16:41:47 +0200
Subject: [FieldTrip] statistics on non-event-related fields
Message-ID: <CAP6m0dHxFfYpYHFqeSMf83drbHD8TxU=9LqO8eAr8K0QC4mdNw@mail.gmail.com>

Dear Fieldtrip experts,
I have a question regarding the statistics. How can I statistics on non
event-related fields in a between-trials.
Thanks,

Marco
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From eelke.spaak at donders.ru.nl  Wed Jun 19 16:50:48 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Wed, 19 Jun 2013 16:50:48 +0200
Subject: [FieldTrip] statistics on non-event-related fields
In-Reply-To: <CAP6m0dHxFfYpYHFqeSMf83drbHD8TxU=9LqO8eAr8K0QC4mdNw@mail.gmail.com>
References: <CAP6m0dHxFfYpYHFqeSMf83drbHD8TxU=9LqO8eAr8K0QC4mdNw@mail.gmail.com>
Message-ID: <CABPNLUp6KKoApdcKEXJ2EFY29=JoXPJD+utHZ+jpcR3x0pW2=g@mail.gmail.com>

Dear Marco,

What do you mean exactly with "non event-related fields"? I presume
there is some structure in your data that you want to consider as the
independent variable of interest, right? Some more information on what
you want to do would help us to help you.

Best,
Eelke

On 19 June 2013 16:41, Marco Porta <marco.porta88 at gmail.com> wrote:
> Dear Fieldtrip experts,
> I have a question regarding the statistics. How can I statistics on non
> event-related fields in a between-trials.
> Thanks,
>
> Marco
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From jdien07 at mac.com  Thu Jun 20 02:35:35 2013
From: jdien07 at mac.com (Joseph Dien)
Date: Wed, 19 Jun 2013 20:35:35 -0400
Subject: [FieldTrip] ft_dipolefitting options no longer working
Message-ID: <C1AE459D-6A06-4743-ABD1-CAE20510BD28@mac.com>

Hi,
    it looks like changes have been made to ft_dipolefitting that have resulted in the following options no longer working:

        cfg.grid.xgrid  = 'auto';
        cfg.grid.ygrid  = 'auto';
        cfg.grid.zgrid  = 'auto';

The header of the ft_dipolefitting file as of the 20130619 release says:

% This function depends on FT_PREPARE_DIPOLE_GRID which has the following options:
% cfg.grid.xgrid (default set in FT_PREPARE_DIPOLE_GRID: cfg.grid.xgrid = 'auto'), documented
% cfg.grid.ygrid (default set in FT_PREPARE_DIPOLE_GRID: cfg.grid.ygrid = 'auto'), documented
% cfg.grid.zgrid (default set in FT_PREPARE_DIPOLE_GRID: cfg.grid.zgrid = 'auto'), documented

but a Find Files search indicates that FT_PREPARE_DIPOLE_GRID no longer exists.

I don't have copies of FieldTrip older than Feb 2013 so I can't check directly but I know that my function call used to work and no longer does.

Can someone help me find a fix for this?

Any help appreciated!

Joe

--------------------------------------------------------------------------------

Joseph Dien,
Senior Research Scientist
University of Maryland 

E-mail: jdien07 at mac.com
Phone: 301-226-8848
Fax: 301-226-8811
http://joedien.com//











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From jdien07 at mac.com  Thu Jun 20 04:41:49 2013
From: jdien07 at mac.com (Joseph Dien)
Date: Wed, 19 Jun 2013 22:41:49 -0400
Subject: [FieldTrip] ft_dipolefitting options no longer working
In-Reply-To: <C1AE459D-6A06-4743-ABD1-CAE20510BD28@mac.com>
References: <C1AE459D-6A06-4743-ABD1-CAE20510BD28@mac.com>
Message-ID: <B8CFEB76-33B2-474E-856C-4ABE53E5290C@mac.com>

Okay, I got this sorted out.  I was able to use ft_prepare_sourcemodel to set up the config variable.
The header info of ft_dipolefitting should get updated though.

Cheers!

Joe

On Jun 19, 2013, at 8:35 PM, Joseph Dien <jdien07 at mac.com> wrote:

> Hi,
>     it looks like changes have been made to ft_dipolefitting that have resulted in the following options no longer working:
> 
>         cfg.grid.xgrid  = 'auto';
>         cfg.grid.ygrid  = 'auto';
>         cfg.grid.zgrid  = 'auto';
> 
> The header of the ft_dipolefitting file as of the 20130619 release says:
> 
> % This function depends on FT_PREPARE_DIPOLE_GRID which has the following options:
> % cfg.grid.xgrid (default set in FT_PREPARE_DIPOLE_GRID: cfg.grid.xgrid = 'auto'), documented
> % cfg.grid.ygrid (default set in FT_PREPARE_DIPOLE_GRID: cfg.grid.ygrid = 'auto'), documented
> % cfg.grid.zgrid (default set in FT_PREPARE_DIPOLE_GRID: cfg.grid.zgrid = 'auto'), documented
> 
> but a Find Files search indicates that FT_PREPARE_DIPOLE_GRID no longer exists.
> 
> I don't have copies of FieldTrip older than Feb 2013 so I can't check directly but I know that my function call used to work and no longer does.
> 
> Can someone help me find a fix for this?
> 
> Any help appreciated!
> 
> Joe
> 
> --------------------------------------------------------------------------------
> 
> Joseph Dien,
> Senior Research Scientist
> University of Maryland 
> 
> E-mail: jdien07 at mac.com
> Phone: 301-226-8848
> Fax: 301-226-8811
> http://joedien.com//
> 
> 
> 
> 
> 
> 
> 
> 
> 
> 
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


--------------------------------------------------------------------------------

Joseph Dien,
Senior Research Scientist
University of Maryland 

E-mail: jdien07 at mac.com
Phone: 301-226-8848
Fax: 301-226-8811
http://joedien.com//











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From marco.porta88 at gmail.com  Thu Jun 20 14:48:18 2013
From: marco.porta88 at gmail.com (Marco Porta)
Date: Thu, 20 Jun 2013 14:48:18 +0200
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 37
In-Reply-To: <mailman.1.1371722418.14241.fieldtrip@science.ru.nl>
References: <mailman.1.1371722418.14241.fieldtrip@science.ru.nl>
Message-ID: <CAP6m0dGkRm0uo+zweS10nmv6Oj-c-_gmFapqNRDyg9TL3SVE+A@mail.gmail.com>

Dear Users and Eelke,
I have spontaneous LFP data recorded intracranially. I'm interested in
studying phase correlation between sensors and assess such correlation
within single subjects studies. Is it possible to study statistical
significance in such correlation study or should i implement my own
statistic?
Thanks,

Marco



Dear Marco,
>
> What do you mean exactly with "non event-related fields"? I presume
> there is some structure in your data that you want to consider as the
> independent variable of interest, right? Some more information on what
> you want to do would help us to help you.
>
> Best,
> Eelke
>
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From marco.porta88 at gmail.com  Fri Jun 21 14:26:12 2013
From: marco.porta88 at gmail.com (Marco Porta)
Date: Fri, 21 Jun 2013 14:26:12 +0200
Subject: [FieldTrip] statistics on non-event-related fields
Message-ID: <CAP6m0dGJTG=i9dFLsOhL4o9+wp_TXZfMYOa2917ik2TGu-dJeg@mail.gmail.com>

Dear Users and Eelke,
I have spontaneous LFP data recorded intracranially. I'm interested in studying
phase correlation between sensors and assess such correlation within single
subjects studies. Is it possible to study statistical significance in such
correlation study or should i implement my own statistic?
Thanks,

Marco



> Dear Marco,
>
> What do you mean exactly with "non event-related fields"? I presume
> there is some structure in your data that you want to consider as the
> independent variable of interest, right? Some more information on what
> you want to do would help us to help you.
>
> Best,
> Eelke
>
>
>
>
> Dear Fieldtrip experts,
> I have a question regarding the statistics. How can I statistics on non
> event-related fields in a between-trials.
> Thanks,
> Marco
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From politzerahless at gmail.com  Fri Jun 21 20:42:32 2013
From: politzerahless at gmail.com (Stephen Politzer-Ahles)
Date: Fri, 21 Jun 2013 13:42:32 -0500
Subject: [FieldTrip] Using fsaverage in the minimum norm pipeline?
Message-ID: <CAJT2k_8-nPkauRD0ciptFjPJtqbXTXv-0Xnj5GNw1aJ2LR6LJA@mail.gmail.com>

Hello everyone,

I am working through the minimum norm pipeline (
http://fieldtrip.fcdonders.nl/tutorial/minimumnormestimate) on functional
data for multiple participants; for all but one of these participants I
also have anatomical MRI. For the one participant for whom I couldn't get
an MRI, I was hoping to use the freesurfer average surface (fsaverage), but
I'm having some difficulty getting volume conduction models and
sourcespaces from this brain aligned to CTF.

Basically, I'm able to read in the data and create a sourcespace and volume
conduction model using the code below. These models seem to be aligned to
MNI (see the axes on http://i.imgur.com/g0DPs8A.png). To to re-align them
to CTF, what I tried to do was manually do ft_volumerealign on the original
anatomical MRI, and then apply that transformation matrix (which I assume
specifies the transformation from MNI to CTF) to the sourcespace and volume
conductor (in the third and fourth blocks of code below). But the resulting
sourcespace and volume conductor are clearly not aligned to CTF (see the
axes on http://i.imgur.com/MAjyDkL.png), so I assume I am doing something
wrong with the transformation matrix. I admit I do not fully understand how
the transformation matrix is supposed to work, so if anyone has any
feedback I would greatly appreciate it.

Thank you!
Steve


% Read the source space
bnd  =
ft_read_headshape('/tools/freesurfer/subjects/fsaverage/bem/fsaverage-oct-6-src.fif',
'format', 'mne_source');
sourcespace = ft_convert_units(bnd, 'mm');

% Read in the anatomical MRI, segment, and make volume conduction model
fsaverage = ft_read_mri('orig.mgz');
cfg           = [];
cfg.coordsys  = 'spm';
cfg.output    = {'skullstrip' 'brain'};
seg = ft_volumesegment( cfg, fsaverage);
cfg = []
cfg.method = 'singleshell';
cfg.tissue = 'brain';
vol = ft_prepare_headmodel( cfg, seg );

% Get a transformation matrix from MNI to CTF
cfg = [];
cfg.method = 'interactive';
seg_ctf = ft_volumerealign(cfg2, seg); % manually identify NAS, LAP, and RAP
T = seg_ctf.transform;

% Transform the sourcespace and vol
sourcespace_trans = ft_transform_geometry( T, sourcespace );
vol_trans = vol;
vol_trans.bnd = ft_transform_geometry( T, vol_trans.bnd );

% Plot the un-transformed vol and sourcespace (aligned to MNI)
figure;hold on;
ft_plot_vol(vol, 'facecolor', 'none');alpha 0.5;
ft_plot_mesh(sourcespace, 'edgecolor', 'none'); camlight

% Plot the transformed vol and sourcespace
figure;hold on;
ft_plot_vol(vol_trans, 'facecolor', 'none');alpha 0.5;
ft_plot_mesh(sourcespace_trans, 'edgecolor', 'none'); camlight



--
Stephen Politzer-Ahles
University of Kansas
Linguistics Department
http://people.ku.edu/~sjpa/
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From polomacnenad at gmail.com  Sat Jun 22 13:34:56 2013
From: polomacnenad at gmail.com (Nenad Polomac)
Date: Sat, 22 Jun 2013 13:34:56 +0200
Subject: [FieldTrip] padding of segmented data
Message-ID: <CAEk4EpFoOvobO+Ay2GQgx9k4h3g1wZAOoHoZ-t8u-qSodoYN5A@mail.gmail.com>

Dear all,

In my pipeline I need two times to filter data with ft_preprocessing. Is it
somehow possible to pad trials after segmentation? I need this in order to
avoid filter artifacts during the second filtering.

Thank you in advance!

Nenad
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From caspervanheck at gmail.com  Sat Jun 22 14:32:45 2013
From: caspervanheck at gmail.com (Casper van Heck)
Date: Sat, 22 Jun 2013 14:32:45 +0200
Subject: [FieldTrip] padding of segmented data
In-Reply-To: <CAEk4EpFoOvobO+Ay2GQgx9k4h3g1wZAOoHoZ-t8u-qSodoYN5A@mail.gmail.com>
References: <CAEk4EpFoOvobO+Ay2GQgx9k4h3g1wZAOoHoZ-t8u-qSodoYN5A@mail.gmail.com>
Message-ID: <CAJ7RtREwKrgNVCko=XkrjofHJduL64iEU0mESovdcrXqsm7M0A@mail.gmail.com>

Dear Nenad,

I think the option cfg.padding only works for that iteration of
ft_preprocessing, but what you can do, is select larger segments initially,
and then run ft_preprocessing again with smaller segments.

While you can set ft_preprocessing to apply multiple different filters in
one go (like a low-pass, a high-pass, and a DFT-filter, for example), using
a similar filter multiple times (like a high-pass filter at 4Hz, and
another at 8Hz) is usually not required, or recommended. If you do multiple
analyses on the same data (which, for example, require different filters)
you could find it useful to create multiple smaller pipelines with their
own ft_preprocessing. Debugging complex analyses can be a lot easier that
way:)

Hope this helps,

Casper


On Sat, Jun 22, 2013 at 1:34 PM, Nenad Polomac <polomacnenad at gmail.com>wrote:

> Dear all,
>
> In my pipeline I need two times to filter data with ft_preprocessing. Is
> it somehow possible to pad trials after segmentation? I need this in order
> to avoid filter artifacts during the second filtering.
>
> Thank you in advance!
>
> Nenad
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From mbj0310 at gmail.com  Mon Jun 24 06:27:47 2013
From: mbj0310 at gmail.com (Beom Jun Min)
Date: Mon, 24 Jun 2013 13:27:47 +0900
Subject: [FieldTrip] Decreased baseline level after using ICA in ERP data
Message-ID: <CA+v9jvKJnKAfsQDwoDhNVSPAKCmpOpwut8vdmFXa1akp_1WDGA@mail.gmail.com>

Dear all,

I have ERP data and now I am dealing with ICA to remove muscle and eye
artifacts.
However, I found that after ft_rejectcomponent, the baseline level of the
segmented epoch decreased. (The baselinewindow is [-0.2 0].)
The baseline level decreased even though I rejected only one component.

My script is shown below.

*%% Removing the Artifacts*
*cfg = [];
*
*cfg.component = [ ]; % to be removed component(s)*
*post_ICA_temp6 = ft_rejectcomponent(cfg, comp_detrand, data_raw);*
*
*
*%% timelocking*
*
*
*cfg = [];*
*timelock_temp6 = ft_timelockanalysis(cfg, post_ICA_temp6);*
*
*
*%% Plot*
*
*
*figure;*
*cfg = [];*
*cfg.layout = lay;*
*cfg.interactive = 'yes';*
*cfg.channel = ['all', {'-EKG', '-EMG'}];*
*ft_multiplotER(cfg, timelock_temp6)*

Is there something that I missed?

Thanks.

BJ

-- 
BeomJun Min, M.D.

Department of Medical System Engineering (DMSE)
Gwangju Institute of Science and Technology (GIST)
261 Cheomdan-gwagiro(Oryong-dong), Buk-gu, Gwangju
500-712, Republic of Korea (South)
Phone: +82-62-715-3266 / Fax: +82-62-715-3244
E-mail: mbj0310 at gmail.com, http://bmssa.gist.ac.kr
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From d.lozanosoldevilla at fcdonders.ru.nl  Mon Jun 24 10:25:24 2013
From: d.lozanosoldevilla at fcdonders.ru.nl (Lozano Soldevilla, D. (Diego))
Date: Mon, 24 Jun 2013 10:25:24 +0200 (CEST)
Subject: [FieldTrip] Decreased baseline level after using ICA in ERP data
In-Reply-To: <CA+v9jvKJnKAfsQDwoDhNVSPAKCmpOpwut8vdmFXa1akp_1WDGA@mail.gmail.com>
Message-ID: <831995030.1708865.1372062324986.JavaMail.root@sculptor.zimbra.ru.nl>

Dear Beom Jun, I see multiple scenarios why this baseline activity decrease could happen. First of all, how the component you're rejecting look like (i.e. "blink component")? Do you see this activity decrease after the baseline period? The "quality" of the ICA decomposition, how well your artifact/component of interest has been isolated by algorithm in time (i.e. blink time courses) and space (marked frontal topography), will determine the activity that later on you'll reject/select. If your decomposition is not well suited, the rejection of a particular IC activity might have "extra" activity you don't want to reject (effect of interest), might be the algorithm is not able to isolate the components of interests (i.e. artifacts) or a combination of both. To evaluate the quality of your ICA decomposition you might have a look here ( http://www.ncbi.nlm.nih.gov/pubmed/19162199 ). Basically, the authors find that the ICA decomposition improves significantly " increased by removing the mean EEG at each channel for each epoch of data rather than the mean EEG in a prestimulus baseline" . In addition (see here: http://sccn.ucsd.edu/pipermail/eeglablist/2012/004925.html ), high-pass filtering above ~1hz improve the results. It's very important to feed ICA as much relevant data as you can use. The more the data, the better the decomposition. There's a rule of thumb that says that for a reliable IC decomposition 20 time points per channel 2 is needed (see here for a reference http://www.ncbi.nlm.nih.gov/pubmed/16904745 ) I hope that helps, Diego ----- Original Message -----
> From: "Beom Jun Min" <mbj0310 at gmail.com>
> To: "FieldTrip discussion list" <fieldtrip at science.ru.nl>
> Sent: Monday, 24 June, 2013 6:27:47 AM
> Subject: [FieldTrip] Decreased baseline level after using ICA in ERP
> data
> Dear all,
> I have ERP data and now I am dealing with ICA to remove muscle and eye
> artifacts.
> However, I found that after ft_rejectcomponent, the baseline level of
> the segmented epoch decreased. (The baselinewindow is [-0.2 0].)
> The baseline level decreased even though I rejected only one
> component.
> My script is shown below.
> %% Removing the Artifacts
> cfg = [];
> cfg.component = [ ]; % to be removed component(s)
> post_ICA_temp6 = ft_rejectcomponent(cfg, comp_detrand, data_raw);
> %% timelocking
> cfg = [];
> timelock_temp6 = ft_timelockanalysis(cfg, post_ICA_temp6);
> %% Plot
> figure;
> cfg = [];
> cfg.layout = lay;
> cfg.interactive = 'yes';
> cfg.channel = ['all', {'-EKG', '-EMG'}];
> ft_multiplotER(cfg, timelock_temp6)
> Is there something that I missed?
> Thanks.
> BJ
> --
> BeomJun Min, M.D.
> Department of Medical System Engineering (DMSE)
> Gwangju Institute of Science and Technology (GIST)
> 261 Cheomdan-gwagiro(Oryong-dong), Buk-gu, Gwangju
> 500-712, Republic of Korea (South)
> Phone: +82-62-715-3266 / Fax: +82-62-715-3244
> E-mail: mbj0310 at gmail.com , http://bmssa.gist.ac.kr
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
-- PhD Student Neuronal Oscillations Group Donders Institute for Brain, Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud University Nijmegen NL-6525 EN Nijmegen The Netherlands http://www.ru.nl/people/donders/lozano-soldevilla-d/
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From jm.horschig at donders.ru.nl  Mon Jun 24 10:43:11 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Mon, 24 Jun 2013 10:43:11 +0200
Subject: [FieldTrip] padding of segmented data
In-Reply-To: <CAJ7RtREwKrgNVCko=XkrjofHJduL64iEU0mESovdcrXqsm7M0A@mail.gmail.com>
References: <CAEk4EpFoOvobO+Ay2GQgx9k4h3g1wZAOoHoZ-t8u-qSodoYN5A@mail.gmail.com>
	<CAJ7RtREwKrgNVCko=XkrjofHJduL64iEU0mESovdcrXqsm7M0A@mail.gmail.com>
Message-ID: <51C8069F.5070707@donders.ru.nl>

Hi Nenad,

what Casper said is not quite true. You can pad segmented trials, but 
you are limited in how to pad. There are different ways of padding, and 
what Casper was referring to is true data padding. Once you segmented 
your trials you cannot get back to your recorded data and attach more 
data to it. This is because filtering artifacts at edges etc would 
result in discontinuities and the like. However, there are other ways to 
achieve what you want. The most elegant way in my opinion is what Casper 
already suggested. Just for completeness, you can still pad using 
zero-padding (i.e. adding a bunch of 0s in the beginning and at the end 
of your trials). Other ways are mean-padding (pad with the mean value), 
or edge-padding (using the first/last value to padding). However, with 
all these methods you mostly also add a discontinuity, but you 
explicitly ask for that in this case :) The most elegant solution here 
might be to use mirror-padding, which is recently implemented.
See here:
http://fieldtrip.fcdonders.nl/reference/ft_preprocessing
and here:
http://fieldtrip.fcdonders.nl/reference/ft_preproc_padding

Best,
Jörn

On 6/22/2013 2:32 PM, Casper van Heck wrote:
> Dear Nenad,
>
> I think the option cfg.padding only works for that iteration of 
> ft_preprocessing, but what you can do, is select larger segments 
> initially, and then run ft_preprocessing again with smaller segments.
>
> While you can set ft_preprocessing to apply multiple different filters 
> in one go (like a low-pass, a high-pass, and a DFT-filter, for 
> example), using a similar filter multiple times (like a high-pass 
> filter at 4Hz, and another at 8Hz) is usually not required, or 
> recommended. If you do multiple analyses on the same data (which, for 
> example, require different filters) you could find it useful to create 
> multiple smaller pipelines with their own ft_preprocessing. Debugging 
> complex analyses can be a lot easier that way:)
>
> Hope this helps,
>
> Casper
>
>
> On Sat, Jun 22, 2013 at 1:34 PM, Nenad Polomac <polomacnenad at gmail.com 
> <mailto:polomacnenad at gmail.com>> wrote:
>
>     Dear all,
>
>     In my pipeline I need two times to filter data with
>     ft_preprocessing. Is it somehow possible to pad trials
>     after segmentation? I need this in order to avoid filter artifacts
>     during the second filtering.
>
>     Thank you in advance!
>
>     Nenad
>
>     _______________________________________________
>     fieldtrip mailing list
>     fieldtrip at donders.ru.nl <mailto:fieldtrip at donders.ru.nl>
>     http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands

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From polomacnenad at gmail.com  Mon Jun 24 11:02:18 2013
From: polomacnenad at gmail.com (Nenad Polomac)
Date: Mon, 24 Jun 2013 11:02:18 +0200
Subject: [FieldTrip] padding of segmented data
Message-ID: <CAEk4EpHDCCqhQvGRLShGfFU98Q2ccCsy1D=CRbadOzJf6G3ReA@mail.gmail.com>

Hi Jörn and Casper,

Thank you very for your answers
I will use Jörns suggestion. I wasn't aware that you upgraded
ft_preprocessing.
All the best!

Nenad

On 24 June 2013 10:44, <fieldtrip-request at science.ru.nl> wrote:

> Send fieldtrip mailing list submissions to
>         fieldtrip at science.ru.nl
>
> To subscribe or unsubscribe via the World Wide Web, visit
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>
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> When replying, please edit your Subject line so it is more specific
> than "Re: Contents of fieldtrip digest..."
>
>
> Today's Topics:
>
>    1. Decreased baseline level after using ICA in ERP data
>       (Beom Jun Min)
>    2. Re: Decreased baseline level after using ICA in ERP data
>       (Lozano Soldevilla, D. (Diego))
>    3. Re: padding of segmented data (J?rn M. Horschig)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Mon, 24 Jun 2013 13:27:47 +0900
> From: Beom Jun Min <mbj0310 at gmail.com>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: [FieldTrip] Decreased baseline level after using ICA in ERP
>         data
> Message-ID:
>         <
> CA+v9jvKJnKAfsQDwoDhNVSPAKCmpOpwut8vdmFXa1akp_1WDGA at mail.gmail.com>
> Content-Type: text/plain; charset="iso-8859-1"
>
> Dear all,
>
> I have ERP data and now I am dealing with ICA to remove muscle and eye
> artifacts.
> However, I found that after ft_rejectcomponent, the baseline level of the
> segmented epoch decreased. (The baselinewindow is [-0.2 0].)
> The baseline level decreased even though I rejected only one component.
>
> My script is shown below.
>
> *%% Removing the Artifacts*
> *cfg = [];
> *
> *cfg.component = [ ]; % to be removed component(s)*
> *post_ICA_temp6 = ft_rejectcomponent(cfg, comp_detrand, data_raw);*
> *
> *
> *%% timelocking*
> *
> *
> *cfg = [];*
> *timelock_temp6 = ft_timelockanalysis(cfg, post_ICA_temp6);*
> *
> *
> *%% Plot*
> *
> *
> *figure;*
> *cfg = [];*
> *cfg.layout = lay;*
> *cfg.interactive = 'yes';*
> *cfg.channel = ['all', {'-EKG', '-EMG'}];*
> *ft_multiplotER(cfg, timelock_temp6)*
>
> Is there something that I missed?
>
> Thanks.
>
> BJ
>
> --
> BeomJun Min, M.D.
>
> Department of Medical System Engineering (DMSE)
> Gwangju Institute of Science and Technology (GIST)
> 261 Cheomdan-gwagiro(Oryong-dong), Buk-gu, Gwangju
> 500-712, Republic of Korea (South)
> Phone: +82-62-715-3266 / Fax: +82-62-715-3244
> E-mail: mbj0310 at gmail.com, http://bmssa.gist.ac.kr
> -------------- next part --------------
> An HTML attachment was scrubbed...
> URL: <
> http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20130624/02dd2d57/attachment-0001.html
> >
>
> ------------------------------
>
> Message: 2
> Date: Mon, 24 Jun 2013 10:25:24 +0200 (CEST)
> From: "Lozano Soldevilla, D. (Diego)"
>         <d.lozanosoldevilla at fcdonders.ru.nl>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] Decreased baseline level after using ICA in
>         ERP data
> Message-ID:
>         <
> 831995030.1708865.1372062324986.JavaMail.root at sculptor.zimbra.ru.nl>
> Content-Type: text/plain; charset="utf-8"
>
> Dear Beom Jun, I see multiple scenarios why this baseline activity
> decrease could happen. First of all, how the component you're rejecting
> look like (i.e. "blink component")? Do you see this activity decrease after
> the baseline period? The "quality" of the ICA decomposition, how well your
> artifact/component of interest has been isolated by algorithm in time (i.e.
> blink time courses) and space (marked frontal topography), will determine
> the activity that later on you'll reject/select. If your decomposition is
> not well suited, the rejection of a particular IC activity might have
> "extra" activity you don't want to reject (effect of interest), might be
> the algorithm is not able to isolate the components of interests (i.e.
> artifacts) or a combination of both. To evaluate the quality of your ICA
> decomposition you might have a look here (
> http://www.ncbi.nlm.nih.gov/pubmed/19162199 ). Basically, the authors
> find that the ICA decomposition improves significantly " increased by
> removing the mean EEG at each channel for each epoch of data rather than
> the mean EEG in a prestimulus baseline" . In addition (see here:
> http://sccn.ucsd.edu/pipermail/eeglablist/2012/004925.html ), high-pass
> filtering above ~1hz improve the results. It's very important to feed ICA
> as much relevant data as you can use. The more the data, the better the
> decomposition. There's a rule of thumb that says that for a reliable IC
> decomposition 20 time points per channel 2 is needed (see here for a
> reference http://www.ncbi.nlm.nih.gov/pubmed/16904745 ) I hope that
> helps, Diego ----- Original Message -----
> > From: "Beom Jun Min" <mbj0310 at gmail.com>
> > To: "FieldTrip discussion list" <fieldtrip at science.ru.nl>
> > Sent: Monday, 24 June, 2013 6:27:47 AM
> > Subject: [FieldTrip] Decreased baseline level after using ICA in ERP
> > data
> > Dear all,
> > I have ERP data and now I am dealing with ICA to remove muscle and eye
> > artifacts.
> > However, I found that after ft_rejectcomponent, the baseline level of
> > the segmented epoch decreased. (The baselinewindow is [-0.2 0].)
> > The baseline level decreased even though I rejected only one
> > component.
> > My script is shown below.
> > %% Removing the Artifacts
> > cfg = [];
> > cfg.component = [ ]; % to be removed component(s)
> > post_ICA_temp6 = ft_rejectcomponent(cfg, comp_detrand, data_raw);
> > %% timelocking
> > cfg = [];
> > timelock_temp6 = ft_timelockanalysis(cfg, post_ICA_temp6);
> > %% Plot
> > figure;
> > cfg = [];
> > cfg.layout = lay;
> > cfg.interactive = 'yes';
> > cfg.channel = ['all', {'-EKG', '-EMG'}];
> > ft_multiplotER(cfg, timelock_temp6)
> > Is there something that I missed?
> > Thanks.
> > BJ
> > --
> > BeomJun Min, M.D.
> > Department of Medical System Engineering (DMSE)
> > Gwangju Institute of Science and Technology (GIST)
> > 261 Cheomdan-gwagiro(Oryong-dong), Buk-gu, Gwangju
> > 500-712, Republic of Korea (South)
> > Phone: +82-62-715-3266 / Fax: +82-62-715-3244
> > E-mail: mbj0310 at gmail.com , http://bmssa.gist.ac.kr
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> -- PhD Student Neuronal Oscillations Group Donders Institute for Brain,
> Cognition and Behaviour Centre for Cognitive Neuroimaging Radboud
> University Nijmegen NL-6525 EN Nijmegen The Netherlands
> http://www.ru.nl/people/donders/lozano-soldevilla-d/
> -------------- next part --------------
> An HTML attachment was scrubbed...
> URL: <
> http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20130624/ea1393f7/attachment-0001.html
> >
>
> ------------------------------
>
> Message: 3
> Date: Mon, 24 Jun 2013 10:43:11 +0200
> From: "J?rn M. Horschig" <jm.horschig at donders.ru.nl>
> To: fieldtrip at science.ru.nl
> Subject: Re: [FieldTrip] padding of segmented data
> Message-ID: <51C8069F.5070707 at donders.ru.nl>
> Content-Type: text/plain; charset="iso-8859-1"; Format="flowed"
>
> Hi Nenad,
>
> what Casper said is not quite true. You can pad segmented trials, but
> you are limited in how to pad. There are different ways of padding, and
> what Casper was referring to is true data padding. Once you segmented
> your trials you cannot get back to your recorded data and attach more
> data to it. This is because filtering artifacts at edges etc would
> result in discontinuities and the like. However, there are other ways to
> achieve what you want. The most elegant way in my opinion is what Casper
> already suggested. Just for completeness, you can still pad using
> zero-padding (i.e. adding a bunch of 0s in the beginning and at the end
> of your trials). Other ways are mean-padding (pad with the mean value),
> or edge-padding (using the first/last value to padding). However, with
> all these methods you mostly also add a discontinuity, but you
> explicitly ask for that in this case :) The most elegant solution here
> might be to use mirror-padding, which is recently implemented.
> See here:
> http://fieldtrip.fcdonders.nl/reference/ft_preprocessing
> and here:
> http://fieldtrip.fcdonders.nl/reference/ft_preproc_padding
>
> Best,
> J?rn
>
> On 6/22/2013 2:32 PM, Casper van Heck wrote:
> > Dear Nenad,
> >
> > I think the option cfg.padding only works for that iteration of
> > ft_preprocessing, but what you can do, is select larger segments
> > initially, and then run ft_preprocessing again with smaller segments.
> >
> > While you can set ft_preprocessing to apply multiple different filters
> > in one go (like a low-pass, a high-pass, and a DFT-filter, for
> > example), using a similar filter multiple times (like a high-pass
> > filter at 4Hz, and another at 8Hz) is usually not required, or
> > recommended. If you do multiple analyses on the same data (which, for
> > example, require different filters) you could find it useful to create
> > multiple smaller pipelines with their own ft_preprocessing. Debugging
> > complex analyses can be a lot easier that way:)
> >
> > Hope this helps,
> >
> > Casper
> >
> >
> > On Sat, Jun 22, 2013 at 1:34 PM, Nenad Polomac <polomacnenad at gmail.com
> > <mailto:polomacnenad at gmail.com>> wrote:
> >
> >     Dear all,
> >
> >     In my pipeline I need two times to filter data with
> >     ft_preprocessing. Is it somehow possible to pad trials
> >     after segmentation? I need this in order to avoid filter artifacts
> >     during the second filtering.
> >
> >     Thank you in advance!
> >
> >     Nenad
> >
> >     _______________________________________________
> >     fieldtrip mailing list
> >     fieldtrip at donders.ru.nl <mailto:fieldtrip at donders.ru.nl>
> >     http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >
> >
> >
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
> --
> J?rn M. Horschig
> PhD Student
> Donders Institute for Brain, Cognition and Behaviour
> Centre for Cognitive Neuroimaging
> Radboud University Nijmegen
> Neuronal Oscillations Group
> FieldTrip Development Team
>
> P.O. Box 9101
> NL-6500 HB Nijmegen
> The Netherlands
>
> Contact:
> E-Mail: jm.horschig at donders.ru.nl
> Tel:    +31-(0)24-36-68493
> Web: http://www.ru.nl/donders
>
> Visiting address:
> Trigon, room 2.30
> Kapittelweg 29
> NL-6525 EN Nijmegen
> The Netherlands
>
> -------------- next part --------------
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>
> ------------------------------
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
> End of fieldtrip Digest, Vol 31, Issue 41
> *****************************************
>
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From eelke.spaak at donders.ru.nl  Mon Jun 24 11:31:35 2013
From: eelke.spaak at donders.ru.nl (Eelke Spaak)
Date: Mon, 24 Jun 2013 11:31:35 +0200
Subject: [FieldTrip] statistics on non-event-related fields
In-Reply-To: <CAP6m0dGJTG=i9dFLsOhL4o9+wp_TXZfMYOa2917ik2TGu-dJeg@mail.gmail.com>
References: <CAP6m0dGJTG=i9dFLsOhL4o9+wp_TXZfMYOa2917ik2TGu-dJeg@mail.gmail.com>
Message-ID: <CABPNLUrej3zMr7F7JW1Uvbz5ogdyFORFGhKuWVqr0a2pYN=NcA@mail.gmail.com>

Dear Marco,

The FieldTrip statistics routines support permutation of condition
labels among units of observation. I guess in your data you don't
really have 'units of observation', i.e. you have continuous data of
one (or several) subjects. In that case I would recommend taking care
of the statistics outside of FieldTrip, for instance by using a
randomisation approach based on shifting time series of different
channels by different, random, amounts. The coupling values obtained
by these shifted time series can serve as a distribution under the
null hypothesis of no coupling. The usual cluster machinery can then
be applied (i.e. combining above-(nonparametric)threshold
time-frequency-channel voxels into cluster candidates, compute cluster
statistics per randomization, and compare the observed cluster
statistic to the randomization distribution). You would also need to
write this yourself, but it should not be very difficult. The
mex-files bwlabel and spm_bwlabel (distributed with FieldTrip) are
very useful; they give index labels to connected clusters in a binary
matrix.

Note, however, that there is an important caveat with the approach I
describe here. The time shifting per channel also destroys the
between-channel structure in your data that is due to electric volume
conduction. So even if you find significant connectivity by this
approach, although the connectivity would be 'real' in a sense, it
still might not be meaningful if you do not account for this volume
conduction. This is something to think about apart from the
statistics.

Hope this helps.
Best,
Eelke

On 21 June 2013 14:26, Marco Porta <marco.porta88 at gmail.com> wrote:
> Dear Users and Eelke,
> I have spontaneous LFP data recorded intracranially. I'm interested in
> studying phase correlation between sensors and assess such correlation
> within single subjects studies. Is it possible to study statistical
> significance in such correlation study or should i implement my own
> statistic?
> Thanks,
>
> Marco
>
>
>
>> Dear Marco,
>>
>> What do you mean exactly with "non event-related fields"? I presume
>> there is some structure in your data that you want to consider as the
>> independent variable of interest, right? Some more information on what
>> you want to do would help us to help you.
>>
>> Best,
>> Eelke
>>
>>
>>
>>
>> Dear Fieldtrip experts,
>> I have a question regarding the statistics. How can I statistics on non
>> event-related fields in a between-trials.
>> Thanks,
>> Marco
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


From nomeserio at gmail.com  Mon Jun 24 14:43:06 2013
From: nomeserio at gmail.com (Michele Barsotti)
Date: Mon, 24 Jun 2013 14:43:06 +0200
Subject: [FieldTrip] Loading Data into a fieldtrip structure
Message-ID: <CAGZjeH68Aq61DQBgPvVhOj2=f2ndrtWDuxFn58TKb8An4BUm7g@mail.gmail.com>

Dear FieldTrip Users,
  I'm working with eeglab since 2 years and now I would like to use also
fieldtrip. I've got many dataset in .mat format organized as [channels x
dataframe]. For each dataset I've got the channel location in a .ced file
format.
Can anyone help me to import these dataset into a fieldtrip data structure?

The channels (rows of the variable contained in the .mat file) are
organized like that:
1- time
2:17 - eeg channels
18:end - possible triggers

thank you in advance

cheers

-- 
        -Michele-
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From d.lozanosoldevilla at fcdonders.ru.nl  Mon Jun 24 14:55:18 2013
From: d.lozanosoldevilla at fcdonders.ru.nl (Diego Lozano Soldevilla)
Date: Mon, 24 Jun 2013 14:55:18 +0200
Subject: [FieldTrip] Loading Data into a fieldtrip structure
In-Reply-To: <CAGZjeH68Aq61DQBgPvVhOj2=f2ndrtWDuxFn58TKb8An4BUm7g@mail.gmail.com>
References: <CAGZjeH68Aq61DQBgPvVhOj2=f2ndrtWDuxFn58TKb8An4BUm7g@mail.gmail.com>
Message-ID: <CAEVBUjgj4FBxO-oGC5AcaS2h4V-2L=9DaGq1zbcB7a6B0CVz-A@mail.gmail.com>

Dear Michele,

You might have a look to the following FAQ:
http://fieldtrip.fcdonders.nl/faq/how_can_i_import_my_own_dataformat?s[]=import&s[]=data

I'm not sure about the state of the art of the eeglab2fieldtrip.m function
but it might help you out as well. To know more about the fieldtrip data
type field structures you need to have to work in Fieldtrip, the
ft_datatype* functions will be important for you, i.e.:

ft_datatype_freq
ft_datatype_raw
ft_datatype_sens
ft_datatype_timelock

I hope that helps

Diego






On 24 June 2013 14:43, Michele Barsotti <nomeserio at gmail.com> wrote:

> Dear FieldTrip Users,
>   I'm working with eeglab since 2 years and now I would like to use also
> fieldtrip. I've got many dataset in .mat format organized as [channels x
> dataframe]. For each dataset I've got the channel location in a .ced file
> format.
> Can anyone help me to import these dataset into a fieldtrip data structure?
>
> The channels (rows of the variable contained in the .mat file) are
> organized like that:
> 1- time
> 2:17 - eeg channels
> 18:end - possible triggers
>
> thank you in advance
>
> cheers
>
> --
>         -Michele-
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From david.schubring at uni-konstanz.de  Mon Jun 24 16:34:46 2013
From: david.schubring at uni-konstanz.de (David Schubring)
Date: Mon, 24 Jun 2013 16:34:46 +0200
Subject: [FieldTrip]  Matlab 2012/2013
In-Reply-To: <CAEVBUjgj4FBxO-oGC5AcaS2h4V-2L=9DaGq1zbcB7a6B0CVz-A@mail.gmail.com>
References: <CAGZjeH68Aq61DQBgPvVhOj2=f2ndrtWDuxFn58TKb8An4BUm7g@mail.gmail.com>
	<CAEVBUjgj4FBxO-oGC5AcaS2h4V-2L=9DaGq1zbcB7a6B0CVz-A@mail.gmail.com>
Message-ID: <51C85906.2090204@uni-konstanz.de>

Dear FieldTrip Users,

I was wondering if the incompatibility issues with fieldtrip and the 
latest MATLAB 2013a version still exist (and if so, which bugs exactly 
occur)?

(Some of our Matlab 2012a/b installations stopped working, maybe due to 
the latest java-update, and only the 2013 version still works.)

Thanks in advance and best regards,
David Schubring


From politzerahless at gmail.com  Mon Jun 24 17:19:59 2013
From: politzerahless at gmail.com (Stephen Politzer-Ahles)
Date: Mon, 24 Jun 2013 10:19:59 -0500
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 27
In-Reply-To: <mailman.200.1371117940.1243.fieldtrip@science.ru.nl>
References: <mailman.200.1371117940.1243.fieldtrip@science.ru.nl>
Message-ID: <CAJT2k_-XpQZ0diLY+pYtyOmD0R1s_0rKKRNSzfT2Ac9iuWPEbA@mail.gmail.com>

Hi everyone,

I recently tried
http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_spaceand
noticed some inconsistencies between the example code and the results;
I updated the code on the wiki but I wanted to send a message to the list
to double-check whether my changes are ok. Firstly, I had to add a call to
ft_convert_units, because otherwise the vol was expressed in mm and the
grid in cm, causing the grid to be much smaller than the volume conductor
(see http://i.imgur.com/gzct9Dm.png). Is this change ok?

The result I get is still not quite consistent with the examples shown on
that page, though; in my result, the grid is a cube (
http://i.imgur.com/NSgCFpg.png), whereas in the example the grid is
brain-shaped. I used the same Fieldtrip brain template and the same code
from the example (except for the change above), so I'm not sure if the
difference is due to different plot settings, a change in the Fieldtrip
code since this example was made, or a change in the sample brain included
in Fieldtrip since the example was made.

Best,
Steve


On Thu, Jun 13, 2013 at 5:05 AM, <fieldtrip-request at science.ru.nl> wrote:
>
> Send fieldtrip mailing list submissions to
>         fieldtrip at science.ru.nl
>
> To subscribe or unsubscribe via the World Wide Web, visit
>         http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> or, via email, send a message with subject or body 'help' to
>         fieldtrip-request at science.ru.nl
>
> You can reach the person managing the list at
>         fieldtrip-owner at science.ru.nl
>
> When replying, please edit your Subject line so it is more specific
> than "Re: Contents of fieldtrip digest..."
>
>
> Today's Topics:
>
>    1. Re: Source statistics on spatio-temporal source
>       reconstruction data (MNE) (Nicolai Mersebak)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Thu, 13 Jun 2013 12:04:34 +0200
> From: Nicolai Mersebak <nicolai at mersebak.dk>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] Source statistics on spatio-temporal source
>         reconstruction data (MNE)
> Message-ID: <6F3697BB-194F-422F-A1BF-EBBB132F805B at mersebak.dk>
> Content-Type: text/plain; charset="iso-8859-1"
>
> Thanks to all of you for your comments and ideas - they are very helpful!
>
> I ( off course :) ) have some follow up questions.
>
> I have created an ERP structure for my MNE source, so the only think
which I need and that is not straight forward is the neighbour structure.
>
> I am using the standard bem template
(fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model
and use the following code to get a grid for all subjects as I don't have
any subject specific information regarding the anatomy.
>
> cfg = [];
> cfg.grid.xgrid  = -100:10:100;
> cfg.grid.ygrid  = -100:10:100;
> cfg.grid.zgrid  = -100:10:100;
> cfg.grid.tight  = 'yes';
> cfg.grid.unit   = hdm.unit; % unit: mm
> cfg.vol        = hdm;
> grid  = ft_prepare_sourcemodel(cfg);
>
>
> @Jan-Mathijs and Stephan: I guess making a subject specific grid based on
a warped template requires anatomic information for each subject, e.g. a
MRI image like this tutorial shows:
>
http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
>
> The final grid output in the tutorial - does it have this 3D grid which
can be used as a neighbour structure ?
>
> I am not sure how to go from my cortical sheet [vertices x
coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
>
> A second thing I would like to know is, if any of you have tried to use
an atlas (e.g ALL template atlas) where the regions now are channels in the
permutation test? Going from source points to atlas regions can be done
through ft_sourcestatistics, but I am still interested in keeping the
temporal dimension. The reason to use atlas regions instead of source
points is to decrease the computation time.
>
> Best,
>
> Nicolai
>
>


On Thu, Jun 13, 2013 at 5:05 AM, <fieldtrip-request at science.ru.nl> wrote:

> Send fieldtrip mailing list submissions to
>         fieldtrip at science.ru.nl
>
> To subscribe or unsubscribe via the World Wide Web, visit
>         http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> or, via email, send a message with subject or body 'help' to
>         fieldtrip-request at science.ru.nl
>
> You can reach the person managing the list at
>         fieldtrip-owner at science.ru.nl
>
> When replying, please edit your Subject line so it is more specific
> than "Re: Contents of fieldtrip digest..."
>
>
> Today's Topics:
>
>    1. Re: Source statistics on spatio-temporal source
>       reconstruction data (MNE) (Nicolai Mersebak)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Thu, 13 Jun 2013 12:04:34 +0200
> From: Nicolai Mersebak <nicolai at mersebak.dk>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] Source statistics on spatio-temporal source
>         reconstruction data (MNE)
> Message-ID: <6F3697BB-194F-422F-A1BF-EBBB132F805B at mersebak.dk>
> Content-Type: text/plain; charset="iso-8859-1"
>
> Thanks to all of you for your comments and ideas - they are very helpful!
>
> I ( off course :) ) have some follow up questions.
>
> I have created an ERP structure for my MNE source, so the only think which
> I need and that is not straight forward is the neighbour structure.
>
> I am using the standard bem template
> (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model
> and use the following code to get a grid for all subjects as I don't have
> any subject specific information regarding the anatomy.
>
> cfg = [];
> cfg.grid.xgrid  = -100:10:100;
> cfg.grid.ygrid  = -100:10:100;
> cfg.grid.zgrid  = -100:10:100;
> cfg.grid.tight  = 'yes';
> cfg.grid.unit   = hdm.unit; % unit: mm
> cfg.vol        = hdm;
> grid  = ft_prepare_sourcemodel(cfg);
>
>
> @Jan-Mathijs and Stephan: I guess making a subject specific grid based on
> a warped template requires anatomic information for each subject, e.g. a
> MRI image like this tutorial shows:
>
> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
>
> The final grid output in the tutorial - does it have this 3D grid which
> can be used as a neighbour structure ?
>
> I am not sure how to go from my cortical sheet [vertices x
> coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
>
> A second thing I would like to know is, if any of you have tried to use an
> atlas (e.g ALL template atlas) where the regions now are channels in the
> permutation test? Going from source points to atlas regions can be done
> through ft_sourcestatistics, but I am still interested in keeping the
> temporal dimension. The reason to use atlas regions instead of source
> points is to decrease the computation time.
>
> Best,
>
> Nicolai
>
>
> Den 12/06/2013 kl. 18.58 skrev "smoratti at psi.ucm.es" <smoratti at psi.ucm.es
> >:
>
> >
> > I think Jan.Mathijs alternative suggestion is quite attractive. With the
> neighbors on a cortical sheet I also had the problems that sometimes the
> vertices do not have the same distance and then clustering may be biased to
> smaller or bigger clusters as the number of neighbors does not guarantee
> same cluster sizes. With the interpolation onto a 3D grid, you won't have
> that problem.
> >
> > best,
> >
> > Stephan
> >
> >
> > ________________________________________________________
> > Stephan Moratti, PhD
> >
> > see also: http://web.me.com/smoratti/
> >
> > Universidad Complutense de Madrid
> > Facultad de Psicolog?a
> > Departamento de Psicolog?a B?sica I
> > Campus de Somosaguas
> > 28223 Pozuelo de Alarc?n (Madrid)
> > Spain
> >
> > and
> >
> > Center for Biomedical Technology
> > Laboratory for Cognitive and Computational Neuroscience
> > Parque Cient?fico y Tecnol?gico de la Universidad Politecnica de Madrid
> > Campus Montegancedo
> > 28223 Pozuelo de Alarc?n (Madrid)
> > Spain
> >
> >
> > email: smoratti at psi.ucm.es
> > Tel.:    +34 679219982
> >
> > El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribi?:
> >
> >> An alternative would be to interpolate the cortical sheet to a 3D grid
> (where the grid is defined for each subject based on a warped template grid
> defined in a standard space), and then do clustering using a regular 3D
> spatial neighbourhood structure. The rationale being that two vertices on
> the sheet may appear as disconnected  (e.g. being on two sides of a sulcus)
> whereas, given the poor spatial resolution, they belong to the same spatial
> blob.
> >>
> >> Best,
> >> Jan-Mathijs
> >>
> >> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
> >>
> >>> Dear Nicolai,
> >>>
> >>> Indeed I have used ft_timelockstatistics for minimum norm source data.
> The trick is to put the source level data into a ERF structure. Determining
> the neighbors of a source surface with vertices is not trivial. However I
> used tess_vertconn.m from the BrainStorm toolbox to get the connectivity
> matrix that tells you who is a neighbor. This you can feed into
> timelockstats.
> >>>
> >>> Hope that helps,
> >>>
> >>> Stephan
> >>>
> >>> ________________________________________________________
> >>> Stephan Moratti, PhD
> >>>
> >>> see also: http://web.me.com/smoratti/
> >>>
> >>> Universidad Complutense de Madrid
> >>> Facultad de Psicolog?a
> >>> Departamento de Psicolog?a B?sica I
> >>> Campus de Somosaguas
> >>> 28223 Pozuelo de Alarc?n (Madrid)
> >>> Spain
> >>>
> >>> and
> >>>
> >>> Center for Biomedical Technology
> >>> Laboratory for Cognitive and Computational Neuroscience
> >>> Parque Cient?fico y Tecnol?gico de la Universidad Politecnica de Madrid
> >>> Campus Montegancedo
> >>> 28223 Pozuelo de Alarc?n (Madrid)
> >>> Spain
> >>>
> >>>
> >>> email: smoratti at psi.ucm.es
> >>> Tel.:    +34 679219982
> >>>
> >>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribi?:
> >>>
> >>>> Dear all,
> >>>>
> >>>> I have a question concerning the usage of ft_sourcegrandaverage and
> ft_sourcestatistics.
> >>>>
> >>>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal
> source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and
> 897 time points.
> >>>>
> >>>> Now I would like to use the cluster-based permutation test on my
> source reconstructed data. However it seems like ft_sourcegrandaverage and
> ft_sourcestatistics don't support source level time courses. E.g when I am
> using ft_sourcegrandaverage I am getting the following error:
> >>>>
> >>>> Error in ft_sourcegrandaverage (line 158)
> >>>>   dat(:,i) = tmp(:);
> >>>>
> >>>> Looking into the code:
> >>>>
> >>>>   for i=1:Nsubject
> >>>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter,
> varargin{i}));
> >>>>     dat(:,i) = tmp(:);
> >>>>     tmp = getsubfield(varargin{i}, 'inside');
> >>>>     inside(tmp,i) = 1;
> >>>>   end
> >>>>
> >>>> I see that "tmp" are getting the structure [N_sources x timepoints]
> from source.avg.pow for one subject, where "dat" requires the structure
> [N_sources x 1].
> >>>>
> >>>> I seached the mailing list for similar issues and found this thread:
> >>>>
> >>>>
> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
> >>>>
> >>>> Since I am interested in using the temporal dimension in my
> statistics, I would like to know if it is still not possible to use
> spatio-temporal source reconstructed data in ft_sourcestatistics and
> ft_sourcegrandaverage ?
> >>>>
> >>>> Or if any have succeeded in using the cluster-based permutation test
> on source level also including the temporal dimension ?
> >>>>
> >>>> Alternative I was thinking that I might could use
> ft_timelockstatistics, where I substituted the channels with sources, e.g
> instead of having 64 channels, I would now have 4050 "channels".
> >>>> If so I need to calculate a label structure and an appropriate
> neighbor structure, which I guess is possible as I have all the 3D
> coordinates for each source, e.g in leadfield.pos ?
> >>>> I know this is a work around solution, but have anyone tried or have
> any experience using such an approach ?
> >>>>
> >>>> Best,
> >>>>
> >>>> Nicolai
> >>>>
> >>>> _______________________________________________
> >>>> fieldtrip mailing list
> >>>> fieldtrip at donders.ru.nl
> >>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >>>
> >>> _______________________________________________
> >>> fieldtrip mailing list
> >>> fieldtrip at donders.ru.nl
> >>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >>
> >> Jan-Mathijs Schoffelen, MD PhD
> >>
> >> Donders Institute for Brain, Cognition and Behaviour,
> >> Centre for Cognitive Neuroimaging,
> >> Radboud University Nijmegen, The Netherlands
> >>
> >> Max Planck Institute for Psycholinguistics,
> >> Nijmegen, The Netherlands
> >>
> >> J.Schoffelen at donders.ru.nl
> >> Telephone: +31-24-3614793
> >>
> >> http://www.hettaligebrein.nl
> >>
> >> _______________________________________________
> >> fieldtrip mailing list
> >> fieldtrip at donders.ru.nl
> >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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>
> ------------------------------
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
> End of fieldtrip Digest, Vol 31, Issue 27
> *****************************************
>



-- 
Stephen Politzer-Ahles
University of Kansas
Linguistics Department
http://people.ku.edu/~sjpa/
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From a.stolk at fcdonders.ru.nl  Mon Jun 24 20:11:26 2013
From: a.stolk at fcdonders.ru.nl (Stolk, A.)
Date: Mon, 24 Jun 2013 20:11:26 +0200 (CEST)
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 27
In-Reply-To: <CAJT2k_-XpQZ0diLY+pYtyOmD0R1s_0rKKRNSzfT2Ac9iuWPEbA@mail.gmail.com>
Message-ID: <331233946.1725662.1372097486678.JavaMail.root@sculptor.zimbra.ru.nl>

Hi Steve, With respect to the cube vs. brain-shaped grid; this seems to be plotting-related? template_grid.inside in the snippet of code below selects only the grid points that have been determined as inside the brain, but with a negative inwardshift, hence it's also outside. ft_plot_mesh ( template_grid. pos ( template_grid. inside ,: ) ) ; % taken from the wiki Hopefully someone else has up-to-date knowledge to answer your question pertaining to the units (mm vs. cm) of the volume conductor and the source model. Best regards, Arjen ----- Oorspronkelijk bericht -----
> Van: "Stephen Politzer-Ahles" <politzerahless at gmail.com>
> Aan: fieldtrip at science.ru.nl
> Verzonden: Maandag 24 juni 2013 17:19:59
> Onderwerp: Re: [FieldTrip] fieldtrip Digest, Vol 31, Issue 27
> Hi everyone,
> I recently tried
> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space
> and noticed some inconsistencies between the example code and the
> results; I updated the code on the wiki but I wanted to send a message
> to the list to double-check whether my changes are ok. Firstly, I had
> to add a call to ft_convert_units, because otherwise the vol was
> expressed in mm and the grid in cm, causing the grid to be much
> smaller than the volume conductor (see http://i.imgur.com/gzct9Dm.png
> ). Is this change ok?
> The result I get is still not quite consistent with the examples shown
> on that page, though; in my result, the grid is a cube (
> http://i.imgur.com/NSgCFpg.png ), whereas in the example the grid is
> brain-shaped. I used the same Fieldtrip brain template and the same
> code from the example (except for the change above), so I'm not sure
> if the difference is due to different plot settings, a change in the
> Fieldtrip code since this example was made, or a change in the sample
> brain included in Fieldtrip since the example was made.
> Best,
> Steve
> On Thu, Jun 13, 2013 at 5:05 AM, < fieldtrip-request at science.ru.nl >
> wrote:
> >
> > Send fieldtrip mailing list submissions to
> > fieldtrip at science.ru.nl
> >
> > To subscribe or unsubscribe via the World Wide Web, visit
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > or, via email, send a message with subject or body 'help' to
> > fieldtrip-request at science.ru.nl
> >
> > You can reach the person managing the list at
> > fieldtrip-owner at science.ru.nl
> >
> > When replying, please edit your Subject line so it is more specific
> > than "Re: Contents of fieldtrip digest..."
> >
> >
> > Today's Topics:
> >
> > 1. Re: Source statistics on spatio-temporal source
> > reconstruction data (MNE) (Nicolai Mersebak)
> >
> >
> > ----------------------------------------------------------------------
> >
> > Message: 1
> > Date: Thu, 13 Jun 2013 12:04:34 +0200
> > From: Nicolai Mersebak < nicolai at mersebak.dk >
> > To: FieldTrip discussion list < fieldtrip at science.ru.nl >
> > Subject: Re: [FieldTrip] Source statistics on spatio-temporal source
> > reconstruction data (MNE)
> > Message-ID: < 6F3697BB-194F-422F-A1BF-EBBB132F805B at mersebak.dk >
> > Content-Type: text/plain; charset="iso-8859-1"
> >
> > Thanks to all of you for your comments and ideas - they are very
> > helpful!
> >
> > I ( off course :) ) have some follow up questions.
> >
> > I have created an ERP structure for my MNE source, so the only think
> > which I need and that is not straight forward is the neighbour
> > structure.
> >
> > I am using the standard bem template
> > (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head
> > model and use the following code to get a grid for all subjects as I
> > don't have any subject specific information regarding the anatomy.
> >
> > cfg = [];
> > cfg.grid.xgrid = -100:10:100;
> > cfg.grid.ygrid = -100:10:100;
> > cfg.grid.zgrid = -100:10:100;
> > cfg.grid.tight = 'yes';
> > cfg.grid.unit = hdm.unit; % unit: mm
> > cfg.vol = hdm;
> > grid = ft_prepare_sourcemodel(cfg);
> >
> >
> > @Jan-Mathijs and Stephan: I guess making a subject specific grid
> > based on a warped template requires anatomic information for each
> > subject, e.g. a MRI image like this tutorial shows:
> > http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
> >
> > The final grid output in the tutorial - does it have this 3D grid
> > which can be used as a neighbour structure ?
> >
> > I am not sure how to go from my cortical sheet [vertices x
> > coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour
> > structure ?
> >
> > A second thing I would like to know is, if any of you have tried to
> > use an atlas (e.g ALL template atlas) where the regions now are
> > channels in the permutation test? Going from source points to atlas
> > regions can be done through ft_sourcestatistics, but I am still
> > interested in keeping the temporal dimension. The reason to use
> > atlas regions instead of source points is to decrease the
> > computation time.
> >
> > Best,
> >
> > Nicolai
> >
> >
> On Thu, Jun 13, 2013 at 5:05 AM, < fieldtrip-request at science.ru.nl >
> wrote:
> > Send fieldtrip mailing list submissions to
> > fieldtrip at science.ru.nl
> > To subscribe or unsubscribe via the World Wide Web, visit
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > or, via email, send a message with subject or body 'help' to
> > fieldtrip-request at science.ru.nl
> > You can reach the person managing the list at
> > fieldtrip-owner at science.ru.nl
> > When replying, please edit your Subject line so it is more specific
> > than "Re: Contents of fieldtrip digest..."
> > Today's Topics:
> > 1. Re: Source statistics on spatio-temporal source
> > reconstruction data (MNE) (Nicolai Mersebak)
> > ----------------------------------------------------------------------
> > Message: 1
> > Date: Thu, 13 Jun 2013 12:04:34 +0200
> > From: Nicolai Mersebak < nicolai at mersebak.dk >
> > To: FieldTrip discussion list < fieldtrip at science.ru.nl >
> > Subject: Re: [FieldTrip] Source statistics on spatio-temporal source
> > reconstruction data (MNE)
> > Message-ID: < 6F3697BB-194F-422F-A1BF-EBBB132F805B at mersebak.dk >
> > Content-Type: text/plain; charset="iso-8859-1"
> > Thanks to all of you for your comments and ideas - they are very
> > helpful!
> > I ( off course :) ) have some follow up questions.
> > I have created an ERP structure for my MNE source, so the only think
> > which I need and that is not straight forward is the neighbour
> > structure.
> > I am using the standard bem template
> > (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head
> > model and use the following code to get a grid for all subjects as I
> > don't have any subject specific information regarding the anatomy.
> > cfg = [];
> > cfg.grid.xgrid = -100:10:100;
> > cfg.grid.ygrid = -100:10:100;
> > cfg.grid.zgrid = -100:10:100;
> > cfg.grid.tight = 'yes';
> > cfg.grid.unit = hdm.unit; % unit: mm
> > cfg.vol = hdm;
> > grid = ft_prepare_sourcemodel(cfg);
> > @Jan-Mathijs and Stephan: I guess making a subject specific grid
> > based
> > on a warped template requires anatomic information for each subject,
> > e.g. a MRI image like this tutorial shows:
> > http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
> > The final grid output in the tutorial - does it have this 3D grid
> > which can be used as a neighbour structure ?
> > I am not sure how to go from my cortical sheet [vertices x
> > coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour
> > structure ?
> > A second thing I would like to know is, if any of you have tried to
> > use an atlas (e.g ALL template atlas) where the regions now are
> > channels in the permutation test? Going from source points to atlas
> > regions can be done through ft_sourcestatistics, but I am still
> > interested in keeping the temporal dimension. The reason to use
> > atlas
> > regions instead of source points is to decrease the computation
> > time.
> > Best,
> > Nicolai
> > Den 12/06/2013 kl. 18.58 skrev " smoratti at psi.ucm.es " <
> > smoratti at psi.ucm.es >:
> > >
> > > I think Jan.Mathijs alternative suggestion is quite attractive.
> > > With
> > > the neighbors on a cortical sheet I also had the problems that
> > > sometimes the vertices do not have the same distance and then
> > > clustering may be biased to smaller or bigger clusters as the
> > > number
> > > of neighbors does not guarantee same cluster sizes. With the
> > > interpolation onto a 3D grid, you won't have that problem.
> > >
> > > best,
> > >
> > > Stephan
> > >
> > >
> > > ________________________________________________________
> > > Stephan Moratti, PhD
> > >
> > > see also: http://web.me.com/smoratti/
> > >
> > > Universidad Complutense de Madrid
> > > Facultad de Psicolog?a
> > > Departamento de Psicolog?a B?sica I
> > > Campus de Somosaguas
> > > 28223 Pozuelo de Alarc?n (Madrid)
> > > Spain
> > >
> > > and
> > >
> > > Center for Biomedical Technology
> > > Laboratory for Cognitive and Computational Neuroscience
> > > Parque Cient?fico y Tecnol?gico de la Universidad Politecnica de
> > > Madrid
> > > Campus Montegancedo
> > > 28223 Pozuelo de Alarc?n (Madrid)
> > > Spain
> > >
> > >
> > > email: smoratti at psi.ucm.es
> > > Tel.: +34 679219982
> > >
> > > El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribi?:
> > >
> > >> An alternative would be to interpolate the cortical sheet to a 3D
> > >> grid (where the grid is defined for each subject based on a
> > >> warped
> > >> template grid defined in a standard space), and then do
> > >> clustering
> > >> using a regular 3D spatial neighbourhood structure. The rationale
> > >> being that two vertices on the sheet may appear as disconnected
> > >> (e.g. being on two sides of a sulcus) whereas, given the poor
> > >> spatial resolution, they belong to the same spatial blob.
> > >>
> > >> Best,
> > >> Jan-Mathijs
> > >>
> > >> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
> > >>
> > >>> Dear Nicolai,
> > >>>
> > >>> Indeed I have used ft_timelockstatistics for minimum norm source
> > >>> data. The trick is to put the source level data into a ERF
> > >>> structure. Determining the neighbors of a source surface with
> > >>> vertices is not trivial. However I used tess_vertconn.m from the
> > >>> BrainStorm toolbox to get the connectivity matrix that tells you
> > >>> who is a neighbor. This you can feed into timelockstats.
> > >>>
> > >>> Hope that helps,
> > >>>
> > >>> Stephan
> > >>>
> > >>> ________________________________________________________
> > >>> Stephan Moratti, PhD
> > >>>
> > >>> see also: http://web.me.com/smoratti/
> > >>>
> > >>> Universidad Complutense de Madrid
> > >>> Facultad de Psicolog?a
> > >>> Departamento de Psicolog?a B?sica I
> > >>> Campus de Somosaguas
> > >>> 28223 Pozuelo de Alarc?n (Madrid)
> > >>> Spain
> > >>>
> > >>> and
> > >>>
> > >>> Center for Biomedical Technology
> > >>> Laboratory for Cognitive and Computational Neuroscience
> > >>> Parque Cient?fico y Tecnol?gico de la Universidad Politecnica de
> > >>> Madrid
> > >>> Campus Montegancedo
> > >>> 28223 Pozuelo de Alarc?n (Madrid)
> > >>> Spain
> > >>>
> > >>>
> > >>> email: smoratti at psi.ucm.es
> > >>> Tel.: +34 679219982
> > >>>
> > >>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribi?:
> > >>>
> > >>>> Dear all,
> > >>>>
> > >>>> I have a question concerning the usage of ft_sourcegrandaverage
> > >>>> and ft_sourcestatistics.
> > >>>>
> > >>>> After using ft_sourceanalysis (method: MNE), I get
> > >>>> spatio-temporal source reconstructed data in source.avg.pow
> > >>>> (4050
> > >>>> x 897): 4050 sources and 897 time points.
> > >>>>
> > >>>> Now I would like to use the cluster-based permutation test on
> > >>>> my
> > >>>> source reconstructed data. However it seems like
> > >>>> ft_sourcegrandaverage and ft_sourcestatistics don't support
> > >>>> source level time courses. E.g when I am using
> > >>>> ft_sourcegrandaverage I am getting the following error:
> > >>>>
> > >>>> Error in ft_sourcegrandaverage (line 158)
> > >>>> dat(:,i) = tmp(:);
> > >>>>
> > >>>> Looking into the code:
> > >>>>
> > >>>> for i=1:Nsubject
> > >>>> tmp = getsubfield(varargin{i},
> > >>>> parameterselection(cfg.parameter,
> > >>>> varargin{i}));
> > >>>> dat(:,i) = tmp(:);
> > >>>> tmp = getsubfield(varargin{i}, 'inside');
> > >>>> inside(tmp,i) = 1;
> > >>>> end
> > >>>>
> > >>>> I see that "tmp" are getting the structure [N_sources x
> > >>>> timepoints] from source.avg.pow for one subject, where "dat"
> > >>>> requires the structure [N_sources x 1].
> > >>>>
> > >>>> I seached the mailing list for similar issues and found this
> > >>>> thread:
> > >>>>
> > >>>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
> > >>>>
> > >>>> Since I am interested in using the temporal dimension in my
> > >>>> statistics, I would like to know if it is still not possible to
> > >>>> use spatio-temporal source reconstructed data in
> > >>>> ft_sourcestatistics and ft_sourcegrandaverage ?
> > >>>>
> > >>>> Or if any have succeeded in using the cluster-based permutation
> > >>>> test on source level also including the temporal dimension ?
> > >>>>
> > >>>> Alternative I was thinking that I might could use
> > >>>> ft_timelockstatistics, where I substituted the channels with
> > >>>> sources, e.g instead of having 64 channels, I would now have
> > >>>> 4050
> > >>>> "channels".
> > >>>> If so I need to calculate a label structure and an appropriate
> > >>>> neighbor structure, which I guess is possible as I have all the
> > >>>> 3D coordinates for each source, e.g in leadfield.pos ?
> > >>>> I know this is a work around solution, but have anyone tried or
> > >>>> have any experience using such an approach ?
> > >>>>
> > >>>> Best,
> > >>>>
> > >>>> Nicolai
> > >>>>
> > >>>> _______________________________________________
> > >>>> fieldtrip mailing list
> > >>>> fieldtrip at donders.ru.nl
> > >>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > >>>
> > >>> _______________________________________________
> > >>> fieldtrip mailing list
> > >>> fieldtrip at donders.ru.nl
> > >>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > >>
> > >> Jan-Mathijs Schoffelen, MD PhD
> > >>
> > >> Donders Institute for Brain, Cognition and Behaviour,
> > >> Centre for Cognitive Neuroimaging,
> > >> Radboud University Nijmegen, The Netherlands
> > >>
> > >> Max Planck Institute for Psycholinguistics,
> > >> Nijmegen, The Netherlands
> > >>
> > >> J.Schoffelen at donders.ru.nl
> > >> Telephone: +31-24-3614793
> > >>
> > >> http://www.hettaligebrein.nl
> > >>
> > >> _______________________________________________
> > >> fieldtrip mailing list
> > >> fieldtrip at donders.ru.nl
> > >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > >
> > > _______________________________________________
> > > fieldtrip mailing list
> > > fieldtrip at donders.ru.nl
> > > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
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> > >
> > ------------------------------
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > End of fieldtrip Digest, Vol 31, Issue 27
> > *****************************************
> --
> Stephen Politzer-Ahles
> University of Kansas
> Linguistics Department
> http://people.ku.edu/~sjpa/
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
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From politzerahless at gmail.com  Mon Jun 24 20:29:01 2013
From: politzerahless at gmail.com (Stephen Politzer-Ahles)
Date: Mon, 24 Jun 2013 13:29:01 -0500
Subject: [FieldTrip] Source statistics on spatio-temporal source
	reconstruction data (MNE)
Message-ID: <CAJT2k__aWw_68dy7K2MnGHkP2cEEyredBduU+VgoSVatx=_hYw@mail.gmail.com>

Hi Arjen,

Thanks, I also just tried that (after noticing that code in a later part of
the example) and can confirm that that change makes the plot come out like
the plot in the example. I updated the wiki accordingly.

Best,
Steve

> Message: 1
> Date: Mon, 24 Jun 2013 20:11:26 +0200 (CEST)
> From: "Stolk, A." <a.stolk at fcdonders.ru.nl>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] fieldtrip Digest, Vol 31, Issue 27
> Message-ID:
>         <
331233946.1725662.1372097486678.JavaMail.root at sculptor.zimbra.ru.nl>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Steve, With respect to the cube vs. brain-shaped grid; this seems to
be plotting-related? template_grid.inside in the snippet of code below
selects only the grid points that have been determined as inside the brain,
but with a negative inwardshift, hence it's also outside. ft_plot_mesh (
template_grid. pos ( template_grid. inside ,: ) ) ; % taken from the wiki
Hopefully someone else has up-to-date knowledge to answer your question
pertaining to the units (mm vs. cm) of the volume conductor and the source
model. Best regards, Arjen ----- Oorspronkelijk bericht -----
> > Van: "Stephen Politzer-Ahles" <politzerahless at gmail.com>
> > Aan: fieldtrip at science.ru.nl
> > Verzonden: Maandag 24 juni 2013 17:19:59
> > Onderwerp: Re: [FieldTrip] fieldtrip Digest, Vol 31, Issue 27
> > Hi everyone,
> > I recently tried
> >
http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space
> > and noticed some inconsistencies between the example code and the
> > results; I updated the code on the wiki but I wanted to send a message
> > to the list to double-check whether my changes are ok. Firstly, I had
> > to add a call to ft_convert_units, because otherwise the vol was
> > expressed in mm and the grid in cm, causing the grid to be much
> > smaller than the volume conductor (see http://i.imgur.com/gzct9Dm.png
> > ). Is this change ok?
> > The result I get is still not quite consistent with the examples shown
> > on that page, though; in my result, the grid is a cube (
> > http://i.imgur.com/NSgCFpg.png ), whereas in the example the grid is
> > brain-shaped. I used the same Fieldtrip brain template and the same
> > code from the example (except for the change above), so I'm not sure
> > if the difference is due to different plot settings, a change in the
> > Fieldtrip code since this example was made, or a change in the sample
> > brain included in Fieldtrip since the example was made.
> > Best,
> > Steve
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From joramvandriel at gmail.com  Tue Jun 25 09:17:27 2013
From: joramvandriel at gmail.com (Joram van Driel)
Date: Tue, 25 Jun 2013 09:17:27 +0200
Subject: [FieldTrip] fieldtrip Digest, Vol 31, Issue 27
In-Reply-To: <331233946.1725662.1372097486678.JavaMail.root@sculptor.zimbra.ru.nl>
References: <CAJT2k_-XpQZ0diLY+pYtyOmD0R1s_0rKKRNSzfT2Ac9iuWPEbA@mail.gmail.com>
	<331233946.1725662.1372097486678.JavaMail.root@sculptor.zimbra.ru.nl>
Message-ID: <CAKk__WW9+yaz6FwUSRQ-4SqSCy66-PbYsWxDkpe7TO=TvxH_mA@mail.gmail.com>

Hi Steve,
I had the same problem a while ago.

First of all, you need to take care of all the necessary ingredients to be
in cm before computing the volume conduction model and the leadfield
matrix, by using ft_convertunits.

Second, I also first had a brain-shaped grid, which was not a plot-related
problem; I noticed during the computation of the leadfield in the Matlab
command lines that it estimated 0 dipoles outside, and x-number of dipoles
inside the brain, which already made me suspicious. Check whether you get
this as well, then you know it's not a plotting problem.
In the end I managed to get a x inside and x outside number of dipoles, and
I think the difference was that I first used ft_prepare_singleshell (which
gave me the weird brain-shaped results with 0 dipoles outside), while I
think you should use ft_prepare_headmodel with cfg.method='singleshell'.
Maybe it doesn't matter at all, and the problem lies somewhere else, but
for me it worked and I got a nice cube-shaped grid in the end.

Hope this helps.
Best,
Joram


On Mon, Jun 24, 2013 at 8:11 PM, Stolk, A. <a.stolk at fcdonders.ru.nl> wrote:

> Hi Steve,
>
> With respect to the cube vs. brain-shaped grid; this seems to be
> plotting-related? template_grid.inside in the snippet of code below selects
> only the grid points that have been determined as inside the brain, but
> with a negative inwardshift, hence it's also outside.
>
> ft_plot_mesh(template_grid.pos(template_grid.inside,:)); % taken from the
> wiki
>
> Hopefully someone else has up-to-date knowledge to answer your question
> pertaining to the units (mm vs. cm) of the volume conductor and the source
> model.
>
> Best regards,
> Arjen
>
> ------------------------------
>
> *Van: *"Stephen Politzer-Ahles" <politzerahless at gmail.com>
> *Aan: *fieldtrip at science.ru.nl
> *Verzonden: *Maandag 24 juni 2013 17:19:59
> *Onderwerp: *Re: [FieldTrip] fieldtrip Digest, Vol 31, Issue 27
>
>
> Hi everyone,
>
> I recently tried
> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_spaceand noticed some inconsistencies between the example code and the results;
> I updated the code on the wiki but I wanted to send a message to the list
> to double-check whether my changes are ok. Firstly, I had to add a call to
> ft_convert_units, because otherwise the vol was expressed in mm and the
> grid in cm, causing the grid to be much smaller than the volume conductor
> (see http://i.imgur.com/gzct9Dm.png). Is this change ok?
>
> The result I get is still not quite consistent with the examples shown on
> that page, though; in my result, the grid is a cube (
> http://i.imgur.com/NSgCFpg.png), whereas in the example the grid is
> brain-shaped. I used the same Fieldtrip brain template and the same code
> from the example (except for the change above), so I'm not sure if the
> difference is due to different plot settings, a change in the Fieldtrip
> code since this example was made, or a change in the sample brain included
> in Fieldtrip since the example was made.
>
> Best,
> Steve
>
>
> On Thu, Jun 13, 2013 at 5:05 AM, <fieldtrip-request at science.ru.nl> wrote:
> >
> > Send fieldtrip mailing list submissions to
> >         fieldtrip at science.ru.nl
> >
> > To subscribe or unsubscribe via the World Wide Web, visit
> >         http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> > or, via email, send a message with subject or body 'help' to
> >         fieldtrip-request at science.ru.nl
> >
> > You can reach the person managing the list at
> >         fieldtrip-owner at science.ru.nl
> >
> > When replying, please edit your Subject line so it is more specific
> > than "Re: Contents of fieldtrip digest..."
> >
> >
> > Today's Topics:
> >
> >    1. Re: Source statistics on spatio-temporal source
> >       reconstruction data (MNE) (Nicolai Mersebak)
> >
> >
> > ----------------------------------------------------------------------
> >
> > Message: 1
> > Date: Thu, 13 Jun 2013 12:04:34 +0200
> > From: Nicolai Mersebak <nicolai at mersebak.dk>
> > To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> > Subject: Re: [FieldTrip] Source statistics on spatio-temporal source
> >         reconstruction data (MNE)
> > Message-ID: <6F3697BB-194F-422F-A1BF-EBBB132F805B at mersebak.dk>
> > Content-Type: text/plain; charset="iso-8859-1"
> >
> > Thanks to all of you for your comments and ideas - they are very helpful!
> >
> > I ( off course :) ) have some follow up questions.
> >
> > I have created an ERP structure for my MNE source, so the only think
> which I need and that is not straight forward is the neighbour structure.
> >
> > I am using the standard bem template
> (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model
> and use the following code to get a grid for all subjects as I don't have
> any subject specific information regarding the anatomy.
> >
> > cfg = [];
> > cfg.grid.xgrid  = -100:10:100;
> > cfg.grid.ygrid  = -100:10:100;
> > cfg.grid.zgrid  = -100:10:100;
> > cfg.grid.tight  = 'yes';
> > cfg.grid.unit   = hdm.unit; % unit: mm
> > cfg.vol        = hdm;
> > grid  = ft_prepare_sourcemodel(cfg);
> >
> >
> > @Jan-Mathijs and Stephan: I guess making a subject specific grid based
> on a warped template requires anatomic information for each subject, e.g. a
> MRI image like this tutorial shows:
> >
> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
> >
> > The final grid output in the tutorial - does it have this 3D grid which
> can be used as a neighbour structure ?
> >
> > I am not sure how to go from my cortical sheet [vertices x
> coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
> >
> > A second thing I would like to know is, if any of you have tried to use
> an atlas (e.g ALL template atlas) where the regions now are channels in the
> permutation test? Going from source points to atlas regions can be done
> through ft_sourcestatistics, but I am still interested in keeping the
> temporal dimension. The reason to use atlas regions instead of source
> points is to decrease the computation time.
> >
> > Best,
> >
> > Nicolai
> >
> >
>
>
> On Thu, Jun 13, 2013 at 5:05 AM, <fieldtrip-request at science.ru.nl> wrote:
>
>> Send fieldtrip mailing list submissions to
>>         fieldtrip at science.ru.nl
>>
>> To subscribe or unsubscribe via the World Wide Web, visit
>>         http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> or, via email, send a message with subject or body 'help' to
>>         fieldtrip-request at science.ru.nl
>>
>> You can reach the person managing the list at
>>         fieldtrip-owner at science.ru.nl
>>
>> When replying, please edit your Subject line so it is more specific
>> than "Re: Contents of fieldtrip digest..."
>>
>>
>> Today's Topics:
>>
>>    1. Re: Source statistics on spatio-temporal source
>>       reconstruction data (MNE) (Nicolai Mersebak)
>>
>>
>> ----------------------------------------------------------------------
>>
>> Message: 1
>> Date: Thu, 13 Jun 2013 12:04:34 +0200
>> From: Nicolai Mersebak <nicolai at mersebak.dk>
>> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
>> Subject: Re: [FieldTrip] Source statistics on spatio-temporal source
>>         reconstruction data (MNE)
>> Message-ID: <6F3697BB-194F-422F-A1BF-EBBB132F805B at mersebak.dk>
>> Content-Type: text/plain; charset="iso-8859-1"
>>
>> Thanks to all of you for your comments and ideas - they are very helpful!
>>
>> I ( off course :) ) have some follow up questions.
>>
>> I have created an ERP structure for my MNE source, so the only think
>> which I need and that is not straight forward is the neighbour structure.
>>
>> I am using the standard bem template
>> (fieldtrip-20130124/template/headmodel/standard_bem.mat) as a head model
>> and use the following code to get a grid for all subjects as I don't have
>> any subject specific information regarding the anatomy.
>>
>> cfg = [];
>> cfg.grid.xgrid  = -100:10:100;
>> cfg.grid.ygrid  = -100:10:100;
>> cfg.grid.zgrid  = -100:10:100;
>> cfg.grid.tight  = 'yes';
>> cfg.grid.unit   = hdm.unit; % unit: mm
>> cfg.vol        = hdm;
>> grid  = ft_prepare_sourcemodel(cfg);
>>
>>
>> @Jan-Mathijs and Stephan: I guess making a subject specific grid based on
>> a warped template requires anatomic information for each subject, e.g. a
>> MRI image like this tutorial shows:
>>
>> http://fieldtrip.fcdonders.nl/example/create_single-subject_grids_in_individual_head_space_that_are_all_aligned_in_mni_space?s%5B
>>
>> The final grid output in the tutorial - does it have this 3D grid which
>> can be used as a neighbour structure ?
>>
>> I am not sure how to go from my cortical sheet [vertices x
>> coordinates(x,y,z)] to a 3D grid, which I can use as a neighbour structure ?
>>
>> A second thing I would like to know is, if any of you have tried to use
>> an atlas (e.g ALL template atlas) where the regions now are channels in the
>> permutation test? Going from source points to atlas regions can be done
>> through ft_sourcestatistics, but I am still interested in keeping the
>> temporal dimension. The reason to use atlas regions instead of source
>> points is to decrease the computation time.
>>
>> Best,
>>
>> Nicolai
>>
>>
>> Den 12/06/2013 kl. 18.58 skrev "smoratti at psi.ucm.es" <smoratti at psi.ucm.es
>> >:
>>
>> >
>> > I think Jan.Mathijs alternative suggestion is quite attractive. With
>> the neighbors on a cortical sheet I also had the problems that sometimes
>> the vertices do not have the same distance and then clustering may be
>> biased to smaller or bigger clusters as the number of neighbors does not
>> guarantee same cluster sizes. With the interpolation onto a 3D grid, you
>> won't have that problem.
>> >
>> > best,
>> >
>> > Stephan
>> >
>> >
>> > ________________________________________________________
>> > Stephan Moratti, PhD
>> >
>> > see also: http://web.me.com/smoratti/
>> >
>> > Universidad Complutense de Madrid
>> > Facultad de Psicolog?a
>> > Departamento de Psicolog?a B?sica I
>> > Campus de Somosaguas
>> > 28223 Pozuelo de Alarc?n (Madrid)
>> > Spain
>> >
>> > and
>> >
>> > Center for Biomedical Technology
>> > Laboratory for Cognitive and Computational Neuroscience
>> > Parque Cient?fico y Tecnol?gico de la Universidad Politecnica de Madrid
>> > Campus Montegancedo
>> > 28223 Pozuelo de Alarc?n (Madrid)
>> > Spain
>> >
>> >
>> > email: smoratti at psi.ucm.es
>> > Tel.:    +34 679219982
>> >
>> > El 12/06/2013, a las 18:00, jan-mathijs schoffelen escribi?:
>> >
>> >> An alternative would be to interpolate the cortical sheet to a 3D grid
>> (where the grid is defined for each subject based on a warped template grid
>> defined in a standard space), and then do clustering using a regular 3D
>> spatial neighbourhood structure. The rationale being that two vertices on
>> the sheet may appear as disconnected  (e.g. being on two sides of a sulcus)
>> whereas, given the poor spatial resolution, they belong to the same spatial
>> blob.
>> >>
>> >> Best,
>> >> Jan-Mathijs
>> >>
>> >> On Jun 12, 2013, at 5:44 PM, smoratti at psi.ucm.es wrote:
>> >>
>> >>> Dear Nicolai,
>> >>>
>> >>> Indeed I have used ft_timelockstatistics for minimum norm source
>> data. The trick is to put the source level data into a ERF structure.
>> Determining the neighbors of a source surface with vertices is not trivial.
>> However I used tess_vertconn.m from the BrainStorm toolbox to get the
>> connectivity matrix that tells you who is a neighbor. This you can feed
>> into timelockstats.
>> >>>
>> >>> Hope that helps,
>> >>>
>> >>> Stephan
>> >>>
>> >>> ________________________________________________________
>> >>> Stephan Moratti, PhD
>> >>>
>> >>> see also: http://web.me.com/smoratti/
>> >>>
>> >>> Universidad Complutense de Madrid
>> >>> Facultad de Psicolog?a
>> >>> Departamento de Psicolog?a B?sica I
>> >>> Campus de Somosaguas
>> >>> 28223 Pozuelo de Alarc?n (Madrid)
>> >>> Spain
>> >>>
>> >>> and
>> >>>
>> >>> Center for Biomedical Technology
>> >>> Laboratory for Cognitive and Computational Neuroscience
>> >>> Parque Cient?fico y Tecnol?gico de la Universidad Politecnica de
>> Madrid
>> >>> Campus Montegancedo
>> >>> 28223 Pozuelo de Alarc?n (Madrid)
>> >>> Spain
>> >>>
>> >>>
>> >>> email: smoratti at psi.ucm.es
>> >>> Tel.:    +34 679219982
>> >>>
>> >>> El 12/06/2013, a las 15:44, Nicolai Mersebak escribi?:
>> >>>
>> >>>> Dear all,
>> >>>>
>> >>>> I have a question concerning the usage of ft_sourcegrandaverage and
>> ft_sourcestatistics.
>> >>>>
>> >>>> After using ft_sourceanalysis (method: MNE), I get spatio-temporal
>> source reconstructed data in source.avg.pow (4050 x 897): 4050 sources and
>> 897 time points.
>> >>>>
>> >>>> Now I would like to use the cluster-based permutation test on my
>> source reconstructed data. However it seems like ft_sourcegrandaverage and
>> ft_sourcestatistics don't support source level time courses. E.g when I am
>> using ft_sourcegrandaverage I am getting the following error:
>> >>>>
>> >>>> Error in ft_sourcegrandaverage (line 158)
>> >>>>   dat(:,i) = tmp(:);
>> >>>>
>> >>>> Looking into the code:
>> >>>>
>> >>>>   for i=1:Nsubject
>> >>>>     tmp = getsubfield(varargin{i}, parameterselection(cfg.parameter,
>> varargin{i}));
>> >>>>     dat(:,i) = tmp(:);
>> >>>>     tmp = getsubfield(varargin{i}, 'inside');
>> >>>>     inside(tmp,i) = 1;
>> >>>>   end
>> >>>>
>> >>>> I see that "tmp" are getting the structure [N_sources x timepoints]
>> from source.avg.pow for one subject, where "dat" requires the structure
>> [N_sources x 1].
>> >>>>
>> >>>> I seached the mailing list for similar issues and found this thread:
>> >>>>
>> >>>>
>> http://mailman.science.ru.nl/pipermail/fieldtrip/2010-September/003122.html
>> >>>>
>> >>>> Since I am interested in using the temporal dimension in my
>> statistics, I would like to know if it is still not possible to use
>> spatio-temporal source reconstructed data in ft_sourcestatistics and
>> ft_sourcegrandaverage ?
>> >>>>
>> >>>> Or if any have succeeded in using the cluster-based permutation test
>> on source level also including the temporal dimension ?
>> >>>>
>> >>>> Alternative I was thinking that I might could use
>> ft_timelockstatistics, where I substituted the channels with sources, e.g
>> instead of having 64 channels, I would now have 4050 "channels".
>> >>>> If so I need to calculate a label structure and an appropriate
>> neighbor structure, which I guess is possible as I have all the 3D
>> coordinates for each source, e.g in leadfield.pos ?
>> >>>> I know this is a work around solution, but have anyone tried or have
>> any experience using such an approach ?
>> >>>>
>> >>>> Best,
>> >>>>
>> >>>> Nicolai
>> >>>>
>> >>>> _______________________________________________
>> >>>> fieldtrip mailing list
>> >>>> fieldtrip at donders.ru.nl
>> >>>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> >>>
>> >>> _______________________________________________
>> >>> fieldtrip mailing list
>> >>> fieldtrip at donders.ru.nl
>> >>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> >>
>> >> Jan-Mathijs Schoffelen, MD PhD
>> >>
>> >> Donders Institute for Brain, Cognition and Behaviour,
>> >> Centre for Cognitive Neuroimaging,
>> >> Radboud University Nijmegen, The Netherlands
>> >>
>> >> Max Planck Institute for Psycholinguistics,
>> >> Nijmegen, The Netherlands
>> >>
>> >> J.Schoffelen at donders.ru.nl
>> >> Telephone: +31-24-3614793
>> >>
>> >> http://www.hettaligebrein.nl
>> >>
>> >> _______________________________________________
>> >> fieldtrip mailing list
>> >> fieldtrip at donders.ru.nl
>> >> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> >
>> > _______________________________________________
>> > fieldtrip mailing list
>> > fieldtrip at donders.ru.nl
>> > http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>> -------------- next part --------------
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>> http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20130613/5974284f/attachment.html
>> >
>>
>> ------------------------------
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>> End of fieldtrip Digest, Vol 31, Issue 27
>> *****************************************
>>
>
>
>
> --
> Stephen Politzer-Ahles
> University of Kansas
> Linguistics Department
> http://people.ku.edu/~sjpa/
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
Joram van Driel, MSc.
PhD student at the University of Amsterdam
Department of Psychology, Brain & Cognition
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From mbj0310 at gmail.com  Tue Jun 25 13:04:15 2013
From: mbj0310 at gmail.com (Beom Jun Min)
Date: Tue, 25 Jun 2013 20:04:15 +0900
Subject: [FieldTrip] Decreased baseline level after using ICA in ERP data
In-Reply-To: <831995030.1708865.1372062324986.JavaMail.root@sculptor.zimbra.ru.nl>
References: <CA+v9jvKJnKAfsQDwoDhNVSPAKCmpOpwut8vdmFXa1akp_1WDGA@mail.gmail.com>
	<831995030.1708865.1372062324986.JavaMail.root@sculptor.zimbra.ru.nl>
Message-ID: <CA+v9jvLu5ox++Dt0AZnJrXtZ0COt_6421YquhOTUUHDbejsjTQ@mail.gmail.com>

Dear Diego,

Thank you for your kind answer.
The importance of 'quality' you mentioned and the references that you
attached could help me to understand the ICA algorithm further.
And I have an additional question about preprocessing before ICA. Is
detrending needed before the decomposition if there is a linear trend in
the segmented data?
Because I noticed one component showing linearly and consistently decreased
(or increased) activity during one segment in some trials after ICA, I
wondered why that happened.

Apart from that, I found the possible cause of the past problem. It looks
like the ft_rejectcomponent might remove the 'demean' effect.
After I used the function without any component removing, (cfg.component =
[];) the baseline level decreased again but the shape of the ERP does not
change.
However, I have not found the way to correct this decreased baseline yet.
The ft_preprocessing with demean pre-stimulus does not work.

Thanks.

BJ



2013/6/24 Lozano Soldevilla, D. (Diego) <d.lozanosoldevilla at fcdonders.ru.nl>

> Dear Beom Jun,
>
> I see multiple scenarios why this baseline activity decrease could happen.
> First of all, how the component you're rejecting look like (i.e. "blink
> component")? Do you see this activity decrease after the baseline period?
>
> The "quality" of the ICA decomposition, how well your artifact/component
> of interest has been isolated by algorithm in time (i.e. blink time
> courses) and space (marked frontal topography), will determine the activity
> that later on you'll reject/select. If your decomposition is not well
> suited, the rejection of a particular IC activity might have "extra"
> activity you don't want to reject (effect of interest), might be the
> algorithm is not able to isolate the components of interests (i.e.
> artifacts) or a combination of both.
>
> To evaluate the quality of your ICA decomposition you might have a look
> here (http://www.ncbi.nlm.nih.gov/pubmed/19162199). Basically, the
> authors find that the ICA decomposition improves significantly "increased
> by removing the mean EEG at each channel for each epoch of data rather than
> the mean EEG in a prestimulus baseline". In addition (see here:
> http://sccn.ucsd.edu/pipermail/eeglablist/2012/004925.html), high-pass
> filtering above ~1hz improve the results.
>
> It's very important to feed ICA as much relevant data as you can use. The
> more the data, the better the decomposition. There's a rule of thumb that
> says that for a reliable IC decomposition 20 time points per channel2  is
> needed (see here for a reference
> http://www.ncbi.nlm.nih.gov/pubmed/16904745)
>
> I hope that helps,
>
> Diego
> ------------------------------
>
> *From: *"Beom Jun Min" <mbj0310 at gmail.com>
> *To: *"FieldTrip discussion list" <fieldtrip at science.ru.nl>
> *Sent: *Monday, 24 June, 2013 6:27:47 AM
> *Subject: *[FieldTrip] Decreased baseline level after using ICA in ERP
> data
>
>
> Dear all,
>
> I have ERP data and now I am dealing with ICA to remove muscle and eye
> artifacts.
> However, I found that after ft_rejectcomponent, the baseline level of the
> segmented epoch decreased. (The baselinewindow is [-0.2 0].)
> The baseline level decreased even though I rejected only one component.
>
> My script is shown below.
>
> *%% Removing the Artifacts*
> *cfg = [];
> *
> *cfg.component = [ ]; % to be removed component(s)*
> *post_ICA_temp6 = ft_rejectcomponent(cfg, comp_detrand, data_raw);*
> *
> *
> *%% timelocking*
> *
> *
> *cfg = [];*
> *timelock_temp6 = ft_timelockanalysis(cfg, post_ICA_temp6);*
> *
> *
> *%% Plot*
> *
> *
> *figure;*
> *cfg = [];*
> *cfg.layout = lay;*
> *cfg.interactive = 'yes';*
> *cfg.channel = ['all', {'-EKG', '-EMG'}];*
> *ft_multiplotER(cfg, timelock_temp6)*
>
> Is there something that I missed?
>
> Thanks.
>
> BJ
>
> --
> BeomJun Min, M.D.
>
> Department of Medical System Engineering (DMSE)
> Gwangju Institute of Science and Technology (GIST)
> 261 Cheomdan-gwagiro(Oryong-dong), Buk-gu, Gwangju
> 500-712, Republic of Korea (South)
> Phone: +82-62-715-3266 / Fax: +82-62-715-3244
> E-mail: mbj0310 at gmail.com, http://bmssa.gist.ac.kr
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
>
> --
> PhD Student
> Neuronal Oscillations Group
> Donders Institute for Brain, Cognition and Behaviour
> Centre for Cognitive Neuroimaging
> Radboud University Nijmegen
> NL-6525 EN Nijmegen
> The Netherlands
> http://www.ru.nl/people/donders/lozano-soldevilla-d/
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
BeomJun Min, M.D.

Department of Medical System Engineering (DMSE)
Gwangju Institute of Science and Technology (GIST)
261 Cheomdan-gwagiro(Oryong-dong), Buk-gu, Gwangju
500-712, Republic of Korea (South)
Phone: +82-62-715-3266 / Fax: +82-62-715-3244
E-mail: mbj0310 at gmail.com, http://bmssa.gist.ac.kr
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From mengtongxiao at gmail.com  Tue Jun 25 15:29:41 2013
From: mengtongxiao at gmail.com (=?GB2312?B?s8LRqQ==?=)
Date: Tue, 25 Jun 2013 21:29:41 +0800
Subject: [FieldTrip] source reconstruction data (MNE .fif)
Message-ID: <CADiddyVSK6SqRU5BP1kNpSAR21f8heFkkZuOiAh1QKgCH+8xag@mail.gmail.com>

Dear all
 I have a .fif file and want to source  reconstruction .

I want use the template  sourcemodel in fieldtrip,but  I see there are two
different  coordinate system.
Shold I convert the fif coordinate to template coordinate?

thanks
best,
xiao
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From m.chait at ucl.ac.uk  Tue Jun 25 16:39:16 2013
From: m.chait at ucl.ac.uk (Chait, Maria)
Date: Tue, 25 Jun 2013 14:39:16 +0000
Subject: [FieldTrip] PhD studentship at the UCL Ear Institute
Message-ID: <3BA3DF582C0B7542AE0CB625F0119AB8378B0451@DB3PRD0111MB492.eurprd01.prod.exchangelabs.com>


Please forward to anyone who might be interested.

A 3 year PhD studentship in auditory cognitive neuroscience is available as part of a research collaboration between the UCL Ear Institute (London, UK) and NTT Communication Science Labs (Nippon Telegraph and Telephone corporation, Atsugi, Japan). The student will be based at the UCL Ear Institute and supervised by Dr. Maria Chait. They will also be working with Prof. Makio Kashino and Dr. Shigeto Furukawa (NTT).  The project will use psychophysics, eye tracking, autonomic response measures and MEG functional brain imaging to investigate which features of sound are perceptually salient. Namely, those sounds that automatically capture attention in a busy scene, even when listeners' initial perceptual focus is elsewhere.

The UCL Ear Institute provides state-of-the-art research facilities across a wide range of disciplines and is one of the foremost centres for hearing, speech and language-related research within Europe.

Key Requirements
The PhD start date would be September  2013.  Applicants should have a UK/EU nationality and a 1St class, or upper 2nd degree in a relevant discipline (e.g. Psychology, Neuroscience, Engineering). The PhD work would require good programming skills (e.g. in Matlab). Previous experience with auditory research, functional brain imaging, signal processing and/or acoustics is desirable.

For an informal discussion, or to submit an application please contact Dr. Maria Chait (m.chait at ucl.ac.uk<mailto:m.chait at ucl.ac.uk>). Applicants should submit a supporting statement, a CV, and the details of two academic referees.  The closing date for receipt of applications is July 15th, 2013.The studentship includes fees and a yearly stipend (about £16000;  tax free).


Maria Chait PhD
m.chait at ucl.ac.uk<mailto:m.chait at ucl.ac.uk>

Senior Lecturer
UCL Ear Institute
332 Gray's Inn Road
London WC1X 8EE

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From matt.craddock at uni-leipzig.de  Tue Jun 25 17:17:43 2013
From: matt.craddock at uni-leipzig.de (Matt Craddock)
Date: Tue, 25 Jun 2013 17:17:43 +0200
Subject: [FieldTrip] Decreased baseline level after using ICA in ERP data
In-Reply-To: <CA+v9jvLu5ox++Dt0AZnJrXtZ0COt_6421YquhOTUUHDbejsjTQ@mail.gmail.com>
References: <CA+v9jvKJnKAfsQDwoDhNVSPAKCmpOpwut8vdmFXa1akp_1WDGA@mail.gmail.com>
	<831995030.1708865.1372062324986.JavaMail.root@sculptor.zimbra.ru.nl>
	<CA+v9jvLu5ox++Dt0AZnJrXtZ0COt_6421YquhOTUUHDbejsjTQ@mail.gmail.com>
Message-ID: <51C9B497.7080105@uni-leipzig.de>

Dear Beom Jun,

Regarding detrending - ICA works better with relatively stationary data, 
which is why high-pass filtering - as Diego mentioned - is often 
performed. Both detrending and high-pass filtering remove/attenuate slow 
fluctuations in the signal, so I'd suggest using one or the other 
procedure before running ICA if you think such low frequency activity is 
affecting your decompositions.

Cheers,
Matt

On 25/06/2013 13:04, Beom Jun Min wrote:
> Dear Diego,
>
> Thank you for your kind answer.
> The importance of 'quality' you mentioned and the references that you
> attached could help me to understand the ICA algorithm further.
> And I have an additional question about preprocessing before ICA. Is
> detrending needed before the decomposition if there is a linear trend in
> the segmented data?
> Because I noticed one component showing linearly and consistently
> decreased (or increased) activity during one segment in some trials
> after ICA, I wondered why that happened.
> Apart from that, I found the possible cause of the past problem. It
> looks like the ft_rejectcomponent might remove the 'demean' effect.
> After I used the function without any component removing, (cfg.component
> = [];) the baseline level decreased again but the shape of the ERP does
> not change.
> However, I have not found the way to correct this decreased baseline
> yet. The ft_preprocessing with demean pre-stimulus does not work.
>
> Thanks.
>
> BJ



-- 
Dr. Matt Craddock

Post-doctoral researcher,
Institute of Psychology,
University of Leipzig,
Neumarkt 9-19,
04109 Leipzig, Germany
Phone: +49 341 973 95 44


From l.verhagen at fcdonders.ru.nl  Wed Jun 26 11:33:36 2013
From: l.verhagen at fcdonders.ru.nl (Verhagen, L. (Lennart))
Date: Wed, 26 Jun 2013 11:33:36 +0200 (CEST)
Subject: [FieldTrip] Brain Stimulation (TMS-tDCS-EEG) toolkit course at
	Donders, Nijmegen - registration is now open
Message-ID: <1380b01ce7250$3bba7a70$b32f6f50$@verhagen@fcdonders.ru.nl>

On September 2-4, 2013, we will host the “Toolkit of Cognitive Neuroscience: 
Transcranial Brain Stimulation” at the Donders Institute in Nijmegen.



This intensive three-day toolkit course will provide in-depth knowledge on 
transcranial magnetic stimulation (TMS) and transcranial current stimulation 
(tDCS/tACS). The course will cover both basic and advanced topics, 
discussing online and offline approaches of quantification, interference, 
and modulation of neural activity. We will specifically address multimodal 
applications of non-invasive brain stimulation, with an emphasis on 
concurrent electroencephalography (EEG).



The course involves a series of lectures and hands-on training of 
stimulation application, data acquisition and data analysis. These address 
fundamental paradigms, such as single-pulse TMS, repetitive TMS, tDCS and 
tACS, and advanced topics, such as paired-pulse TMS and concurrent 
TMS-tDCS-EEG. Keynote lectures will be given by Rogier Mars (Oxford), 
Jacinta O’Shea (Oxford), Alexander Sack (Maastricht), and Gregor Thut 
(Glasgow). Please see the program for more details.



The participation fee is €150 for (PhD) students and €300 for more senior 
researchers. This includes coffee/tea, Dutch sandwich lunches, and social 
diner and drinks on Monday and Tuesday. Because of space limitations the 
number of participants in the hands-on sessions is limited to 30; please 
indicate your preference to join these additional sessions when registering.



Location: Donders Institute for Brain, Cognition and Behaviour, Centre for 
Cognitive Neuroimaging, Kapittelweg 29, 6525 EN Nijmegen

Organizers: Lennart Verhagen (l.verhagen at donders.ru.nl) Til Ole Bergmann 
(t.bergmann at donders.ru.nl)

Registration: 
www.ru.nl/donders/course-information/2013courses/toolkit-cognitive-7



Best regards,

Lennart Verhagen and Til Ole Bergmann



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From graham at peyton.co.za  Wed Jun 26 12:13:58 2013
From: graham at peyton.co.za (Graham Peyton)
Date: Wed, 26 Jun 2013 12:13:58 +0200
Subject: [FieldTrip] QSUB toolbox on a multi-core computer
Message-ID: <CANOxK9E+ZCy9zFqYw1kR_aK7wnEpq0cF9efVj93wFxg5zJWmhQ@mail.gmail.com>

Dear FieldTrip community,

I am trying to carry out an MEG analysis using the qsub distributed
computing toolbox. I'm using a quad-core i7 computer, and was hoping that
I'd be able to distribute the workload over all four cores.

I have followed the tutorial below exactly:
http://fieldtrip.fcdonders.nl/tutorial/distributedcomputing

The problem I am having is this: I managed to run example 1 (with my own
dataset), but I am finding that when I use qsubcellfun, the function
ft_definetrial is executed *sequentially* (for each condition), *not* in *
parallel*. Is there a way I can correct this, so as to parallelize the
analysis? Or is the toolbox not designed for multi-core machines?

Many thanks,

Graham Peyton
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From m.vandenieuwenhuijzen at fcdonders.ru.nl  Wed Jun 26 15:07:02 2013
From: m.vandenieuwenhuijzen at fcdonders.ru.nl (Marieke van de Nieuwenhuijzen)
Date: Wed, 26 Jun 2013 15:07:02 +0200 (CEST)
Subject: [FieldTrip] ROI selection of beamformer grid points
Message-ID: <1483937264.1423478.1372252022737.JavaMail.root@draco.zimbra.ru.nl>

Dear Fieldtrippers,

I am running my analyses on time courses reconstructed in source space. Basically, that means that my working dataset is a matrix of grid point x time. What I want to do now is do some analyses on a subset of that dataset, a bit analogous to selecting some sensors to restrict analyses to. Therefore, what I would ideally want to do, is select a subset of grid points corresponding to a specific location (for example only the occipital grid points, or only the grid points corresponding to a specific atlas label).

Does anyone have any suggestions about how I should go about selecting specific grid points? Is there perhaps some grid based atlas, or is it possible to select grid points based on their corresponding mni coordinates which you get after running ft_sourceinterpolate and ft_volumenormalise (in other words, is it possible to reverse ft_volumenormalise and ft_sourceinterpolate to map the mni coordinates to the grid points instead of the grid points to mni representation).

Any pointers would be much appreciated.

Best,
Marieke


From jm.horschig at donders.ru.nl  Wed Jun 26 15:26:41 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Wed, 26 Jun 2013 15:26:41 +0200
Subject: [FieldTrip] ROI selection of beamformer grid points
In-Reply-To: <1483937264.1423478.1372252022737.JavaMail.root@draco.zimbra.ru.nl>
References: <1483937264.1423478.1372252022737.JavaMail.root@draco.zimbra.ru.nl>
Message-ID: <51CAEC11.10702@donders.ru.nl>

Hi Marieke,

I basically use two approaches (in the end, both failed, so any other 
hints are appreciated):

  (a) Select voxels purely based on anatomical labels, as found in an 
atlas or in literature.

  (b) Select voxels based on some local maxima or minima, e.g. power 
maximum or maximum difference of log-ratio


(a) should be pretty straight forward. In essence it involves getting 
MNI coordinates, inversely warping your grids to MNI space, getting 
closest voxel. If you have your region of interest not in MNI 
coordinates you need to transform them. I found some tal2mni functions 
on the web for this, but note that this is just an estimate. Of course, 
(a) is also applicable if you have a localizer task using fMRI and want 
to focus on some localized voxels.
(b) is a bit more tricky, because you might be faced with huge 
inter-subject variability. Best of course would be to have the 
subject-specific, fMRI localized voxel. What I done in the past is to 
define a rough region of interest, e.g. posterior neocortex (based on 
some quick&dirty coordinate thresholding), using ft_volumesmooth to 
apply a gaussian blur on single subject-activity and then select the 
voxel that suits me best (i.e. the one of maximum activity). Of course 
your ROI could also be based on the grand-average or what have you. I 
had the feeling that especially this latter approach (base ROI on GA +/- 
3 cm, smooth individual subject data, select most sensitive voxel) 
worked quite well, but I cannot tell for sure, because in the end my 
results were not reliable enough.

Oh and btw, if the question just aims on 'how' to select 
programming-wise: Match the coordinate with your template, store the 
index based on the template-grid and use this index on your 
subject-specific grid to get voxel of interest in subject-specific 
coordinates.

Good luck!
Best,
Jörn

On 6/26/2013 3:07 PM, Marieke van de Nieuwenhuijzen wrote:
> Dear Fieldtrippers,
>
> I am running my analyses on time courses reconstructed in source space. Basically, that means that my working dataset is a matrix of grid point x time. What I want to do now is do some analyses on a subset of that dataset, a bit analogous to selecting some sensors to restrict analyses to. Therefore, what I would ideally want to do, is select a subset of grid points corresponding to a specific location (for example only the occipital grid points, or only the grid points corresponding to a specific atlas label).
>
> Does anyone have any suggestions about how I should go about selecting specific grid points? Is there perhaps some grid based atlas, or is it possible to select grid points based on their corresponding mni coordinates which you get after running ft_sourceinterpolate and ft_volumenormalise (in other words, is it possible to reverse ft_volumenormalise and ft_sourceinterpolate to map the mni coordinates to the grid points instead of the grid points to mni representation).
>
> Any pointers would be much appreciated.
>
> Best,
> Marieke
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands



From andmib at gmail.com  Wed Jun 26 19:22:33 2013
From: andmib at gmail.com (Andrew Brooks)
Date: Wed, 26 Jun 2013 13:22:33 -0400
Subject: [FieldTrip] Siemens GUI Streamer Disconnecting
Message-ID: <CALJPz6_8Vrq9ebz3vj5N=FWwoTP9HuJiXd-=PV5nqDqSbiFZ5g@mail.gmail.com>

Hello all,

I have a protocol that includes three separate sequences. I start the
Siemens GUI streamer prior to the first sequence, and keep it open through
all three sequences. Only on the last sequence do I run
ft_omri_pipeline_nuisance. I've been running into a problem where the
Siemens GUI streamer disconnects as soon as the the third sequence starts
running (and the ft_omri_pipeline script is waiting for data). I have to
manually click 'connect' as soon as it disconnects, and then it works fine.

Any ideas as to why the streamer would disconnect like this?

Thanks!
Andrew
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From j.herring at fcdonders.ru.nl  Thu Jun 27 12:45:53 2013
From: j.herring at fcdonders.ru.nl (Herring, J.D. (Jim))
Date: Thu, 27 Jun 2013 12:45:53 +0200 (CEST)
Subject: [FieldTrip] QSUB toolbox on a multi-core computer
In-Reply-To: <CANOxK9E+ZCy9zFqYw1kR_aK7wnEpq0cF9efVj93wFxg5zJWmhQ@mail.gmail.com>
References: <CANOxK9E+ZCy9zFqYw1kR_aK7wnEpq0cF9efVj93wFxg5zJWmhQ@mail.gmail.com>
Message-ID: <004701ce7323$7fa9ff20$7efdfd60$@herring@fcdonders.ru.nl>

Dear Graham,

 

As stated in the tutorial the distributed computing functions are intended
to distribute workload over different computers running a Torque or SGE
batch system: "This tutorial covered how to distribute your
computations/workload over multiple computers in a cluster that uses the
Torque or SGE batch queue system". However, what you could do is make use
of Matlab's parallel processing tools. Matlab allows you to open a pool of
so-called 'workers' to distribute processing jobs to allowing you to run
multiple processes in parallel. Please see
http://www.mathworks.nl/help/distcomp/matlabpool.html and
http://www.mathworks.nl/help/matlab/ref/parfor.html.

 

Once you've opened a pool of workers using 'matlabpool', you can use
'parfor' in the same way as you would use 'for' to create a loop that runs
all processes in parallel over all four cores. 

 

Best,

Jim

From: fieldtrip-bounces at science.ru.nl
[mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of Graham Peyton
Sent: woensdag 26 juni 2013 12:14
To: fieldtrip at science.ru.nl
Subject: [FieldTrip] QSUB toolbox on a multi-core computer

 

Dear FieldTrip community,

I am trying to carry out an MEG analysis using the qsub distributed
computing toolbox. I'm using a quad-core i7 computer, and was hoping that
I'd be able to distribute the workload over all four cores. 

I have followed the tutorial below exactly:
http://fieldtrip.fcdonders.nl/tutorial/distributedcomputing

The problem I am having is this: I managed to run example 1 (with my own
dataset), but I am finding that when I use qsubcellfun, the function
ft_definetrial is executed sequentially (for each condition), not in
parallel. Is there a way I can correct this, so as to parallelize the
analysis? Or is the toolbox not designed for multi-core machines? 

 

Many thanks,

Graham Peyton

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From ana.hincapie at gmail.com  Fri Jun 28 09:31:24 2013
From: ana.hincapie at gmail.com (=?ISO-8859-1?Q?Ana_Sof=EDa_Hincapi=E9_Casas?=)
Date: Fri, 28 Jun 2013 09:31:24 +0200
Subject: [FieldTrip] In the forward problem,
 how are the points for the grid.inside and grid.outside defined?
Message-ID: <CAN+fi=zVBtweOXxwEWaHWnp1wKfDTXBXoUgeFgyoeVgQ=jCOxA@mail.gmail.com>

Hi,

I´am new in FieldTrip and I would like to what are the grid.inside and
grid.outside points and if I could used the whole grid to calculate the
leadfields.

Thanks in advance for the help you could bring me.

Regards,

-- 
Ana Hincapié
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From jm.horschig at donders.ru.nl  Fri Jun 28 10:42:03 2013
From: jm.horschig at donders.ru.nl (=?ISO-8859-1?Q?=22J=F6rn_M=2E_Horschig=22?=)
Date: Fri, 28 Jun 2013 10:42:03 +0200
Subject: [FieldTrip] In the forward problem,
 how are the points for the grid.inside and grid.outside defined?
In-Reply-To: <CAN+fi=zVBtweOXxwEWaHWnp1wKfDTXBXoUgeFgyoeVgQ=jCOxA@mail.gmail.com>
References: <CAN+fi=zVBtweOXxwEWaHWnp1wKfDTXBXoUgeFgyoeVgQ=jCOxA@mail.gmail.com>
Message-ID: <51CD4C5B.5030909@donders.ru.nl>

Hi Ana,

inside and outside just describe whether the grid point is inside or 
outside the brain. You can plot this to see for yourself:
% plot only what is inside the brain
figure;
ft_plot_vol(vol, 'edgecolor', 'none'); alpha 0.4;
ft_plot_mesh(grid.pos(grid.inside,:));

% plot the whole grid
figure;
ft_plot_vol(vol, 'edgecolor', 'none'); alpha 0.4;
ft_plot_mesh(grid.pos(:,:));

FieldTrip will use that information automatically to only use grid 
points inside the brain, so yes, you can use the whole grid to compute 
the leadfield matrix. If you do not want that, you can modify 
grid.inside and grid.outside yourself.

Have fun fieldtrippin' :)
Jörn

On 6/28/2013 9:31 AM, Ana Sofía Hincapié Casas wrote:
> Hi,
>
> I´am new in FieldTrip and I would like to what are the grid.inside and 
> grid.outside points and if I could used the whole grid to calculate 
> the leadfields.
>
> Thanks in advance for the help you could bring me.
>
> Regards,
>
> -- 
> Ana Hincapié
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> http://mailman.science.ru.nl/mailman/listinfo/fieldtrip


-- 
Jörn M. Horschig
PhD Student
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Neuronal Oscillations Group
FieldTrip Development Team

P.O. Box 9101
NL-6500 HB Nijmegen
The Netherlands

Contact:
E-Mail: jm.horschig at donders.ru.nl
Tel:    +31-(0)24-36-68493
Web: http://www.ru.nl/donders

Visiting address:
Trigon, room 2.30
Kapittelweg 29
NL-6525 EN Nijmegen
The Netherlands

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From ggonesc at upo.es  Fri Jun 28 18:28:57 2013
From: ggonesc at upo.es (Gabriel Gonzalez Escamilla)
Date: Fri, 28 Jun 2013 18:28:57 +0200
Subject: [FieldTrip] problem appending data
Message-ID: <2350c7b9464ea50a.51cdd5e9@upo.es>

Dear Fieldtrip experts,

I'm working with restin-state EEG data, I'm looking for performing EEG coherence analysis between my normal EEG channels and a channel from the same subject but aquired with a different name

I did: data = ft_appenddata([], dataEEG_allchans, dataEEG_1chan)
and it did concatenate the one single channel at the end of the dataEEG_allchans, so now I have a matrix with Nchans+1, that looks perfect to me, then I did perform fourier transformations with a hanning window, and workded perfectly, but if I set 
cfg.method='coh'
cfg.complex='imag'
cfg.channelcbm={'all', 'ref-P7'}
icohe=ft_connectovityanalysis(cfg,)

I always get the following error:
???? attempted to access siz(4); index out of bounds because numel(siz=3)
Error in ==> ft_checkdata>fixcsd at 798

I have also tried something like:
cfg.channelcbm={{1x40cell}, 'ref-P7'}
where {1x40 cell} is a cell matrix containing the names of all my sensors

but it didn't worked.

Any help will be appreciated

Many thanks in advanced,
Gabriel

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From manuel.mercier at einstein.yu.edu  Fri Jun 28 22:43:54 2013
From: manuel.mercier at einstein.yu.edu (Manuel  Mercier)
Date: Fri, 28 Jun 2013 20:43:54 +0000
Subject: [FieldTrip] PLV formula
Message-ID: <D0B70B31DE8EC849948A63FAED36B67D2A14420D@AEWEXCPM21.yuad.uds.yu.edu>

Dear Fieldtripers
Sometime ago I wrote for myself a function that was computing PLV and some related non parametric statistics.
(Phase Locking Value as define as the mean across trials of the phase angle difference recorded at two loci ; based on Lachaux et al., 1999, HBM).
I implemented PLV in matlab using the following formula:
plv = squeeze(abs(mean(exp(1i*(angle(data.fourierspctrm(:,cmb(1),:,:)) ...
                                                -angle(data.fourierspctrm(:,cmb(2),:,:)))),1)));
with cmb(1) and cmb(2) being the indices of the electrodes of interest (between which PLV is computed).
I compared my results with the ft_connectivityanalysis function from Fieldtrip and the results were exactly the same.
So far so good.

But I recently went back to my code, and I was a little bit confused.
Since I was dealing with angles, I though that the best way to do the subtraction should be done in the complex plane
Like:
plv = squeeze(abs(mean(exp(1i*(angle(exp(1i*(angle(data.fourierspctrm(:,cmb(1),:,:)))) ...
                                                        - exp(1i*(angle(data.fourierspctrm(:,cmb(2),:,:))))))),1)));
(for instance if the two angles: pi/2 and -pi/2 the direct subtraction will give pi,
whereas in the complex plan it will be pi/2 - with the norm x2).

The result I got with this code is obviously different from the previous one, and what I got from Fieldtrip.
I went back to the archive of the mailing list but didn't find a clear answer to my point. Does anyone can enlighten me ?
Thanks !

Manuel


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