From kramerrobin92 at gmail.com  Fri Jul  1 11:53:06 2016
From: kramerrobin92 at gmail.com (Robin Kramer)
Date: Fri, 1 Jul 2016 11:53:06 +0200
Subject: [FieldTrip] Automatic artifact detection (no rejection)
Message-ID: <CAHnFAUi9soOTkJvq6hLtHNn8cUfUgvSHuGP7zJuO8=X_1c4fPQ@mail.gmail.com>

Hi all,

I want to use automatic artifact detection to easily find the trials where
range-thresholds may be exceeded. However, because the segments are a
little larger than the time of interest (for baseline correction a.o.), I
do not always want to remove all the trials where the threshold is
exceeded. Is there a way to deselect the automatically detected artifacts?

Best,

Robin Kramer
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160701/99d2e6b1/attachment.htm>

From stephen.politzer-ahles at ling-phil.ox.ac.uk  Fri Jul  1 12:25:59 2016
From: stephen.politzer-ahles at ling-phil.ox.ac.uk (Stephen Politzer-Ahles)
Date: Fri, 1 Jul 2016 11:25:59 +0100
Subject: [FieldTrip] Automatic artifact detection (no rejection)
Message-ID: <CAJT2k_9uf0yxJD9r3Zd1tnxs5ccO=EPdcn0oiz+-3uiCtVhroA@mail.gmail.com>

Hi Robin,

Rather than deselecting certain trials, it sounds like what you'd want to
do is just not mark a trial 'bad' at all if the artifact is outside your
time window of interest. For this, I think negative trial-padding (
http://www.fieldtriptoolbox.org/tutorial/automatic_artifact_rejection#negative_trialpadding)
should be able to do what you need.

Best,
Steve



---
Stephen Politzer-Ahles
University of Oxford
Language and Brain Lab
Faculty of Linguistics, Phonetics & Philology
http://users.ox.ac.uk/~cpgl0080/



> Message: 3
> Date: Fri, 1 Jul 2016 11:53:06 +0200
> From: Robin Kramer <kramerrobin92 at gmail.com>
> To: fieldtrip at science.ru.nl
> Subject: [FieldTrip] Automatic artifact detection (no rejection)
> Message-ID:
>         <CAHnFAUi9soOTkJvq6hLtHNn8cUfUgvSHuGP7zJuO8=
> X_1c4fPQ at mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> Hi all,
>
> I want to use automatic artifact detection to easily find the trials where
> range-thresholds may be exceeded. However, because the segments are a
> little larger than the time of interest (for baseline correction a.o.), I
> do not always want to remove all the trials where the threshold is
> exceeded. Is there a way to deselect the automatically detected artifacts?
>
> Best,
>
> Robin Kramer
>


> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
> End of fieldtrip Digest, Vol 68, Issue 1
> ****************************************
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160701/312a4a9e/attachment.htm>

From p.taesler at uke.de  Fri Jul  1 12:34:22 2016
From: p.taesler at uke.de (Philipp Taesler)
Date: Fri, 1 Jul 2016 12:34:22 +0200
Subject: [FieldTrip] Automatic artifact detection (no rejection)
In-Reply-To: <adb4543a5c374a169e96eac70de01aa3@EXCCAHT-3.mail.uke.ads>
References: <adb4543a5c374a169e96eac70de01aa3@EXCCAHT-3.mail.uke.ads>
Message-ID: <dfbe5573-8d83-b690-deb2-b1ce51666369@uke.de>

Hi Robin,

you might be interested in the section "Negative trialpadding" in the
rejection tutorial at

http://www.fieldtriptoolbox.org/tutorial/automatic_artifact_rejection

Otherwise, you can just pass the structure containing the artifact info
from automatic detection (cfg.artfctdef.xxx) to ft_databrowser. This way
you can screen the data and manually define and/or remove artifacts from
the trials.

Cheers,
Phil



Am 01.07.2016 um 11:53 schrieb Robin Kramer:
> Hi all,
> 
> I want to use automatic artifact detection to easily find the trials
> where range-thresholds may be exceeded. However, because the segments
> are a little larger than the time of interest (for baseline correction
> a.o.), I do not always want to remove all the trials where the threshold
> is exceeded. Is there a way to deselect the automatically detected
> artifacts? 
> 
> Best,
> 
> Robin Kramer

-- 
Philipp Taesler
Department of Systems Neuroscience
University Medical Center Hamburg-Eppendorf
Martinistr. 52, W34, 20248 Hamburg, Germany

Phone: +49-40-7410-59902
Fax:   +49-40-7410-59955
Email: p.taesler at uke.de
--

_____________________________________________________________________

Universitätsklinikum Hamburg-Eppendorf; Körperschaft des öffentlichen Rechts; Gerichtsstand: Hamburg | www.uke.de
Vorstandsmitglieder: Prof. Dr. Burkhard Göke (Vorsitzender), Prof. Dr. Dr. Uwe Koch-Gromus, Joachim Prölß, Rainer Schoppik
_____________________________________________________________________

SAVE PAPER - THINK BEFORE PRINTING



From kramerrobin92 at gmail.com  Fri Jul  1 13:45:18 2016
From: kramerrobin92 at gmail.com (Robin Kramer)
Date: Fri, 1 Jul 2016 13:45:18 +0200
Subject: [FieldTrip] Automatic artifact detection (no rejection)
In-Reply-To: <CAJT2k_9uf0yxJD9r3Zd1tnxs5ccO=EPdcn0oiz+-3uiCtVhroA@mail.gmail.com>
References: <CAJT2k_9uf0yxJD9r3Zd1tnxs5ccO=EPdcn0oiz+-3uiCtVhroA@mail.gmail.com>
Message-ID: <CAHnFAUjzrkXHsQSi0AvtEb6PAA45gc97OD5NvYR6MX2hdh17eg@mail.gmail.com>

Hi Steve and Phil,

Thank you, that is exactly what I was looking for. However, it seems as if
it not yet implemented in ft_artifact_threshold(). I see no difference
between the amount of rejected trials. Moreover, the option is not
specified on the reference page, though it is on ft_artifact_eog for
instance. Is that correct?

Best,
Robin

2016-07-01 12:25 GMT+02:00 Stephen Politzer-Ahles <
stephen.politzer-ahles at ling-phil.ox.ac.uk>:

> Hi Robin,
>
> Rather than deselecting certain trials, it sounds like what you'd want to
> do is just not mark a trial 'bad' at all if the artifact is outside your
> time window of interest. For this, I think negative trial-padding (
> http://www.fieldtriptoolbox.org/tutorial/automatic_artifact_rejection#negative_trialpadding)
> should be able to do what you need.
>
> Best,
> Steve
>
>
>
> ---
> Stephen Politzer-Ahles
> University of Oxford
> Language and Brain Lab
> Faculty of Linguistics, Phonetics & Philology
> http://users.ox.ac.uk/~cpgl0080/
>
>
>
>> Message: 3
>> Date: Fri, 1 Jul 2016 11:53:06 +0200
>> From: Robin Kramer <kramerrobin92 at gmail.com>
>> To: fieldtrip at science.ru.nl
>> Subject: [FieldTrip] Automatic artifact detection (no rejection)
>> Message-ID:
>>         <CAHnFAUi9soOTkJvq6hLtHNn8cUfUgvSHuGP7zJuO8=
>> X_1c4fPQ at mail.gmail.com>
>> Content-Type: text/plain; charset="utf-8"
>>
>> Hi all,
>>
>> I want to use automatic artifact detection to easily find the trials where
>> range-thresholds may be exceeded. However, because the segments are a
>> little larger than the time of interest (for baseline correction a.o.), I
>> do not always want to remove all the trials where the threshold is
>> exceeded. Is there a way to deselect the automatically detected artifacts?
>>
>> Best,
>>
>> Robin Kramer
>>
>
>
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>> End of fieldtrip Digest, Vol 68, Issue 1
>> ****************************************
>>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160701/e926f308/attachment.htm>

From p.taesler at uke.de  Fri Jul  1 14:10:09 2016
From: p.taesler at uke.de (Philipp Taesler)
Date: Fri, 1 Jul 2016 14:10:09 +0200
Subject: [FieldTrip] Automatic artifact detection (no rejection)
In-Reply-To: <a6e8ccf443d44e8783ca00d0bb4085b5@EXCCAHT-4.mail.uke.ads>
References: <CAJT2k_9uf0yxJD9r3Zd1tnxs5ccO=EPdcn0oiz+-3uiCtVhroA@mail.gmail.com>
 <a6e8ccf443d44e8783ca00d0bb4085b5@EXCCAHT-4.mail.uke.ads>
Message-ID: <15e80a9d-3eba-0c7b-cd77-af2e5f1d80c4@uke.de>

Hi Robin,

you are right, the comment in the function explicitly says:

% Contrary to the other artifact detection functions, this function
% will mark the whole trial as an artifact if the threshold is exceeded.
% Furthermore, this function does not support artifact- or filterpadding.

I didn't know that. Hmmm, then I guess your only option is to either
visually review the marked trials and unmark the ones you want to keep.
Another possibilty might be to use ft_redefinetrial to create a dataset
with shorter trials, run the rejection on this data, and use the
resulting artefact definitions for your original data. (Not sure if that
is straightforward, since I never did this myself).

Cheers,
Phil


Am 01.07.2016 um 13:45 schrieb Robin Kramer:
> Hi Steve and Phil,
> 
> Thank you, that is exactly what I was looking for. However, it seems as
> if it not yet implemented in ft_artifact_threshold(). I see no
> difference between the amount of rejected trials. Moreover, the option
> is not specified on the reference page, though it is on ft_artifact_eog
> for instance. Is that correct?
> 
> Best,
> Robin
> 
> 2016-07-01 12:25 GMT+02:00 Stephen Politzer-Ahles
> <stephen.politzer-ahles at ling-phil.ox.ac.uk
> <mailto:stephen.politzer-ahles at ling-phil.ox.ac.uk>>:
> 
>     Hi Robin,
> 
>     Rather than deselecting certain trials, it sounds like what you'd
>     want to do is just not mark a trial 'bad' at all if the artifact is
>     outside your time window of interest. For this, I think negative
>     trial-padding
>     (http://www.fieldtriptoolbox.org/tutorial/automatic_artifact_rejection#negative_trialpadding)
>     should be able to do what you need.
> 
>     Best,
>     Steve
> 
> 
> 
>     ---
>     Stephen Politzer-Ahles
>     University of Oxford
>     Language and Brain Lab
>     Faculty of Linguistics, Phonetics & Philology
>     http://users.ox.ac.uk/~cpgl0080/
> 
>      
> 
>         Message: 3
>         Date: Fri, 1 Jul 2016 11:53:06 +0200
>         From: Robin Kramer <kramerrobin92 at gmail.com
>         <mailto:kramerrobin92 at gmail.com>>
>         To: fieldtrip at science.ru.nl <mailto:fieldtrip at science.ru.nl>
>         Subject: [FieldTrip] Automatic artifact detection (no rejection)
>         Message-ID:
>                
>         <CAHnFAUi9soOTkJvq6hLtHNn8cUfUgvSHuGP7zJuO8=X_1c4fPQ at mail.gmail.com
>         <mailto:X_1c4fPQ at mail.gmail.com>>
>         Content-Type: text/plain; charset="utf-8"
> 
>         Hi all,
> 
>         I want to use automatic artifact detection to easily find the
>         trials where
>         range-thresholds may be exceeded. However, because the segments
>         are a
>         little larger than the time of interest (for baseline correction
>         a.o.), I
>         do not always want to remove all the trials where the threshold is
>         exceeded. Is there a way to deselect the automatically detected
>         artifacts?
> 
>         Best,
> 
>         Robin Kramer
> 

-- 
Philipp Taesler
Department of Systems Neuroscience
University Medical Center Hamburg-Eppendorf
Martinistr. 52, W34, 20248 Hamburg, Germany

Phone: +49-40-7410-59902
Fax:   +49-40-7410-59955
Email: p.taesler at uke.de
--

_____________________________________________________________________

Universitätsklinikum Hamburg-Eppendorf; Körperschaft des öffentlichen Rechts; Gerichtsstand: Hamburg | www.uke.de
Vorstandsmitglieder: Prof. Dr. Burkhard Göke (Vorsitzender), Prof. Dr. Dr. Uwe Koch-Gromus, Joachim Prölß, Rainer Schoppik
_____________________________________________________________________

SAVE PAPER - THINK BEFORE PRINTING



From viviana.betti at gmail.com  Fri Jul  1 15:56:18 2016
From: viviana.betti at gmail.com (Viviana Betti)
Date: Fri, 1 Jul 2016 15:56:18 +0200
Subject: [FieldTrip] PhD Position in Rome
Message-ID: <CAC6MOcZqo6RTQB4d4LZxjA92chDWMqkObsERKSiq_KNLm=AyAA@mail.gmail.com>

Dear Fieldtrip community,
Please see below the opportunity for the "International PhD in Cognitive
Social Affective and Social Neuroscience" (CoSAN, http://www.cosanphd.com/)
at the Department of Psychology, Sapienza University of Rome and the
research-oriented hospital IRCCS Fondazione Santa Lucia in Rome.



In the attachment you may find all the information concerning the details
of the PhD program.

I would kindly ask you to spread the voice to your Department or any other
Institution, colleague, or to any potential applicant you think may qualify
for the post.


Best wishes

Viviana Betti
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160701/8fc9db2d/attachment.htm>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: Attachment.pdf
Type: application/pdf
Size: 247299 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160701/8fc9db2d/attachment.pdf>

From stephen.politzer-ahles at ling-phil.ox.ac.uk  Fri Jul  1 16:29:47 2016
From: stephen.politzer-ahles at ling-phil.ox.ac.uk (Stephen Politzer-Ahles)
Date: Fri, 1 Jul 2016 15:29:47 +0100
Subject: [FieldTrip] Automatic artifact detection (no rejection)
Message-ID: <CAJT2k_-BhfOSUZ9jYXOBq7-c3Ap4zsboJU_k8L8=gt46=1kEnA@mail.gmail.com>

I second Phil's suggestion. While I haven't done this myself, what i would
do if I were in this situation is something like the following:

1. Create a dataset with the shorter epochs
2. Run the artifact rejection
3. Save the list of good trials (trials that weren't rejected)
4. Throw out that dataset, and make a new dataset with the epoch length I
actually want
5. Directly use the list of good trials at whatever stage is relevant
(ft_timelockanalysis or whatever) to make sure you're only keeping the
trials that would have made it through artifact rejection

Best,
Steve



---
Stephen Politzer-Ahles
University of Oxford
Language and Brain Lab
Faculty of Linguistics, Phonetics & Philology
http://users.ox.ac.uk/~cpgl0080/


>
> Message: 4
> Date: Fri, 1 Jul 2016 14:10:09 +0200
> From: Philipp Taesler <p.taesler at uke.de>
> To: <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] Automatic artifact detection (no rejection)
> Message-ID: <15e80a9d-3eba-0c7b-cd77-af2e5f1d80c4 at uke.de>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Robin,
>
> you are right, the comment in the function explicitly says:
>
> % Contrary to the other artifact detection functions, this function
> % will mark the whole trial as an artifact if the threshold is exceeded.
> % Furthermore, this function does not support artifact- or filterpadding.
>
> I didn't know that. Hmmm, then I guess your only option is to either
> visually review the marked trials and unmark the ones you want to keep.
> Another possibilty might be to use ft_redefinetrial to create a dataset
> with shorter trials, run the rejection on this data, and use the
> resulting artefact definitions for your original data. (Not sure if that
> is straightforward, since I never did this myself).
>
> Cheers,
> Phil
>
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160701/9ec194e0/attachment.htm>

From viviana.betti at gmail.com  Fri Jul  1 21:27:07 2016
From: viviana.betti at gmail.com (Viviana Betti)
Date: Fri, 1 Jul 2016 19:27:07 +0000
Subject: [FieldTrip] PhD position in Rome
Message-ID: <3c8cb771f59a449ebf442e3379facc76@EXPRD02.hosting.ru.nl>

Dear Fieldtrip community,
Please see below the opportunity for the "International PhD in Cognitive Social Affective and Social Neuroscience" (CoSAN, http://www.cosanphd.com/) at the Department of Psychology, Sapienza University of Rome and the research-oriented hospital IRCCS Fondazione Santa Lucia in Rome.

In the attachment you may find all the information concerning the details of the PhD program.
I would kindly ask you to spread the voice to your Department or any other Institution, colleague, or to any potential applicant.

Best wishes
Viviana Betti
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160701/e18b54df/attachment.htm>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: Attachment.pdf
Type: application/pdf
Size: 247299 bytes
Desc: Attachment.pdf
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160701/e18b54df/attachment.pdf>

From jan at brogger.no  Sat Jul  2 01:13:57 2016
From: jan at brogger.no (=?iso-8859-1?Q?Jan_Br=F8gger?=)
Date: Sat, 2 Jul 2016 01:13:57 +0200
Subject: [FieldTrip] EEGLAB integration code question
Message-ID: <007101d1d3ee$3ec1cae0$bc4560a0$@brogger.no>

I just submitted a pull request to read Nicolet/Nervus files with fieldtrip
(https://github.com/fieldtrip/fieldtrip/pull/186) based on Joost Wagenaar’s
code from https://github.com/ieeg-portal/Nicolet-Reader with some updates
from me. Nicolet/Nervus is popular for clinical EEG. The chief advantage is
that it reads the file without depending on any external (vendor-supplied)
DLLs or conversion to EDF.

 

I have two questions that concern EEGLAB and fieldtrip integration:

1.       How can I make EEGLAB know that the Nervus/Nicolet EEG file read
with fieldtrip was originally recorded with a common reference (Fp1-REF,
Fp2-REF)? As far as I know, almost all clinical EEG is recorded with REF in
this way. There is an example in ft_read_header.m line 299 for the ‘Anywave’
format, which says “hdr.reference = orig.reference(:);” but apparently
EEGLAB doesn’t use this field.   In fieldtrip2eeglab.m there is no
functionality to say that this is a common reference.  There are many
references in the EEGLAB code similar to EEG.ref = ‘common’ but I can’t
quite make heads or tails of it.

2.       How can I make EEGLAB know the original filename of the
Nervus/Nicolet EEG file read with fieldtrip? In fieldtrip2eeglab.m line 25
it simply says “EEG.filename   = '';”. Could I submit a pull request to
EEGLAB with “EEG.filename = hdr.filename;” (with a check to see if the
filename field exists?)

3.       There are often breaks in clinical EEG recordings (e.g. adjusting
the photic lamps, instructing in hyperventilation etc.). Currently the
Nicolet/Nervus code handles this by creating events of type ‘boundary’,
which should make it work for EEGLAB. I hope I don’t have to use the
“trials” functionality of fieldtrip to indicate discontinuities. Will
fieldtrip understand events of type ‘boundary’?

 

 

Yours sincerely,

 

Jan Brogger

Clinical neurophysiologist/software developer, MD PhD

Bergen, Norway

 

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160702/b850f1da/attachment.htm>

From andrejakosticln at gmail.com  Wed Jul  6 15:33:01 2016
From: andrejakosticln at gmail.com (=?UTF-8?Q?Andreja_Kosti=C4=87?=)
Date: Wed, 6 Jul 2016 15:33:01 +0200
Subject: [FieldTrip] How do I use an atlas to find regions on an individual
	MRI?
Message-ID: <CAFjWhnLYHm926w6bi86_-5HPJsn-nbhRXBRPVodN_mrF38omOg@mail.gmail.com>

Hello dear Fieldtrippers!

This is my first post on the mailing list, so I apologize if this looks a
bit confused.



So I'm trying to use the WFU PickAtlas for Brodmann areas in what I think
are MNI coordinates to find specific regions inside of a brain (I'm coming
from electrical engineering background, so I can't do that "by hand") in an
individual whole-head MRI and I'm having issues getting sane results.

I suspect that my workflow is the problem, so I would be very grateful if
someone could provide some advice as to what I should be actually doing.

My original idea was to take MRI in CTF coordinates, convert it to MNI
coordinates and then just use atlas to make masks. From what I could
gather, it's not that simple.

So here are examples of what I'm doing right now:

ft_defaults;

%Let's read atlas

atlas =
ft_read_atlas('C:\REALY_LONG_PATH_TO_PICKATLAS\wfu_pickatlas\MNI_atlas_templates\TD_brodmann.nii');


%Using Subject01from FT tutorials right now, for simplicity's sake.
mri = ft_read_mri('Subject01\Subject01.mri');


%Reslice, apply transformations
cfg=[];
cfg.dim=[256 256 256];
mri_resliced=ft_volumereslice(cfg, mri);

cfg=[];
mri_norm1=ft_volumenormalise(cfg,mri_resliced);

%Unfortunately, this cuts off everything below the nose!

%Still let's take a look at the visualization with atlas

cfg=[];
cfg.inputcoord='mni';
cfg.atlas=atlas;
cfg.roi='brodmann area 4';

mask4 = ft_volumelookup(cfg, mri_norm1);
mri_norm1.mask4=mask4;

cfg=[];
cfg.atlas=atlas;
cfg.funparameter = 'mask4';
ft_sourceplot(cfg,mri_norm1)



%The result doesn't look so good, big part of the area seems to fit inside
of the gaps between brain tissue!

So this doesn't seem to have worked out. My next attempt was to directly
use ft_convert_coordsys. This fixed the cutting issue, but it didn't solve
the problem of results looking strange.

So my other idea was to try with

template=ft_read_mri('C:\PathToFT\external\spm8\templates\T1.nii');

cfg=[];
cfg.method='spm';
cfg.coordsys='spm';
mri_realigned=ft_volumerealign(cfg,mri_resliced,template);

But this produces very obviously wrong results, like coronal slices on
sagittal plane.

I'm also not sure if I should be trying to somehow transform an atlas to
fit the individual MRI that I'm using?

All the best,
Andreja Kostić
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160706/aa2f7cae/attachment.htm>

From jan.schoffelen at donders.ru.nl  Wed Jul  6 16:06:16 2016
From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs))
Date: Wed, 6 Jul 2016 14:06:16 +0000
Subject: [FieldTrip] How do I use an atlas to find regions on an
 individual	MRI?
In-Reply-To: <CAFjWhnLYHm926w6bi86_-5HPJsn-nbhRXBRPVodN_mrF38omOg@mail.gmail.com>
References: <CAFjWhnLYHm926w6bi86_-5HPJsn-nbhRXBRPVodN_mrF38omOg@mail.gmail.com>
Message-ID: <78D16A4A-6C63-4FDB-A3CD-09C759B7140D@donders.ru.nl>

Dear Andreja,

I have never understood ft_volumelookup myself, so I wonder whether you would be helped by proposing a different strategy…

I would do the following:

% read in the atlas
atlas = ft_read_atlas(‘somefilename’);

% read in and normalise the anatomical image
mri = ft_read_mri(‘someotherfilename’)
mri = ft_volumenormalise([], mri);

% assuming that both atlas and mri are in the same coordinate system
cfg = [];
cfg.parameter = ‘tissue’;
mri2 = ft_sourceinterpolate(cfg, atlas, mri);

The last step gives you the atlas interpolated onto the anatomical MRI.

It should be straightforward to create a boolean mask from here that specifies a particular ROI

mri2.mask = mri2.tissue==strcmp(atlas.tissuelabel, ‘yourfavoritebrodmannarea’);


I hope this helps.

Best wishes,
Jan-Mathijs



On 06 Jul 2016, at 15:33, Andreja Kostić <andrejakosticln at gmail.com<mailto:andrejakosticln at gmail.com>> wrote:

Hello dear Fieldtrippers!
This is my first post on the mailing list, so I apologize if this looks a bit confused.

So I'm trying to use the WFU PickAtlas for Brodmann areas in what I think are MNI coordinates to find specific regions inside of a brain (I'm coming from electrical engineering background, so I can't do that "by hand") in an individual whole-head MRI and I'm having issues getting sane results.

I suspect that my workflow is the problem, so I would be very grateful if someone could provide some advice as to what I should be actually doing.

My original idea was to take MRI in CTF coordinates, convert it to MNI coordinates and then just use atlas to make masks. From what I could gather, it's not that simple.
So here are examples of what I'm doing right now:

ft_defaults;
%Let's read atlas
atlas = ft_read_atlas('C:\REALY_LONG_PATH_TO_PICKATLAS\wfu_pickatlas\MNI_atlas_templates\TD_brodmann.nii');


%Using Subject01from FT tutorials right now, for simplicity's sake.
mri = ft_read_mri('Subject01\Subject01.mri');


%Reslice, apply transformations
cfg=[];
cfg.dim=[256 256 256];
mri_resliced=ft_volumereslice(cfg, mri);

cfg=[];
mri_norm1=ft_volumenormalise(cfg,mri_resliced);
%Unfortunately, this cuts off everything below the nose!
%Still let's take a look at the visualization with atlas

cfg=[];
cfg.inputcoord='mni';
cfg.atlas=atlas;
cfg.roi='brodmann area 4';

mask4 = ft_volumelookup(cfg, mri_norm1);
mri_norm1.mask4=mask4;

cfg=[];
cfg.atlas=atlas;
cfg.funparameter = 'mask4';
ft_sourceplot(cfg,mri_norm1)

%The result doesn't look so good, big part of the area seems to fit inside of the gaps between brain tissue!
So this doesn't seem to have worked out. My next attempt was to directly use ft_convert_coordsys. This fixed the cutting issue, but it didn't solve the problem of results looking strange.
So my other idea was to try with

template=ft_read_mri('C:\PathToFT\external\spm8\templates\T1.nii');

cfg=[];
cfg.method='spm';
cfg.coordsys='spm';
mri_realigned=ft_volumerealign(cfg,mri_resliced,template);
But this produces very obviously wrong results, like coronal slices on sagittal plane.
I'm also not sure if I should be trying to somehow transform an atlas to fit the individual MRI that I'm using?

All the best,
Andreja Kostić








_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160706/bcc493f5/attachment.htm>

From r.thomas at nin.knaw.nl  Wed Jul  6 17:11:04 2016
From: r.thomas at nin.knaw.nl (Rajat Thomas)
Date: Wed, 6 Jul 2016 15:11:04 +0000
Subject: [FieldTrip] Group analysis, source surface recon
Message-ID: <1467817864661.72517@nin.knaw.nl>

Dear Fieldtrippers,


I did a MinimumNorm source recon on individual subjects successfully following the nice

tutorial on minnorm on fieldtrip.org!


Now, I want to do a group analysis extending this tutorial to the group level.


Q1. Anyone has done or knows how to do group analysis using surfaces (that we so painfully

constructed using freesurfer)?


Q2. Any helper scripts for group analysis (even volumetric) would be highly appreciated.


If it all works, I will be happy to upload my scripts and write up a neat group analysis tutorial. :-)


Thank you.


Rajat


Rajat Mani Thomas
Social Brain Lab
Netherlands Institute for Neuroscience
Amsterdam
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160706/f11f35c2/attachment.htm>

From andrejakosticln at gmail.com  Wed Jul  6 18:20:48 2016
From: andrejakosticln at gmail.com (=?UTF-8?Q?Andreja_Kosti=C4=87?=)
Date: Wed, 6 Jul 2016 18:20:48 +0200
Subject: [FieldTrip] How do I use an atlas to find regions on an
 individual MRI?
In-Reply-To: <78D16A4A-6C63-4FDB-A3CD-09C759B7140D@donders.ru.nl>
References: <CAFjWhnLYHm926w6bi86_-5HPJsn-nbhRXBRPVodN_mrF38omOg@mail.gmail.com>
 <78D16A4A-6C63-4FDB-A3CD-09C759B7140D@donders.ru.nl>
Message-ID: <CAFjWhnJUmHn013ArNHjFm58YbpU1Q9dRqkncNCUuyw_2r2PNDg@mail.gmail.com>

Hello Jan-Mathijs and thank you very much for your answer!!

Since my approach is not producing results, I'm naturally very open to
different strategies!



Unfortunately, I do not understand how exactly your suggested process of
creating a mask works.

Namely, at least for me, the mri2.tissue is a 3D matrix that has the same
size as the anatomy. Result of strcmp(atlas.tissuelabel,
‘yourfavoritebrodmannarea’) is a vector that has a 1 at the index of my
favorite Brodmann area. Matlab does not allow comparison between two of
them.

At first I thought that the value in the tissue structure is a number
matching the index of a label, but then I saw that there are also decimal
numbers in the mri2.tissue as well, which confused me.

I also tried with following:
mri2.mask = mri2.tissue==find(strcmp(atlas.tissuelabel,'brodmann area
17'));

which does return something, but the mask has points spread around the
whole brain, so this obviously doesn't work the way I thought it does.

So I'm not really sure how to make this mask work.


All the best,
Andreja Kostić

2016-07-06 16:06 GMT+02:00 Schoffelen, J.M. (Jan Mathijs) <
jan.schoffelen at donders.ru.nl>:

> Dear Andreja,
>
> I have never understood ft_volumelookup myself, so I wonder whether you
> would be helped by proposing a different strategy…
>
> I would do the following:
>
> % read in the atlas
> atlas = ft_read_atlas(‘somefilename’);
>
> % read in and normalise the anatomical image
> mri = ft_read_mri(‘someotherfilename’)
> mri = ft_volumenormalise([], mri);
>
> % assuming that both atlas and mri are in the same coordinate system
> cfg = [];
> cfg.parameter = ‘tissue’;
> mri2 = ft_sourceinterpolate(cfg, atlas, mri);
>
> The last step gives you the atlas interpolated onto the anatomical MRI.
>
> It should be straightforward to create a boolean mask from here that
> specifies a particular ROI
>
> mri2.mask = mri2.tissue==strcmp(atlas.tissuelabel,
> ‘yourfavoritebrodmannarea’);
>
>
> I hope this helps.
>
> Best wishes,
> Jan-Mathijs
>
>
>
> On 06 Jul 2016, at 15:33, Andreja Kostić <andrejakosticln at gmail.com>
> wrote:
>
> Hello dear Fieldtrippers!
>
> This is my first post on the mailing list, so I apologize if this looks a
> bit confused.
>
>
> So I'm trying to use the WFU PickAtlas for Brodmann areas in what I think
> are MNI coordinates to find specific regions inside of a brain (I'm coming
> from electrical engineering background, so I can't do that "by hand") in an
> individual whole-head MRI and I'm having issues getting sane results.
>
> I suspect that my workflow is the problem, so I would be very grateful if
> someone could provide some advice as to what I should be actually doing.
>
> My original idea was to take MRI in CTF coordinates, convert it to MNI
> coordinates and then just use atlas to make masks. From what I could
> gather, it's not that simple.
>
> So here are examples of what I'm doing right now:
>
> ft_defaults;
>
> %Let's read atlas
>
> atlas =
> ft_read_atlas('C:\REALY_LONG_PATH_TO_PICKATLAS\wfu_pickatlas\MNI_atlas_templates\TD_brodmann.nii');
>
>
> %Using Subject01from FT tutorials right now, for simplicity's sake.
> mri = ft_read_mri('Subject01\Subject01.mri');
>
>
> %Reslice, apply transformations
> cfg=[];
> cfg.dim=[256 256 256];
> mri_resliced=ft_volumereslice(cfg, mri);
>
> cfg=[];
> mri_norm1=ft_volumenormalise(cfg,mri_resliced);
>
> %Unfortunately, this cuts off everything below the nose!
>
> %Still let's take a look at the visualization with atlas
>
> cfg=[];
> cfg.inputcoord='mni';
> cfg.atlas=atlas;
> cfg.roi='brodmann area 4';
>
> mask4 = ft_volumelookup(cfg, mri_norm1);
> mri_norm1.mask4=mask4;
>
> cfg=[];
> cfg.atlas=atlas;
> cfg.funparameter = 'mask4';
> ft_sourceplot(cfg,mri_norm1)
>
>
> %The result doesn't look so good, big part of the area seems to fit inside
> of the gaps between brain tissue!
>
> So this doesn't seem to have worked out. My next attempt was to directly
> use ft_convert_coordsys. This fixed the cutting issue, but it didn't solve
> the problem of results looking strange.
>
> So my other idea was to try with
>
> template=ft_read_mri('C:\PathToFT\external\spm8\templates\T1.nii');
>
> cfg=[];
> cfg.method='spm';
> cfg.coordsys='spm';
> mri_realigned=ft_volumerealign(cfg,mri_resliced,template);
>
> But this produces very obviously wrong results, like coronal slices on
> sagittal plane.
>
> I'm also not sure if I should be trying to somehow transform an atlas to
> fit the individual MRI that I'm using?
>
> All the best,
> Andreja Kostić
>
>
>
>
>
>
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160706/04d9ca25/attachment.htm>

From jan.schoffelen at donders.ru.nl  Wed Jul  6 18:43:20 2016
From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs))
Date: Wed, 6 Jul 2016 16:43:20 +0000
Subject: [FieldTrip] How do I use an atlas to find regions on an
 individual MRI?
In-Reply-To: <CAFjWhnJUmHn013ArNHjFm58YbpU1Q9dRqkncNCUuyw_2r2PNDg@mail.gmail.com>
References: <CAFjWhnLYHm926w6bi86_-5HPJsn-nbhRXBRPVodN_mrF38omOg@mail.gmail.com>
 <78D16A4A-6C63-4FDB-A3CD-09C759B7140D@donders.ru.nl>
 <CAFjWhnJUmHn013ArNHjFm58YbpU1Q9dRqkncNCUuyw_2r2PNDg@mail.gmail.com>
Message-ID: <F40D5B89-F020-4DF3-AC17-41EC0C71865D@donders.ru.nl>

Sorry Andreja,
I forgot the find() indeed.
Also, I forgot to mention that the cfg to ft_sourceinterpolate should specify the interpolation method to be ‘nearest’.
I hope this helps.
Best,
Jan-Mathijs

On 06 Jul 2016, at 18:20, Andreja Kostić <andrejakosticln at gmail.com<mailto:andrejakosticln at gmail.com>> wrote:

Hello Jan-Mathijs and thank you very much for your answer!!
Since my approach is not producing results, I'm naturally very open to different strategies!

Unfortunately, I do not understand how exactly your suggested process of creating a mask works.
Namely, at least for me, the mri2.tissue is a 3D matrix that has the same size as the anatomy. Result of strcmp(atlas.tissuelabel, ‘yourfavoritebrodmannarea’) is a vector that has a 1 at the index of my favorite Brodmann area. Matlab does not allow comparison between two of them.
At first I thought that the value in the tissue structure is a number matching the index of a label, but then I saw that there are also decimal numbers in the mri2.tissue as well, which confused me.
I also tried with following:
mri2.mask = mri2.tissue==find(strcmp(atlas.tissuelabel,'brodmann area 17'));
which does return something, but the mask has points spread around the whole brain, so this obviously doesn't work the way I thought it does.
So I'm not really sure how to make this mask work.

All the best,
Andreja Kostić

2016-07-06 16:06 GMT+02:00 Schoffelen, J.M. (Jan Mathijs) <jan.schoffelen at donders.ru.nl<mailto:jan.schoffelen at donders.ru.nl>>:
Dear Andreja,

I have never understood ft_volumelookup myself, so I wonder whether you would be helped by proposing a different strategy…

I would do the following:

% read in the atlas
atlas = ft_read_atlas(‘somefilename’);

% read in and normalise the anatomical image
mri = ft_read_mri(‘someotherfilename’)
mri = ft_volumenormalise([], mri);

% assuming that both atlas and mri are in the same coordinate system
cfg = [];
cfg.parameter = ‘tissue’;
mri2 = ft_sourceinterpolate(cfg, atlas, mri);

The last step gives you the atlas interpolated onto the anatomical MRI.

It should be straightforward to create a boolean mask from here that specifies a particular ROI

mri2.mask = mri2.tissue==strcmp(atlas.tissuelabel, ‘yourfavoritebrodmannarea’);


I hope this helps.

Best wishes,
Jan-Mathijs



On 06 Jul 2016, at 15:33, Andreja Kostić <andrejakosticln at gmail.com<mailto:andrejakosticln at gmail.com>> wrote:

Hello dear Fieldtrippers!
This is my first post on the mailing list, so I apologize if this looks a bit confused.

So I'm trying to use the WFU PickAtlas for Brodmann areas in what I think are MNI coordinates to find specific regions inside of a brain (I'm coming from electrical engineering background, so I can't do that "by hand") in an individual whole-head MRI and I'm having issues getting sane results.

I suspect that my workflow is the problem, so I would be very grateful if someone could provide some advice as to what I should be actually doing.

My original idea was to take MRI in CTF coordinates, convert it to MNI coordinates and then just use atlas to make masks. From what I could gather, it's not that simple.
So here are examples of what I'm doing right now:

ft_defaults;
%Let's read atlas
atlas = ft_read_atlas('C:\REALY_LONG_PATH_TO_PICKATLAS\wfu_pickatlas\MNI_atlas_templates\TD_brodmann.nii');


%Using Subject01from FT tutorials right now, for simplicity's sake.
mri = ft_read_mri('Subject01\Subject01.mri');


%Reslice, apply transformations
cfg=[];
cfg.dim=[256 256 256];
mri_resliced=ft_volumereslice(cfg, mri);

cfg=[];
mri_norm1=ft_volumenormalise(cfg,mri_resliced);
%Unfortunately, this cuts off everything below the nose!
%Still let's take a look at the visualization with atlas

cfg=[];
cfg.inputcoord='mni';
cfg.atlas=atlas;
cfg.roi='brodmann area 4';

mask4 = ft_volumelookup(cfg, mri_norm1);
mri_norm1.mask4=mask4;

cfg=[];
cfg.atlas=atlas;
cfg.funparameter = 'mask4';
ft_sourceplot(cfg,mri_norm1)

%The result doesn't look so good, big part of the area seems to fit inside of the gaps between brain tissue!
So this doesn't seem to have worked out. My next attempt was to directly use ft_convert_coordsys. This fixed the cutting issue, but it didn't solve the problem of results looking strange.
So my other idea was to try with

template=ft_read_mri('C:\PathToFT\external\spm8\templates\T1.nii');

cfg=[];
cfg.method='spm';
cfg.coordsys='spm';
mri_realigned=ft_volumerealign(cfg,mri_resliced,template);
But this produces very obviously wrong results, like coronal slices on sagittal plane.
I'm also not sure if I should be trying to somehow transform an atlas to fit the individual MRI that I'm using?

All the best,
Andreja Kostić








_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
https://mailman.science.ru.nl/mailman/listinfo/fieldtrip


_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160706/0d138ab0/attachment.htm>

From jan.schoffelen at donders.ru.nl  Thu Jul  7 07:36:01 2016
From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs))
Date: Thu, 7 Jul 2016 05:36:01 +0000
Subject: [FieldTrip] Group analysis, source surface recon
In-Reply-To: <1467817864661.72517@nin.knaw.nl>
References: <1467817864661.72517@nin.knaw.nl>
Message-ID: <A4A29D30-DCF8-46A1-B69E-FE6F5A75CB59@donders.ru.nl>

Dear Rajat,

Q1. Anyone has done or knows how to do group analysis using surfaces (that we so painfully
constructed using freesurfer)?

A1: Yes, I have done it, and know how to do so.

Q2. Any helper scripts for group analysis (even volumetric) would be highly appreciated.

A2: This question has been asked and answered before. A good start would be to look at the following (so that I don’t need to type it again :o) ):

https://mailman.science.ru.nl/pipermail/fieldtrip/2016-June/010539.html

https://mailman.science.ru.nl/pipermail/fieldtrip/2015-July/009348.html

https://mailman.science.ru.nl/pipermail/fieldtrip/2015-June/009312.html

https://mailman.science.ru.nl/pipermail/fieldtrip/2015-September/009669.html



If it all works, I will be happy to upload my scripts and write up a neat group analysis tutorial. :-)


That sounds like a good deal, but be warned: in the past I gently nudged the people involved to contribute their solution back to the wiki. I haven’t heard back from them since. Whether this is due them running into problems, or whether it has other reasons…?

Best,
Jan-Mathijs



Thank you.

Rajat


Rajat Mani Thomas
Social Brain Lab
Netherlands Institute for Neuroscience
Amsterdam
_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160707/5773268b/attachment.htm>

From martinvinck at gmail.com  Fri Jul  8 17:04:10 2016
From: martinvinck at gmail.com (Martin Vinck)
Date: Fri, 8 Jul 2016 17:04:10 +0200
Subject: [FieldTrip] =?utf-8?q?PhD/postdoc_positions_at_Ernst_Str=C3=BCngm?=
	=?utf-8?q?ann_Institute_for_Neuroscience?=
Message-ID: <CAAn08hSGnZFiYftr7oyXRvS1Mk8SgAm279P2Cvfi4cQA+bwbgw@mail.gmail.com>

Our laboratory at the Ernst Strüngmann Institute for Neuroscience in
Cooperation with Max Planck Society is seeking candidates for Postdoc and
Ph.D. positions.

Projects involve the application of parallel, large-scale
electrophysiological recording techniques of single units and EEG in
combination with closed-loop optogenetic manipulation methods to
investigate mechanisms of information encoding and transmission in mice
brains. We are particularly interested in the way in which the brain
efficiently encodes information, and the way in which sensory predictions
established in higher areas influence sensory representations in earlier
sensory areas. We are furthermore interested in investigating the role of
GABAergic interneurons in selective attention and neuronal oscillations. We
address these questions using laminar recordings in combination with
optogenetics in mice, as well as through the development of novel tools for
the quantitative analysis of large-scale electrophysiological data. Within
the ESI, tight collaborations exist with the lab of Prof. Dr. Pascal Fries.

Because we are searching for members that can strengthen an
interdisciplinary team, we are encouraging students/researchers with a
background either in biological/medical sciences or in
physics/engineering/mathematics/etc. to apply. The ideal PhD or postdoc
candidate has previous experience and strengths either in 1) performing
hands-on experimental work and electrophysiological recordings or 2)
hardware engineering and quantitative analysis of large-scale data. We are
searching for applicants with good communication skills and a high
commitment and curiosity about neuroscientific questions.

Interested candidates are invited to send their application materials in
electronic form (PDF format) to martin.vinck at esi-frankfurt.de

Applications should contain a letter of intent, a detailed curriculum
vitae, lists of university courses completed with marks obtained (only for
PhD candidates), and the names of at least two scientists who can give
references. The advertisement will be valid until positions are filled.

Dr. Martin Vinck
martin.vinck at esi-frankfurt.de
Research Group Leader
Ernst Strüngmann Institute (ESI) for Neuroscience in Cooperation with Max
Planck Society
Deutschordenstr. 46, D-60528
Frankfurt am Main, Germany
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160708/e3852a34/attachment.htm>

From RICHARDS at mailbox.sc.edu  Mon Jul 11 04:14:41 2016
From: RICHARDS at mailbox.sc.edu (RICHARDS, JOHN)
Date: Mon, 11 Jul 2016 02:14:41 +0000
Subject: [FieldTrip] tissue labels in mesh for prepare head model
Message-ID: <C035D3CE-3EF2-4152-88B6-A4EAA02871E7@mailbox.sc.edu>

I switched a couple of months ago to a version of FT.  I am using simbio meshes and ft_prepare_headmodel for a FEM source analysis.

This is the code to prepare the mesh:  (mri.tissuelabel is in the mri structure).
cfg        = [];
cfg.shift  = 0.3;
cfg.method = 'hexahedral';
cfg.tissue = mri.tissuelabel;
mesh = ft_prepare_mesh(cfg,mri);

This results in a struct with
hex
labels
tissue
tissuelabel

When I run 
cfg        = [];
cfg.method ='simbio';
cfg.conductivity=conductivity1;
vol        = ft_prepare_headmodel(cfg, mesh);    

I get several instances warnings (see below).  The warnings are because the getdimord does not recognize “labels” and “tissue”.  But the ft_headmodel_simbio needs the tissue to tell which tissues to assign conductivity to a hex voxel.  See header of the ft_headmodel_simbio, designates hex, tissue, and tissuelabel.  

This used to work in the previous version; it may still be working just giving a warning.

Any help?

John

E.g., from header
Use as
    headmodel = ft_headmodel_simbio(mesh,'conductivity', conductivities, ...)
 
  The mesh is given as a volumetric mesh, using ft_datatype_parcellation
    mesh.pos = vertex positions
    mesh.tet/mesh.hex = list of volume elements
    mesh.tissue = tissue assignment for elements
    mesh.tissuelabel = labels correspondig to tissues
 
  Required input arguments should be specified in key-value pairs and have

Warning: could not determine dimord of "tissue" in the following data 
> In getdimord (line 549)
  In ft_datatype_source (line 232)
  In ft_datatype_parcellation (line 178)
  In ft_headmodel_simbio (line 46)
  In ft_prepare_headmodel (line 430)
  In CreateFieldtripHeadModels (line 348) 
            hex: [1440558x8 double]
         labels: [1440558x1 double]
         tissue: [1440558x1 double]
    tissuelabel: {'wm'  'gm'  't2wcsf'  'dura'  'skull'  'scalp'  'head'  'eyes'  'nasalcavity'  'nma_pve'}
           unit: 'mm'
            cfg: [1x1 struct]
            pos: [1487661x3 double]
         inside: [1487661x1 logical]

AND

Warning: could not determine dimord of "labels" in the following data 
> In getdimord (line 549)
  In ft_datatype_source (line 232)
  In ft_datatype_parcellation (line 178)
  In ft_headmodel_simbio (line 46)
  In ft_prepare_headmodel (line 430)
  In CreateFieldtripHeadModels (line 348) 
            hex: [1440558x8 double]
         labels: [1440558x1 double]
         tissue: [1440558x1 double]
    tissuelabel: {'wm'  'gm'  't2wcsf'  'dura'  'skull'  'scalp'  'head'  'eyes'  'nasalcavity'  'nma_pve'}
           unit: 'mm'
            cfg: [1x1 struct]
            pos: [1487661x3 double]
         inside: [1487661x1 logical]

***********************************************
John E. Richards Carolina Distinguished Professor
Department of Psychology
University of South Carolina
Columbia, SC  29208
Dept Phone: 803 777 2079
Fax: 803 777 9558
HTTP: jerlab.psych.sc.edu
***********************************************






From simon.nougaret at uniroma1.it  Mon Jul 11 12:56:15 2016
From: simon.nougaret at uniroma1.it (Simon Nougaret)
Date: Mon, 11 Jul 2016 12:56:15 +0200
Subject: [FieldTrip] Significance of the cross correlogram
Message-ID: <CAMU8U1ET6oyh-P1gf=KiikDDV8KZDEJoXUUR+TRQFjbqxTikNw@mail.gmail.com>

Hello everybody,
I'm a new Fildtrip User and I use it principally to compute
crosscorrelations analysis.
I tried to find a topic in the archives of the discussion about a technique
to compute significance level of the correlations performed by filedtrip
but I didn't found anything.

My first question concern the ft_spike_xcorr function where I do not
understand the case 'shiftpredictor' line 272.
Why the 'shuffling' method means to compute the cross correlation between
the trial n of the neuron 1 on the trial n-1 of the neuron 2 ?
Why is it not a real shuffle ? (to keep the same 'shuffle' curve if we redo
the analysis ?)

My second is about significance between the shuffled and real
cross-correlogram.
Do you think that it is correct, instead of the lines 275 to 278 :
          inTrial1_old = spike.trial{indx(1)}==cfg.trials(iTrial-1);
          ts1_old      = sort(spike.time{indx(1)}(inTrial1_old(:) &
inWindow1(:)));
          inTrial2_old = spike.trial{indx(2)}==cfg.trials(iTrial-1);
          ts2_old      = sort(spike.time{indx(2)}(inTrial2_old(:) &
inWindow2(:)));

to perform the analysis between trials taken by chance ?

          RandTrial = 1 + (nTrials-1) * rand(1);
          RandTrial = round(RandTrial);

          inTrial1_shuff = spike.trial{indx(1)}==cfg.trials(RandTrial);
          ts1_Rand      = sort(spike.time{indx(1)}(inTrial1_shuff(:) &
inWindow1(:)));
          inTrial2_shuff = spike.trial{indx(2)}==cfg.trials(RandTrial);
          ts2_Rand      = sort(spike.time{indx(2)}(inTrial2_shuff(:) &
inWindow2(:)));

The idea is to compute that thousand times to have the possibility to get
an equivalent of the p.value (as a kind of bootstrap analysis).
I join a figure of this computation where we can easily calculate p-values
for each bins of the crosscorrelogram. For each bin the value of the black
curve (real crosscorrelogram) will be compared to the level of chance based
of the thousands of repetitions.

Thank you in advance for your feedbacks and your responses.

Best regards,
Simon Nougaret

-- 
___________________________________________
INVESTI SUL FUTURO, FAI CRESCERE L’UNIVERSITÀ:

*DONA IL 5 PER MILLE ALLA SAPIENZA*

CODICE FISCALE *80209930587*
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160711/dc479a23/attachment.htm>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: Example shuffling.png
Type: image/png
Size: 196932 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160711/dc479a23/attachment.png>

From stephen.whitmarsh at gmail.com  Mon Jul 11 15:39:54 2016
From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh)
Date: Mon, 11 Jul 2016 15:39:54 +0200
Subject: [FieldTrip] User-defined random seed in ft_componentanalysis
	(runica)
Message-ID: <CAFrxm=zjGrPE5fc_SjLf=Q6anMyKq=eci13-1s8x=Pn2MDO66Q@mail.gmail.com>

Hi there,

I have a question about the use of the cfg.randomseed option in
ft_componentanalysis. I would like to be able to use the same seed over
different iterations of ft_componentanalysis, which should result in the
same output.

Can anyone confirm this is actually the case? I cannot see how
cfg.randomseed is passed through to runica.m, and line 812 (runica.m) reads:

rand('state',sum(100*clock));  % set the random number generator state to
                               % a position dependent on the system clock


Best,
Stephen
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160711/1d20fee7/attachment.htm>

From jan.schoffelen at donders.ru.nl  Mon Jul 11 17:06:23 2016
From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs))
Date: Mon, 11 Jul 2016 15:06:23 +0000
Subject: [FieldTrip] User-defined random seed in
	ft_componentanalysis	(runica)
In-Reply-To: <CAFrxm=zjGrPE5fc_SjLf=Q6anMyKq=eci13-1s8x=Pn2MDO66Q@mail.gmail.com>
References: <CAFrxm=zjGrPE5fc_SjLf=Q6anMyKq=eci13-1s8x=Pn2MDO66Q@mail.gmail.com>
Message-ID: <6329D8FE-28FE-421C-9DD6-CD4282B021D5@donders.ru.nl>

Hi Stephen,

The fieldtrip-version of runica (in fieldtrip/external/eeglab/runica) allows for a user-specified setting reset_randomseed, that can be passed on from the higher level function (i.e. ft_componentanalysis). This way the user can pass on a predefined random seed, allowing for deterministic behaviour of runica upon different function calls. This has been changed about a year ago. Time to update your fieldtrip copy?

Best,

Jan-Mathijs




> On 11 Jul 2016, at 15:39, Stephen Whitmarsh <stephen.whitmarsh at gmail.com> wrote:
> 
> Hi there,
> 
> I have a question about the use of the cfg.randomseed option in ft_componentanalysis. I would like to be able to use the same seed over different iterations of ft_componentanalysis, which should result in the same output.
> 
> Can anyone confirm this is actually the case? I cannot see how cfg.randomseed is passed through to runica.m, and line 812 (runica.m) reads:
> 
> rand('state',sum(100*clock));  % set the random number generator state to
>                                % a position dependent on the system clock
> 
> 
> Best,
> Stephen
> 
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip




From Holger.Krause at med.uni-duesseldorf.de  Mon Jul 11 17:16:00 2016
From: Holger.Krause at med.uni-duesseldorf.de (Holger Krause)
Date: Mon, 11 Jul 2016 17:16:00 +0200
Subject: [FieldTrip] User-defined random seed in ft_componentanalysis
	(runica)
In-Reply-To: <CAFrxm=zjGrPE5fc_SjLf=Q6anMyKq=eci13-1s8x=Pn2MDO66Q@mail.gmail.com>
References: <CAFrxm=zjGrPE5fc_SjLf=Q6anMyKq=eci13-1s8x=Pn2MDO66Q@mail.gmail.com>
Message-ID: <1903164.HQZdkoyGZl@metta>

Am Montag, 11. Juli 2016, 15:39:54 schrieb Stephen Whitmarsh:
> Hi there,
> 
> I have a question about the use of the cfg.randomseed option in
> ft_componentanalysis. I would like to be able to use the same seed over
> different iterations of ft_componentanalysis, which should result in the
> same output.
> 
> Can anyone confirm this is actually the case? I cannot see how
> cfg.randomseed is passed through to runica.m, and line 812 (runica.m) reads:
> 
> rand('state',sum(100*clock));  % set the random number generator state to
>                                % a position dependent on the system clock

Hi Stephen,

That's a known bug, which has been fixed last year (see 
http://bugzilla.fcdonders.nl/show_bug.cgi?id=2585). Should you need to stick 
to an older version of FT, it might be sufficient to disable the line you 
mentioned above. If I remember correctly, FT will handle setting the random 
seed elsewhere. (So there's no need to pass through 'cfg.randomseed'.)

Best,

Holger

-- 
Dr. rer. nat. Holger Krause                                         MEG-Labor
                     Institut für klinische Neurowissenschaften
http://www.uniklinik-duesseldorf.de/klinneurowiss        Uniklinik Düsseldorf




From nugenta at mail.nih.gov  Tue Jul 12 02:40:54 2016
From: nugenta at mail.nih.gov (Nugent, Allison C. (NIH/NIMH) [E])
Date: Tue, 12 Jul 2016 00:40:54 +0000
Subject: [FieldTrip] NIH MEG workshop
Message-ID: <C8161699639FAA44AA4D5FFF39CED88531C5BF2B@msgb07.nih.gov>

It is our pleasure to announce the NIH MEG North America workshop, to be held November 1st and 2nd at the NIH campus in Bethesda, MD.

A call for abstracts is currently open!  We are soliciting abstracts based on the four themes for discussion below, as well as for a general scientific session.  Visit http://megworkshop.nih.gov for more details.  Abstracts are due by September 1st.

At this meeting, we plan to address the following four themes:


1.   What does MEG add to the field of neuroscience above and beyond other existing techniques?

2.   How can we support the evolution of MEG acquisition and methods, through both software and hardware?

3.   How can we develop and support infrastructure to share data and facilitate big science?

4.   How could an MEG-North America consortium work to address these issues?

Keynote Speakers:

Sylvain Baillet, PhD<http://www.mcgill.ca/neuro/research/researchers/baillet>, Director, MEG Core McGill University, McConnell Brain Imaging Center
Dimitrios Pantazis, PhD<http://mcgovern.mit.edu/technology/meg-lab/people/dimitrios-pantazis>, Director of MEG Lab, Martinos Imaging Center
Timothy P. Roberts, PhD,<http://www.chop.edu/clinical-staff/roberts-timothy-p> Vice Chair of Research, Department of Radiology, The Children's Hospital of Philadelphia
Julia M. Stephen, PhD<http://www.mrn.org/people/julia-m-stephen/principal-investigators>, Director, MEG/EEG Core, The Mind Research Network

For more details, visit http://megworkshop.nih.gov

Registration to this NIH sponsored event is free of charge.

We hope to see you in Bethesda in November!

Dr. Richard Coppola<mailto:coppolar at mail.nih.gov>, Director, NIMH MEG Core
Dr. Allison C Nugent<mailto:nugenta at mail.nih.gov>, Director of Neuroimaging Research, Experimental Therapeutics and Pathophysiology Branch, NIMH

Register Now at Eventbrite! <https://www.eventbrite.com/e/meg-north-america-tickets-23931715405?ref=enivtefor001&invite=MTAyNzAwMDgvbnVnZW50YUBtYWlsLm5paC5nb3YvMA%3D%3D&utm_source=eb_email&utm_medium=email&utm_campaign=inviteformalv2&ref=enivtefor001&utm_term=attend>



Allison Nugent, PhD
Director of Neuroimaging Research
Experimental Therapeutics and Pathophysiology Branch
NIMH/NIH/DHHS
Ph 301-451-8863

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160712/f0464055/attachment.htm>

From ha438 at georgetown.edu  Tue Jul 12 18:35:05 2016
From: ha438 at georgetown.edu (Hassan Aleem)
Date: Tue, 12 Jul 2016 12:35:05 -0400
Subject: [FieldTrip] ft_sourcemovie
Message-ID: <CAEpb3L3mLM149oLR_z=pGzUgUFR2jzCSVkUARUhoK4PCtpGk0A@mail.gmail.com>

Does anyone have an example of how to use ft_sourcemovie to look at source
localization across time with the 'lcmv' method. would be greatly
appreciated. Thanks!
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160712/0afe264f/attachment.htm>

From joseluisblues at gmail.com  Tue Jul 12 19:45:21 2016
From: joseluisblues at gmail.com (Jose)
Date: Tue, 12 Jul 2016 19:45:21 +0200
Subject: [FieldTrip] grand average (with average across frequencies)
Message-ID: <CAH3cVdCcqR3R8LLgG7sNYDjXn2U2WjBOgA_zM-gKQ-X+2cqqMA@mail.gmail.com>

dear list,

I'm analysing CTF MEG data. I computed the power of my data for frequencies
from 1 to 50 Hz. Is it possible to perform a grand average across my
subjects, but additionally averaging across frequencies for exploratory
purposes? Maybe there is a way to do it with ft_freqgrandaverage?, but so
far I haven't find it,

Many thanks for any hint,
Jose
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160712/5f58c065/attachment.htm>

From aborna at sandia.gov  Wed Jul 13 02:47:14 2016
From: aborna at sandia.gov (Borna, Amir)
Date: Wed, 13 Jul 2016 00:47:14 +0000
Subject: [FieldTrip] Running "ft_preprocessing" on user defined data
Message-ID: <b2de3a873ff544b3993050c22101409d@ES06AMSNLNT.srn.sandia.gov>


Hi,
I have successfully imported my data into the fieldtrip's data structure according to the instructions on:
http://www.fieldtriptoolbox.org/faq/how_can_i_import_my_own_dataformat

Later I save the data in "fif" format using fieldtrip2fiff.

When I read back the data using "ft_preprocessing", the chantype and chanunit are all unknown except for the trigger. Is there any solution to this issue? Thank you.

Regards,
Amir Borna.


-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160713/86bdc328/attachment.htm>

From xiew1202 at gmail.com  Wed Jul 13 04:22:30 2016
From: xiew1202 at gmail.com (Xie Wanze)
Date: Tue, 12 Jul 2016 22:22:30 -0400
Subject: [FieldTrip] grand average (with average across frequencies)
In-Reply-To: <CAH3cVdCcqR3R8LLgG7sNYDjXn2U2WjBOgA_zM-gKQ-X+2cqqMA@mail.gmail.com>
References: <CAH3cVdCcqR3R8LLgG7sNYDjXn2U2WjBOgA_zM-gKQ-X+2cqqMA@mail.gmail.com>
Message-ID: <CAA6G0Y_tJx_FzYHvALY1+Mnh9Cj_BtBXDs5VUue-BsqhBT9ALg@mail.gmail.com>

 Jose,
 It is not difficult to do grand average across subjects or frequencies if
I understand your questions correctly.
 After you get the powspctrm matrix (chan x freq) for each subject, you can
write a "for loop" to read in each person's data and then divided by the
total number of subjects. Assuming you name your output structure as
EEG_freq for each subject, the syntax would be something like:
  freqtotal = []; numsubject = 0;
  for i = 1:length(subjects)
     ...load your data here;
        if ~numsubject; freqtotal = EEG_freq.powspctrm;
        else; freqtotal = freqtotal + EEG_freq.powspctrm;
        end;
        numsubject = numsubject + 1;
 end;
 freqavg = freqtotal / numsubject;  or freqavg = freqtotal /
length(subjects);

 To get average across frequencies, simply use the "mean" function. If you
have the chan x pow structure for your output then use "mean (freqavg, 2)"
will do the average across the second dimension (i.e., frequencies).
 Or you can do the average for frequencies for each subject then do the
average across subjects.

 Hope this will answer your questions.

 Wanze



2016-07-12 13:45 GMT-04:00 Jose <joseluisblues at gmail.com>:

> dear list,
>
> I'm analysing CTF MEG data. I computed the power of my data for
> frequencies from 1 to 50 Hz. Is it possible to perform a grand average
> across my subjects, but additionally averaging across frequencies for
> exploratory purposes? Maybe there is a way to do it with
> ft_freqgrandaverage?, but so far I haven't find it,
>
> Many thanks for any hint,
> Jose
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160712/fda69ccd/attachment.htm>

From sarathykousik at gmail.com  Wed Jul 13 10:09:01 2016
From: sarathykousik at gmail.com (kousik sarathy)
Date: Wed, 13 Jul 2016 10:09:01 +0200
Subject: [FieldTrip] grand average (with average across frequencies)
In-Reply-To: <CAA6G0Y_tJx_FzYHvALY1+Mnh9Cj_BtBXDs5VUue-BsqhBT9ALg@mail.gmail.com>
References: <CAH3cVdCcqR3R8LLgG7sNYDjXn2U2WjBOgA_zM-gKQ-X+2cqqMA@mail.gmail.com>
 <CAA6G0Y_tJx_FzYHvALY1+Mnh9Cj_BtBXDs5VUue-BsqhBT9ALg@mail.gmail.com>
Message-ID: <CAEypuQucFDw8=cJecT7QyTivCVr-dysDCJkq8+3+JUQ9bkNwGg@mail.gmail.com>

Hey Jose,

It might not be the most elegant solution, but I would suggest something
like ft_selectdata with ''cfg.avgovrfreq" & cfg.frequency=[10 50] arguments
before the actual grandaverage.
Hope it helps.

--
Regards,
Kousik Sarathy, S


On Wed, Jul 13, 2016 at 4:22 AM, Xie Wanze <xiew1202 at gmail.com> wrote:

>  Jose,
>  It is not difficult to do grand average across subjects or frequencies if
> I understand your questions correctly.
>  After you get the powspctrm matrix (chan x freq) for each subject, you
> can write a "for loop" to read in each person's data and then divided by
> the total number of subjects. Assuming you name your output structure as
> EEG_freq for each subject, the syntax would be something like:
>   freqtotal = []; numsubject = 0;
>   for i = 1:length(subjects)
>      ...load your data here;
>         if ~numsubject; freqtotal = EEG_freq.powspctrm;
>         else; freqtotal = freqtotal + EEG_freq.powspctrm;
>         end;
>         numsubject = numsubject + 1;
>  end;
>  freqavg = freqtotal / numsubject;  or freqavg = freqtotal /
> length(subjects);
>
>  To get average across frequencies, simply use the "mean" function. If you
> have the chan x pow structure for your output then use "mean (freqavg, 2)"
> will do the average across the second dimension (i.e., frequencies).
>  Or you can do the average for frequencies for each subject then do the
> average across subjects.
>
>  Hope this will answer your questions.
>
>  Wanze
>
>
>
> 2016-07-12 13:45 GMT-04:00 Jose <joseluisblues at gmail.com>:
>
>> dear list,
>>
>> I'm analysing CTF MEG data. I computed the power of my data for
>> frequencies from 1 to 50 Hz. Is it possible to perform a grand average
>> across my subjects, but additionally averaging across frequencies for
>> exploratory purposes? Maybe there is a way to do it with
>> ft_freqgrandaverage?, but so far I haven't find it,
>>
>> Many thanks for any hint,
>> Jose
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160713/a255a0a7/attachment.htm>

From stephen.whitmarsh at gmail.com  Wed Jul 13 11:21:22 2016
From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh)
Date: Wed, 13 Jul 2016 11:21:22 +0200
Subject: [FieldTrip] User-defined random seed in ft_componentanalysis
	(runica)
In-Reply-To: <1903164.HQZdkoyGZl@metta>
References: <CAFrxm=zjGrPE5fc_SjLf=Q6anMyKq=eci13-1s8x=Pn2MDO66Q@mail.gmail.com>
 <1903164.HQZdkoyGZl@metta>
Message-ID: <CAFrxm=wxtjiGD9Wzs1fG0K7JYk+4UfSM4cPkBcs3vf6AcjuGVw@mail.gmail.com>

Hi guys,

Thanks! And oops... I will update FT :-)

Cheers,
Stephen

On 11 July 2016 at 17:16, Holger Krause <
Holger.Krause at med.uni-duesseldorf.de> wrote:

> Am Montag, 11. Juli 2016, 15:39:54 schrieb Stephen Whitmarsh:
> > Hi there,
> >
> > I have a question about the use of the cfg.randomseed option in
> > ft_componentanalysis. I would like to be able to use the same seed over
> > different iterations of ft_componentanalysis, which should result in the
> > same output.
> >
> > Can anyone confirm this is actually the case? I cannot see how
> > cfg.randomseed is passed through to runica.m, and line 812 (runica.m)
> reads:
> >
> > rand('state',sum(100*clock));  % set the random number generator state to
> >                                % a position dependent on the system clock
>
> Hi Stephen,
>
> That's a known bug, which has been fixed last year (see
> http://bugzilla.fcdonders.nl/show_bug.cgi?id=2585). Should you need to
> stick
> to an older version of FT, it might be sufficient to disable the line you
> mentioned above. If I remember correctly, FT will handle setting the random
> seed elsewhere. (So there's no need to pass through 'cfg.randomseed'.)
>
> Best,
>
> Holger
>
> --
> Dr. rer. nat. Holger Krause
>  MEG-Labor
>                      Institut für klinische Neurowissenschaften
> http://www.uniklinik-duesseldorf.de/klinneurowiss        Uniklinik
> Düsseldorf
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160713/3ce6c8e3/attachment.htm>

From deb.desideri at gmail.com  Wed Jul 13 12:01:26 2016
From: deb.desideri at gmail.com (Debora Desideri)
Date: Wed, 13 Jul 2016 12:01:26 +0200
Subject: [FieldTrip] ft_sourcemovie
In-Reply-To: <CAEpb3L3mLM149oLR_z=pGzUgUFR2jzCSVkUARUhoK4PCtpGk0A@mail.gmail.com>
References: <CAEpb3L3mLM149oLR_z=pGzUgUFR2jzCSVkUARUhoK4PCtpGk0A@mail.gmail.com>
Message-ID: <CAMhf6hEgoL+biY5GziFDGmduxaoLwD-=A9VS0EZ3MAK5jnPeqg@mail.gmail.com>

Dear Hassan,
to my knowledge ft_sourcemovie works only with sources estimated using MNE.
What you can do is exctrating the source time course (for example using
ft_sourcedescriptives) and then plot each frame and create your own movie
using the matlab function getframe.

Here is a sample code:

%%% Extract source timecourse with ft_sourcedescriptives

%%% source is the output of ft_sourceanalysis with method lcmv

cfg = [];
cfg.projectmom         = 'yes';
cfg.fixedori           = 'over_trials';
source_timecourse         = ft_sourcedescriptives(cfg,source);


Npos = size(source.pos,1);
Ntime = length(source.time);

source_timecourse.avg.momint = nan(Npos,Ntime);


idx = find(source_timecourse.inside);

for i = 1:length(idx)
    index = idx(i);
    source_timecourse.avg.momint(index,:) =
source_timecourse.avg.mom{index};

end

%% Interpolate each time point of interest

 for tt = 1:length(source_timecourse.time) % full trial length or you can
select a time window of interest


    src = source_timecourse;
    src.time = source_timecourse.time(:,tt);

    src.avg.momint = source_tc.avg.momint(:,tt);  % here you may just leave
the time course as it is, or square it or normalize it by a baseline etc etc



    cfg = [];
    cfg.parameter         = 'momint';
    sourceInt{tt}        = ft_sourceinterpolate(cfg, src, mri); % mri is
the mri of your subject or a template mri

    clear src
end



%% Plot on surface ( if you want you can set the colorlimt to be the same
in each frames so you will be able to see changes in the "amplitude" as
well)


for tt = 1:length(sourceInt{tt})


    cfg = [];
    cfg.method            = 'surface';
    cfg.funparameter      = 'momint';
    cfg.funcolormap = 'hot';
    ft_sourceplot(cfg, sourceInt{tt})
    drawnow
    Frames(tt) = getframe; % get the current frame and store it



end

%% Show movie
figure
movie(Frames,1)


%% Save movie (frames) in AVI format

writerObj = VideoWriter('Movie.avi'); % Name it.
%writerObj.FrameRate = 60; % How many frames per second.
open(writerObj);

for tt=1:size(Frames,2)

    writeVideo(writerObj, Frames(tt));
    %end

end
hold off
close(writerObj); % Saves the movie.


Hope this helps :)
Best,
Debora


On Tue, Jul 12, 2016 at 6:35 PM, Hassan Aleem <ha438 at georgetown.edu> wrote:

> Does anyone have an example of how to use ft_sourcemovie to look at source
> localization across time with the 'lcmv' method. would be greatly
> appreciated. Thanks!
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 

Debora Desideri, PhD Student
BNP Lab - Neurology Department
University Hospital Tübingen
Eberhard Karls University Tübingen
Hoppe-Seyler Str. 3
D-72076 Tübingen
Tel: +49 7071/29 80478
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160713/34d7a00b/attachment.htm>

From s.homolle at donders.ru.nl  Wed Jul 13 12:41:35 2016
From: s.homolle at donders.ru.nl (Simon Homolle)
Date: Wed, 13 Jul 2016 12:41:35 +0200
Subject: [FieldTrip] tissue labels in mesh for prepare head model
In-Reply-To: <C035D3CE-3EF2-4152-88B6-A4EAA02871E7@mailbox.sc.edu>
References: <C035D3CE-3EF2-4152-88B6-A4EAA02871E7@mailbox.sc.edu>
Message-ID: <2962B32C-549C-4D62-9A61-06C276D026C9@donders.ru.nl>

Dear John,

Can you still recall the previous and current version of fieldtrip you are using? 

I tried ft_prepare_headmodel (cfg.method =simbio) myself with the fieldtrip version from today and did not encounter this warning.
The structure of my mesh looks quite similar:

            hex: [4992121x8 double]
         labels: [4992121x1 double]
         tissue: [4992121x1 double]
    tissuelabel: {'csf'  'gray'  'scalp'  'skull'  'white'}
           unit: 'mm'
            cfg: [1x1 struct]
            pos: [5105088x3 double]
         inside: [5105088x1 logical]

Simon Homölle
PhD Candidate
Donders Institute for Brain, Cognition and Behaviour
Centre for Cognitive Neuroimaging
Radboud University Nijmegen
Phone: +31-(0)24-36-65059

> On 11 Jul 2016, at 04:14, RICHARDS, JOHN <RICHARDS at mailbox.sc.edu> wrote:
> 
> I switched a couple of months ago to a version of FT.  I am using simbio meshes and ft_prepare_headmodel for a FEM source analysis.
> 
> This is the code to prepare the mesh:  (mri.tissuelabel is in the mri structure).
> cfg        = [];
> cfg.shift  = 0.3;
> cfg.method = 'hexahedral';
> cfg.tissue = mri.tissuelabel;
> mesh = ft_prepare_mesh(cfg,mri);
> 
> This results in a struct with
> hex
> labels
> tissue
> tissuelabel
> 
> When I run 
> cfg        = [];
> cfg.method ='simbio';
> cfg.conductivity=conductivity1;
> vol        = ft_prepare_headmodel(cfg, mesh);    
> 
> I get several instances warnings (see below).  The warnings are because the getdimord does not recognize “labels” and “tissue”.  But the ft_headmodel_simbio needs the tissue to tell which tissues to assign conductivity to a hex voxel.  See header of the ft_headmodel_simbio, designates hex, tissue, and tissuelabel.  
> 
> This used to work in the previous version; it may still be working just giving a warning.
> 
> Any help?
> 
> John
> 
> E.g., from header
> Use as
>    headmodel = ft_headmodel_simbio(mesh,'conductivity', conductivities, ...)
> 
>  The mesh is given as a volumetric mesh, using ft_datatype_parcellation
>    mesh.pos = vertex positions
>    mesh.tet/mesh.hex = list of volume elements
>    mesh.tissue = tissue assignment for elements
>    mesh.tissuelabel = labels correspondig to tissues
> 
>  Required input arguments should be specified in key-value pairs and have
> 
> Warning: could not determine dimord of "tissue" in the following data 
>> In getdimord (line 549)
>  In ft_datatype_source (line 232)
>  In ft_datatype_parcellation (line 178)
>  In ft_headmodel_simbio (line 46)
>  In ft_prepare_headmodel (line 430)
>  In CreateFieldtripHeadModels (line 348) 
>            hex: [1440558x8 double]
>         labels: [1440558x1 double]
>         tissue: [1440558x1 double]
>    tissuelabel: {'wm'  'gm'  't2wcsf'  'dura'  'skull'  'scalp'  'head'  'eyes'  'nasalcavity'  'nma_pve'}
>           unit: 'mm'
>            cfg: [1x1 struct]
>            pos: [1487661x3 double]
>         inside: [1487661x1 logical]
> 
> AND
> 
> Warning: could not determine dimord of "labels" in the following data 
>> In getdimord (line 549)
>  In ft_datatype_source (line 232)
>  In ft_datatype_parcellation (line 178)
>  In ft_headmodel_simbio (line 46)
>  In ft_prepare_headmodel (line 430)
>  In CreateFieldtripHeadModels (line 348) 
>            hex: [1440558x8 double]
>         labels: [1440558x1 double]
>         tissue: [1440558x1 double]
>    tissuelabel: {'wm'  'gm'  't2wcsf'  'dura'  'skull'  'scalp'  'head'  'eyes'  'nasalcavity'  'nma_pve'}
>           unit: 'mm'
>            cfg: [1x1 struct]
>            pos: [1487661x3 double]
>         inside: [1487661x1 logical]
> 
> ***********************************************
> John E. Richards Carolina Distinguished Professor
> Department of Psychology
> University of South Carolina
> Columbia, SC  29208
> Dept Phone: 803 777 2079
> Fax: 803 777 9558
> HTTP: jerlab.psych.sc.edu
> ***********************************************
> 
> 
> 
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip




From rleese12 at berkeley.edu  Thu Jul 14 08:50:42 2016
From: rleese12 at berkeley.edu (Nakyung Lee)
Date: Wed, 13 Jul 2016 23:50:42 -0700
Subject: [FieldTrip]  Unsupported data format
Message-ID: <CAJir=i-tKPtva6URMrLzKxo=ZpwUKPEpwcyj8fiy45Hh=qK=nA@mail.gmail.com>

Dear FieldTrip community,

My name is Rachel Lee and I'm a research assistant in Prof. Ming Hsu's lab
in UC Berkeley.

We currently have a .Tbk file, a .Tdx file, .tev file, .tsq file to
preprocess and analyze but it seems like those data formats are not yet
supported by FieldTrip.
So, instead of using those raw data files, we've been trying to find a
workaround by transforming them into a .mat file (and casting the .mat file
into a raw datatype in FieldTrip by manually assigning fields to it).
This hasn't been so successful; we've been unable to call ft_preprocessing
because of the lack of a proper header format (which is needed in
ft_read_header, one of the lower level functions that ft_preprocessing
calls).
I've been looking at the codes but been unable to come up with a solution.

Does anyone have a similar experience?
Is there any way to circumvent this issue?
Any type of help would be appreciated.

Thank you,
Rachel Lee
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160713/df09476a/attachment.htm>

From a.stolk8 at gmail.com  Thu Jul 14 09:10:45 2016
From: a.stolk8 at gmail.com (Arjen Stolk)
Date: Thu, 14 Jul 2016 00:10:45 -0700
Subject: [FieldTrip] Unsupported data format
In-Reply-To: <CAJir=i-tKPtva6URMrLzKxo=ZpwUKPEpwcyj8fiy45Hh=qK=nA@mail.gmail.com>
References: <CAJir=i-tKPtva6URMrLzKxo=ZpwUKPEpwcyj8fiy45Hh=qK=nA@mail.gmail.com>
Message-ID: <EC8F65F8-0F12-4B9C-A410-E71FFDCC695E@gmail.com>

Hi Rachel,

What is the error you're receiving, and how are you calling ft_preprocessing? 

If the data is in raw format (incl a trial, time and label field), it should theoretically be possible to use ft_preprocessing on it, eg;
cfg = []
cfg ..
data = ft_preprocessing(cfg, raw)

where raw is your data as described above.

Best,
Arjen

> On Jul 13, 2016, at 11:50 PM, Nakyung Lee <rleese12 at berkeley.edu> wrote:
> 
> Dear FieldTrip community,
> 
> My name is Rachel Lee and I'm a research assistant in Prof. Ming Hsu's lab in UC Berkeley.
> 
> We currently have a .Tbk file, a .Tdx file, .tev file, .tsq file to preprocess and analyze but it seems like those data formats are not yet supported by FieldTrip.
> So, instead of using those raw data files, we've been trying to find a workaround by transforming them into a .mat file (and casting the .mat file into a raw datatype in FieldTrip by manually assigning fields to it).
> This hasn't been so successful; we've been unable to call ft_preprocessing because of the lack of a proper header format (which is needed in ft_read_header, one of the lower level functions that ft_preprocessing calls).
> I've been looking at the codes but been unable to come up with a solution.
> 
> Does anyone have a similar experience?
> Is there any way to circumvent this issue?
> Any type of help would be appreciated.
> 
> Thank you,
> Rachel Lee
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip



From muthuraman10 at hotmail.com  Thu Jul 14 13:20:58 2016
From: muthuraman10 at hotmail.com (Muthuraman Muthuraman)
Date: Thu, 14 Jul 2016 11:20:58 +0000
Subject: [FieldTrip] Post-Doc position with focus on multimodal brain imaging
Message-ID: <PS1PR03MB1658601BD793E28912BF26B2CE320@PS1PR03MB1658.apcprd03.prod.outlook.com>

Post-Doc


Neuroscientist with focus on multimodal brain imaging


The medical faculty of the University of Mainz, Germany, invites
applications for a

Post Doc Position


for a functional translational neuroscience (FTN) scholarship two years position to work on multi-modal imaging, neurostimulation (TMS) and EEG.  Additionally, the new position requires experience with structural and functional MRI data analysis, computational modeling or magnetic diffusion imaging. The candidate should have a PhD or equivalent degree preferably in neuroscience, biomedical physics, psychology, psychiatry, or biology and should be able to supervise experiments and data analyses in programming platforms. The working language at the institute is English.

The location for this research will mainly be the workgroups "Section of movement disorders, neurostimulation and neuroimaging" of Prof. Sergiu Groppa at the Department of Neurology and "Biomedical statistics and multimodal signal processing unit" of Prof. Muthuraman Muthuraman, both at the Focus Program Translational Neurosciences (http://www.ftn.uni-mainz.de/) and Neuroimaging Centre Mainz (http://www.ftn.nic.uni-mainz.de/) and within the CRC "Neurobiology of resilience to stress-related mental dysfunction" and SFB TR-128 "Initiating/effector versus regulatory mechanisms in Multiple Sclerosis"  (www.sfbtr128.de<http://www.sfbtr128.de/>). Expected close collaborations with national and international partners.



The application should include a statement of research interests and reasons for applying to the project, curriculum vitae (max. 4 pages) composed according to good scientific practice.

The position will be open until filled. To apply for the position, please send the above documents to Prof. Sergiu Groppa and Prof. Muthuraman Muthuraman, Department of Neurology, Section of Movement Disorders and Neurostimulation, University of Mainz, Langenbeckstrasse 1, 55131 Mainz, Germany, or by Email to segroppa(at)uni-mainz.de & mmuthura(at)uni-mainz.de.




Prof. Dr.- Ing. M.Muthuraman

Biomedical statistics and multimodal signal processing unit
Movement Disorders and Neurostimulation,

Department of Neurology,

Focus Program Translational Neuroscience (FTN)

Johannes-Gutenberg-University Hospital,

Langenbeckstr. 1

55131 Mainz, Germany

Email: mmuthura at uni-mainz.de

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160714/9192bd10/attachment.htm>

From sarang at cfin.au.dk  Thu Jul 14 18:02:05 2016
From: sarang at cfin.au.dk (Sarang S. Dalal)
Date: Thu, 14 Jul 2016 16:02:05 +0000
Subject: [FieldTrip] Running "ft_preprocessing" on user defined data
In-Reply-To: <b2de3a873ff544b3993050c22101409d@ES06AMSNLNT.srn.sandia.gov>
References: <b2de3a873ff544b3993050c22101409d@ES06AMSNLNT.srn.sandia.gov>
Message-ID: <1468519324767.97865@cfin.au.dk>

Dear Amir,


Perhaps you were a?ffected by this bug (introduced and fixed last month):

http://bugzilla.fieldtriptoolbox.org/show_bug.cgi?id=3154


So maybe the newest version of FieldTrip would work for you. If not, you may like to file a bug report through the bugzilla website.


Cheers,

Sarang


________________________________
From: fieldtrip-bounces at science.ru.nl <fieldtrip-bounces at science.ru.nl> on behalf of Borna, Amir <aborna at sandia.gov>
Sent: Wednesday, July 13, 2016 2:47 AM
To: fieldtrip at science.ru.nl
Subject: [FieldTrip] Running "ft_preprocessing" on user defined data


Hi,
I have successfully imported my data into the fieldtrip's data structure according to the instructions on:
http://www.fieldtriptoolbox.org/faq/how_can_i_import_my_own_dataformat

Later I save the data in "fif" format using fieldtrip2fiff.

When I read back the data using "ft_preprocessing", the chantype and chanunit are all unknown except for the trigger. Is there any solution to this issue? Thank you.

Regards,
Amir Borna.


-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160714/b04f3ba7/attachment.htm>

From rleese12 at berkeley.edu  Fri Jul 15 08:49:41 2016
From: rleese12 at berkeley.edu (Nakyung Lee)
Date: Thu, 14 Jul 2016 23:49:41 -0700
Subject: [FieldTrip] Unsupported data format
In-Reply-To: <EC8F65F8-0F12-4B9C-A410-E71FFDCC695E@gmail.com>
References: <CAJir=i-tKPtva6URMrLzKxo=ZpwUKPEpwcyj8fiy45Hh=qK=nA@mail.gmail.com>
 <EC8F65F8-0F12-4B9C-A410-E71FFDCC695E@gmail.com>
Message-ID: <CAJir=i_KO8O6ssXzM3-TNGGRsoSyzO2uCorH1xGwAyT4ZCJNfQ@mail.gmail.com>

Hi Arjen,

Thank you for your reply.
Your email got forwarded successfully.

So currently I tried using 'ft_definetrial' and 'ft_preprocessing'.
'ft_definetrial' returns an error when used with 'ft_trialfun' set to
default.
Below is the code I used (and 'signal_raw.mat' is a fieldtrip raw data and
it has all three fields you mentioned).

cfg.dataset = 'signal_raw.mat';
cfg.trialdef.event = subj_globals.buttonpress_times;
cfg = ft_definetrial(cfg);

So I simply call ft_definetrial with minimal configuration and here's the
error I got:

Error using ft_read_header (line 2194)
unsupported header format "matlab"

Error in ft_trialfun_general (line 78)
hdr = ft_read_header(cfg.headerfile, 'headerformat', cfg.headerformat);

Error in ft_definetrial (line 177)
    [trl, event] = feval(cfg.trialfun, cfg);

Error in trialdef_alsotest (line 12)
cfg = ft_definetrial(cfg);

I circumvented this issue by using my own trialfun ('ft_trialfun_test' in
the code).
We already have all the necessary timestamps so I could build a very simple
one.
Here's a new code (I ran the code with minimal cfg for 'ft_preprocessing'
to isolate the problem):

cfg.dataset = 'signal_raw.mat';
cfg.trialfun = 'ft_trialfun_test';
cfg.trialdef.event = subj_globals.buttonpress_times;

cfg = ft_definetrial(cfg);

cfg.continuous = 'yes';
buttonpress_hg = ft_preprocessing(cfg);

And here's the error I got:

Error using ft_read_header (line 2194)
unsupported header format "matlab"

Error in ft_preprocessing (line 397)
  hdr = ft_read_header(cfg.headerfile, 'headerformat', cfg.headerformat,
'coordsys', cfg.coordsys, 'coilaccuracy',
  cfg.coilaccuracy);

Error in test_trialdef (line 18)
buttonpress_hg = ft_preprocessing(cfg);

So both error come from 'ft_read_header'.
I've been looking at the code but it seemed quite hard to debug as
'ft_read_header' uses a lower level function that directly reads from the
file (hence it seemed like a simple fix like passing in a fake header
wouldn't work).
Am I doing something wrong here?

Again, thank you for your reply and let me know if you need more
information.

Best,
Rachel

On Thu, Jul 14, 2016 at 12:10 AM, Arjen Stolk <a.stolk8 at gmail.com> wrote:

> Hi Rachel,
>
> What is the error you're receiving, and how are you calling
> ft_preprocessing?
>
> If the data is in raw format (incl a trial, time and label field), it
> should theoretically be possible to use ft_preprocessing on it, eg;
> cfg = []
> cfg ..
> data = ft_preprocessing(cfg, raw)
>
> where raw is your data as described above.
>
> Best,
> Arjen
>
> > On Jul 13, 2016, at 11:50 PM, Nakyung Lee <rleese12 at berkeley.edu> wrote:
> >
> > Dear FieldTrip community,
> >
> > My name is Rachel Lee and I'm a research assistant in Prof. Ming Hsu's
> lab in UC Berkeley.
> >
> > We currently have a .Tbk file, a .Tdx file, .tev file, .tsq file to
> preprocess and analyze but it seems like those data formats are not yet
> supported by FieldTrip.
> > So, instead of using those raw data files, we've been trying to find a
> workaround by transforming them into a .mat file (and casting the .mat file
> into a raw datatype in FieldTrip by manually assigning fields to it).
> > This hasn't been so successful; we've been unable to call
> ft_preprocessing because of the lack of a proper header format (which is
> needed in ft_read_header, one of the lower level functions that
> ft_preprocessing calls).
> > I've been looking at the codes but been unable to come up with a
> solution.
> >
> > Does anyone have a similar experience?
> > Is there any way to circumvent this issue?
> > Any type of help would be appreciated.
> >
> > Thank you,
> > Rachel Lee
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160714/be0f5a56/attachment.htm>

From jan.schoffelen at donders.ru.nl  Fri Jul 15 10:10:02 2016
From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs))
Date: Fri, 15 Jul 2016 08:10:02 +0000
Subject: [FieldTrip] Unsupported data format
In-Reply-To: <CAJir=i_KO8O6ssXzM3-TNGGRsoSyzO2uCorH1xGwAyT4ZCJNfQ@mail.gmail.com>
References: <CAJir=i-tKPtva6URMrLzKxo=ZpwUKPEpwcyj8fiy45Hh=qK=nA@mail.gmail.com>
 <EC8F65F8-0F12-4B9C-A410-E71FFDCC695E@gmail.com>
 <CAJir=i_KO8O6ssXzM3-TNGGRsoSyzO2uCorH1xGwAyT4ZCJNfQ@mail.gmail.com>
Message-ID: <5DD7AA41-AB91-408F-804C-0A8FCC7A633C@donders.ru.nl>

Hi Rachel,

Once your data is represented in a fieldtrip-style structure, there’s no need anymore to call ft_definetrial with a specified named dataset in the cfg.

If you want to segment your data, you may still want to call ft_definetrial to generate a so-called ‘trl’ matrix, and subsequently use ft_redefinetrial to re-segment, i.e.:

load(’signal_raw.mat’); % I assume that this files contains the fieldtrip-style data structure

cfg = [];
cfg.trl = trl;
data_epoched = ft_redefinetrial(cfg, data);

So, note that ft_preprocessing shouldn’t be called, this is onlyl useable when reading proprietary data from disk.

It seems that you don’t need the cfg.dataset argument to begin with, and if you manage to titrate your ft_trialfun_test such that it converts the timestamps you provide it with into the correct trl-matrix, I don’t see a reason why it shouldn’t work.

Best,
Jan-Mathijs


On 15 Jul 2016, at 08:49, Nakyung Lee <rleese12 at berkeley.edu<mailto:rleese12 at berkeley.edu>> wrote:

Hi Arjen,

Thank you for your reply.
Your email got forwarded successfully.

So currently I tried using 'ft_definetrial' and 'ft_preprocessing'.
'ft_definetrial' returns an error when used with 'ft_trialfun' set to default.
Below is the code I used (and 'signal_raw.mat' is a fieldtrip raw data and it has all three fields you mentioned).

cfg.dataset = 'signal_raw.mat';
cfg.trialdef.event = subj_globals.buttonpress_times;
cfg = ft_definetrial(cfg);

So I simply call ft_definetrial with minimal configuration and here's the error I got:

Error using ft_read_header (line 2194)
unsupported header format "matlab"

Error in ft_trialfun_general (line 78)
hdr = ft_read_header(cfg.headerfile, 'headerformat', cfg.headerformat);

Error in ft_definetrial (line 177)
    [trl, event] = feval(cfg.trialfun, cfg);

Error in trialdef_alsotest (line 12)
cfg = ft_definetrial(cfg);

I circumvented this issue by using my own trialfun ('ft_trialfun_test' in the code).
We already have all the necessary timestamps so I could build a very simple one.
Here's a new code (I ran the code with minimal cfg for 'ft_preprocessing' to isolate the problem):

cfg.dataset = 'signal_raw.mat';
cfg.trialfun = 'ft_trialfun_test';
cfg.trialdef.event = subj_globals.buttonpress_times;

cfg = ft_definetrial(cfg);

cfg.continuous = 'yes';
buttonpress_hg = ft_preprocessing(cfg);

And here's the error I got:

Error using ft_read_header (line 2194)
unsupported header format "matlab"

Error in ft_preprocessing (line 397)
  hdr = ft_read_header(cfg.headerfile, 'headerformat', cfg.headerformat, 'coordsys', cfg.coordsys, 'coilaccuracy',
  cfg.coilaccuracy);

Error in test_trialdef (line 18)
buttonpress_hg = ft_preprocessing(cfg);

So both error come from 'ft_read_header'.
I've been looking at the code but it seemed quite hard to debug as 'ft_read_header' uses a lower level function that directly reads from the file (hence it seemed like a simple fix like passing in a fake header wouldn't work).
Am I doing something wrong here?

Again, thank you for your reply and let me know if you need more information.

Best,
Rachel

On Thu, Jul 14, 2016 at 12:10 AM, Arjen Stolk <a.stolk8 at gmail.com<mailto:a.stolk8 at gmail.com>> wrote:
Hi Rachel,

What is the error you're receiving, and how are you calling ft_preprocessing?

If the data is in raw format (incl a trial, time and label field), it should theoretically be possible to use ft_preprocessing on it, eg;
cfg = []
cfg ..
data = ft_preprocessing(cfg, raw)

where raw is your data as described above.

Best,
Arjen

> On Jul 13, 2016, at 11:50 PM, Nakyung Lee <rleese12 at berkeley.edu<mailto:rleese12 at berkeley.edu>> wrote:
>
> Dear FieldTrip community,
>
> My name is Rachel Lee and I'm a research assistant in Prof. Ming Hsu's lab in UC Berkeley.
>
> We currently have a .Tbk file, a .Tdx file, .tev file, .tsq file to preprocess and analyze but it seems like those data formats are not yet supported by FieldTrip.
> So, instead of using those raw data files, we've been trying to find a workaround by transforming them into a .mat file (and casting the .mat file into a raw datatype in FieldTrip by manually assigning fields to it).
> This hasn't been so successful; we've been unable to call ft_preprocessing because of the lack of a proper header format (which is needed in ft_read_header, one of the lower level functions that ft_preprocessing calls).
> I've been looking at the codes but been unable to come up with a solution.
>
> Does anyone have a similar experience?
> Is there any way to circumvent this issue?
> Any type of help would be appreciated.
>
> Thank you,
> Rachel Lee
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160715/35093a23/attachment.htm>

From ecr38 at cam.ac.uk  Fri Jul 15 17:35:03 2016
From: ecr38 at cam.ac.uk (E.C. Rocheteau)
Date: Fri, 15 Jul 2016 16:35:03 +0100
Subject: [FieldTrip] Request for help in re-organising my data for use in
	FieldTrip
Message-ID: <d9ae179adccdb1f47d51cb7d1b5131ea@cam.ac.uk>

I already my time-locked trial data in a structure in MATLAB, and I want 
to start using FieldTrip. How do I go about doing re-organising my data 
into something which is usable to the functions in FieldTrip? I've 
looked at the ft_preprocessing functions but I have no idea what the 
trial info, sample info, hdr, or grad fields are for, and what I should 
put in them.

-- 
Best Wishes,

Emma


From rleese12 at berkeley.edu  Fri Jul 15 18:51:54 2016
From: rleese12 at berkeley.edu (Nakyung Lee)
Date: Fri, 15 Jul 2016 09:51:54 -0700
Subject: [FieldTrip] Unsupported data format
In-Reply-To: <5DD7AA41-AB91-408F-804C-0A8FCC7A633C@donders.ru.nl>
References: <CAJir=i-tKPtva6URMrLzKxo=ZpwUKPEpwcyj8fiy45Hh=qK=nA@mail.gmail.com>
 <EC8F65F8-0F12-4B9C-A410-E71FFDCC695E@gmail.com>
 <CAJir=i_KO8O6ssXzM3-TNGGRsoSyzO2uCorH1xGwAyT4ZCJNfQ@mail.gmail.com>
 <5DD7AA41-AB91-408F-804C-0A8FCC7A633C@donders.ru.nl>
Message-ID: <CAJir=i91S+qAQ1QQNvME8ThfZSpxhNkJXdssaB9CKPiWO23TWA@mail.gmail.com>

Hi Jan-Mathijs,

Thanks for your advice.
Yes, I used 'ft_=definetrial' to segment the data.
My data is in the fieldtrip style data format not because it's been
segmented and preprocessed through fieldtrip but because our original
dataformat is unsupported by fieldtrip (.Tbk, .Tdx, .tev, .tsq to be exact).
So my coworker transformed those data into a .mat file and I transformed
into a fieldtrip style raw data but it still needs some segmenting and some
other preprocessing done on it (for example high-gamma filtering).
But if 'ft_preprocessing' is only useable when reading proprietary data
from disk, there's just no way we can preprocess the above data using
fieldtrip?

Thank you,
Rachel

On Fri, Jul 15, 2016 at 1:10 AM, Schoffelen, J.M. (Jan Mathijs) <
jan.schoffelen at donders.ru.nl> wrote:

> Hi Rachel,
>
> Once your data is represented in a fieldtrip-style structure, there’s no
> need anymore to call ft_definetrial with a specified named dataset in the
> cfg.
>
> If you want to segment your data, you may still want to call
> ft_definetrial to generate a so-called ‘trl’ matrix, and subsequently use
> ft_redefinetrial to re-segment, i.e.:
>
> load(’signal_raw.mat’); % I assume that this files contains the
> fieldtrip-style data structure
>
> cfg = [];
> cfg.trl = trl;
> data_epoched = ft_redefinetrial(cfg, data);
>
> So, note that ft_preprocessing shouldn’t be called, this is onlyl useable
> when reading proprietary data from disk.
>
> It seems that you don’t need the cfg.dataset argument to begin with, and
> if you manage to titrate your ft_trialfun_test such that it converts the
> timestamps you provide it with into the correct trl-matrix, I don’t see a
> reason why it shouldn’t work.
>
> Best,
> Jan-Mathijs
>
>
> On 15 Jul 2016, at 08:49, Nakyung Lee <rleese12 at berkeley.edu> wrote:
>
> Hi Arjen,
>
> Thank you for your reply.
> Your email got forwarded successfully.
>
> So currently I tried using 'ft_definetrial' and 'ft_preprocessing'.
> 'ft_definetrial' returns an error when used with 'ft_trialfun' set to
> default.
> Below is the code I used (and 'signal_raw.mat' is a fieldtrip raw data and
> it has all three fields you mentioned).
>
> cfg.dataset = 'signal_raw.mat';
> cfg.trialdef.event = subj_globals.buttonpress_times;
> cfg = ft_definetrial(cfg);
>
> So I simply call ft_definetrial with minimal configuration and here's the
> error I got:
>
> Error using ft_read_header (line 2194)
> unsupported header format "matlab"
>
> Error in ft_trialfun_general (line 78)
> hdr = ft_read_header(cfg.headerfile, 'headerformat', cfg.headerformat);
>
> Error in ft_definetrial (line 177)
>     [trl, event] = feval(cfg.trialfun, cfg);
>
> Error in trialdef_alsotest (line 12)
> cfg = ft_definetrial(cfg);
>
> I circumvented this issue by using my own trialfun ('ft_trialfun_test' in
> the code).
> We already have all the necessary timestamps so I could build a very
> simple one.
> Here's a new code (I ran the code with minimal cfg for 'ft_preprocessing'
> to isolate the problem):
>
> cfg.dataset = 'signal_raw.mat';
> cfg.trialfun = 'ft_trialfun_test';
> cfg.trialdef.event = subj_globals.buttonpress_times;
>
> cfg = ft_definetrial(cfg);
>
> cfg.continuous = 'yes';
> buttonpress_hg = ft_preprocessing(cfg);
>
> And here's the error I got:
>
> Error using ft_read_header (line 2194)
> unsupported header format "matlab"
>
> Error in ft_preprocessing (line 397)
>   hdr = ft_read_header(cfg.headerfile, 'headerformat', cfg.headerformat,
> 'coordsys', cfg.coordsys, 'coilaccuracy',
>   cfg.coilaccuracy);
>
> Error in test_trialdef (line 18)
> buttonpress_hg = ft_preprocessing(cfg);
>
> So both error come from 'ft_read_header'.
> I've been looking at the code but it seemed quite hard to debug as
> 'ft_read_header' uses a lower level function that directly reads from the
> file (hence it seemed like a simple fix like passing in a fake header
> wouldn't work).
> Am I doing something wrong here?
>
> Again, thank you for your reply and let me know if you need more
> information.
>
> Best,
> Rachel
>
> On Thu, Jul 14, 2016 at 12:10 AM, Arjen Stolk <a.stolk8 at gmail.com> wrote:
>
>> Hi Rachel,
>>
>> What is the error you're receiving, and how are you calling
>> ft_preprocessing?
>>
>> If the data is in raw format (incl a trial, time and label field), it
>> should theoretically be possible to use ft_preprocessing on it, eg;
>> cfg = []
>> cfg ..
>> data = ft_preprocessing(cfg, raw)
>>
>> where raw is your data as described above.
>>
>> Best,
>> Arjen
>>
>> > On Jul 13, 2016, at 11:50 PM, Nakyung Lee <rleese12 at berkeley.edu>
>> wrote:
>> >
>> > Dear FieldTrip community,
>> >
>> > My name is Rachel Lee and I'm a research assistant in Prof. Ming Hsu's
>> lab in UC Berkeley.
>> >
>> > We currently have a .Tbk file, a .Tdx file, .tev file, .tsq file to
>> preprocess and analyze but it seems like those data formats are not yet
>> supported by FieldTrip.
>> > So, instead of using those raw data files, we've been trying to find a
>> workaround by transforming them into a .mat file (and casting the .mat file
>> into a raw datatype in FieldTrip by manually assigning fields to it).
>> > This hasn't been so successful; we've been unable to call
>> ft_preprocessing because of the lack of a proper header format (which is
>> needed in ft_read_header, one of the lower level functions that
>> ft_preprocessing calls).
>> > I've been looking at the codes but been unable to come up with a
>> solution.
>> >
>> > Does anyone have a similar experience?
>> > Is there any way to circumvent this issue?
>> > Any type of help would be appreciated.
>> >
>> > Thank you,
>> > Rachel Lee
>> > _______________________________________________
>> > fieldtrip mailing list
>> > fieldtrip at donders.ru.nl
>> > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160715/d5302f06/attachment.htm>

From a.stolk8 at gmail.com  Fri Jul 15 19:01:07 2016
From: a.stolk8 at gmail.com (Arjen Stolk)
Date: Fri, 15 Jul 2016 10:01:07 -0700
Subject: [FieldTrip] Unsupported data format
In-Reply-To: <CAJir=i91S+qAQ1QQNvME8ThfZSpxhNkJXdssaB9CKPiWO23TWA@mail.gmail.com>
References: <CAJir=i-tKPtva6URMrLzKxo=ZpwUKPEpwcyj8fiy45Hh=qK=nA@mail.gmail.com>
 <EC8F65F8-0F12-4B9C-A410-E71FFDCC695E@gmail.com>
 <CAJir=i_KO8O6ssXzM3-TNGGRsoSyzO2uCorH1xGwAyT4ZCJNfQ@mail.gmail.com>
 <5DD7AA41-AB91-408F-804C-0A8FCC7A633C@donders.ru.nl>
 <CAJir=i91S+qAQ1QQNvME8ThfZSpxhNkJXdssaB9CKPiWO23TWA@mail.gmail.com>
Message-ID: <CAAiwptQ5CWOTY3ovmgikSgrS-G9_KoeZg_=JLTj4Y096m7P=gQ@mail.gmail.com>

Hi Rachel,

Given that you already have the data imported into matlab and organized
into trials, try creating a structure 'data' with the following fields
(i.e. data.label, data.time, data.trial) and the following dimensions:

label: {151x1 cell}      the channel labels (e.g. 'MRC13')
time: {1x266 cell}      the timeaxis [1*Ntime double] per trial
trial: {1x266 cell}      the numeric data [151*Ntime double] per trial

Then, for a proof of principle, try:

cfg = [];
cfg.demean = 'yes';
data2 = ft_preprocessing(cfg, data);

Let us know if this worked for you.
Arjen


2016-07-15 9:51 GMT-07:00 Nakyung Lee <rleese12 at berkeley.edu>:

> Hi Jan-Mathijs,
>
> Thanks for your advice.
> Yes, I used 'ft_=definetrial' to segment the data.
> My data is in the fieldtrip style data format not because it's been
> segmented and preprocessed through fieldtrip but because our original
> dataformat is unsupported by fieldtrip (.Tbk, .Tdx, .tev, .tsq to be exact).
> So my coworker transformed those data into a .mat file and I transformed
> into a fieldtrip style raw data but it still needs some segmenting and some
> other preprocessing done on it (for example high-gamma filtering).
> But if 'ft_preprocessing' is only useable when reading proprietary data
> from disk, there's just no way we can preprocess the above data using
> fieldtrip?
>
> Thank you,
> Rachel
>
> On Fri, Jul 15, 2016 at 1:10 AM, Schoffelen, J.M. (Jan Mathijs) <
> jan.schoffelen at donders.ru.nl> wrote:
>
>> Hi Rachel,
>>
>> Once your data is represented in a fieldtrip-style structure, there’s no
>> need anymore to call ft_definetrial with a specified named dataset in the
>> cfg.
>>
>> If you want to segment your data, you may still want to call
>> ft_definetrial to generate a so-called ‘trl’ matrix, and subsequently use
>> ft_redefinetrial to re-segment, i.e.:
>>
>> load(’signal_raw.mat’); % I assume that this files contains the
>> fieldtrip-style data structure
>>
>> cfg = [];
>> cfg.trl = trl;
>> data_epoched = ft_redefinetrial(cfg, data);
>>
>> So, note that ft_preprocessing shouldn’t be called, this is onlyl useable
>> when reading proprietary data from disk.
>>
>> It seems that you don’t need the cfg.dataset argument to begin with, and
>> if you manage to titrate your ft_trialfun_test such that it converts the
>> timestamps you provide it with into the correct trl-matrix, I don’t see a
>> reason why it shouldn’t work.
>>
>> Best,
>> Jan-Mathijs
>>
>>
>> On 15 Jul 2016, at 08:49, Nakyung Lee <rleese12 at berkeley.edu> wrote:
>>
>> Hi Arjen,
>>
>> Thank you for your reply.
>> Your email got forwarded successfully.
>>
>> So currently I tried using 'ft_definetrial' and 'ft_preprocessing'.
>> 'ft_definetrial' returns an error when used with 'ft_trialfun' set to
>> default.
>> Below is the code I used (and 'signal_raw.mat' is a fieldtrip raw data
>> and it has all three fields you mentioned).
>>
>> cfg.dataset = 'signal_raw.mat';
>> cfg.trialdef.event = subj_globals.buttonpress_times;
>> cfg = ft_definetrial(cfg);
>>
>> So I simply call ft_definetrial with minimal configuration and here's the
>> error I got:
>>
>> Error using ft_read_header (line 2194)
>> unsupported header format "matlab"
>>
>> Error in ft_trialfun_general (line 78)
>> hdr = ft_read_header(cfg.headerfile, 'headerformat', cfg.headerformat);
>>
>> Error in ft_definetrial (line 177)
>>     [trl, event] = feval(cfg.trialfun, cfg);
>>
>> Error in trialdef_alsotest (line 12)
>> cfg = ft_definetrial(cfg);
>>
>> I circumvented this issue by using my own trialfun ('ft_trialfun_test' in
>> the code).
>> We already have all the necessary timestamps so I could build a very
>> simple one.
>> Here's a new code (I ran the code with minimal cfg for 'ft_preprocessing'
>> to isolate the problem):
>>
>> cfg.dataset = 'signal_raw.mat';
>> cfg.trialfun = 'ft_trialfun_test';
>> cfg.trialdef.event = subj_globals.buttonpress_times;
>>
>> cfg = ft_definetrial(cfg);
>>
>> cfg.continuous = 'yes';
>> buttonpress_hg = ft_preprocessing(cfg);
>>
>> And here's the error I got:
>>
>> Error using ft_read_header (line 2194)
>> unsupported header format "matlab"
>>
>> Error in ft_preprocessing (line 397)
>>   hdr = ft_read_header(cfg.headerfile, 'headerformat', cfg.headerformat,
>> 'coordsys', cfg.coordsys, 'coilaccuracy',
>>   cfg.coilaccuracy);
>>
>> Error in test_trialdef (line 18)
>> buttonpress_hg = ft_preprocessing(cfg);
>>
>> So both error come from 'ft_read_header'.
>> I've been looking at the code but it seemed quite hard to debug as
>> 'ft_read_header' uses a lower level function that directly reads from the
>> file (hence it seemed like a simple fix like passing in a fake header
>> wouldn't work).
>> Am I doing something wrong here?
>>
>> Again, thank you for your reply and let me know if you need more
>> information.
>>
>> Best,
>> Rachel
>>
>> On Thu, Jul 14, 2016 at 12:10 AM, Arjen Stolk <a.stolk8 at gmail.com> wrote:
>>
>>> Hi Rachel,
>>>
>>> What is the error you're receiving, and how are you calling
>>> ft_preprocessing?
>>>
>>> If the data is in raw format (incl a trial, time and label field), it
>>> should theoretically be possible to use ft_preprocessing on it, eg;
>>> cfg = []
>>> cfg ..
>>> data = ft_preprocessing(cfg, raw)
>>>
>>> where raw is your data as described above.
>>>
>>> Best,
>>> Arjen
>>>
>>> > On Jul 13, 2016, at 11:50 PM, Nakyung Lee <rleese12 at berkeley.edu>
>>> wrote:
>>> >
>>> > Dear FieldTrip community,
>>> >
>>> > My name is Rachel Lee and I'm a research assistant in Prof. Ming Hsu's
>>> lab in UC Berkeley.
>>> >
>>> > We currently have a .Tbk file, a .Tdx file, .tev file, .tsq file to
>>> preprocess and analyze but it seems like those data formats are not yet
>>> supported by FieldTrip.
>>> > So, instead of using those raw data files, we've been trying to find a
>>> workaround by transforming them into a .mat file (and casting the .mat file
>>> into a raw datatype in FieldTrip by manually assigning fields to it).
>>> > This hasn't been so successful; we've been unable to call
>>> ft_preprocessing because of the lack of a proper header format (which is
>>> needed in ft_read_header, one of the lower level functions that
>>> ft_preprocessing calls).
>>> > I've been looking at the codes but been unable to come up with a
>>> solution.
>>> >
>>> > Does anyone have a similar experience?
>>> > Is there any way to circumvent this issue?
>>> > Any type of help would be appreciated.
>>> >
>>> > Thank you,
>>> > Rachel Lee
>>> > _______________________________________________
>>> > fieldtrip mailing list
>>> > fieldtrip at donders.ru.nl
>>> > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>>
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160715/fd59beb7/attachment.htm>

From rleese12 at berkeley.edu  Fri Jul 15 19:33:35 2016
From: rleese12 at berkeley.edu (Nakyung Lee)
Date: Fri, 15 Jul 2016 10:33:35 -0700
Subject: [FieldTrip] Unsupported data format
In-Reply-To: <CAAiwptQ5CWOTY3ovmgikSgrS-G9_KoeZg_=JLTj4Y096m7P=gQ@mail.gmail.com>
References: <CAJir=i-tKPtva6URMrLzKxo=ZpwUKPEpwcyj8fiy45Hh=qK=nA@mail.gmail.com>
 <EC8F65F8-0F12-4B9C-A410-E71FFDCC695E@gmail.com>
 <CAJir=i_KO8O6ssXzM3-TNGGRsoSyzO2uCorH1xGwAyT4ZCJNfQ@mail.gmail.com>
 <5DD7AA41-AB91-408F-804C-0A8FCC7A633C@donders.ru.nl>
 <CAJir=i91S+qAQ1QQNvME8ThfZSpxhNkJXdssaB9CKPiWO23TWA@mail.gmail.com>
 <CAAiwptQ5CWOTY3ovmgikSgrS-G9_KoeZg_=JLTj4Y096m7P=gQ@mail.gmail.com>
Message-ID: <CAJir=i_xHhV2qLmqaB5TJvGfJBt5QShA6-3M2onaSWy2eyor2A@mail.gmail.com>

Hi Arjen,

Yes, that is exactly the structure of 'signal_raw' I'm using.
I tried your code (without running 'ft_definetrial' beforehand) and here's
the log:

>> cfg = [];
>> cfg.demean = 'yes';
>> data = signal_raw

data =

      label: {176x1 cell}
       time: {[1x721186 double]}
      trial: {[176x721186 double]}
    fsample: 1000

>> data2 = ft_preprocessing(cfg, data);
Warning: the data does not contain a trial definition
> In ft_warning (line 184)
  In fixsampleinfo (line 66)
  In ft_datatype_raw (line 175)
  In ft_checkdata (line 219)
  In ft_preprocessing (line 274)
Warning: reconstructing sampleinfo by assuming that the trials are
consecutive segments of a continuous recording
> In ft_warning (line 184)
  In fixsampleinfo (line 79)
  In ft_datatype_raw (line 175)
  In ft_checkdata (line 219)
  In ft_preprocessing (line 274)
Error using cell/ismember (line 34)
Input A of class cell and input B of class cell must be cell arrays of
strings, unless one is a string.

Error in ft_senstype (line 303)
    if     (mean(ismember(ft_senslabel('ant128'),         sens.label)) >
0.8)

Error in ft_channelselection (line 83)
  senstype = ft_senstype(datachannel);

Error in ft_selectdata>getselection_chan (line 649)
  selchannel = ft_channelselection(cfg.channel, varargin{k}.label);

Error in ft_selectdata (line 279)
if haschan,    [selchan,    cfg] = getselection_chan   (cfg, varargin{:},
cfg.select); end

Error in ft_preprocessing (line 317)
  data   = ft_selectdata(tmpcfg, data);

This data is not segmented yet so there's only one trial (and hence
time: {[1x721186
double]} and trial: {[176x721186 double]}) with 'Ntime' equal to '721186'.
There were warning signs but seems like those are ignore-able ones.
Again, let me know if you need more information and thank you.

Best,
Rachel

On Fri, Jul 15, 2016 at 10:01 AM, Arjen Stolk <a.stolk8 at gmail.com> wrote:

> Hi Rachel,
>
> Given that you already have the data imported into matlab and organized
> into trials, try creating a structure 'data' with the following fields
> (i.e. data.label, data.time, data.trial) and the following dimensions:
>
> label: {151x1 cell}      the channel labels (e.g. 'MRC13')
> time: {1x266 cell}      the timeaxis [1*Ntime double] per trial
> trial: {1x266 cell}      the numeric data [151*Ntime double] per trial
>
> Then, for a proof of principle, try:
>
> cfg = [];
> cfg.demean = 'yes';
> data2 = ft_preprocessing(cfg, data);
>
> Let us know if this worked for you.
> Arjen
>
>
> 2016-07-15 9:51 GMT-07:00 Nakyung Lee <rleese12 at berkeley.edu>:
>
>> Hi Jan-Mathijs,
>>
>> Thanks for your advice.
>> Yes, I used 'ft_=definetrial' to segment the data.
>> My data is in the fieldtrip style data format not because it's been
>> segmented and preprocessed through fieldtrip but because our original
>> dataformat is unsupported by fieldtrip (.Tbk, .Tdx, .tev, .tsq to be exact).
>> So my coworker transformed those data into a .mat file and I transformed
>> into a fieldtrip style raw data but it still needs some segmenting and some
>> other preprocessing done on it (for example high-gamma filtering).
>> But if 'ft_preprocessing' is only useable when reading proprietary data
>> from disk, there's just no way we can preprocess the above data using
>> fieldtrip?
>>
>> Thank you,
>> Rachel
>>
>> On Fri, Jul 15, 2016 at 1:10 AM, Schoffelen, J.M. (Jan Mathijs) <
>> jan.schoffelen at donders.ru.nl> wrote:
>>
>>> Hi Rachel,
>>>
>>> Once your data is represented in a fieldtrip-style structure, there’s no
>>> need anymore to call ft_definetrial with a specified named dataset in the
>>> cfg.
>>>
>>> If you want to segment your data, you may still want to call
>>> ft_definetrial to generate a so-called ‘trl’ matrix, and subsequently use
>>> ft_redefinetrial to re-segment, i.e.:
>>>
>>> load(’signal_raw.mat’); % I assume that this files contains the
>>> fieldtrip-style data structure
>>>
>>> cfg = [];
>>> cfg.trl = trl;
>>> data_epoched = ft_redefinetrial(cfg, data);
>>>
>>> So, note that ft_preprocessing shouldn’t be called, this is onlyl
>>> useable when reading proprietary data from disk.
>>>
>>> It seems that you don’t need the cfg.dataset argument to begin with, and
>>> if you manage to titrate your ft_trialfun_test such that it converts the
>>> timestamps you provide it with into the correct trl-matrix, I don’t see a
>>> reason why it shouldn’t work.
>>>
>>> Best,
>>> Jan-Mathijs
>>>
>>>
>>> On 15 Jul 2016, at 08:49, Nakyung Lee <rleese12 at berkeley.edu> wrote:
>>>
>>> Hi Arjen,
>>>
>>> Thank you for your reply.
>>> Your email got forwarded successfully.
>>>
>>> So currently I tried using 'ft_definetrial' and 'ft_preprocessing'.
>>> 'ft_definetrial' returns an error when used with 'ft_trialfun' set to
>>> default.
>>> Below is the code I used (and 'signal_raw.mat' is a fieldtrip raw data
>>> and it has all three fields you mentioned).
>>>
>>> cfg.dataset = 'signal_raw.mat';
>>> cfg.trialdef.event = subj_globals.buttonpress_times;
>>> cfg = ft_definetrial(cfg);
>>>
>>> So I simply call ft_definetrial with minimal configuration and here's
>>> the error I got:
>>>
>>> Error using ft_read_header (line 2194)
>>> unsupported header format "matlab"
>>>
>>> Error in ft_trialfun_general (line 78)
>>> hdr = ft_read_header(cfg.headerfile, 'headerformat', cfg.headerformat);
>>>
>>> Error in ft_definetrial (line 177)
>>>     [trl, event] = feval(cfg.trialfun, cfg);
>>>
>>> Error in trialdef_alsotest (line 12)
>>> cfg = ft_definetrial(cfg);
>>>
>>> I circumvented this issue by using my own trialfun ('ft_trialfun_test'
>>> in the code).
>>> We already have all the necessary timestamps so I could build a very
>>> simple one.
>>> Here's a new code (I ran the code with minimal cfg for
>>> 'ft_preprocessing' to isolate the problem):
>>>
>>> cfg.dataset = 'signal_raw.mat';
>>> cfg.trialfun = 'ft_trialfun_test';
>>> cfg.trialdef.event = subj_globals.buttonpress_times;
>>>
>>> cfg = ft_definetrial(cfg);
>>>
>>> cfg.continuous = 'yes';
>>> buttonpress_hg = ft_preprocessing(cfg);
>>>
>>> And here's the error I got:
>>>
>>> Error using ft_read_header (line 2194)
>>> unsupported header format "matlab"
>>>
>>> Error in ft_preprocessing (line 397)
>>>   hdr = ft_read_header(cfg.headerfile, 'headerformat', cfg.headerformat,
>>> 'coordsys', cfg.coordsys, 'coilaccuracy',
>>>   cfg.coilaccuracy);
>>>
>>> Error in test_trialdef (line 18)
>>> buttonpress_hg = ft_preprocessing(cfg);
>>>
>>> So both error come from 'ft_read_header'.
>>> I've been looking at the code but it seemed quite hard to debug as
>>> 'ft_read_header' uses a lower level function that directly reads from the
>>> file (hence it seemed like a simple fix like passing in a fake header
>>> wouldn't work).
>>> Am I doing something wrong here?
>>>
>>> Again, thank you for your reply and let me know if you need more
>>> information.
>>>
>>> Best,
>>> Rachel
>>>
>>> On Thu, Jul 14, 2016 at 12:10 AM, Arjen Stolk <a.stolk8 at gmail.com>
>>> wrote:
>>>
>>>> Hi Rachel,
>>>>
>>>> What is the error you're receiving, and how are you calling
>>>> ft_preprocessing?
>>>>
>>>> If the data is in raw format (incl a trial, time and label field), it
>>>> should theoretically be possible to use ft_preprocessing on it, eg;
>>>> cfg = []
>>>> cfg ..
>>>> data = ft_preprocessing(cfg, raw)
>>>>
>>>> where raw is your data as described above.
>>>>
>>>> Best,
>>>> Arjen
>>>>
>>>> > On Jul 13, 2016, at 11:50 PM, Nakyung Lee <rleese12 at berkeley.edu>
>>>> wrote:
>>>> >
>>>> > Dear FieldTrip community,
>>>> >
>>>> > My name is Rachel Lee and I'm a research assistant in Prof. Ming
>>>> Hsu's lab in UC Berkeley.
>>>> >
>>>> > We currently have a .Tbk file, a .Tdx file, .tev file, .tsq file to
>>>> preprocess and analyze but it seems like those data formats are not yet
>>>> supported by FieldTrip.
>>>> > So, instead of using those raw data files, we've been trying to find
>>>> a workaround by transforming them into a .mat file (and casting the .mat
>>>> file into a raw datatype in FieldTrip by manually assigning fields to it).
>>>> > This hasn't been so successful; we've been unable to call
>>>> ft_preprocessing because of the lack of a proper header format (which is
>>>> needed in ft_read_header, one of the lower level functions that
>>>> ft_preprocessing calls).
>>>> > I've been looking at the codes but been unable to come up with a
>>>> solution.
>>>> >
>>>> > Does anyone have a similar experience?
>>>> > Is there any way to circumvent this issue?
>>>> > Any type of help would be appreciated.
>>>> >
>>>> > Thank you,
>>>> > Rachel Lee
>>>> > _______________________________________________
>>>> > fieldtrip mailing list
>>>> > fieldtrip at donders.ru.nl
>>>> > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>
>>>> _______________________________________________
>>>> fieldtrip mailing list
>>>> fieldtrip at donders.ru.nl
>>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>
>>>
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>
>>>
>>>
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>
>>
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160715/3b381564/attachment.htm>

From a.stolk8 at gmail.com  Fri Jul 15 19:47:39 2016
From: a.stolk8 at gmail.com (Arjen Stolk)
Date: Fri, 15 Jul 2016 10:47:39 -0700
Subject: [FieldTrip] Unsupported data format
In-Reply-To: <CAJir=i_xHhV2qLmqaB5TJvGfJBt5QShA6-3M2onaSWy2eyor2A@mail.gmail.com>
References: <CAJir=i-tKPtva6URMrLzKxo=ZpwUKPEpwcyj8fiy45Hh=qK=nA@mail.gmail.com>
 <EC8F65F8-0F12-4B9C-A410-E71FFDCC695E@gmail.com>
 <CAJir=i_KO8O6ssXzM3-TNGGRsoSyzO2uCorH1xGwAyT4ZCJNfQ@mail.gmail.com>
 <5DD7AA41-AB91-408F-804C-0A8FCC7A633C@donders.ru.nl>
 <CAJir=i91S+qAQ1QQNvME8ThfZSpxhNkJXdssaB9CKPiWO23TWA@mail.gmail.com>
 <CAAiwptQ5CWOTY3ovmgikSgrS-G9_KoeZg_=JLTj4Y096m7P=gQ@mail.gmail.com>
 <CAJir=i_xHhV2qLmqaB5TJvGfJBt5QShA6-3M2onaSWy2eyor2A@mail.gmail.com>
Message-ID: <CAAiwptTfOCmV0PZ38h_UivUnmpRQ+ksOchyJaHu-qR=L4Bz+PQ@mail.gmail.com>

Almost there, Rachel. :) Now ensure your data.label field contains strings
and not numbers, i.e.

data.label = {'1';'2'} and not {1;2}

2016-07-15 10:33 GMT-07:00 Nakyung Lee <rleese12 at berkeley.edu>:

> Hi Arjen,
>
> Yes, that is exactly the structure of 'signal_raw' I'm using.
> I tried your code (without running 'ft_definetrial' beforehand) and here's
> the log:
>
> >> cfg = [];
> >> cfg.demean = 'yes';
> >> data = signal_raw
>
> data =
>
>       label: {176x1 cell}
>        time: {[1x721186 double]}
>       trial: {[176x721186 double]}
>     fsample: 1000
>
> >> data2 = ft_preprocessing(cfg, data);
> Warning: the data does not contain a trial definition
> > In ft_warning (line 184)
>   In fixsampleinfo (line 66)
>   In ft_datatype_raw (line 175)
>   In ft_checkdata (line 219)
>   In ft_preprocessing (line 274)
> Warning: reconstructing sampleinfo by assuming that the trials are
> consecutive segments of a continuous recording
> > In ft_warning (line 184)
>   In fixsampleinfo (line 79)
>   In ft_datatype_raw (line 175)
>   In ft_checkdata (line 219)
>   In ft_preprocessing (line 274)
> Error using cell/ismember (line 34)
> Input A of class cell and input B of class cell must be cell arrays of
> strings, unless one is a string.
>
> Error in ft_senstype (line 303)
>     if     (mean(ismember(ft_senslabel('ant128'),         sens.label)) >
> 0.8)
>
> Error in ft_channelselection (line 83)
>   senstype = ft_senstype(datachannel);
>
> Error in ft_selectdata>getselection_chan (line 649)
>   selchannel = ft_channelselection(cfg.channel, varargin{k}.label);
>
> Error in ft_selectdata (line 279)
> if haschan,    [selchan,    cfg] = getselection_chan   (cfg, varargin{:},
> cfg.select); end
>
> Error in ft_preprocessing (line 317)
>   data   = ft_selectdata(tmpcfg, data);
>
> This data is not segmented yet so there's only one trial (and hence time: {[1x721186
> double]} and trial: {[176x721186 double]}) with 'Ntime' equal to '721186'.
> There were warning signs but seems like those are ignore-able ones.
> Again, let me know if you need more information and thank you.
>
> Best,
> Rachel
>
> On Fri, Jul 15, 2016 at 10:01 AM, Arjen Stolk <a.stolk8 at gmail.com> wrote:
>
>> Hi Rachel,
>>
>> Given that you already have the data imported into matlab and organized
>> into trials, try creating a structure 'data' with the following fields
>> (i.e. data.label, data.time, data.trial) and the following dimensions:
>>
>> label: {151x1 cell}      the channel labels (e.g. 'MRC13')
>> time: {1x266 cell}      the timeaxis [1*Ntime double] per trial
>> trial: {1x266 cell}      the numeric data [151*Ntime double] per trial
>>
>> Then, for a proof of principle, try:
>>
>> cfg = [];
>> cfg.demean = 'yes';
>> data2 = ft_preprocessing(cfg, data);
>>
>> Let us know if this worked for you.
>> Arjen
>>
>>
>> 2016-07-15 9:51 GMT-07:00 Nakyung Lee <rleese12 at berkeley.edu>:
>>
>>> Hi Jan-Mathijs,
>>>
>>> Thanks for your advice.
>>> Yes, I used 'ft_=definetrial' to segment the data.
>>> My data is in the fieldtrip style data format not because it's been
>>> segmented and preprocessed through fieldtrip but because our original
>>> dataformat is unsupported by fieldtrip (.Tbk, .Tdx, .tev, .tsq to be exact).
>>> So my coworker transformed those data into a .mat file and I transformed
>>> into a fieldtrip style raw data but it still needs some segmenting and some
>>> other preprocessing done on it (for example high-gamma filtering).
>>> But if 'ft_preprocessing' is only useable when reading proprietary data
>>> from disk, there's just no way we can preprocess the above data using
>>> fieldtrip?
>>>
>>> Thank you,
>>> Rachel
>>>
>>> On Fri, Jul 15, 2016 at 1:10 AM, Schoffelen, J.M. (Jan Mathijs) <
>>> jan.schoffelen at donders.ru.nl> wrote:
>>>
>>>> Hi Rachel,
>>>>
>>>> Once your data is represented in a fieldtrip-style structure, there’s
>>>> no need anymore to call ft_definetrial with a specified named dataset in
>>>> the cfg.
>>>>
>>>> If you want to segment your data, you may still want to call
>>>> ft_definetrial to generate a so-called ‘trl’ matrix, and subsequently use
>>>> ft_redefinetrial to re-segment, i.e.:
>>>>
>>>> load(’signal_raw.mat’); % I assume that this files contains the
>>>> fieldtrip-style data structure
>>>>
>>>> cfg = [];
>>>> cfg.trl = trl;
>>>> data_epoched = ft_redefinetrial(cfg, data);
>>>>
>>>> So, note that ft_preprocessing shouldn’t be called, this is onlyl
>>>> useable when reading proprietary data from disk.
>>>>
>>>> It seems that you don’t need the cfg.dataset argument to begin with,
>>>> and if you manage to titrate your ft_trialfun_test such that it converts
>>>> the timestamps you provide it with into the correct trl-matrix, I don’t see
>>>> a reason why it shouldn’t work.
>>>>
>>>> Best,
>>>> Jan-Mathijs
>>>>
>>>>
>>>> On 15 Jul 2016, at 08:49, Nakyung Lee <rleese12 at berkeley.edu> wrote:
>>>>
>>>> Hi Arjen,
>>>>
>>>> Thank you for your reply.
>>>> Your email got forwarded successfully.
>>>>
>>>> So currently I tried using 'ft_definetrial' and 'ft_preprocessing'.
>>>> 'ft_definetrial' returns an error when used with 'ft_trialfun' set to
>>>> default.
>>>> Below is the code I used (and 'signal_raw.mat' is a fieldtrip raw data
>>>> and it has all three fields you mentioned).
>>>>
>>>> cfg.dataset = 'signal_raw.mat';
>>>> cfg.trialdef.event = subj_globals.buttonpress_times;
>>>> cfg = ft_definetrial(cfg);
>>>>
>>>> So I simply call ft_definetrial with minimal configuration and here's
>>>> the error I got:
>>>>
>>>> Error using ft_read_header (line 2194)
>>>> unsupported header format "matlab"
>>>>
>>>> Error in ft_trialfun_general (line 78)
>>>> hdr = ft_read_header(cfg.headerfile, 'headerformat', cfg.headerformat);
>>>>
>>>> Error in ft_definetrial (line 177)
>>>>     [trl, event] = feval(cfg.trialfun, cfg);
>>>>
>>>> Error in trialdef_alsotest (line 12)
>>>> cfg = ft_definetrial(cfg);
>>>>
>>>> I circumvented this issue by using my own trialfun ('ft_trialfun_test'
>>>> in the code).
>>>> We already have all the necessary timestamps so I could build a very
>>>> simple one.
>>>> Here's a new code (I ran the code with minimal cfg for
>>>> 'ft_preprocessing' to isolate the problem):
>>>>
>>>> cfg.dataset = 'signal_raw.mat';
>>>> cfg.trialfun = 'ft_trialfun_test';
>>>> cfg.trialdef.event = subj_globals.buttonpress_times;
>>>>
>>>> cfg = ft_definetrial(cfg);
>>>>
>>>> cfg.continuous = 'yes';
>>>> buttonpress_hg = ft_preprocessing(cfg);
>>>>
>>>> And here's the error I got:
>>>>
>>>> Error using ft_read_header (line 2194)
>>>> unsupported header format "matlab"
>>>>
>>>> Error in ft_preprocessing (line 397)
>>>>   hdr = ft_read_header(cfg.headerfile, 'headerformat',
>>>> cfg.headerformat, 'coordsys', cfg.coordsys, 'coilaccuracy',
>>>>   cfg.coilaccuracy);
>>>>
>>>> Error in test_trialdef (line 18)
>>>> buttonpress_hg = ft_preprocessing(cfg);
>>>>
>>>> So both error come from 'ft_read_header'.
>>>> I've been looking at the code but it seemed quite hard to debug as
>>>> 'ft_read_header' uses a lower level function that directly reads from the
>>>> file (hence it seemed like a simple fix like passing in a fake header
>>>> wouldn't work).
>>>> Am I doing something wrong here?
>>>>
>>>> Again, thank you for your reply and let me know if you need more
>>>> information.
>>>>
>>>> Best,
>>>> Rachel
>>>>
>>>> On Thu, Jul 14, 2016 at 12:10 AM, Arjen Stolk <a.stolk8 at gmail.com>
>>>> wrote:
>>>>
>>>>> Hi Rachel,
>>>>>
>>>>> What is the error you're receiving, and how are you calling
>>>>> ft_preprocessing?
>>>>>
>>>>> If the data is in raw format (incl a trial, time and label field), it
>>>>> should theoretically be possible to use ft_preprocessing on it, eg;
>>>>> cfg = []
>>>>> cfg ..
>>>>> data = ft_preprocessing(cfg, raw)
>>>>>
>>>>> where raw is your data as described above.
>>>>>
>>>>> Best,
>>>>> Arjen
>>>>>
>>>>> > On Jul 13, 2016, at 11:50 PM, Nakyung Lee <rleese12 at berkeley.edu>
>>>>> wrote:
>>>>> >
>>>>> > Dear FieldTrip community,
>>>>> >
>>>>> > My name is Rachel Lee and I'm a research assistant in Prof. Ming
>>>>> Hsu's lab in UC Berkeley.
>>>>> >
>>>>> > We currently have a .Tbk file, a .Tdx file, .tev file, .tsq file to
>>>>> preprocess and analyze but it seems like those data formats are not yet
>>>>> supported by FieldTrip.
>>>>> > So, instead of using those raw data files, we've been trying to find
>>>>> a workaround by transforming them into a .mat file (and casting the .mat
>>>>> file into a raw datatype in FieldTrip by manually assigning fields to it).
>>>>> > This hasn't been so successful; we've been unable to call
>>>>> ft_preprocessing because of the lack of a proper header format (which is
>>>>> needed in ft_read_header, one of the lower level functions that
>>>>> ft_preprocessing calls).
>>>>> > I've been looking at the codes but been unable to come up with a
>>>>> solution.
>>>>> >
>>>>> > Does anyone have a similar experience?
>>>>> > Is there any way to circumvent this issue?
>>>>> > Any type of help would be appreciated.
>>>>> >
>>>>> > Thank you,
>>>>> > Rachel Lee
>>>>> > _______________________________________________
>>>>> > fieldtrip mailing list
>>>>> > fieldtrip at donders.ru.nl
>>>>> > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>>
>>>>> _______________________________________________
>>>>> fieldtrip mailing list
>>>>> fieldtrip at donders.ru.nl
>>>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>>
>>>>
>>>> _______________________________________________
>>>> fieldtrip mailing list
>>>> fieldtrip at donders.ru.nl
>>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>
>>>>
>>>>
>>>> _______________________________________________
>>>> fieldtrip mailing list
>>>> fieldtrip at donders.ru.nl
>>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>
>>>
>>>
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>
>>
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160715/d74e8eb4/attachment.htm>

From rleese12 at berkeley.edu  Sat Jul 16 03:54:29 2016
From: rleese12 at berkeley.edu (Nakyung Lee)
Date: Fri, 15 Jul 2016 18:54:29 -0700
Subject: [FieldTrip] Unsupported data format
In-Reply-To: <CAAiwptTfOCmV0PZ38h_UivUnmpRQ+ksOchyJaHu-qR=L4Bz+PQ@mail.gmail.com>
References: <CAJir=i-tKPtva6URMrLzKxo=ZpwUKPEpwcyj8fiy45Hh=qK=nA@mail.gmail.com>
 <EC8F65F8-0F12-4B9C-A410-E71FFDCC695E@gmail.com>
 <CAJir=i_KO8O6ssXzM3-TNGGRsoSyzO2uCorH1xGwAyT4ZCJNfQ@mail.gmail.com>
 <5DD7AA41-AB91-408F-804C-0A8FCC7A633C@donders.ru.nl>
 <CAJir=i91S+qAQ1QQNvME8ThfZSpxhNkJXdssaB9CKPiWO23TWA@mail.gmail.com>
 <CAAiwptQ5CWOTY3ovmgikSgrS-G9_KoeZg_=JLTj4Y096m7P=gQ@mail.gmail.com>
 <CAJir=i_xHhV2qLmqaB5TJvGfJBt5QShA6-3M2onaSWy2eyor2A@mail.gmail.com>
 <CAAiwptTfOCmV0PZ38h_UivUnmpRQ+ksOchyJaHu-qR=L4Bz+PQ@mail.gmail.com>
Message-ID: <CAJir=i8d0q1n5S2JdQctiw8nOOEsp8WU+V_=fm5xFXQSm7PwFQ@mail.gmail.com>

Hooray, it works!
Thanks for being patient with me :)

>> cfg = [];
>> cfg.demean = 'yes';
>> data = signal_raw

data =

      label: {176x1 cell}
       time: {[1x721186 double]}
      trial: {[176x721186 double]}
    fsample: 1000

>> data2 = ft_preprocessing(cfg, data);
Warning: discarding non-unique channel names
> In ft_channelselection (line 102)
  In ft_selectdata>getselection_chan (line 649)
  In ft_selectdata (line 279)
  In ft_preprocessing (line 317)
the call to "ft_selectdata" took 2 seconds
preprocessing
preprocessing trial 1 from 1

the call to "ft_preprocessing" took 4 seconds

And thanks again.

Best,
Rachel

On Fri, Jul 15, 2016 at 10:47 AM, Arjen Stolk <a.stolk8 at gmail.com> wrote:

> Almost there, Rachel. :) Now ensure your data.label field contains strings
> and not numbers, i.e.
>
> data.label = {'1';'2'} and not {1;2}
>
> 2016-07-15 10:33 GMT-07:00 Nakyung Lee <rleese12 at berkeley.edu>:
>
>> Hi Arjen,
>>
>> Yes, that is exactly the structure of 'signal_raw' I'm using.
>> I tried your code (without running 'ft_definetrial' beforehand) and
>> here's the log:
>>
>> >> cfg = [];
>> >> cfg.demean = 'yes';
>> >> data = signal_raw
>>
>> data =
>>
>>       label: {176x1 cell}
>>        time: {[1x721186 double]}
>>       trial: {[176x721186 double]}
>>     fsample: 1000
>>
>> >> data2 = ft_preprocessing(cfg, data);
>> Warning: the data does not contain a trial definition
>> > In ft_warning (line 184)
>>   In fixsampleinfo (line 66)
>>   In ft_datatype_raw (line 175)
>>   In ft_checkdata (line 219)
>>   In ft_preprocessing (line 274)
>> Warning: reconstructing sampleinfo by assuming that the trials are
>> consecutive segments of a continuous recording
>> > In ft_warning (line 184)
>>   In fixsampleinfo (line 79)
>>   In ft_datatype_raw (line 175)
>>   In ft_checkdata (line 219)
>>   In ft_preprocessing (line 274)
>> Error using cell/ismember (line 34)
>> Input A of class cell and input B of class cell must be cell arrays of
>> strings, unless one is a string.
>>
>> Error in ft_senstype (line 303)
>>     if     (mean(ismember(ft_senslabel('ant128'),         sens.label)) >
>> 0.8)
>>
>> Error in ft_channelselection (line 83)
>>   senstype = ft_senstype(datachannel);
>>
>> Error in ft_selectdata>getselection_chan (line 649)
>>   selchannel = ft_channelselection(cfg.channel, varargin{k}.label);
>>
>> Error in ft_selectdata (line 279)
>> if haschan,    [selchan,    cfg] = getselection_chan   (cfg, varargin{:},
>> cfg.select); end
>>
>> Error in ft_preprocessing (line 317)
>>   data   = ft_selectdata(tmpcfg, data);
>>
>> This data is not segmented yet so there's only one trial (and hence time: {[1x721186
>> double]} and trial: {[176x721186 double]}) with 'Ntime' equal to
>> '721186'.
>> There were warning signs but seems like those are ignore-able ones.
>> Again, let me know if you need more information and thank you.
>>
>> Best,
>> Rachel
>>
>> On Fri, Jul 15, 2016 at 10:01 AM, Arjen Stolk <a.stolk8 at gmail.com> wrote:
>>
>>> Hi Rachel,
>>>
>>> Given that you already have the data imported into matlab and organized
>>> into trials, try creating a structure 'data' with the following fields
>>> (i.e. data.label, data.time, data.trial) and the following dimensions:
>>>
>>> label: {151x1 cell}      the channel labels (e.g. 'MRC13')
>>> time: {1x266 cell}      the timeaxis [1*Ntime double] per trial
>>> trial: {1x266 cell}      the numeric data [151*Ntime double] per trial
>>>
>>> Then, for a proof of principle, try:
>>>
>>> cfg = [];
>>> cfg.demean = 'yes';
>>> data2 = ft_preprocessing(cfg, data);
>>>
>>> Let us know if this worked for you.
>>> Arjen
>>>
>>>
>>> 2016-07-15 9:51 GMT-07:00 Nakyung Lee <rleese12 at berkeley.edu>:
>>>
>>>> Hi Jan-Mathijs,
>>>>
>>>> Thanks for your advice.
>>>> Yes, I used 'ft_=definetrial' to segment the data.
>>>> My data is in the fieldtrip style data format not because it's been
>>>> segmented and preprocessed through fieldtrip but because our original
>>>> dataformat is unsupported by fieldtrip (.Tbk, .Tdx, .tev, .tsq to be exact).
>>>> So my coworker transformed those data into a .mat file and I
>>>> transformed into a fieldtrip style raw data but it still needs some
>>>> segmenting and some other preprocessing done on it (for example high-gamma
>>>> filtering).
>>>> But if 'ft_preprocessing' is only useable when reading proprietary
>>>> data from disk, there's just no way we can preprocess the above data using
>>>> fieldtrip?
>>>>
>>>> Thank you,
>>>> Rachel
>>>>
>>>> On Fri, Jul 15, 2016 at 1:10 AM, Schoffelen, J.M. (Jan Mathijs) <
>>>> jan.schoffelen at donders.ru.nl> wrote:
>>>>
>>>>> Hi Rachel,
>>>>>
>>>>> Once your data is represented in a fieldtrip-style structure, there’s
>>>>> no need anymore to call ft_definetrial with a specified named dataset in
>>>>> the cfg.
>>>>>
>>>>> If you want to segment your data, you may still want to call
>>>>> ft_definetrial to generate a so-called ‘trl’ matrix, and subsequently use
>>>>> ft_redefinetrial to re-segment, i.e.:
>>>>>
>>>>> load(’signal_raw.mat’); % I assume that this files contains the
>>>>> fieldtrip-style data structure
>>>>>
>>>>> cfg = [];
>>>>> cfg.trl = trl;
>>>>> data_epoched = ft_redefinetrial(cfg, data);
>>>>>
>>>>> So, note that ft_preprocessing shouldn’t be called, this is onlyl
>>>>> useable when reading proprietary data from disk.
>>>>>
>>>>> It seems that you don’t need the cfg.dataset argument to begin with,
>>>>> and if you manage to titrate your ft_trialfun_test such that it converts
>>>>> the timestamps you provide it with into the correct trl-matrix, I don’t see
>>>>> a reason why it shouldn’t work.
>>>>>
>>>>> Best,
>>>>> Jan-Mathijs
>>>>>
>>>>>
>>>>> On 15 Jul 2016, at 08:49, Nakyung Lee <rleese12 at berkeley.edu> wrote:
>>>>>
>>>>> Hi Arjen,
>>>>>
>>>>> Thank you for your reply.
>>>>> Your email got forwarded successfully.
>>>>>
>>>>> So currently I tried using 'ft_definetrial' and 'ft_preprocessing'.
>>>>> 'ft_definetrial' returns an error when used with 'ft_trialfun' set to
>>>>> default.
>>>>> Below is the code I used (and 'signal_raw.mat' is a fieldtrip raw data
>>>>> and it has all three fields you mentioned).
>>>>>
>>>>> cfg.dataset = 'signal_raw.mat';
>>>>> cfg.trialdef.event = subj_globals.buttonpress_times;
>>>>> cfg = ft_definetrial(cfg);
>>>>>
>>>>> So I simply call ft_definetrial with minimal configuration and here's
>>>>> the error I got:
>>>>>
>>>>> Error using ft_read_header (line 2194)
>>>>> unsupported header format "matlab"
>>>>>
>>>>> Error in ft_trialfun_general (line 78)
>>>>> hdr = ft_read_header(cfg.headerfile, 'headerformat', cfg.headerformat);
>>>>>
>>>>> Error in ft_definetrial (line 177)
>>>>>     [trl, event] = feval(cfg.trialfun, cfg);
>>>>>
>>>>> Error in trialdef_alsotest (line 12)
>>>>> cfg = ft_definetrial(cfg);
>>>>>
>>>>> I circumvented this issue by using my own trialfun ('ft_trialfun_test'
>>>>> in the code).
>>>>> We already have all the necessary timestamps so I could build a very
>>>>> simple one.
>>>>> Here's a new code (I ran the code with minimal cfg for
>>>>> 'ft_preprocessing' to isolate the problem):
>>>>>
>>>>> cfg.dataset = 'signal_raw.mat';
>>>>> cfg.trialfun = 'ft_trialfun_test';
>>>>> cfg.trialdef.event = subj_globals.buttonpress_times;
>>>>>
>>>>> cfg = ft_definetrial(cfg);
>>>>>
>>>>> cfg.continuous = 'yes';
>>>>> buttonpress_hg = ft_preprocessing(cfg);
>>>>>
>>>>> And here's the error I got:
>>>>>
>>>>> Error using ft_read_header (line 2194)
>>>>> unsupported header format "matlab"
>>>>>
>>>>> Error in ft_preprocessing (line 397)
>>>>>   hdr = ft_read_header(cfg.headerfile, 'headerformat',
>>>>> cfg.headerformat, 'coordsys', cfg.coordsys, 'coilaccuracy',
>>>>>   cfg.coilaccuracy);
>>>>>
>>>>> Error in test_trialdef (line 18)
>>>>> buttonpress_hg = ft_preprocessing(cfg);
>>>>>
>>>>> So both error come from 'ft_read_header'.
>>>>> I've been looking at the code but it seemed quite hard to debug as
>>>>> 'ft_read_header' uses a lower level function that directly reads from the
>>>>> file (hence it seemed like a simple fix like passing in a fake header
>>>>> wouldn't work).
>>>>> Am I doing something wrong here?
>>>>>
>>>>> Again, thank you for your reply and let me know if you need more
>>>>> information.
>>>>>
>>>>> Best,
>>>>> Rachel
>>>>>
>>>>> On Thu, Jul 14, 2016 at 12:10 AM, Arjen Stolk <a.stolk8 at gmail.com>
>>>>> wrote:
>>>>>
>>>>>> Hi Rachel,
>>>>>>
>>>>>> What is the error you're receiving, and how are you calling
>>>>>> ft_preprocessing?
>>>>>>
>>>>>> If the data is in raw format (incl a trial, time and label field), it
>>>>>> should theoretically be possible to use ft_preprocessing on it, eg;
>>>>>> cfg = []
>>>>>> cfg ..
>>>>>> data = ft_preprocessing(cfg, raw)
>>>>>>
>>>>>> where raw is your data as described above.
>>>>>>
>>>>>> Best,
>>>>>> Arjen
>>>>>>
>>>>>> > On Jul 13, 2016, at 11:50 PM, Nakyung Lee <rleese12 at berkeley.edu>
>>>>>> wrote:
>>>>>> >
>>>>>> > Dear FieldTrip community,
>>>>>> >
>>>>>> > My name is Rachel Lee and I'm a research assistant in Prof. Ming
>>>>>> Hsu's lab in UC Berkeley.
>>>>>> >
>>>>>> > We currently have a .Tbk file, a .Tdx file, .tev file, .tsq file to
>>>>>> preprocess and analyze but it seems like those data formats are not yet
>>>>>> supported by FieldTrip.
>>>>>> > So, instead of using those raw data files, we've been trying to
>>>>>> find a workaround by transforming them into a .mat file (and casting the
>>>>>> .mat file into a raw datatype in FieldTrip by manually assigning fields to
>>>>>> it).
>>>>>> > This hasn't been so successful; we've been unable to call
>>>>>> ft_preprocessing because of the lack of a proper header format (which is
>>>>>> needed in ft_read_header, one of the lower level functions that
>>>>>> ft_preprocessing calls).
>>>>>> > I've been looking at the codes but been unable to come up with a
>>>>>> solution.
>>>>>> >
>>>>>> > Does anyone have a similar experience?
>>>>>> > Is there any way to circumvent this issue?
>>>>>> > Any type of help would be appreciated.
>>>>>> >
>>>>>> > Thank you,
>>>>>> > Rachel Lee
>>>>>> > _______________________________________________
>>>>>> > fieldtrip mailing list
>>>>>> > fieldtrip at donders.ru.nl
>>>>>> > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>>>
>>>>>> _______________________________________________
>>>>>> fieldtrip mailing list
>>>>>> fieldtrip at donders.ru.nl
>>>>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>>>
>>>>>
>>>>> _______________________________________________
>>>>> fieldtrip mailing list
>>>>> fieldtrip at donders.ru.nl
>>>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>>
>>>>>
>>>>>
>>>>> _______________________________________________
>>>>> fieldtrip mailing list
>>>>> fieldtrip at donders.ru.nl
>>>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>>
>>>>
>>>>
>>>> _______________________________________________
>>>> fieldtrip mailing list
>>>> fieldtrip at donders.ru.nl
>>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>
>>>
>>>
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>
>>
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160715/4c348dd9/attachment.htm>

From a.stolk8 at gmail.com  Sat Jul 16 04:26:32 2016
From: a.stolk8 at gmail.com (Arjen Stolk)
Date: Fri, 15 Jul 2016 19:26:32 -0700
Subject: [FieldTrip] Unsupported data format
In-Reply-To: <CAJir=i8d0q1n5S2JdQctiw8nOOEsp8WU+V_=fm5xFXQSm7PwFQ@mail.gmail.com>
References: <CAJir=i-tKPtva6URMrLzKxo=ZpwUKPEpwcyj8fiy45Hh=qK=nA@mail.gmail.com>
 <EC8F65F8-0F12-4B9C-A410-E71FFDCC695E@gmail.com>
 <CAJir=i_KO8O6ssXzM3-TNGGRsoSyzO2uCorH1xGwAyT4ZCJNfQ@mail.gmail.com>
 <5DD7AA41-AB91-408F-804C-0A8FCC7A633C@donders.ru.nl>
 <CAJir=i91S+qAQ1QQNvME8ThfZSpxhNkJXdssaB9CKPiWO23TWA@mail.gmail.com>
 <CAAiwptQ5CWOTY3ovmgikSgrS-G9_KoeZg_=JLTj4Y096m7P=gQ@mail.gmail.com>
 <CAJir=i_xHhV2qLmqaB5TJvGfJBt5QShA6-3M2onaSWy2eyor2A@mail.gmail.com>
 <CAAiwptTfOCmV0PZ38h_UivUnmpRQ+ksOchyJaHu-qR=L4Bz+PQ@mail.gmail.com>
 <CAJir=i8d0q1n5S2JdQctiw8nOOEsp8WU+V_=fm5xFXQSm7PwFQ@mail.gmail.com>
Message-ID: <43EC80C7-0230-40E6-AD33-57B625D414DC@gmail.com>

Great to hear!

> On Jul 15, 2016, at 6:54 PM, Nakyung Lee <rleese12 at berkeley.edu> wrote:
> 
> Hooray, it works!
> Thanks for being patient with me :)
> 
> >> cfg = [];
> >> cfg.demean = 'yes';
> >> data = signal_raw
> 
> data = 
> 
>       label: {176x1 cell}
>        time: {[1x721186 double]}
>       trial: {[176x721186 double]}
>     fsample: 1000
> 
> >> data2 = ft_preprocessing(cfg, data);
> Warning: discarding non-unique channel names 
> > In ft_channelselection (line 102)
>   In ft_selectdata>getselection_chan (line 649)
>   In ft_selectdata (line 279)
>   In ft_preprocessing (line 317) 
> the call to "ft_selectdata" took 2 seconds
> preprocessing
> preprocessing trial 1 from 1
> 
> the call to "ft_preprocessing" took 4 seconds
> 
> And thanks again.
> 
> Best,
> Rachel
> 
>> On Fri, Jul 15, 2016 at 10:47 AM, Arjen Stolk <a.stolk8 at gmail.com> wrote:
>> Almost there, Rachel. :) Now ensure your data.label field contains strings and not numbers, i.e.
>> 
>> data.label = {'1';'2'} and not {1;2}
>> 
>> 2016-07-15 10:33 GMT-07:00 Nakyung Lee <rleese12 at berkeley.edu>:
>>> Hi Arjen,
>>> 
>>> Yes, that is exactly the structure of 'signal_raw' I'm using.
>>> I tried your code (without running 'ft_definetrial' beforehand) and here's the log:
>>> 
>>> >> cfg = [];
>>> >> cfg.demean = 'yes';
>>> >> data = signal_raw
>>> 
>>> data = 
>>> 
>>>       label: {176x1 cell}
>>>        time: {[1x721186 double]}
>>>       trial: {[176x721186 double]}
>>>     fsample: 1000
>>> 
>>> >> data2 = ft_preprocessing(cfg, data);
>>> Warning: the data does not contain a trial definition 
>>> > In ft_warning (line 184)
>>>   In fixsampleinfo (line 66)
>>>   In ft_datatype_raw (line 175)
>>>   In ft_checkdata (line 219)
>>>   In ft_preprocessing (line 274) 
>>> Warning: reconstructing sampleinfo by assuming that the trials are consecutive segments of a continuous recording 
>>> > In ft_warning (line 184)
>>>   In fixsampleinfo (line 79)
>>>   In ft_datatype_raw (line 175)
>>>   In ft_checkdata (line 219)
>>>   In ft_preprocessing (line 274) 
>>> Error using cell/ismember (line 34)
>>> Input A of class cell and input B of class cell must be cell arrays of strings, unless one is a string.
>>> 
>>> Error in ft_senstype (line 303)
>>>     if     (mean(ismember(ft_senslabel('ant128'),         sens.label)) > 0.8)
>>> 
>>> Error in ft_channelselection (line 83)
>>>   senstype = ft_senstype(datachannel);
>>> 
>>> Error in ft_selectdata>getselection_chan (line 649)
>>>   selchannel = ft_channelselection(cfg.channel, varargin{k}.label);
>>> 
>>> Error in ft_selectdata (line 279)
>>> if haschan,    [selchan,    cfg] = getselection_chan   (cfg, varargin{:}, cfg.select); end
>>> 
>>> Error in ft_preprocessing (line 317)
>>>   data   = ft_selectdata(tmpcfg, data);
>>>  
>>> This data is not segmented yet so there's only one trial (and hence time: {[1x721186 double]} and trial: {[176x721186 double]}) with 'Ntime' equal to '721186'.
>>> There were warning signs but seems like those are ignore-able ones.
>>> Again, let me know if you need more information and thank you.
>>> 
>>> Best,
>>> Rachel
>>> 
>>>> On Fri, Jul 15, 2016 at 10:01 AM, Arjen Stolk <a.stolk8 at gmail.com> wrote:
>>>> Hi Rachel,
>>>> 
>>>> Given that you already have the data imported into matlab and organized into trials, try creating a structure 'data' with the following fields (i.e. data.label, data.time, data.trial) and the following dimensions:
>>>> 
>>>> label: {151x1 cell}      the channel labels (e.g. 'MRC13')
>>>> time: {1x266 cell}      the timeaxis [1*Ntime double] per trial
>>>> trial: {1x266 cell}      the numeric data [151*Ntime double] per trial
>>>> Then, for a proof of principle, try:
>>>> 
>>>> cfg = [];
>>>> cfg.demean = 'yes';
>>>> data2 = ft_preprocessing(cfg, data);
>>>> 
>>>> Let us know if this worked for you.
>>>> Arjen
>>>> 
>>>> 
>>>> 2016-07-15 9:51 GMT-07:00 Nakyung Lee <rleese12 at berkeley.edu>:
>>>>> Hi Jan-Mathijs,
>>>>> 
>>>>> Thanks for your advice.
>>>>> Yes, I used 'ft_=definetrial' to segment the data.
>>>>> My data is in the fieldtrip style data format not because it's been segmented and preprocessed through fieldtrip but because our original dataformat is unsupported by fieldtrip (.Tbk, .Tdx, .tev, .tsq to be exact).
>>>>> So my coworker transformed those data into a .mat file and I transformed into a fieldtrip style raw data but it still needs some segmenting and some other preprocessing done on it (for example high-gamma filtering).
>>>>> But if 'ft_preprocessing' is only useable when reading proprietary data from disk, there's just no way we can preprocess the above data using fieldtrip?
>>>>> 
>>>>> Thank you,
>>>>> Rachel
>>>>> 
>>>>>> On Fri, Jul 15, 2016 at 1:10 AM, Schoffelen, J.M. (Jan Mathijs) <jan.schoffelen at donders.ru.nl> wrote:
>>>>>> Hi Rachel,
>>>>>> 
>>>>>> Once your data is represented in a fieldtrip-style structure, there’s no need anymore to call ft_definetrial with a specified named dataset in the cfg.
>>>>>> 
>>>>>> If you want to segment your data, you may still want to call ft_definetrial to generate a so-called ‘trl’ matrix, and subsequently use ft_redefinetrial to re-segment, i.e.:
>>>>>> 
>>>>>> load(’signal_raw.mat’); % I assume that this files contains the fieldtrip-style data structure
>>>>>> 
>>>>>> cfg = [];
>>>>>> cfg.trl = trl;
>>>>>> data_epoched = ft_redefinetrial(cfg, data);
>>>>>> 
>>>>>> So, note that ft_preprocessing shouldn’t be called, this is onlyl useable when reading proprietary data from disk.
>>>>>> 
>>>>>> It seems that you don’t need the cfg.dataset argument to begin with, and if you manage to titrate your ft_trialfun_test such that it converts the timestamps you provide it with into the correct trl-matrix, I don’t see a reason why it shouldn’t work.
>>>>>> 
>>>>>> Best,
>>>>>> Jan-Mathijs
>>>>>> 
>>>>>> 
>>>>>>> On 15 Jul 2016, at 08:49, Nakyung Lee <rleese12 at berkeley.edu> wrote:
>>>>>>> 
>>>>>>> Hi Arjen,
>>>>>>> 
>>>>>>> Thank you for your reply.
>>>>>>> Your email got forwarded successfully.
>>>>>>> 
>>>>>>> So currently I tried using 'ft_definetrial' and 'ft_preprocessing'.
>>>>>>> 'ft_definetrial' returns an error when used with 'ft_trialfun' set to default.
>>>>>>> Below is the code I used (and 'signal_raw.mat' is a fieldtrip raw data and it has all three fields you mentioned).
>>>>>>> 
>>>>>>> cfg.dataset = 'signal_raw.mat';
>>>>>>> cfg.trialdef.event = subj_globals.buttonpress_times;
>>>>>>> cfg = ft_definetrial(cfg);
>>>>>>> 
>>>>>>> So I simply call ft_definetrial with minimal configuration and here's the error I got:
>>>>>>> 
>>>>>>> Error using ft_read_header (line 2194)
>>>>>>> unsupported header format "matlab"
>>>>>>> 
>>>>>>> Error in ft_trialfun_general (line 78)
>>>>>>> hdr = ft_read_header(cfg.headerfile, 'headerformat', cfg.headerformat);
>>>>>>> 
>>>>>>> Error in ft_definetrial (line 177)
>>>>>>>     [trl, event] = feval(cfg.trialfun, cfg);
>>>>>>> 
>>>>>>> Error in trialdef_alsotest (line 12)
>>>>>>> cfg = ft_definetrial(cfg);
>>>>>>> 
>>>>>>> I circumvented this issue by using my own trialfun ('ft_trialfun_test' in the code).
>>>>>>> We already have all the necessary timestamps so I could build a very simple one.
>>>>>>> Here's a new code (I ran the code with minimal cfg for 'ft_preprocessing' to isolate the problem):
>>>>>>> 
>>>>>>> cfg.dataset = 'signal_raw.mat';
>>>>>>> cfg.trialfun = 'ft_trialfun_test'; 
>>>>>>> cfg.trialdef.event = subj_globals.buttonpress_times;
>>>>>>> 
>>>>>>> cfg = ft_definetrial(cfg);
>>>>>>> 
>>>>>>> cfg.continuous = 'yes';
>>>>>>> buttonpress_hg = ft_preprocessing(cfg);
>>>>>>> 
>>>>>>> And here's the error I got:
>>>>>>> 
>>>>>>> Error using ft_read_header (line 2194)
>>>>>>> unsupported header format "matlab"
>>>>>>> 
>>>>>>> Error in ft_preprocessing (line 397)
>>>>>>>   hdr = ft_read_header(cfg.headerfile, 'headerformat', cfg.headerformat, 'coordsys', cfg.coordsys, 'coilaccuracy',
>>>>>>>   cfg.coilaccuracy);
>>>>>>> 
>>>>>>> Error in test_trialdef (line 18)
>>>>>>> buttonpress_hg = ft_preprocessing(cfg);
>>>>>>> 
>>>>>>> So both error come from 'ft_read_header'.
>>>>>>> I've been looking at the code but it seemed quite hard to debug as 'ft_read_header' uses a lower level function that directly reads from the file (hence it seemed like a simple fix like passing in a fake header wouldn't work).
>>>>>>> Am I doing something wrong here?
>>>>>>> 
>>>>>>> Again, thank you for your reply and let me know if you need more information.
>>>>>>> 
>>>>>>> Best,
>>>>>>> Rachel
>>>>>>> 
>>>>>>>> On Thu, Jul 14, 2016 at 12:10 AM, Arjen Stolk <a.stolk8 at gmail.com> wrote:
>>>>>>>> Hi Rachel,
>>>>>>>> 
>>>>>>>> What is the error you're receiving, and how are you calling ft_preprocessing?
>>>>>>>> 
>>>>>>>> If the data is in raw format (incl a trial, time and label field), it should theoretically be possible to use ft_preprocessing on it, eg;
>>>>>>>> cfg = []
>>>>>>>> cfg ..
>>>>>>>> data = ft_preprocessing(cfg, raw)
>>>>>>>> 
>>>>>>>> where raw is your data as described above.
>>>>>>>> 
>>>>>>>> Best,
>>>>>>>> Arjen
>>>>>>>> 
>>>>>>>> > On Jul 13, 2016, at 11:50 PM, Nakyung Lee <rleese12 at berkeley.edu> wrote:
>>>>>>>> >
>>>>>>>> > Dear FieldTrip community,
>>>>>>>> >
>>>>>>>> > My name is Rachel Lee and I'm a research assistant in Prof. Ming Hsu's lab in UC Berkeley.
>>>>>>>> >
>>>>>>>> > We currently have a .Tbk file, a .Tdx file, .tev file, .tsq file to preprocess and analyze but it seems like those data formats are not yet supported by FieldTrip.
>>>>>>>> > So, instead of using those raw data files, we've been trying to find a workaround by transforming them into a .mat file (and casting the .mat file into a raw datatype in FieldTrip by manually assigning fields to it).
>>>>>>>> > This hasn't been so successful; we've been unable to call ft_preprocessing because of the lack of a proper header format (which is needed in ft_read_header, one of the lower level functions that ft_preprocessing calls).
>>>>>>>> > I've been looking at the codes but been unable to come up with a solution.
>>>>>>>> >
>>>>>>>> > Does anyone have a similar experience?
>>>>>>>> > Is there any way to circumvent this issue?
>>>>>>>> > Any type of help would be appreciated.
>>>>>>>> >
>>>>>>>> > Thank you,
>>>>>>>> > Rachel Lee
>>>>>>>> > _______________________________________________
>>>>>>>> > fieldtrip mailing list
>>>>>>>> > fieldtrip at donders.ru.nl
>>>>>>>> > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>>>>> 
>>>>>>>> _______________________________________________
>>>>>>>> fieldtrip mailing list
>>>>>>>> fieldtrip at donders.ru.nl
>>>>>>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>>>> 
>>>>>>> _______________________________________________
>>>>>>> fieldtrip mailing list
>>>>>>> fieldtrip at donders.ru.nl
>>>>>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>>> 
>>>>>> 
>>>>>> _______________________________________________
>>>>>> fieldtrip mailing list
>>>>>> fieldtrip at donders.ru.nl
>>>>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>> 
>>>>> 
>>>>> _______________________________________________
>>>>> fieldtrip mailing list
>>>>> fieldtrip at donders.ru.nl
>>>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>> 
>>>> 
>>>> _______________________________________________
>>>> fieldtrip mailing list
>>>> fieldtrip at donders.ru.nl
>>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>> 
>>> 
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>> 
>> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160715/ceafcb89/attachment.htm>

From icelandhouse at gmail.com  Sun Jul 17 21:30:37 2016
From: icelandhouse at gmail.com (Maris Skujevskis)
Date: Sun, 17 Jul 2016 21:30:37 +0200
Subject: [FieldTrip] warnings when running ft_sourceinterpolate
Message-ID: <CAKEvDieRx7eN2oTmtOv+j4zhjVEpGSfa+X0Fe+LG36T1iAmOcw@mail.gmail.com>

Hi all,

I get two warnings when running ft_sourceinterpolate after DICS beamformer
based source reconstruction. The warnings and my question come after the
pasted code section.

The code that generates the input to ft_sourceinterpolate:
%% Source analysis
    cfg                            = [ ];
    cfg.method               = 'dics';
    cfg.frequency           = 10;
    cfg.grid                     = leadfield_ft;  (leadfield_ft.leadfield
is a cell structure with non-empty cells containing matrices of size
channel count x 3 )
    cfg.keepleadfield      = 'yes';
    cfg.headmodel         = vol;
    cfg.dics.keepfilter     = 'yes';
    cfg.dics.lambda        = '5%';
    cfg.dics.fixedori        = 'yes';
    cfg.dics.keepmom    = 'no';
    cfg.dics.realfilter       = 'yes';
    source_A                  = ft_sourceanalysis(cfg, trials_A);

>>source_A =
                     freq: 9.8462
                     dim: [18 21 18]
                 inside: [6804x1 logical]
             leadfield: {1x6804 cell}
                     pos: [6804x3 double]
               method: 'average'
                     avg: [1x1 struct]
                      cfg: [1x1 struct]



%% Source interpolation

cfg                             = [ ];
cfg.parameter           = 'pow';
A_int                         = ft_sourceinterpolate(cfg, source_A,
template_mri);

WARNING 1
Warning: could not determine dimord of "filter" in the following data
> In getdimord (line 541)
  In getdatfield (line 31)
  In ft_datatype_volume (line 133)
  In ft_checkdata (line 329)
  In ft_sourceinterpolate (line 160)
            freq: 9.8462
            dim: [18 21 18]
        inside: [6804x1 logical]
    leadfield: {1x6804 cell}
             cfg: [1x1 struct]
           pow: [6804x1 double]
           filter: {6804x1 cell}
  transform: [4x4 double]


WARNING 2
Warning: could not reshape freq to the expected dimensions
> In ft_datatype_volume (line 138)
  In ft_checkdata (line 329)
  In ft_sourceinterpolate (line 160)


I understand that cfg.dics.fixedori  = 'yes' reduces the dimensions of the
leadfield matrices from 3 x channel number, to 1 x channel number. Does it
mean I can safely ignore the "could not determine dimord of "filter" in the
following data" ? Or is there something wrong in the data structure that I
need to manually fix?

Warning 2 escapes me. There is a only single frequency, to what dimensions
does it need to be reshaped? Can I safely ignore this one or again, some
fixing is needed?

Thanks a lot!

Maris
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160717/49261170/attachment.htm>

From amickan1990 at gmail.com  Mon Jul 18 14:22:48 2016
From: amickan1990 at gmail.com (Anne Mickan)
Date: Mon, 18 Jul 2016 14:22:48 +0200
Subject: [FieldTrip] 3x2 ANOVA using permutation tests?
Message-ID: <CANX43OLDu7h1hHutA1tou0HuGqD3i=oySwONHnFPKVL5=h7wJA@mail.gmail.com>

Dear fieldtrip community,

I've been using cluster-based permutation tests to analysis my EEG data in
which I have 3 groups and 2 conditions each. Ultimately I want to know
whether groups differ from each other with respect to differences in
conditions. In a traditional analysis I would do an ANOVA on preselected
time-windows, but I haven't been able to figure out how to properly do that
within the permutation test.

So far I simply did permutation tests for each of the groups separately.
Then on the basis of these I choose windows for an ANOVA (and a regression
analysis with some behavioral measures I acquired). Is that OK? Or is there
a way to do the permutation tests for all groups together and add group as
a between-subject factor (in addition to the within-subjects factor
condition)? And would that be better / obligatory to do (instead of what I
did so far).

How do I need to change the cfg.design in order to do that?

Thanks a lot in advance!

Best,
Anne
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160718/42b945fa/attachment.htm>

From tineke.snijders at donders.ru.nl  Mon Jul 18 14:54:30 2016
From: tineke.snijders at donders.ru.nl (Snijders, T.M. (Tineke))
Date: Mon, 18 Jul 2016 12:54:30 +0000
Subject: [FieldTrip] 3x2 ANOVA using permutation tests?
In-Reply-To: <CANX43OLDu7h1hHutA1tou0HuGqD3i=oySwONHnFPKVL5=h7wJA@mail.gmail.com>
References: <CANX43OLDu7h1hHutA1tou0HuGqD3i=oySwONHnFPKVL5=h7wJA@mail.gmail.com>
Message-ID: <815A9820E75FBC4F96B7CD3A8089D11C378ED8B3@exprd04.hosting.ru.nl>

Hi Anne,

To first do the analysis on separate groups, and then do an ANOVA on the resulting time-windows comparing the groups is double dipping.

The simplest solution is to first do the cluster randomization test on all 3 groups together (i.e. treat them as 1 group), and compare the 2 conditions (so just a depsamplesT).
Based on this you get a time-window & electrodes that show a difference between conditions.
You then extract the subject means from this time-window&electrodes (meaning you get one value per subject per condition), and use these in an ANOVA to compare the different groups, and to look at the effect of the behavioral regressor.

Alternatively, you can use the difference scores (condition 2- condition 1) as an input for the cluster randomization, with the three groups as between-subject factor (indepsamplesF).

Best,

Tineke



________________________________
From: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl] on behalf of Anne Mickan [amickan1990 at gmail.com]
Sent: Monday, July 18, 2016 2:22 PM
To: fieldtrip at science.ru.nl
Subject: [FieldTrip] 3x2 ANOVA using permutation tests?

Dear fieldtrip community,

I've been using cluster-based permutation tests to analysis my EEG data in which I have 3 groups and 2 conditions each. Ultimately I want to know whether groups differ from each other with respect to differences in conditions. In a traditional analysis I would do an ANOVA on preselected time-windows, but I haven't been able to figure out how to properly do that within the permutation test.

So far I simply did permutation tests for each of the groups separately. Then on the basis of these I choose windows for an ANOVA (and a regression analysis with some behavioral measures I acquired). Is that OK? Or is there a way to do the permutation tests for all groups together and add group as a between-subject factor (in addition to the within-subjects factor condition)? And would that be better / obligatory to do (instead of what I did so far).

How do I need to change the cfg.design in order to do that?

Thanks a lot in advance!

Best,
Anne
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160718/7f208e09/attachment.htm>

From joseluisblues at gmail.com  Mon Jul 18 18:07:31 2016
From: joseluisblues at gmail.com (Jose)
Date: Mon, 18 Jul 2016 18:07:31 +0200
Subject: [FieldTrip] cluster-based permutation test - baseline correction
Message-ID: <CAH3cVdCQXs5grRDV==GWVjUuduOGPe_iM-G_o6W1U5vACPZ5og@mail.gmail.com>

dear community,

I'm performing analysis of CTF MEG data. I have two conditions of interest:
A and B, and I have performed spectral decomposition with the wavelet
method to obtain the power (frequencies from 1 to 50 Hz). I would like to
perform a cluster-based permutation test to assess if there are significant
power differences between my two conditions of interest between the onset
of my stimulus and 1 sec after,

While I understand the principles of cluster-based permutation test, with
their distinct versions: between trials, within trials and within subjects,
what I am interested in is to test differences between my two conditions in
their baseline-corrected versions. Since I haven't seen this procedure in
the tutorial, but it seems logic to me, I would like to verify the way to
proceed is do baseline correction (for each condition and subject) and then
run my cluster-permutation test. Is there anything else I should consider?

Also, since I haven't used 'demean' during my trial definition (I was
advised not to do this), I was wondering if this could impact my baseline
correction, and subsequent statistical analysis. I've seen some messages in
the forum referring to this procedure,

Thanks in advance,

Jose
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160718/88a38535/attachment.htm>

From r.thomas at nin.knaw.nl  Tue Jul 19 08:10:24 2016
From: r.thomas at nin.knaw.nl (Rajat Thomas)
Date: Tue, 19 Jul 2016 06:10:24 +0000
Subject: [FieldTrip] Sourcestatistics on surfaces
Message-ID: <1468908624743.12047@nin.knaw.nl>

Hi Fieldtrippers,


I have been working on source statistics after source analysis on surfaces using MNE.

I used the following configuration;


% run statistics over subjects %
cfg=[];
cfg.latency         = [0 0.7]; %s
cfg.avgovertime = 'no';
cfg.method        = 'montecarlo';
cfg.statistic        = 'ft_statfun_depsamplesT';
cfg.parameter    = 'pow';
cfg.correctm                = 'cluster';
cfg.numrandomization = 100;
cfg.alpha       = 0.05; % note that this only implies single-sided testing
cfg.tail        = 0;

cfg.tri         = sourcespace.tri;

nsubj=numel(all_source_intact);
cfg.design(1,:) = [1:nsubj 1:nsubj];
cfg.design(2,:) = [ones(1,nsubj) ones(1,nsubj)*2];
cfg.uvar        = 1; % row of design matrix that contains unit variable (in this case: subjects)
cfg.ivar        = 2; % row of design matrix that contains independent variable (the conditions)

stat = ft_sourcestatistics(cfg, all_source_condA{:}, all_source_condB{:});
save('stat_cluster.mat', 'stat');



%----

I wanted to know if there are other options typically set when I do sourcestatistics on surfaces.

Any guide would be helpful.

Thank you.
Rajat

Rajat Mani Thomas
Social Brain Lab
Netherlands Institute for Neuroscience
Amsterdam
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160719/a70f2f19/attachment.htm>

From J.Herring at donders.ru.nl  Tue Jul 19 09:28:58 2016
From: J.Herring at donders.ru.nl (Herring, J.D. (Jim))
Date: Tue, 19 Jul 2016 07:28:58 +0000
Subject: [FieldTrip] cluster-based permutation test - baseline correction
In-Reply-To: <CAH3cVdCQXs5grRDV==GWVjUuduOGPe_iM-G_o6W1U5vACPZ5og@mail.gmail.com>
References: <CAH3cVdCQXs5grRDV==GWVjUuduOGPe_iM-G_o6W1U5vACPZ5og@mail.gmail.com>
Message-ID: <6F9804CE79B042468FDC7E8C86CF4CBC49EB592A@exprd04.hosting.ru.nl>

Dear Jose,

If you assume there to be (perhaps trivial) differences in the baselines of conditions A and B, but you are interested in the difference in change from baseline then doing a baseline correction is indeed what you want to do. If you do not assume a difference at baseline it is in principle not necessary to correct for it (It might even hurt: http://datacolada.org/39) .

With regards to ‘demeaning’ (and detrending), have a look at these two pages:
http://www.fieldtriptoolbox.org/faq/why_does_my_tfr_look_strange
http://www.fieldtriptoolbox.org/faq/why_does_my_tfr_look_strange_part_ii

It might be beneficial to demean and detrend before doing your frequency analysis.

Best,

Jim
From: fieldtrip-bounces at science.ru.nl [mailto:fieldtrip-bounces at science.ru.nl] On Behalf Of Jose
Sent: Monday, July 18, 2016 6:08 PM
To: fieldtrip at science.ru.nl
Subject: [FieldTrip] cluster-based permutation test - baseline correction

dear community,

I'm performing analysis of CTF MEG data. I have two conditions of interest: A and B, and I have performed spectral decomposition with the wavelet method to obtain the power (frequencies from 1 to 50 Hz). I would like to perform a cluster-based permutation test to assess if there are significant power differences between my two conditions of interest between the onset of my stimulus and 1 sec after,

While I understand the principles of cluster-based permutation test, with their distinct versions: between trials, within trials and within subjects, what I am interested in is to test differences between my two conditions in their baseline-corrected versions. Since I haven't seen this procedure in the tutorial, but it seems logic to me, I would like to verify the way to proceed is do baseline correction (for each condition and subject) and then run my cluster-permutation test. Is there anything else I should consider?

Also, since I haven't used 'demean' during my trial definition (I was advised not to do this), I was wondering if this could impact my baseline correction, and subsequent statistical analysis. I've seen some messages in the forum referring to this procedure,

Thanks in advance,
Jose
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160719/d657ce4d/attachment.htm>

From constantino.mendezbertolo at ctb.upm.es  Tue Jul 19 02:45:04 2016
From: constantino.mendezbertolo at ctb.upm.es (=?UTF-8?Q?Constantino_M=C3=A9ndez_B=C3=A9rtolo?=)
Date: Tue, 19 Jul 2016 02:45:04 +0200
Subject: [FieldTrip] QuickCap64 layout and PO8
Message-ID: <CA+OxHErEd4UGQHTDVanFLBo_TNz7aufc9nZLEFBk0UFNtA_uLQ@mail.gmail.com>

Dears,

Sorry if this is silly question or I am doing something wrong.
I have been handled EEG data recorded with a QuickCap64 electrode "helmet".
I had planned to apply QuickCap64.lay present at
/fieldtrip/templates/layouts since ~2012.
When I use "cfg = []; cfg.layout = 'QuickCap64.lay'; ft_layoutplot(cfg)" I
get the following picture (attached)
Seemingly there is no PO8 electrode.
If I explore the structure lay inside "quickcap64.lay" I see there IS PO8
though. I am also able to mulitplotER my data and everybody is there,
including PO8
I am using 20160607 version and this is the same with some 2014 version.
So the question is: *anyone thinks this will poss a problem further on the
analysis?* I think it may be only an "error" (or not that much) with the
visualization
Any ideas what I am doing wrong, or not seeing? (besides PO8 :)
Cheers,
T


​

-- 
Constantino Méndez-Bértolo
Laboratorio de Neurociencia Clínica, Centro de Tecnología Biomédica (CTB)

Parque Científico y Tecnológico de la UPM, Campus de Montegancedo

28223 Pozuelo de Alarcón, Madrid, SPAIN
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160719/57f213e5/attachment.htm>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: QuickCap64_pic.bmp
Type: image/bmp
Size: 2102754 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160719/57f213e5/attachment.bin>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: QuickCap64_pic.bmp
Type: image/bmp
Size: 2102754 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160719/57f213e5/attachment-0001.bin>

From stephen.politzer-ahles at ling-phil.ox.ac.uk  Tue Jul 19 11:16:06 2016
From: stephen.politzer-ahles at ling-phil.ox.ac.uk (Stephen Politzer-Ahles)
Date: Tue, 19 Jul 2016 10:16:06 +0100
Subject: [FieldTrip] 3x2 ANOVA using permutation tests?
Message-ID: <CAJT2k__YrMxx6nBQ_AUaCtOrXCJqHNfkQ6Mx3r8Eq=R0+3Qaag@mail.gmail.com>

Hi Anne,

I agree with Tineke. The best thing, I think, would be to calculate the
difference waves for each individual (essentially turning it into a
1-condition design with 3 groups) and then use indepsamplesT to compare the
three groups; this is conceptually the same as testing the group*condition
interaction; see
http://www.fieldtriptoolbox.org/faq/how_can_i_test_an_interaction_effect_using_cluster-based_permutation_tests.
I guess you could also test the main effect of group (by using the two
conditions' data and treating all subjects together as if they're one
group, to compare the two conditions across all subjects) or the main
effect of group (by getting the average, rather than the difference, of the
two conditions for each subject, and then comparing that across the three
groups), but I guess based on your design that the group*condition
interaction is probably the thing of primary interest.

best,
Steve



---
Stephen Politzer-Ahles
University of Oxford
Language and Brain Lab
Faculty of Linguistics, Phonetics & Philology
http://users.ox.ac.uk/~cpgl0080/


> Message: 2
> Date: Mon, 18 Jul 2016 12:54:30 +0000
> From: "Snijders, T.M. (Tineke)" <tineke.snijders at donders.ru.nl>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Subject: Re: [FieldTrip] 3x2 ANOVA using permutation tests?
> Message-ID:
>         <815A9820E75FBC4F96B7CD3A8089D11C378ED8B3 at exprd04.hosting.ru.nl>
> Content-Type: text/plain; charset="iso-8859-1"
>
> Hi Anne,
>
> To first do the analysis on separate groups, and then do an ANOVA on the
> resulting time-windows comparing the groups is double dipping.
>
> The simplest solution is to first do the cluster randomization test on all
> 3 groups together (i.e. treat them as 1 group), and compare the 2
> conditions (so just a depsamplesT).
> Based on this you get a time-window & electrodes that show a difference
> between conditions.
> You then extract the subject means from this time-window&electrodes
> (meaning you get one value per subject per condition), and use these in an
> ANOVA to compare the different groups, and to look at the effect of the
> behavioral regressor.
>
> Alternatively, you can use the difference scores (condition 2- condition
> 1) as an input for the cluster randomization, with the three groups as
> between-subject factor (indepsamplesF).
>
> Best,
>
> Tineke
>
>
>
> ________________________________
> From: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl]
> on behalf of Anne Mickan [amickan1990 at gmail.com]
> Sent: Monday, July 18, 2016 2:22 PM
> To: fieldtrip at science.ru.nl
> Subject: [FieldTrip] 3x2 ANOVA using permutation tests?
>
> Dear fieldtrip community,
>
> I've been using cluster-based permutation tests to analysis my EEG data in
> which I have 3 groups and 2 conditions each. Ultimately I want to know
> whether groups differ from each other with respect to differences in
> conditions. In a traditional analysis I would do an ANOVA on preselected
> time-windows, but I haven't been able to figure out how to properly do that
> within the permutation test.
>
> So far I simply did permutation tests for each of the groups separately.
> Then on the basis of these I choose windows for an ANOVA (and a regression
> analysis with some behavioral measures I acquired). Is that OK? Or is there
> a way to do the permutation tests for all groups together and add group as
> a between-subject factor (in addition to the within-subjects factor
> condition)? And would that be better / obligatory to do (instead of what I
> did so far).
>
> How do I need to change the cfg.design in order to do that?
>
> Thanks a lot in advance!
>
> Best,
> Anne
> -------------- next part --------------
> An HTML attachment was scrubbed...
> URL: <
> http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160718/7f208e09/attachment-0001.html
> >
>
>
>
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160719/e1225eaa/attachment.htm>

From gauthierb.ens at gmail.com  Wed Jul 20 11:49:50 2016
From: gauthierb.ens at gmail.com (Baptiste Gauthier)
Date: Wed, 20 Jul 2016 11:49:50 +0200
Subject: [FieldTrip] Regression test and t-test providing almost identical
	results
Message-ID: <CAGfUivx3kzjhzUXHYb5mYsr6VQ2OKWYvqCE=ciPo6vqW_jFDRQ@mail.gmail.com>

Dear Fieldtrippers,

I recently observed a strange behavior with the results provided with the
regression statistics provided by “ft_statfun_depsamplesregrT”:

I did a regression test on 3 conditions: cond1, cond2 and cond3:

Here are the results:


[image: Images intégrées 1]



*Output for group-level regression test:*

the call to "ft_timelockgrandaverage" took 36 seconds and required the
additional allocation of an estimated 0 MB
reading layout from file
/neurospin/meg/meg_tmp/MTT_MEG_Baptiste/From_laptop/fieldtrip-20130901/template/layout/NM306mag.lay
the call to "ft_prepare_layout" took 0 seconds and required the additional
allocation of an estimated 0 MB
the call to "ft_selectdata" took 0 seconds and required the additional
allocation of an estimated 0 MB
using "ft_statistics_montecarlo" for the statistical testing
using "ft_statfun_depsamplesregrT" for the single-sample statistics
constructing randomized design
total number of measurements     = 57
total number of variables        = 2
number of independent variables  = 1
number of unit variables         = 1
number of within-cell variables  = 0
number of control variables      = 0
using a permutation resampling approach
repeated measurement in variable 1 over 19 levels
number of repeated measurements in each level is 3 3 3 3 3 3 3 3 3 3 3 3 3
3 3 3 3 3 3
computing a parametric threshold for clustering
computing statistic
estimated time per randomization is 0.26 seconds
computing statistic 1000 from 1000

Warning: adding
/neurospin/meg/meg_tmp/MTT_MEG_Baptiste/fieldtrip-20160719/external/spm8
toolbox to your MATLAB path
found 13 positive clusters in observed data
found 9 negative clusters in observed data
computing clusters in randomization
computing clusters in randomization 1000 from 1000

using a cluster-based method for multiple comparison correction
the returned probabilities and the thresholded mask are corrected for
multiple comparisons
the call to "ft_timelockstatistics" took 55 seconds and required the
additional allocation of an estimated 12 MB



Afterwards, for some other reasons I performed directly a T-test between
condition 1 and condition 3. Here is the result:


[image: Images intégrées 2]


*Output for group-level T-test:*

the call to "ft_timelockgrandaverage" took 36 seconds and required the
additional allocation of an estimated 0 MB
reading layout from file
/neurospin/meg/meg_tmp/MTT_MEG_Baptiste/From_laptop/fieldtrip-20130901/template/layout/NM306mag.lay
the call to "ft_prepare_layout" took 0 seconds and required the additional
allocation of an estimated 0 MB
the call to "ft_selectdata" took 0 seconds and required the additional
allocation of an estimated 0 MB
using "ft_statistics_montecarlo" for the statistical testing
using "ft_statfun_depsamplesT" for the single-sample statistics
constructing randomized design
total number of measurements     = 38
total number of variables        = 2
number of independent variables  = 1
number of unit variables         = 1
number of within-cell variables  = 0
number of control variables      = 0
using a permutation resampling approach
repeated measurement in variable 1 over 19 levels
number of repeated measurements in each level is 2 2 2 2 2 2 2 2 2 2 2 2 2
2 2 2 2 2 2
computing a parametric threshold for clustering
computing statistic
estimated time per randomization is 0.04 seconds
computing statistic 1000 from 1000

found 9 positive clusters in observed data
found 13 negative clusters in observed data
computing clusters in randomization
computing clusters in randomization 1000 from 1000

using a cluster-based method for multiple comparison correction
the returned probabilities and the thresholded mask are corrected for
multiple comparisons
the call to "ft_timelockstatistics" took 46 seconds and required the
additional allocation of an estimated 0 MB



I checked that I actually provided the good data and parameters to the
function, but I am puzzled by the resemblance (if you invert the sign) of
the results. To doublecheck, I directly compared the stat.stat field from
the two tests. Here are the results:


[image: Images intégrées 3]


So basically, it is the same if you round to the 3rd digits after the
floating point. It sounds really weird to me.

Has someone ever noticed something similar when performing regression
tests? I there any simple mathematical tricks that could explain that?


Best regards,



Baptiste Gauthier, PhD

-- 
Baptiste Gauthier
Postdoctoral Research Fellow

INSERM-CEA Cognitive Neuroimaging unit
CEA/SAC/DSV/DRM/Neurospin center
Bât 145, Point Courier 156
F-91191 Gif-sur-Yvette Cedex FRANCE
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160720/dc2d72df/attachment.htm>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: image.png
Type: image/png
Size: 102935 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160720/dc2d72df/attachment.png>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: image.png
Type: image/png
Size: 87834 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160720/dc2d72df/attachment-0001.png>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: image.png
Type: image/png
Size: 30501 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160720/dc2d72df/attachment-0002.png>

From jan at brogger.no  Wed Jul 20 12:25:17 2016
From: jan at brogger.no (jan at brogger.no)
Date: Wed, 20 Jul 2016 12:25:17 +0200
Subject: [FieldTrip] Regression test and t-test providing almost
	identical results
Message-ID: <3047B000-8594-4A7B-B58F-A6541108D763@brogger.no>

That is because a t- test and a regression test are the same. See this link: http://stats.stackexchange.com/questions/59047/how-are-regression-the-t-test-and-the-anova-all-versions-of-the-general-linear

Yours,

Jan Brogger



From tineke.snijders at donders.ru.nl  Wed Jul 20 13:16:41 2016
From: tineke.snijders at donders.ru.nl (Snijders, T.M. (Tineke))
Date: Wed, 20 Jul 2016 11:16:41 +0000
Subject: [FieldTrip] Regression test and t-test providing almost
 identical results
Message-ID: <815A9820E75FBC4F96B7CD3A8089D11C49E75C7E@exprd04.hosting.ru.nl>

Hi Baptiste,

Indeed, as Jan points out, t-test and regression are all GLM.
You wonder what happened to the condition (cond 2) that you didn't use in the t-test:
In a regression with 3 conditions, the GLM 'contrasts' would be [-1 0 1] and [1 0 -1], so the 2nd condition is coded as ''0", meaning that without the 2nd condition the regression would also give exactly the same results...

Best,
Tineke

________________________________________
From: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl] on behalf of jan at brogger.no [jan at brogger.no]
Sent: Wednesday, July 20, 2016 12:25 PM
To: fieldtrip at science.ru.nl
Subject: Re: [FieldTrip] Regression test and t-test providing almost    identical results

That is because a t- test and a regression test are the same. See this link: http://stats.stackexchange.com/questions/59047/how-are-regression-the-t-test-and-the-anova-all-versions-of-the-general-linear

Yours,

Jan Brogger

_______________________________________________
fieldtrip mailing list


________________________________
From: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl] on behalf of Baptiste Gauthier [gauthierb.ens at gmail.com]
Sent: Wednesday, July 20, 2016 11:49 AM
To: fieldtrip at science.ru.nl
Subject: [FieldTrip] Regression test and t-test providing almost identical results

Dear Fieldtrippers,
I recently observed a strange behavior with the results provided with the regression statistics provided by “ft_statfun_depsamplesregrT”:
I did a regression test on 3 conditions: cond1, cond2 and cond3:
Here are the results:

[Images intégrées 1]

Output for group-level regression test:
the call to "ft_timelockgrandaverage" took 36 seconds and required the additional allocation of an estimated 0 MB
reading layout from file /neurospin/meg/meg_tmp/MTT_MEG_Baptiste/From_laptop/fieldtrip-20130901/template/layout/NM306mag.lay
the call to "ft_prepare_layout" took 0 seconds and required the additional allocation of an estimated 0 MB
the call to "ft_selectdata" took 0 seconds and required the additional allocation of an estimated 0 MB
using "ft_statistics_montecarlo" for the statistical testing
using "ft_statfun_depsamplesregrT" for the single-sample statistics
constructing randomized design
total number of measurements     = 57
total number of variables        = 2
number of independent variables  = 1
number of unit variables         = 1
number of within-cell variables  = 0
number of control variables      = 0
using a permutation resampling approach
repeated measurement in variable 1 over 19 levels
number of repeated measurements in each level is 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
computing a parametric threshold for clustering
computing statistic
estimated time per randomization is 0.26 seconds
computing statistic 1000 from 1000

Warning: adding /neurospin/meg/meg_tmp/MTT_MEG_Baptiste/fieldtrip-20160719/external/spm8 toolbox to your MATLAB path
found 13 positive clusters in observed data
found 9 negative clusters in observed data
computing clusters in randomization
computing clusters in randomization 1000 from 1000

using a cluster-based method for multiple comparison correction
the returned probabilities and the thresholded mask are corrected for multiple comparisons
the call to "ft_timelockstatistics" took 55 seconds and required the additional allocation of an estimated 12 MB

Afterwards, for some other reasons I performed directly a T-test between condition 1 and condition 3. Here is the result:

[Images intégrées 2]

Output for group-level T-test:
the call to "ft_timelockgrandaverage" took 36 seconds and required the additional allocation of an estimated 0 MB
reading layout from file /neurospin/meg/meg_tmp/MTT_MEG_Baptiste/From_laptop/fieldtrip-20130901/template/layout/NM306mag.lay
the call to "ft_prepare_layout" took 0 seconds and required the additional allocation of an estimated 0 MB
the call to "ft_selectdata" took 0 seconds and required the additional allocation of an estimated 0 MB
using "ft_statistics_montecarlo" for the statistical testing
using "ft_statfun_depsamplesT" for the single-sample statistics
constructing randomized design
total number of measurements     = 38
total number of variables        = 2
number of independent variables  = 1
number of unit variables         = 1
number of within-cell variables  = 0
number of control variables      = 0
using a permutation resampling approach
repeated measurement in variable 1 over 19 levels
number of repeated measurements in each level is 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
computing a parametric threshold for clustering
computing statistic
estimated time per randomization is 0.04 seconds
computing statistic 1000 from 1000

found 9 positive clusters in observed data
found 13 negative clusters in observed data
computing clusters in randomization
computing clusters in randomization 1000 from 1000

using a cluster-based method for multiple comparison correction
the returned probabilities and the thresholded mask are corrected for multiple comparisons
the call to "ft_timelockstatistics" took 46 seconds and required the additional allocation of an estimated 0 MB


I checked that I actually provided the good data and parameters to the function, but I am puzzled by the resemblance (if you invert the sign) of the results. To doublecheck, I directly compared the stat.stat field from the two tests. Here are the results:

[Images intégrées 3]

So basically, it is the same if you round to the 3rd digits after the floating point. It sounds really weird to me.
Has someone ever noticed something similar when performing regression tests? I there any simple mathematical tricks that could explain that?

Best regards,

Baptiste Gauthier, PhD

--
Baptiste Gauthier
Postdoctoral Research Fellow

INSERM-CEA Cognitive Neuroimaging unit
CEA/SAC/DSV/DRM/Neurospin center
Bât 145, Point Courier 156
F-91191 Gif-sur-Yvette Cedex FRANCE
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160720/749f1950/attachment.htm>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: image.png
Type: image/png
Size: 102935 bytes
Desc: image.png
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160720/749f1950/attachment.png>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: image.png
Type: image/png
Size: 87834 bytes
Desc: image.png
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160720/749f1950/attachment-0001.png>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: image.png
Type: image/png
Size: 30501 bytes
Desc: image.png
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160720/749f1950/attachment-0002.png>

From e.maris at donders.ru.nl  Wed Jul 20 13:25:29 2016
From: e.maris at donders.ru.nl (Maris, E.G.G. (Eric))
Date: Wed, 20 Jul 2016 11:25:29 +0000
Subject: [FieldTrip] fieldtrip Digest, Vol 68, Issue 18
In-Reply-To: <mailman.127.1469013404.5164.fieldtrip@science.ru.nl>
References: <mailman.127.1469013404.5164.fieldtrip@science.ru.nl>
Message-ID: <F575376E-78D0-4601-A8F3-7BDEBA5FE60F@donders.ru.nl>

Hi Baptiste & Tineke,


Hi Baptiste,

Indeed, as Jan points out, t-test and regression are all GLM.
You wonder what happened to the condition (cond 2) that you didn't use in the t-test:
In a regression with 3 conditions, the GLM 'contrasts' would be [-1 0 1] and [1 0 -1], so the 2nd condition is coded as ''0", meaning that without the 2nd condition the regression would also give exactly the same results...

Best,
Tineke


Is there a typo here, Tineke? The two contrast that you list are actually one and the same. There are multiple ways to specify the contrasts, and this is one way: [-1 1 0] and [0 -1 1].

Baptiste, what is your independent variable? This should be a quantitative variable (e.g., memory load) that varies over the three within-subjects conditions. Could you show your cfg.design? This would allow others to help you better.

Btw, I may not reply to next post. I’m about to leave for vacation.

best,
Eric Maris







________________________________________
From: fieldtrip-bounces at science.ru.nl<mailto:fieldtrip-bounces at science.ru.nl> [fieldtrip-bounces at science.ru.nl<mailto:fieldtrip-bounces at science.ru.nl>] on behalf of jan at brogger.no<mailto:jan at brogger.no> [jan at brogger.no<mailto:jan at brogger.no>]
Sent: Wednesday, July 20, 2016 12:25 PM
To: fieldtrip at science.ru.nl<mailto:fieldtrip at science.ru.nl>
Subject: Re: [FieldTrip] Regression test and t-test providing almost    identical results

That is because a t- test and a regression test are the same. See this link: http://stats.stackexchange.com/questions/59047/how-are-regression-the-t-test-and-the-anova-all-versions-of-the-general-linear

Yours,

Jan Brogger

_______________________________________________
fieldtrip mailing list


________________________________
From: fieldtrip-bounces at science.ru.nl<mailto:fieldtrip-bounces at science.ru.nl> [fieldtrip-bounces at science.ru.nl<mailto:fieldtrip-bounces at science.ru.nl>] on behalf of Baptiste Gauthier [gauthierb.ens at gmail.com<mailto:gauthierb.ens at gmail.com>]
Sent: Wednesday, July 20, 2016 11:49 AM
To: fieldtrip at science.ru.nl<mailto:fieldtrip at science.ru.nl>
Subject: [FieldTrip] Regression test and t-test providing almost identical results

Dear Fieldtrippers,
I recently observed a strange behavior with the results provided with the regression statistics provided by “ft_statfun_depsamplesregrT”:
I did a regression test on 3 conditions: cond1, cond2 and cond3:
Here are the results:

<image.png>


Output for group-level regression test:
the call to "ft_timelockgrandaverage" took 36 seconds and required the additional allocation of an estimated 0 MB
reading layout from file /neurospin/meg/meg_tmp/MTT_MEG_Baptiste/From_laptop/fieldtrip-20130901/template/layout/NM306mag.lay
the call to "ft_prepare_layout" took 0 seconds and required the additional allocation of an estimated 0 MB
the call to "ft_selectdata" took 0 seconds and required the additional allocation of an estimated 0 MB
using "ft_statistics_montecarlo" for the statistical testing
using "ft_statfun_depsamplesregrT" for the single-sample statistics
constructing randomized design
total number of measurements     = 57
total number of variables        = 2
number of independent variables  = 1
number of unit variables         = 1
number of within-cell variables  = 0
number of control variables      = 0
using a permutation resampling approach
repeated measurement in variable 1 over 19 levels
number of repeated measurements in each level is 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3
computing a parametric threshold for clustering
computing statistic
estimated time per randomization is 0.26 seconds
computing statistic 1000 from 1000

Warning: adding /neurospin/meg/meg_tmp/MTT_MEG_Baptiste/fieldtrip-20160719/external/spm8 toolbox to your MATLAB path
found 13 positive clusters in observed data
found 9 negative clusters in observed data
computing clusters in randomization
computing clusters in randomization 1000 from 1000

using a cluster-based method for multiple comparison correction
the returned probabilities and the thresholded mask are corrected for multiple comparisons
the call to "ft_timelockstatistics" took 55 seconds and required the additional allocation of an estimated 12 MB

Afterwards, for some other reasons I performed directly a T-test between condition 1 and condition 3. Here is the result:

<image.png>


Output for group-level T-test:
the call to "ft_timelockgrandaverage" took 36 seconds and required the additional allocation of an estimated 0 MB
reading layout from file /neurospin/meg/meg_tmp/MTT_MEG_Baptiste/From_laptop/fieldtrip-20130901/template/layout/NM306mag.lay
the call to "ft_prepare_layout" took 0 seconds and required the additional allocation of an estimated 0 MB
the call to "ft_selectdata" took 0 seconds and required the additional allocation of an estimated 0 MB
using "ft_statistics_montecarlo" for the statistical testing
using "ft_statfun_depsamplesT" for the single-sample statistics
constructing randomized design
total number of measurements     = 38
total number of variables        = 2
number of independent variables  = 1
number of unit variables         = 1
number of within-cell variables  = 0
number of control variables      = 0
using a permutation resampling approach
repeated measurement in variable 1 over 19 levels
number of repeated measurements in each level is 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
computing a parametric threshold for clustering
computing statistic
estimated time per randomization is 0.04 seconds
computing statistic 1000 from 1000

found 9 positive clusters in observed data
found 13 negative clusters in observed data
computing clusters in randomization
computing clusters in randomization 1000 from 1000

using a cluster-based method for multiple comparison correction
the returned probabilities and the thresholded mask are corrected for multiple comparisons
the call to "ft_timelockstatistics" took 46 seconds and required the additional allocation of an estimated 0 MB


I checked that I actually provided the good data and parameters to the function, but I am puzzled by the resemblance (if you invert the sign) of the results. To doublecheck, I directly compared the stat.stat field from the two tests. Here are the results:

<image.png>


So basically, it is the same if you round to the 3rd digits after the floating point. It sounds really weird to me.
Has someone ever noticed something similar when performing regression tests? I there any simple mathematical tricks that could explain that?

Best regards,

Baptiste Gauthier, PhD

--
Baptiste Gauthier
Postdoctoral Research Fellow

INSERM-CEA Cognitive Neuroimaging unit
CEA/SAC/DSV/DRM/Neurospin center
Bât 145, Point Courier 156
F-91191 Gif-sur-Yvette Cedex FRANCE


_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160720/c47af115/attachment.htm>

From ruil3 at student.unimelb.edu.au  Wed Jul 20 14:12:31 2016
From: ruil3 at student.unimelb.edu.au (Rui Li)
Date: Wed, 20 Jul 2016 22:12:31 +1000
Subject: [FieldTrip] Kurtosis topography at sensor level
Message-ID: <CALeb_wxe3EdXk4j37fyvZa-uBUwzojPvVgdx=+3Y296YHOvHEw@mail.gmail.com>

Dear FieldTrip users,

Recently, I am working on the case 1 dataset of epilepsy tutorial. The
first patient got the MEG recording from Neuromag and CTF, respectively. I
encountered some problems when I tried to depict the Kurtosis topography at
 channel - level.


*Question 1:* why and how does the filter affect the kurtosis?

Figure 1 and Figure 2 are kurtosis topographies at channel level without
band pass filter and with band pass filter, respectively. As we can see,
these two figures are very different. Therefore, I am wondering why and how
does the frequency filter affect the kurtosis?

The figure 1 is generated by the following program;

%% preporcessing the channel level data

dataset = 'case1.ds';

cfg = [];

cfg.dataset   = dataset;

% cfg.hpfilter  = 'yes';

% cfg.hpfreq    = 10;

% cfg.lpfilter  = 'yes';

% cfg.lpfreq    = 70;

cfg.channel   = {'MEG'};

data = ft_preprocessing(cfg);



%% compute channel-level kurtosis



datak = [];

datak.label    = data.label;

datak.dimord   = 'chan';

datak.kurtosis = kurtosis(data.trial{1}')';



cfg = [];

cfg.comment = 'computed channel-level kurtosis';

datak = ft_annotate(cfg, datak);



%% plot kurtosis topography at channel-level



cfg = [];

cfg.layout    = 'CTF275.lay';

cfg.parameter = 'kurtosis';



figure;

ft_topoplotER(cfg, datak);


​

Figure 1 kurtosis topography + no filter + case1.ds

If the band pass filter is included in the pre-processing, the kurtosis
topography is figure 2; the pre-processing matlab program is

%% preporcessing the channel level data

dataset = 'case1.ds';

cfg = [];

cfg.dataset   = dataset;

cfg.hpfilter  = 'yes';

cfg.hpfreq    = 10;

cfg.lpfilter  = 'yes';

cfg.lpfreq    = 70;

cfg.channel   = {'MEG'};

data = ft_preprocessing(cfg);



Figure 2 kurtosis topography +  [10Hz 70Hz] filter + case1.ds

*Question 2:* Why the kurtosis topographies at channel level from two
dataset case1.ds (figure 1 (no filter), figure 2 (filtered)) and
case1_cHPI_raw_trans_sss.fif (figure 3 (no filter) and figure 4 (filtered))
are not consistent? Because these two datasets are measured from the same
patient, the kurtosis topography should be consistent. Do you have any idea
about this?


​

Figure 3 kurtosis topography + no filter + case1_cHPI_raw_trans_sss.fif


​

Figure 4 kurtosis topography + [10Hz 70Hz] filter +
case1_cHPI_raw_trans_sss.fif

Regards,

Rui.
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160720/062ddcd6/attachment.htm>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: 2.png
Type: image/png
Size: 40708 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160720/062ddcd6/attachment.png>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: 1.png
Type: image/png
Size: 52589 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160720/062ddcd6/attachment-0001.png>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: 3.png
Type: image/png
Size: 72472 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160720/062ddcd6/attachment-0002.png>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: 4.png
Type: image/png
Size: 23855 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160720/062ddcd6/attachment-0003.png>

From gauthierb.ens at gmail.com  Wed Jul 20 15:19:40 2016
From: gauthierb.ens at gmail.com (Baptiste Gauthier)
Date: Wed, 20 Jul 2016 15:19:40 +0200
Subject: [FieldTrip] Regression test and t-test providing almost
	identical results
In-Reply-To: <815A9820E75FBC4F96B7CD3A8089D11C49E75C7E@exprd04.hosting.ru.nl>
References: <815A9820E75FBC4F96B7CD3A8089D11C49E75C7E@exprd04.hosting.ru.nl>
Message-ID: <CAGfUivw9p3jG=qYN50HFAHKoMZHDUcZHeVjHLw9MrG1uCkm2Lg@mail.gmail.com>

Thank you for your quick answers!

This is very clear now. i'm familiar with GLM as I use it in fMRI but I did
not thought my question in term of contrast.

So, to test for a linear ordering between cond3,cond2 and cond1, would it
be reasonable to compute a regression beta for each subject and then
compare it to zero with a group t-test? (as it would use the data of
condition 2).

thanks again and best regards

2016-07-20 13:16 GMT+02:00 Snijders, T.M. (Tineke) <
tineke.snijders at donders.ru.nl>:

> Hi Baptiste,
>
> Indeed, as Jan points out, t-test and regression are all GLM.
> You wonder what happened to the condition (cond 2) that you didn't use in
> the t-test:
> In a regression with 3 conditions, the GLM 'contrasts' would be [-1 0 1]
> and [1 0 -1], so the 2nd condition is coded as ''0", meaning that without
> the 2nd condition the regression would also give exactly the same results...
>
> Best,
> Tineke
>
> ________________________________________
> From: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl]
> on behalf of jan at brogger.no [jan at brogger.no]
> Sent: Wednesday, July 20, 2016 12:25 PM
> To: fieldtrip at science.ru.nl
> Subject: Re: [FieldTrip] Regression test and t-test providing almost
>  identical results
>
> That is because a t- test and a regression test are the same. See this
> link:
> http://stats.stackexchange.com/questions/59047/how-are-regression-the-t-test-and-the-anova-all-versions-of-the-general-linear
>
> Yours,
>
> Jan Brogger
>
> _______________________________________________
> fieldtrip mailing list
>
>
> ------------------------------
> *From:* fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl]
> on behalf of Baptiste Gauthier [gauthierb.ens at gmail.com]
> *Sent:* Wednesday, July 20, 2016 11:49 AM
> *To:* fieldtrip at science.ru.nl
> *Subject:* [FieldTrip] Regression test and t-test providing almost
> identical results
>
> Dear Fieldtrippers,
>
> I recently observed a strange behavior with the results provided with the
> regression statistics provided by “ft_statfun_depsamplesregrT”:
>
> I did a regression test on 3 conditions: cond1, cond2 and cond3:
>
> Here are the results:
>
>
> [image: Images intégrées 1]
>
>
>
> *Output for group-level regression test:*
>
> the call to "ft_timelockgrandaverage" took 36 seconds and required the
> additional allocation of an estimated 0 MB
> reading layout from file
> /neurospin/meg/meg_tmp/MTT_MEG_Baptiste/From_laptop/fieldtrip-20130901/template/layout/NM306mag.lay
> the call to "ft_prepare_layout" took 0 seconds and required the additional
> allocation of an estimated 0 MB
> the call to "ft_selectdata" took 0 seconds and required the additional
> allocation of an estimated 0 MB
> using "ft_statistics_montecarlo" for the statistical testing
> using "ft_statfun_depsamplesregrT" for the single-sample statistics
> constructing randomized design
> total number of measurements     = 57
> total number of variables        = 2
> number of independent variables  = 1
> number of unit variables         = 1
> number of within-cell variables  = 0
> number of control variables      = 0
> using a permutation resampling approach
> repeated measurement in variable 1 over 19 levels
> number of repeated measurements in each level is 3 3 3 3 3 3 3 3 3 3 3 3 3
> 3 3 3 3 3 3
> computing a parametric threshold for clustering
> computing statistic
> estimated time per randomization is 0.26 seconds
> computing statistic 1000 from 1000
>
> Warning: adding
> /neurospin/meg/meg_tmp/MTT_MEG_Baptiste/fieldtrip-20160719/external/spm8
> toolbox to your MATLAB path
> found 13 positive clusters in observed data
> found 9 negative clusters in observed data
> computing clusters in randomization
> computing clusters in randomization 1000 from 1000
>
> using a cluster-based method for multiple comparison correction
> the returned probabilities and the thresholded mask are corrected for
> multiple comparisons
> the call to "ft_timelockstatistics" took 55 seconds and required the
> additional allocation of an estimated 12 MB
>
>
>
> Afterwards, for some other reasons I performed directly a T-test between
> condition 1 and condition 3. Here is the result:
>
>
> [image: Images intégrées 2]
>
>
> *Output for group-level T-test:*
>
> the call to "ft_timelockgrandaverage" took 36 seconds and required the
> additional allocation of an estimated 0 MB
> reading layout from file
> /neurospin/meg/meg_tmp/MTT_MEG_Baptiste/From_laptop/fieldtrip-20130901/template/layout/NM306mag.lay
> the call to "ft_prepare_layout" took 0 seconds and required the additional
> allocation of an estimated 0 MB
> the call to "ft_selectdata" took 0 seconds and required the additional
> allocation of an estimated 0 MB
> using "ft_statistics_montecarlo" for the statistical testing
> using "ft_statfun_depsamplesT" for the single-sample statistics
> constructing randomized design
> total number of measurements     = 38
> total number of variables        = 2
> number of independent variables  = 1
> number of unit variables         = 1
> number of within-cell variables  = 0
> number of control variables      = 0
> using a permutation resampling approach
> repeated measurement in variable 1 over 19 levels
> number of repeated measurements in each level is 2 2 2 2 2 2 2 2 2 2 2 2 2
> 2 2 2 2 2 2
> computing a parametric threshold for clustering
> computing statistic
> estimated time per randomization is 0.04 seconds
> computing statistic 1000 from 1000
>
> found 9 positive clusters in observed data
> found 13 negative clusters in observed data
> computing clusters in randomization
> computing clusters in randomization 1000 from 1000
>
> using a cluster-based method for multiple comparison correction
> the returned probabilities and the thresholded mask are corrected for
> multiple comparisons
> the call to "ft_timelockstatistics" took 46 seconds and required the
> additional allocation of an estimated 0 MB
>
>
>
> I checked that I actually provided the good data and parameters to the
> function, but I am puzzled by the resemblance (if you invert the sign) of
> the results. To doublecheck, I directly compared the stat.stat field from
> the two tests. Here are the results:
>
>
> [image: Images intégrées 3]
>
>
> So basically, it is the same if you round to the 3rd digits after the
> floating point. It sounds really weird to me.
>
> Has someone ever noticed something similar when performing regression
> tests? I there any simple mathematical tricks that could explain that?
>
>
> Best regards,
>
>
>
> Baptiste Gauthier, PhD
>
> --
> Baptiste Gauthier
> Postdoctoral Research Fellow
>
> INSERM-CEA Cognitive Neuroimaging unit
> CEA/SAC/DSV/DRM/Neurospin center
> Bât 145, Point Courier 156
> F-91191 Gif-sur-Yvette Cedex FRANCE
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>



-- 
Baptiste Gauthier
Postdoctoral Research Fellow

INSERM-CEA Cognitive Neuroimaging unit
CEA/SAC/DSV/DRM/Neurospin center
Bât 145, Point Courier 156
F-91191 Gif-sur-Yvette Cedex FRANCE
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160720/7880f2d0/attachment.htm>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: image.png
Type: image/png
Size: 102935 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160720/7880f2d0/attachment.png>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: image.png
Type: image/png
Size: 30501 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160720/7880f2d0/attachment-0001.png>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: image.png
Type: image/png
Size: 87834 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160720/7880f2d0/attachment-0002.png>

From roycox.roycox at gmail.com  Thu Jul 21 04:08:34 2016
From: roycox.roycox at gmail.com (Roy Cox)
Date: Wed, 20 Jul 2016 22:08:34 -0400
Subject: [FieldTrip] Fwd: postdoctoral position on sleep and memory
In-Reply-To: <CABafTZeQyaEwSthp1JupLW8kirdhh-nYtHh5sDAi645meOaSjA@mail.gmail.com>
References: <CABafTZeQyaEwSthp1JupLW8kirdhh-nYtHh5sDAi645meOaSjA@mail.gmail.com>
Message-ID: <CABafTZcGDtTKwXaBrHfcWt7Njhh=VswS+gGAJ0b=1SHR6nV_Hw@mail.gmail.com>

hi all,

See attachment for a postdoctoral position in the lab of Dara Manoach
(Martinos Center for Biomedical Imaging and the Psychiatric Neuroimaging
Division of the Psychiatry Department at Massachusetts General Hospital) on
the role of sleep in memory consolidation in healthy and clinical
populations.

Please do NOT contact me for additional information, but contact the PI
directly.

Roy
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160720/34201c3e/attachment.htm>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: SLEEP_Postdoc_2016.docx
Type: application/vnd.openxmlformats-officedocument.wordprocessingml.document
Size: 116578 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160720/34201c3e/attachment.docx>

From ruil3 at student.unimelb.edu.au  Thu Jul 21 08:14:47 2016
From: ruil3 at student.unimelb.edu.au (Rui Li)
Date: Thu, 21 Jul 2016 16:14:47 +1000
Subject: [FieldTrip]  Kurtosis topography at channel level
Message-ID: <CALeb_wz60=fBuWgsiA7Oj6a4P8fvSZPGcnsrB895TgOxfnfYwA@mail.gmail.com>

Dear FieldTrip users,

Recently, I am working on the case 1 dataset of epilepsy tutorial. The
first patient got the MEG recording from Neuromag and CTF, respectively. I
encountered some problems when I tried to depict the Kurtosis topography
at channel - level.


*Question 1:* why and how does the filter affect the kurtosis?

Figure 1 and Figure 2 are kurtosis topographies at channel level without
band pass filter and with band pass filter, respectively. As we can see,
these two figures are very different. Therefore, I am wondering why and how
does the frequency filter affect the kurtosis?

The figure 1 is generated by the following program;

%% preporcessing the channel level data

dataset = 'case1.ds';

cfg = [];

cfg.dataset   = dataset;

% cfg.hpfilter  = 'yes';

% cfg.hpfreq    = 10;

% cfg.lpfilter  = 'yes';

% cfg.lpfreq    = 70;

cfg.channel   = {'MEG'};

data = ft_preprocessing(cfg);



%% compute channel-level kurtosis



datak = [];

datak.label    = data.label;

datak.dimord   = 'chan';

datak.kurtosis = kurtosis(data.trial{1}')';



cfg = [];

cfg.comment = 'computed channel-level kurtosis';

datak = ft_annotate(cfg, datak);



%% plot kurtosis topography at channel-level



cfg = [];

cfg.layout    = 'CTF275.lay';

cfg.parameter = 'kurtosis';



figure;

ft_topoplotER(cfg, datak);


​

Figure 1 kurtosis topography + no filter + case1.ds

If the band pass filter is included in the pre-processing, the kurtosis
topography is figure 2; the pre-processing matlab program is

%% preporcessing the channel level data

dataset = 'case1.ds';

cfg = [];

cfg.dataset   = dataset;

cfg.hpfilter  = 'yes';

cfg.hpfreq    = 10;

cfg.lpfilter  = 'yes';

cfg.lpfreq    = 70;

cfg.channel   = {'MEG'};

data = ft_preprocessing(cfg);



Figure 2 kurtosis topography +  [10Hz 70Hz] filter + case1.ds

*Question 2:* Why the kurtosis topographies at channel level from two
dataset case1.ds (figure 1 (no filter), figure 2 (filtered)) and
case1_cHPI_raw_trans_sss.fif (figure 3 (no filter) and figure 4 (filtered))
are not consistent? Because these two datasets are measured from the same
patient, the kurtosis topography should be consistent. Do you have any idea
about this?


​

Figure 3 kurtosis topography + no filter + case1_cHPI_raw_trans_sss.fif


​

Figure 4 kurtosis topography + [10Hz 70Hz] filter +
case1_cHPI_raw_trans_sss.fif

Regards,

Rui.
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160721/39beecaa/attachment.htm>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: 4.png
Type: image/png
Size: 23855 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160721/39beecaa/attachment.png>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: 1.png
Type: image/png
Size: 52589 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160721/39beecaa/attachment-0001.png>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: 2.png
Type: image/png
Size: 40708 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160721/39beecaa/attachment-0002.png>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: 3.png
Type: image/png
Size: 72472 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160721/39beecaa/attachment-0003.png>

From f.neugebauer at uni-muenster.de  Thu Jul 21 10:48:36 2016
From: f.neugebauer at uni-muenster.de (Frank Neugebauer)
Date: Thu, 21 Jul 2016 10:48:36 +0200 (CEST)
Subject: [FieldTrip] Kurtosis topography at channel level
In-Reply-To: <CALeb_wz60=fBuWgsiA7Oj6a4P8fvSZPGcnsrB895TgOxfnfYwA@mail.gmail.com>
Message-ID: <permail-201607210848365b97421400005aab-f_neug02@message-id.uni-muenster.de>

Hi Rui,

*Question 1:* why and how does the filter affect the kurtosis?

As kurtosis is not linear, that is kurtosis(data+noise)=/=kurtosis(data)+kurtosis(noise), it is a little hard to say how exactly changing your data will change the output kurtosis.
If you filter Gaussian noise the signal should form stronger outlier and thus the data should yield higher kurtosis.
As far as I understand kurtosis, the frequency itself does not directly influence the kurtosis output.


*Question 2:* Why the kurtosis topographies at channel level from two
> dataset case1.ds (figure 1 (no filter), figure 2 (filtered)) and
> case1_cHPI_raw_trans_sss.fif (figure 3 (no filter) and figure 4 (filtered))
> are not consistent? Because these two datasets are measured from the same
> patient, the kurtosis topography should be consistent. Do you have any idea
> about this?


As far as I understand, epileptic activity is hard to measure because you don't know when it will occur and different measurements are not inconsistent, but just show different activity at a different time and circumstance (such as different sensor noise, interference, but also the patient's condition).
In the introduction to the case they say,
>> Corticography also showed interictal discharges in the frontal lobe, though seizures were of parietal origin. <<. Maybe this is the explanation? The kurtosis points to the frontal lobe, too.

I hope this was a little helpful,
best regards,
Frank


Rui Li wrote on 2016-07-21:
> Dear FieldTrip users,

> Recently, I am working on the case 1 dataset of epilepsy tutorial. The
> first patient got the MEG recording from Neuromag and CTF, respectively. I
> encountered some problems when I tried to depict the Kurtosis topography
> at channel - level.


> *Question 1:* why and how does the filter affect the kurtosis?

> Figure 1 and Figure 2 are kurtosis topographies at channel level without
> band pass filter and with band pass filter, respectively. As we can see,
> these two figures are very different. Therefore, I am wondering why and how
> does the frequency filter affect the kurtosis?

> The figure 1 is generated by the following program;

> %% preporcessing the channel level data

> dataset = 'case1.ds';

> cfg = [];

> cfg.dataset = dataset;

> % cfg.hpfilter = 'yes';

> % cfg.hpfreq = 10;

> % cfg.lpfilter = 'yes';

> % cfg.lpfreq = 70;

> cfg.channel = {'MEG'};

> data = ft_preprocessing(cfg);



> %% compute channel-level kurtosis



> datak = [];

> datak.label = data.label;

> datak.dimord = 'chan';

> datak.kurtosis = kurtosis(data.trial{1}')';



> cfg = [];

> cfg.comment = 'computed channel-level kurtosis';

> datak = ft_annotate(cfg, datak);



> %% plot kurtosis topography at channel-level



> cfg = [];

> cfg.layout = 'CTF275.lay';

> cfg.parameter = 'kurtosis';



> figure;

> ft_topoplotER(cfg, datak);


> ​

> Figure 1 kurtosis topography + no filter + case1.ds

> If the band pass filter is included in the pre-processing, the kurtosis
> topography is figure 2; the pre-processing matlab program is

> %% preporcessing the channel level data

> dataset = 'case1.ds';

> cfg = [];

> cfg.dataset = dataset;

> cfg.hpfilter = 'yes';

> cfg.hpfreq = 10;

> cfg.lpfilter = 'yes';

> cfg.lpfreq = 70;

> cfg.channel = {'MEG'};

> data = ft_preprocessing(cfg);



> Figure 2 kurtosis topography + [10Hz 70Hz] filter + case1.ds

> *Question 2:* Why the kurtosis topographies at channel level from two
> dataset case1.ds (figure 1 (no filter), figure 2 (filtered)) and
> case1_cHPI_raw_trans_sss.fif (figure 3 (no filter) and figure 4 (filtered))
> are not consistent? Because these two datasets are measured from the same
> patient, the kurtosis topography should be consistent. Do you have any idea
> about this?


> ​

> Figure 3 kurtosis topography + no filter + case1_cHPI_raw_trans_sss.fif


> ​

> Figure 4 kurtosis topography + [10Hz 70Hz] filter +
> case1_cHPI_raw_trans_sss.fif

> Regards,

> Rui.



From seymourr at aston.ac.uk  Thu Jul 21 17:06:06 2016
From: seymourr at aston.ac.uk (Seymour, Robert (Research Student))
Date: Thu, 21 Jul 2016 15:06:06 +0000
Subject: [FieldTrip] Compensation for maxfilter in source analysis?
Message-ID: <AM4PR0101MB21802E94EAE7CD6240A8A68099090@AM4PR0101MB2180.eurprd01.prod.exchangelabs.com>

Hi Peter,

Would also be interested in the answer to your first question - it is not clear how Fieldtrip combines MAGS+GRADS using ft_sourceanalysis/ft_prepareleadfield.

For your second question I don't think there is a 'right' answer & it depends how aggressively you've Maxfiltered... as a rule of thumb, this is the code I use:

cfg = [];
cfg.method = 'pca';
cfg.updatesens = 'no';
cfg.channel = 'MEGMAG';
comp = ft_componentanalysis(cfg, data);

cfg = [];
cfg.updatesens = 'no';
cfg.component = comp.label(51:end);
data_fix = ft_rejectcomponent(cfg, comp);

Cheers,

Robert Seymour (PhD Student, Aston Brain Centre)
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160721/f9b39e7a/attachment.htm>

From seymourr at aston.ac.uk  Thu Jul 21 17:19:22 2016
From: seymourr at aston.ac.uk (Seymour, Robert (Research Student))
Date: Thu, 21 Jul 2016 15:19:22 +0000
Subject: [FieldTrip] Conte69 Atlas-Based Source Localisation
Message-ID: <AM4PR0101MB21807DADC0ABE7DA30420BA999090@AM4PR0101MB2180.eurprd01.prod.exchangelabs.com>

Dear Fieldtrip Forum,


I'd just like to pick up from an old thread posted to the FT forum: https://mailman.science.ru.nl/pipermail/fieldtrip/2015-October/009682.html. Basically, I am trying to perform source localisation using regions within an atlas described on the Conte69 brain http://brainvis.wustl.edu/wiki/index.php//Caret:Atlases/Conte69_Atlas.


I have run the standard Freesurfer pipeline on my MRIs (in head co-ordinate system), converted the output to the Conte69 atlas using "freesurfer_to_fs_LR" pipeline, and finally down-sampled the mesh using the helpful instructions from the above thread, combined with MNE function: mne_setup_source_space --ico -6 .


So to my questions:


i) How do I map from the atlas vertices (on the 327684 vertex Conte69 brain) to the downsampled mesh with 4096 vertices per hemisphere? I feel it has something to do with the deformation maps...


ii) How to I align everything in the head co-ordinate system (appreciate this is a bit of a general question)?


Many thanks,


Robert Seymour (PhD Student, Aston Brain Centre)

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160721/53fd25f7/attachment.htm>

From jan.schoffelen at donders.ru.nl  Thu Jul 21 17:33:44 2016
From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs))
Date: Thu, 21 Jul 2016 15:33:44 +0000
Subject: [FieldTrip] Conte69 Atlas-Based Source Localisation
In-Reply-To: <AM4PR0101MB21807DADC0ABE7DA30420BA999090@AM4PR0101MB2180.eurprd01.prod.exchangelabs.com>
References: <AM4PR0101MB21807DADC0ABE7DA30420BA999090@AM4PR0101MB2180.eurprd01.prod.exchangelabs.com>
Message-ID: <FB00DD05-6A12-4D4E-951A-BA38FD81A620@donders.ru.nl>

Hi Robert,

If you process the cortical sheet that is shipped with the Conte69 atlas, i.e. pass it through freesurfer_to_fs_LR, and then through mne_setup_source_space, you’ll get a topologically valid low-resolution parcellation, which you could use with your individual source models. Each of the vertices is surface-registered by construction.

Best,
Jan-Mathijs

On 21 Jul 2016, at 17:19, Seymour, Robert (Research Student) <seymourr at aston.ac.uk<mailto:seymourr at aston.ac.uk>> wrote:

Dear Fieldtrip Forum,

I'd just like to pick up from an old thread posted to the FT forum: https://mailman.science.ru.nl/pipermail/fieldtrip/2015-October/009682.html. Basically, I am trying to perform source localisation using regions within an atlas described on the Conte69 brain http://brainvis.wustl.edu/wiki/index.php//Caret:Atlases/Conte69_Atlas.

I have run the standard Freesurfer pipeline on my MRIs (in head co-ordinate system), converted the output to the Conte69 atlas using “freesurfer_to_fs_LR” pipeline, and finally down-sampled the mesh using the helpful instructions from the above thread, combined with MNE function: mne_setup_source_space --ico -6 .

So to my questions:

i) How do I map from the atlas vertices (on the 327684 vertex Conte69 brain) to the downsampled mesh with 4096 vertices per hemisphere? I feel it has something to do with the deformation maps...

ii) How to I align everything in the head co-ordinate system (appreciate this is a bit of a general question)?

Many thanks,

Robert Seymour (PhD Student, Aston Brain Centre)

_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160721/98b5793d/attachment.htm>

From jan.schoffelen at donders.ru.nl  Thu Jul 21 17:59:16 2016
From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs))
Date: Thu, 21 Jul 2016 15:59:16 +0000
Subject: [FieldTrip] Conte69 Atlas-Based Source Localisation
In-Reply-To: <FB00DD05-6A12-4D4E-951A-BA38FD81A620@donders.ru.nl>
References: <AM4PR0101MB21807DADC0ABE7DA30420BA999090@AM4PR0101MB2180.eurprd01.prod.exchangelabs.com>
 <FB00DD05-6A12-4D4E-951A-BA38FD81A620@donders.ru.nl>
Message-ID: <A63A6F13-CB92-47F8-871B-17295744F2FE@donders.ru.nl>

Hi Robert,

Here I am again. I forgot to add to my previous message that you need to look into the sourcemodel.orig.inuse field to find out which vertices in the high resolution cortical sheet are used in the downsampled version.

Best,
Jan-Mathijs


On 21 Jul 2016, at 17:33, Schoffelen, J.M. (Jan Mathijs) <jan.schoffelen at donders.ru.nl<mailto:jan.schoffelen at donders.ru.nl>> wrote:

Hi Robert,

If you process the cortical sheet that is shipped with the Conte69 atlas, i.e. pass it through freesurfer_to_fs_LR, and then through mne_setup_source_space, you’ll get a topologically valid low-resolution parcellation, which you could use with your individual source models. Each of the vertices is surface-registered by construction.

Best,
Jan-Mathijs

On 21 Jul 2016, at 17:19, Seymour, Robert (Research Student) <seymourr at aston.ac.uk<mailto:seymourr at aston.ac.uk>> wrote:

Dear Fieldtrip Forum,

I'd just like to pick up from an old thread posted to the FT forum: https://mailman.science.ru.nl/pipermail/fieldtrip/2015-October/009682.html. Basically, I am trying to perform source localisation using regions within an atlas described on the Conte69 brain http://brainvis.wustl.edu/wiki/index.php//Caret:Atlases/Conte69_Atlas.

I have run the standard Freesurfer pipeline on my MRIs (in head co-ordinate system), converted the output to the Conte69 atlas using “freesurfer_to_fs_LR” pipeline, and finally down-sampled the mesh using the helpful instructions from the above thread, combined with MNE function: mne_setup_source_space --ico -6 .

So to my questions:

i) How do I map from the atlas vertices (on the 327684 vertex Conte69 brain) to the downsampled mesh with 4096 vertices per hemisphere? I feel it has something to do with the deformation maps...

ii) How to I align everything in the head co-ordinate system (appreciate this is a bit of a general question)?

Many thanks,

Robert Seymour (PhD Student, Aston Brain Centre)

_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160721/11a26210/attachment.htm>

From ruil3 at student.unimelb.edu.au  Fri Jul 22 08:05:35 2016
From: ruil3 at student.unimelb.edu.au (Rui Li)
Date: Fri, 22 Jul 2016 16:05:35 +1000
Subject: [FieldTrip] Kurtosis topography at channel level
In-Reply-To: <permail-201607210848365b97421400005aab-f_neug02@message-id.uni-muenster.de>
References: <CALeb_wz60=fBuWgsiA7Oj6a4P8fvSZPGcnsrB895TgOxfnfYwA@mail.gmail.com>
 <permail-201607210848365b97421400005aab-f_neug02@message-id.uni-muenster.de>
Message-ID: <CALeb_wxPjS+KM_fhO5zGp36mMF5ZU_JRbdrKxkiSiT2rHrk1oQ@mail.gmail.com>

Dear Frank,

Thanks for your kind reply.

Regards,
Rui.

On Thu, Jul 21, 2016 at 6:48 PM, Frank Neugebauer <
f.neugebauer at uni-muenster.de> wrote:

> Hi Rui,
>
> *Question 1:* why and how does the filter affect the kurtosis?
>
> As kurtosis is not linear, that is
> kurtosis(data+noise)=/=kurtosis(data)+kurtosis(noise), it is a little hard
> to say how exactly changing your data will change the output kurtosis.
> If you filter Gaussian noise the signal should form stronger outlier and
> thus the data should yield higher kurtosis.
> As far as I understand kurtosis, the frequency itself does not directly
> influence the kurtosis output.
>
>
> *Question 2:* Why the kurtosis topographies at channel level from two
> > dataset case1.ds (figure 1 (no filter), figure 2 (filtered)) and
> > case1_cHPI_raw_trans_sss.fif (figure 3 (no filter) and figure 4
> (filtered))
> > are not consistent? Because these two datasets are measured from the same
> > patient, the kurtosis topography should be consistent. Do you have any
> idea
> > about this?
>
>
> As far as I understand, epileptic activity is hard to measure because you
> don't know when it will occur and different measurements are not
> inconsistent, but just show different activity at a different time and
> circumstance (such as different sensor noise, interference, but also the
> patient's condition).
> In the introduction to the case they say,
> >> Corticography also showed interictal discharges in the frontal lobe,
> though seizures were of parietal origin. <<. Maybe this is the explanation?
> The kurtosis points to the frontal lobe, too.
>
> I hope this was a little helpful,
> best regards,
> Frank
>
>
> Rui Li wrote on 2016-07-21:
> > Dear FieldTrip users,
>
> > Recently, I am working on the case 1 dataset of epilepsy tutorial. The
> > first patient got the MEG recording from Neuromag and CTF, respectively.
> I
> > encountered some problems when I tried to depict the Kurtosis topography
> > at channel - level.
>
>
> > *Question 1:* why and how does the filter affect the kurtosis?
>
> > Figure 1 and Figure 2 are kurtosis topographies at channel level without
> > band pass filter and with band pass filter, respectively. As we can see,
> > these two figures are very different. Therefore, I am wondering why and
> how
> > does the frequency filter affect the kurtosis?
>
> > The figure 1 is generated by the following program;
>
> > %% preporcessing the channel level data
>
> > dataset = 'case1.ds';
>
> > cfg = [];
>
> > cfg.dataset = dataset;
>
> > % cfg.hpfilter = 'yes';
>
> > % cfg.hpfreq = 10;
>
> > % cfg.lpfilter = 'yes';
>
> > % cfg.lpfreq = 70;
>
> > cfg.channel = {'MEG'};
>
> > data = ft_preprocessing(cfg);
>
>
>
> > %% compute channel-level kurtosis
>
>
>
> > datak = [];
>
> > datak.label = data.label;
>
> > datak.dimord = 'chan';
>
> > datak.kurtosis = kurtosis(data.trial{1}')';
>
>
>
> > cfg = [];
>
> > cfg.comment = 'computed channel-level kurtosis';
>
> > datak = ft_annotate(cfg, datak);
>
>
>
> > %% plot kurtosis topography at channel-level
>
>
>
> > cfg = [];
>
> > cfg.layout = 'CTF275.lay';
>
> > cfg.parameter = 'kurtosis';
>
>
>
> > figure;
>
> > ft_topoplotER(cfg, datak);
>
>
> > ​
>
> > Figure 1 kurtosis topography + no filter + case1.ds
>
> > If the band pass filter is included in the pre-processing, the kurtosis
> > topography is figure 2; the pre-processing matlab program is
>
> > %% preporcessing the channel level data
>
> > dataset = 'case1.ds';
>
> > cfg = [];
>
> > cfg.dataset = dataset;
>
> > cfg.hpfilter = 'yes';
>
> > cfg.hpfreq = 10;
>
> > cfg.lpfilter = 'yes';
>
> > cfg.lpfreq = 70;
>
> > cfg.channel = {'MEG'};
>
> > data = ft_preprocessing(cfg);
>
>
>
> > Figure 2 kurtosis topography + [10Hz 70Hz] filter + case1.ds
>
> > *Question 2:* Why the kurtosis topographies at channel level from two
> > dataset case1.ds (figure 1 (no filter), figure 2 (filtered)) and
> > case1_cHPI_raw_trans_sss.fif (figure 3 (no filter) and figure 4
> (filtered))
> > are not consistent? Because these two datasets are measured from the same
> > patient, the kurtosis topography should be consistent. Do you have any
> idea
> > about this?
>
>
> > ​
>
> > Figure 3 kurtosis topography + no filter + case1_cHPI_raw_trans_sss.fif
>
>
> > ​
>
> > Figure 4 kurtosis topography + [10Hz 70Hz] filter +
> > case1_cHPI_raw_trans_sss.fif
>
> > Regards,
>
> > Rui.
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160722/83c9138b/attachment.htm>

From jonas.chatel.goldman at gmail.com  Fri Jul 22 11:27:05 2016
From: jonas.chatel.goldman at gmail.com (Jonas Chatel-Goldman)
Date: Fri, 22 Jul 2016 11:27:05 +0200
Subject: [FieldTrip] Adequate connectivity measure for continuous data
Message-ID: <CAH9_rrvfLLmVfKSEv35ukRJw4D6aoxPGQJwR2xVkv-uMmG7oiA@mail.gmail.com>

Dear Fieldtrippers,

In terms of connectivity measure for EEG signals, WPLI appears to have a
good reputation among the neurophysio community. However it seems to
require multiple trials for its estimation (e.g.,
https://mailman.science.ru.nl/pipermail/fieldtrip/2015-August/009575.html).
Could it be applied on continuous data (e.g., >1 minute resting state
segments) and, if not, what could be an appropriate connectivity measure in
this context?

best,


*Jonas *
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160722/3ee177d9/attachment.htm>

From tzvetan.popov at uni-konstanz.de  Fri Jul 22 12:07:00 2016
From: tzvetan.popov at uni-konstanz.de (Tzvetan Popov)
Date: Fri, 22 Jul 2016 12:07:00 +0200
Subject: [FieldTrip] Adequate connectivity measure for continuous data
In-Reply-To: <CAH9_rrvfLLmVfKSEv35ukRJw4D6aoxPGQJwR2xVkv-uMmG7oiA@mail.gmail.com>
References: <CAH9_rrvfLLmVfKSEv35ukRJw4D6aoxPGQJwR2xVkv-uMmG7oiA@mail.gmail.com>
Message-ID: <646F174E-105D-4A5B-961D-62AAED16862A@uni-konstanz.de>

Dear Jonas,

this paper is quite a good start: http://journal.frontiersin.org/article/10.3389/fnsys.2015.00175/full
Very accessible read also providing some playground data to begin with. 
Good luck,
tzvetan
 



> Dear Fieldtrippers,
> 
> In terms of connectivity measure for EEG signals, WPLI appears to have a good reputation among the neurophysio community. However it seems to require multiple trials for its estimation (e.g., https://mailman.science.ru.nl/pipermail/fieldtrip/2015-August/009575.html). Could it be applied on continuous data (e.g., >1 minute resting state segments) and, if not, what could be an appropriate connectivity measure in this context?
> 
> best, 
> 
> 
> Jonas
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160722/9daa8275/attachment.htm>

From nima.noury at student.uni-tuebingen.de  Fri Jul 22 13:00:16 2016
From: nima.noury at student.uni-tuebingen.de (Nima Noury)
Date: Fri, 22 Jul 2016 13:00:16 +0200
Subject: [FieldTrip] 2016 Tuebingen MEG Symposium, Oct 26-27
Message-ID: <20160722130016.Horde.jxvSalIKRTkLclaFmo6w-Mu@webmail.uni-tuebingen.de>

The MEG Center Tuebingen is pleased to announce the
       2016 Tuebingen MEG Symposium
The symposium takes place on October 26 and 27, 2016 at the University  
Hospital’s Conference Center. The meeting brings together leading  
researchers in the field of MEG and related disciplines.
Join us to learn about the latest  advances in MEG research and beyond.

Confirmed speakers:

Radoslaw Cichy, Berlin
Michael Cohen, Nijmegen
Freek van Ede, Oxford
Stefan Haufe, New York
Vladimir Litvak, London
Laura Marzetti, Chieti
Satu Palva, Helsinki
Rafael Polania, Zurich
Martin Vinck, New Haven
Mark Woolrich, Oxford

For more information and registration, please visit:
http://meg.medizin.uni-tuebingen.de/2016/

Please forward this information to any of your colleagues and  
collaborators that may be interested in the symposium.

Nima Noury
AG Large-Scale Neuronal Interactions
Centre for Integrative Neuroscience (CIN)
University of Tübingen
Otfried Müller-Straße 25
72076 Tübingen
Germany



From jonas.chatel.goldman at gmail.com  Fri Jul 22 16:43:25 2016
From: jonas.chatel.goldman at gmail.com (Jonas Chatel-Goldman)
Date: Fri, 22 Jul 2016 16:43:25 +0200
Subject: [FieldTrip] Adequate connectivity measure for continuous data
In-Reply-To: <646F174E-105D-4A5B-961D-62AAED16862A@uni-konstanz.de>
References: <CAH9_rrvfLLmVfKSEv35ukRJw4D6aoxPGQJwR2xVkv-uMmG7oiA@mail.gmail.com>
 <646F174E-105D-4A5B-961D-62AAED16862A@uni-konstanz.de>
Message-ID: <CAH9_rrtx=RTdcn2LQvVWN4uTVnhPs3JfWvGMhivHwxoP1ogPpQ@mail.gmail.com>

Dear Tzvetan,

thanks for your reply. However the reference you kindly provided doesn't
address the estimation of connectivity in the case of continuous data (all
mentioned measures seem to require being fed with multiple trials data).
Beside, it is a good tutorial but not really exhaustive (for instance not a
word on WPLI).


*Jonas *

2016-07-22 12:07 GMT+02:00 Tzvetan Popov <tzvetan.popov at uni-konstanz.de>:

> Dear Jonas,
>
> this paper is quite a good start:
> http://journal.frontiersin.org/article/10.3389/fnsys.2015.00175/full
> Very accessible read also providing some playground data to begin with.
> Good luck,
> tzvetan
>
>
>
>
> Dear Fieldtrippers,
>
> In terms of connectivity measure for EEG signals, WPLI appears to have a
> good reputation among the neurophysio community. However it seems to
> require multiple trials for its estimation (e.g.,
> https://mailman.science.ru.nl/pipermail/fieldtrip/2015-August/009575.html).
> Could it be applied on continuous data (e.g., >1 minute resting state
> segments) and, if not, what could be an appropriate connectivity measure in
> this context?
>
> best,
>
>
> *Jonas *
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160722/b30d3d15/attachment.htm>

From seymourr at aston.ac.uk  Fri Jul 22 17:42:51 2016
From: seymourr at aston.ac.uk (Seymour, Robert (Research Student))
Date: Fri, 22 Jul 2016 15:42:51 +0000
Subject: [FieldTrip] Conte69 Atlas-Based Source Localisation
Message-ID: <AM4PR0101MB21802FDBD8A59633CA7DC01B990A0@AM4PR0101MB2180.eurprd01.prod.exchangelabs.com>

Thanks Jan-Mathijs,



Now got it working! There's probably a more elegant way to do this but thought I'd attach my code here anyway.



Rob


-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160722/600725af/attachment.htm>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: conte69_atlas.m
Type: application/octet-stream
Size: 854 bytes
Desc: conte69_atlas.m
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160722/600725af/attachment.obj>

From michelic72 at gmail.com  Fri Jul 22 18:03:26 2016
From: michelic72 at gmail.com (Cristiano Micheli)
Date: Fri, 22 Jul 2016 18:03:26 +0200
Subject: [FieldTrip] Adequate connectivity measure for continuous data
In-Reply-To: <CAH9_rrtx=RTdcn2LQvVWN4uTVnhPs3JfWvGMhivHwxoP1ogPpQ@mail.gmail.com>
References: <CAH9_rrvfLLmVfKSEv35ukRJw4D6aoxPGQJwR2xVkv-uMmG7oiA@mail.gmail.com>
 <646F174E-105D-4A5B-961D-62AAED16862A@uni-konstanz.de>
 <CAH9_rrtx=RTdcn2LQvVWN4uTVnhPs3JfWvGMhivHwxoP1ogPpQ@mail.gmail.com>
Message-ID: <CADW7XCBJArW0NmEHjHjWKsSgkCCqb=5=zpiDnku1xXgW8B=9_A@mail.gmail.com>

Dear Jonas
This paper addresses your question:
http://www.hindawi.com/journals/cmmm/2012/186353/abs/

IHTH
Cris


On Fri, Jul 22, 2016 at 4:43 PM, Jonas Chatel-Goldman <
jonas.chatel.goldman at gmail.com> wrote:

> Dear Tzvetan,
>
> thanks for your reply. However the reference you kindly provided doesn't
> address the estimation of connectivity in the case of continuous data (all
> mentioned measures seem to require being fed with multiple trials data).
> Beside, it is a good tutorial but not really exhaustive (for instance not a
> word on WPLI).
>
>
> *Jonas *
>
> 2016-07-22 12:07 GMT+02:00 Tzvetan Popov <tzvetan.popov at uni-konstanz.de>:
>
>> Dear Jonas,
>>
>> this paper is quite a good start:
>> http://journal.frontiersin.org/article/10.3389/fnsys.2015.00175/full
>> Very accessible read also providing some playground data to begin with.
>> Good luck,
>> tzvetan
>>
>>
>>
>>
>> Dear Fieldtrippers,
>>
>> In terms of connectivity measure for EEG signals, WPLI appears to have a
>> good reputation among the neurophysio community. However it seems to
>> require multiple trials for its estimation (e.g.,
>> https://mailman.science.ru.nl/pipermail/fieldtrip/2015-August/009575.html).
>> Could it be applied on continuous data (e.g., >1 minute resting state
>> segments) and, if not, what could be an appropriate connectivity measure in
>> this context?
>>
>> best,
>>
>>
>> *Jonas *
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>>
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160722/1e7d4e7c/attachment.htm>

From tzvetan.popov at uni-konstanz.de  Fri Jul 22 18:20:35 2016
From: tzvetan.popov at uni-konstanz.de (Tzvetan Popov)
Date: Fri, 22 Jul 2016 18:20:35 +0200
Subject: [FieldTrip] Adequate connectivity measure for continuous data
In-Reply-To: <CAH9_rrtx=RTdcn2LQvVWN4uTVnhPs3JfWvGMhivHwxoP1ogPpQ@mail.gmail.com>
References: <CAH9_rrvfLLmVfKSEv35ukRJw4D6aoxPGQJwR2xVkv-uMmG7oiA@mail.gmail.com>
 <646F174E-105D-4A5B-961D-62AAED16862A@uni-konstanz.de>
 <CAH9_rrtx=RTdcn2LQvVWN4uTVnhPs3JfWvGMhivHwxoP1ogPpQ@mail.gmail.com>
Message-ID: <71C6CFDD-7C0B-44A4-9838-36757CDD2F24@uni-konstanz.de>

HI,
you could check out this approach: http://www.fieldtriptoolbox.org/tutorial/networkanalysis. You can compute your desired connectivity metric during the call to ft_connectivity analysis. Many of the issues stressed in the paper still apply though, independent of the metric of your choice. You could also segment your data on the basis of some event you consider relevant, e.g. particular phases of an ongoing signal. It is your model that you believe represents a good “guess” of the cerebral connectivity pattern not so much the metric. 

good luck

tzvetan



> Dear Tzvetan,
> 
> thanks for your reply. However the reference you kindly provided doesn't address the estimation of connectivity in the case of continuous data (all mentioned measures seem to require being fed with multiple trials data). Beside, it is a good tutorial but not really exhaustive (for instance not a word on WPLI).
> 
> 
> Jonas
> 
> 2016-07-22 12:07 GMT+02:00 Tzvetan Popov <tzvetan.popov at uni-konstanz.de>:
> Dear Jonas,
> 
> this paper is quite a good start: http://journal.frontiersin.org/article/10.3389/fnsys.2015.00175/full
> Very accessible read also providing some playground data to begin with. 
> Good luck,
> tzvetan
>  
> 
> 
> 
>> Dear Fieldtrippers,
>> 
>> In terms of connectivity measure for EEG signals, WPLI appears to have a good reputation among the neurophysio community. However it seems to require multiple trials for its estimation (e.g., https://mailman.science.ru.nl/pipermail/fieldtrip/2015-August/009575.html). Could it be applied on continuous data (e.g., >1 minute resting state segments) and, if not, what could be an appropriate connectivity measure in this context?
>> 
>> best, 
>> 
>> 
>> Jonas
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160722/5b712b97/attachment.htm>

From rb643 at medschl.cam.ac.uk  Sat Jul 23 12:51:15 2016
From: rb643 at medschl.cam.ac.uk (Richard Bethlehem)
Date: Sat, 23 Jul 2016 10:51:15 +0000
Subject: [FieldTrip] channel combination after wpli
Message-ID: <3188FAB8621D294696F13E80A7BBC97E010A306F3A@me-mbx3.medschl.cam.ac.uk>

Dear Fieltrippers,

After running ft_connectivityanalysis on a subset of pre-processed resting-state EEG data the dimord is still listed as chan_freq_time (where the first dimension is simply all the pairwise channel comparisons). If I want to run subsequent network analysis on this the ft_networkanalysis require a chan_chan_freq_time matrix. Is there any way to convert this so that I can run the network analysis or am I missing a setting in the connectivity analysis that would give me that output?

This is the code I used (my entire resting-state recording has been replaced into 4 second segments in order to get 'trials' for the WPLI connectivity function:


    cfg_freq = [];

    cfg_freq.method = 'wavelet';

    cfg_freq.output = 'powandcsd';

    cfg_freq.channel = 1:64;

    cfg_freq.keeptrials ='yes'; %do not return an average of all trials for subsequent wpli analysis

    cfg_freq.toi = [0.5:0.05:3.5];

    %delta

    cfg_freq.foi = [2:0.02:4];

    cfg_freq.width = 3; %small width for low frequency

    [freq_data.delta] = ft_freqanalysis(cfg_freq, data_iccleaned);


    cfg_conn = [];

    cfg_conn.method = 'wpli';

    conn.delta = ft_connectivityanalysis(cfg_conn, freq_data.delta);


Cheers,

Richard
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160723/49df1865/attachment.htm>

From johanna.zumer at gmail.com  Sun Jul 24 20:30:32 2016
From: johanna.zumer at gmail.com (Johanna Zumer)
Date: Sun, 24 Jul 2016 19:30:32 +0100
Subject: [FieldTrip] PhD advert
In-Reply-To: <9d9efc01808a4a72ad165f7b66ce4a70@EXHUB01.adf.bham.ac.uk>
References: <9d9efc01808a4a72ad165f7b66ce4a70@EXHUB01.adf.bham.ac.uk>
Message-ID: <CAL4kA6dSvAfUFmyxBhLeagiK4Fd_+=nbrswJ6LnE-5gmT+tH4A@mail.gmail.com>

Dear all,

Please see attached for an advert for a PhD position in Birmingham, UK on
multisensory integration in the group of Uta Noppeney.

Kind regards,
Johanna
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160724/91eeab08/attachment.htm>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: advert2016_multsense_PhD.doc
Type: application/msword
Size: 37888 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160724/91eeab08/attachment.doc>

From RXW494 at student.bham.ac.uk  Mon Jul 25 13:47:37 2016
From: RXW494 at student.bham.ac.uk (Ross Wilson)
Date: Mon, 25 Jul 2016 11:47:37 +0000
Subject: [FieldTrip] Using an fMRI cluster as an ROI
Message-ID: <3105F3FB20D2B242A7F70546785A60FC01752632D7@EX13.adf.bham.ac.uk>

Hello all!

I am attempting to use an fMRI cluster as an ROI to look at virtual electrode timecourses post-beamforming.

I have been using the aal atlas to find virtual electrodes of maximum change between baseline and stimulus period within, for example, the motor cortex afer beamforming. However, the virtual electrodes found are not necessarily in a position similar to that of the fMRI cluster and I'd like to be more specific than that if possible.

The template grid I have been using for beamforming is created from the T1 (code as below, in MNI space: ...fieldtrip\external/spm8/templates/T1.nii). Is it possible to transform an fMRI cluster (in MNI space) onto the template grid so that the data from specific grid points relating to that cluster can be extracted post-beamforming??

Any help with this would be great!

Thank you,

Ross
%%%tempale grid creation
T1 = ft_read_mri('F:\fieldtrip\external/spm8/templates/T1.nii');
T1.coordsys = 'spm';

cfg          = [];
template_seg = ft_volumesegment(cfg, T1);

cfg          = [];
cfg.method   = 'singleshell';
template_vol = ft_prepare_headmodel(cfg, template_seg);
template_vol = ft_convert_units(template_vol, 'cm');

cfg = [];
cfg.grid.xgrid  = -20:0.5:20;
cfg.grid.ygrid  = -20:0.5:20;
cfg.grid.zgrid  = -20:0.5:20;
cfg.grid.unit   = 'cm';
cfg.grid.tight  = 'yes';
cfg.inwardshift = 0.15;
cfg.vol        = template_vol;
template_grid  = ft_prepare_sourcemodel(cfg);
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160725/fc8b34a9/attachment.htm>

From julian.keil at gmail.com  Mon Jul 25 14:03:26 2016
From: julian.keil at gmail.com (Julian Keil)
Date: Mon, 25 Jul 2016 14:03:26 +0200
Subject: [FieldTrip] Using an fMRI cluster as an ROI
In-Reply-To: <3105F3FB20D2B242A7F70546785A60FC01752632D7@EX13.adf.bham.ac.uk>
References: <3105F3FB20D2B242A7F70546785A60FC01752632D7@EX13.adf.bham.ac.uk>
Message-ID: <55341243-86D4-479C-8769-9270AF12B3D1@gmail.com>

Hi Ross,

one way to attempt this, is to create a 3D grid on your fMRI data, so that each voxel is a grid point.
Then you can compute the distance between grid points from the fMRI grid and your virtual electrode grid and find the nearest neighbours.
This sould work for the whole brain as well as for predefined ROIs.

I've attached a function I use for similar problems. I'm sure there are more elegant ways but this works for me. It won't do exactly what you want to do, but maybe some bits and pieces can help you along.

Good luck,

Julian




Am 25.07.2016 um 13:47 schrieb Ross Wilson:

> Hello all!
> 
> I am attempting to use an fMRI cluster as an ROI to look at virtual electrode timecourses post-beamforming.
> 
> I have been using the aal atlas to find virtual electrodes of maximum change between baseline and stimulus period within, for example, the motor cortex afer beamforming. However, the virtual electrodes found are not necessarily in a position similar to that of the fMRI cluster and I’d like to be more specific than that if possible.
> 
> The template grid I have been using for beamforming is created from the T1 (code as below, in MNI space: …fieldtrip\external/spm8/templates/T1.nii). Is it possible to transform an fMRI cluster (in MNI space) onto the template grid so that the data from specific grid points relating to that cluster can be extracted post-beamforming??
> 
> Any help with this would be great!
> 
> Thank you,
> 
> Ross
> %%%tempale grid creation
> T1 = ft_read_mri('F:\fieldtrip\external/spm8/templates/T1.nii');
> T1.coordsys = 'spm';
> 
> cfg          = [];
> template_seg = ft_volumesegment(cfg, T1);
> 
> cfg          = [];
> cfg.method   = 'singleshell';
> template_vol = ft_prepare_headmodel(cfg, template_seg);
> template_vol = ft_convert_units(template_vol, 'cm');
> 
> cfg = [];
> cfg.grid.xgrid  = -20:0.5:20;
> cfg.grid.ygrid  = -20:0.5:20;
> cfg.grid.zgrid  = -20:0.5:20;
> cfg.grid.unit   = 'cm';
> cfg.grid.tight  = 'yes';
> cfg.inwardshift = 0.15;
> cfg.vol        = template_vol;
> template_grid  = ft_prepare_sourcemodel(cfg);
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160725/1c223b0a/attachment.htm>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: vt_make_roifield.m
Type: application/octet-stream
Size: 6646 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160725/1c223b0a/attachment.obj>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160725/1c223b0a/attachment-0001.htm>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: signature.asc
Type: application/pgp-signature
Size: 495 bytes
Desc: Message signed with OpenPGP using GPGMail
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160725/1c223b0a/attachment.sig>

From stan.vanpelt at donders.ru.nl  Tue Jul 26 09:12:59 2016
From: stan.vanpelt at donders.ru.nl (Pelt, S. van (Stan))
Date: Tue, 26 Jul 2016 07:12:59 +0000
Subject: [FieldTrip] Using an fMRI cluster as an ROI
In-Reply-To: <55341243-86D4-479C-8769-9270AF12B3D1@gmail.com>
References: <3105F3FB20D2B242A7F70546785A60FC01752632D7@EX13.adf.bham.ac.uk>,
 <55341243-86D4-479C-8769-9270AF12B3D1@gmail.com>
Message-ID: <1556CA07-969A-4678-8127-948CF195E727@donders.ru.nl>

Hi Ross,

I think what you looking for is explainef in this turorial:
http://www.fieldtriptoolbox.org/tutorial/shared/virtual_sensors?s[]=virtual

Make sure that you first warp the subject's brain coordinates to MNI coordinates. Then enter your ROI coordinates at cfg.grid.pos and run the lcmv beamformer to get the spatial filter that is specific of your ROI peak MNI coordinates.

Hope that helps.

Stan

Op 25 jul. 2016 om 14:06 heeft Julian Keil <julian.keil at gmail.com<mailto:julian.keil at gmail.com>> het volgende geschreven:

Hi Ross,

one way to attempt this, is to create a 3D grid on your fMRI data, so that each voxel is a grid point.
Then you can compute the distance between grid points from the fMRI grid and your virtual electrode grid and find the nearest neighbours.
This sould work for the whole brain as well as for predefined ROIs.

I've attached a function I use for similar problems. I'm sure there are more elegant ways but this works for me. It won't do exactly what you want to do, but maybe some bits and pieces can help you along.

Good luck,

Julian



Am 25.07.2016 um 13:47 schrieb Ross Wilson:

Hello all!

I am attempting to use an fMRI cluster as an ROI to look at virtual electrode timecourses post-beamforming.

I have been using the aal atlas to find virtual electrodes of maximum change between baseline and stimulus period within, for example, the motor cortex afer beamforming. However, the virtual electrodes found are not necessarily in a position similar to that of the fMRI cluster and I’d like to be more specific than that if possible.

The template grid I have been using for beamforming is created from the T1 (code as below, in MNI space: …fieldtrip\external/spm8/templates/T1.nii). Is it possible to transform an fMRI cluster (in MNI space) onto the template grid so that the data from specific grid points relating to that cluster can be extracted post-beamforming??

Any help with this would be great!

Thank you,

Ross
%%%tempale grid creation
T1 = ft_read_mri('F:\fieldtrip\external/spm8/templates/T1.nii');
T1.coordsys = 'spm';

cfg          = [];
template_seg = ft_volumesegment(cfg, T1);

cfg          = [];
cfg.method   = 'singleshell';
template_vol = ft_prepare_headmodel(cfg, template_seg);
template_vol = ft_convert_units(template_vol, 'cm');

cfg = [];
cfg.grid.xgrid  = -20:0.5:20;
cfg.grid.ygrid  = -20:0.5:20;
cfg.grid.zgrid  = -20:0.5:20;
cfg.grid.unit   = 'cm';
cfg.grid.tight  = 'yes';
cfg.inwardshift = 0.15;
cfg.vol        = template_vol;
template_grid  = ft_prepare_sourcemodel(cfg);
_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

<vt_make_roifield.m>
<signature.asc>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160726/9824ad07/attachment.htm>

From carmen.kung at mq.edu.au  Wed Jul 27 08:01:40 2016
From: carmen.kung at mq.edu.au (Carmen Kung)
Date: Wed, 27 Jul 2016 16:01:40 +1000
Subject: [FieldTrip] ft_databrowser error
Message-ID: <d5ef871e-c3f5-fae8-4bcd-96e67d3fde96@mq.edu.au>

Dear fieldtripers,

After running ft_definetrial and ft_preprocessing, we try to plot the 
data using ft_databrowser using the script at follow:


 >> cfg = [];
 >> ft_databrowser(cfg, data);

But this is the error message we got:

the input is raw data with 69 channels and 25 trials
detected   0 visual artifacts
Error using zeros
Size inputs must be integers.

Error in convert_event>artifact2artvec (line 179)
artvec = zeros(length(artifact), endsample);

Error in convert_event (line 103)
     obj = artifact2artvec(obj,endsample);

Error in ft_databrowser (line 501)
artdata.trial{1}       = convert_event(artifact, 'boolvec', 'endsample', 
datendsample); % every artifact is a "channel"


We did try to plot the raw *.cnt file (the cnt is recorded using curry 
7) using ft_databrowser. It worked, but not the epoched data. This is 
the parameters we used for the cfg to run ft_definetrial and 
ft_preprocessing

     cfg = [];
     cfg.dataformat = 'ns_cnt';
     cfg.headerformat= 'ns_cnt';
     cfg.eventformat= 'ns_cnt';
     cfg.trialdef.eventtype = 'stimtype';
     cfg.trialdef.prestim = 0.5;
     cfg.trialdef.poststim = 1.5;
     cfg.trialdef.eventvalue = 114;
     cfg.dataset = [dir filesep 'cnt' filesep subjectdata.subjectnr '_' 
subjectdata.initial '_' subjectdata.date '.cnt'];
     cfg = ft_definetrial(cfg);
     data = ft_preprocessing(cfg);

The analysis is run on fieldtrip-20150522 and Matlab 2014a. Any help 
with this will be appreciated!

Many thanks in advance,
Carmen

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160727/6df4adac/attachment.htm>

From ipalma6 at msn.com  Wed Jul 27 12:18:43 2016
From: ipalma6 at msn.com (=?utf-8?B?SW7DqnMgUA==?=)
Date: Wed, 27 Jul 2016 10:18:43 +0000
Subject: [FieldTrip] Changing density of channels in ft_topoplotER?
Message-ID: <VI1PR1001MB08310E73A63E37DDBF8A072BEB0F0@VI1PR1001MB0831.EURPRD10.PROD.OUTLOOK.COM>

Dear community,

My name is Inês and I'm using fieldtrip to look at EEG data acquired from a 32-channel BioSemi using BCI2000 in my BCI experiment.

Currently I have been looking at the alpha band power over averaged trials in a particular condition, and to do that I have been using both ft_topoplotER and ft_multiplotER ().
My problem is that although my data has 32 channels (all specified under data.label), both plots only display a few main channels - 20 to be exact.
I'm including an example image of the layout and the corresponding topoplot. The same channels are shown in multiplot. Here's my code:

%preprocessing for each subject and extracting desired trials%
cfg=[];
data_alltrials = ft_appenddata(cfg, data{:});

% FFT
freq_cfg = [];
freq_cfg.channel = 'all';
freq_cfg.method = 'mtmfft';
freq_cfg.output = 'pow';
freq_cfg.taper  = 'hanning';
freq_cfg.keeptrials = 'yes';
freq_cfg.foi = foi;
freq_cfg.tapsmofrq = 1;
fft_alltrials = ft_freqanalysis(freq_cfg, data_alltrials);
disp('Preprocessing done.');

cfg = []; cfg.layout = layout;
layout = ft_prepare_layout(cfg, data_alltrials);
ft_layoutplot(cfg, data_alltrials)

cfg = [];
cfg.layout = 'biosemi32.lay';
channel = ft_channelselection({'all'},data_alltrials.label);
cfg.channel = channel;
cfg.colorbar = 'yes';
cfg.showlabels = 'yes';
figure(); ft_topoplotER(cfg, fft_alltrials);
figure(); ft_multiplotER(cfg, fft_alltrials);

So I guess my question is: is there a way to change the density of electrodes plotted, or even show them all?
Can someone tell me if there is something wrong with the cfg settings I use or if I am doing something wrong at any other place?
Looking forward to hear from you all!

Best,
Inês

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160727/fe021f05/attachment.htm>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: example_layout.JPG
Type: image/jpeg
Size: 90342 bytes
Desc: example_layout.JPG
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160727/fe021f05/attachment.jpe>

From M.vanEs at donders.ru.nl  Wed Jul 27 17:04:15 2016
From: M.vanEs at donders.ru.nl (Es, M.W.J. van (Mats))
Date: Wed, 27 Jul 2016 15:04:15 +0000
Subject: [FieldTrip] Source analysis/statistics single subject
Message-ID: <3FC79061C73BEF44A3BEDA5DFC0ADBDF4ECD5569@exprd01.hosting.ru.nl>

Hi FieldTrippers,

I am currently trying to do source analysis on an individual subject (using the fieldtrip tutorial as a guideline). I have baseline (*Bl) and activity (*Act) data. I constructed a common filter (using DICS) and added the filter to the cfg structure before doing sourceanalysis on the individual CSD's of the active and baseline data, respectively. Although I tried specifying cfg.keeptrials = 'yes' in every step, the output of ft_sourceanalysis is an average over trials:

sourceAct =

      freq: 11
    inside: [2004x1 logical]
       pos: [2004x3 double]
    method: 'average'
       avg: [1x1 struct]
       cfg: [1x1 struct]

This (I think) causes errors when I subsequently try to do sourcestatistics:

Error using ft_statistics_montecarlo (line 242)
could not determine the parametric critical value for clustering

Error in ft_sourcestatistics (line 205)
  [stat, cfg] = statmethod(cfg, dat, design);

Can anybody tell me what I'm doing wrong/how to do source statistics on an individual subject? You can find my code below. Thank you!
Mats


% calculate individual CSD
cfg = [];
cfg.method    = 'mtmfft';
cfg.output    = 'powandcsd';
cfg.tapsmofrq = 3;
cfg.foilim    = [11 11];
% cfg.keeptrials = 'yes';
freqAct = ft_freqanalysis(cfg, dataAct);
freqBl = ft_freqanalysis(cfg, dataBl);


% compute common filter
dataAll = ft_appenddata([], dataAct, dataBl);
cfg=[];
cfg.method = 'mtmfft';
cfg.output = 'powandcsd';
cfg.tapsmofrq = 3;
cfg. foilim = [11 11];
freqAll = ft_freqanalysis(cfg, dataAll);

cfg              = [];
cfg.method       = 'dics';
cfg.frequency    = 11;
cfg.grid         = grid; % caculated beforehand
cfg.headmodel    = headmodel; % caculated beforehand
cfg.dics.projectnoise = 'yes';
cfg.dics.lambda       = '5%';
cfg.dics.keepfilter   = 'yes';
cfg.dics.realfilter   = 'yes';
sourceAll = ft_sourceanalysis(cfg, freqAll);


% source analysis
cfg.grid.filter = sourceAll.avg.filter;
cfg.dics.fixedori = 'yes';
cfg.keeptrials = 'yes';
sourceAct  = ft_sourceanalysis(cfg, freqAct);
sourceBl = ft_sourceanalysis(cfg, freqBl);


% source statistics
cfg = [];
cfg.method      = 'montecarlo';
cfg.statistic   = 'ft_statfun_depsamplesT';
cfg.parameter   = 'avg.pow';
cfg.correctm    = 'cluster';
cfg.clusteralpha     = 0.05;
cfg.clusterstatistic = 'maxsum';
cfg.numrandomization = 1000;
cfg.alpha       = 0.05; % note that this only implies single-sided testing
cfg.tail        = 0;
cfg.clustertail      = 0;
cfg.uvar        = 1; % row of design matrix that contains unit variable (in this case: trials)
cfg.ivar        = 2; % row of design matrix that contains independent variable (the conditions)
design = [1:nTrials, 1:nTrials; ones(1, nTrials), 2*ones(1,nTrials)]';
cfg.design           = design';

stat = ft_sourcestatistics(cfg, sourceAct, sourceBl);


-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160727/65a08455/attachment.htm>

From magazzinil at gmail.com  Wed Jul 27 17:24:25 2016
From: magazzinil at gmail.com (Lorenzo Magazzini)
Date: Wed, 27 Jul 2016 16:24:25 +0100
Subject: [FieldTrip] Source analysis/statistics single subject
In-Reply-To: <3FC79061C73BEF44A3BEDA5DFC0ADBDF4ECD5569@exprd01.hosting.ru.nl>
References: <3FC79061C73BEF44A3BEDA5DFC0ADBDF4ECD5569@exprd01.hosting.ru.nl>
Message-ID: <CABQiM1Ti3XgbmrbVFJOJKinMJEBV0W1RNAa7kKTyoY+SkWVjgA@mail.gmail.com>

Hi Mats,

Check out the option cfg.rawtrial='yes'

Lorenzo



Lorenzo Magazzini

PhD Student

magazzinil at cardiff.ac.uk


CUBRIC Building
Maindy Road

Cardiff
CF24 4HQ



On 27 July 2016 at 16:04, Es, M.W.J. van (Mats) <M.vanEs at donders.ru.nl>
wrote:

> Hi FieldTrippers,
>
> I am currently trying to do source analysis on an individual subject
> (using the fieldtrip tutorial as a guideline). I have baseline (*Bl) and
> activity (*Act) data. I constructed a common filter (using DICS) and added
> the filter to the cfg structure before doing sourceanalysis on the
> individual CSD's of the active and baseline data, respectively. Although I
> tried specifying cfg.keeptrials = 'yes' in every step, the output of
> ft_sourceanalysis is an average over trials:
>
> sourceAct =
>
>       freq: 11
>     inside: [2004x1 logical]
>        pos: [2004x3 double]
>     method: 'average'
>        avg: [1x1 struct]
>        cfg: [1x1 struct]
>
> This (I think) causes errors when I subsequently try to do
> sourcestatistics:
>
> Error using ft_statistics_montecarlo (line 242)
> could not determine the parametric critical value for clustering
>
> Error in ft_sourcestatistics (line 205)
>   [stat, cfg] = statmethod(cfg, dat, design);
>
> Can anybody tell me what I'm doing wrong/how to do source statistics on an
> individual subject? You can find my code below. Thank you!
> Mats
>
>
> *% calculate individual CSD*
> *cfg = [];*
> *cfg.method    = 'mtmfft';*
> *cfg.output    = 'powandcsd';*
> *cfg.tapsmofrq = 3;*
> *cfg.foilim    = [11 11];*
> *% cfg.keeptrials = 'yes';*
> *freqAct = ft_freqanalysis(cfg, dataAct);*
> *freqBl = ft_freqanalysis(cfg, dataBl);*
>
>
> *% compute common filter*
> *dataAll = ft_appenddata([], dataAct, dataBl);*
> *cfg=[];*
> *cfg.method = 'mtmfft';*
> *cfg.output = 'powandcsd';*
> *cfg.tapsmofrq = 3;*
> *cfg. foilim = [11 11];*
> *freqAll = ft_freqanalysis(cfg, dataAll);*
>
> * cfg              = []; cfg.method       = 'dics'; cfg.frequency    = 11;
> cfg.grid         = grid; % caculated beforehand cfg.headmodel    =
> headmodel; % caculated beforehand *
>
>
>
>
>
>
> * cfg.dics.projectnoise = 'yes'; cfg.dics.lambda       = '5%';
> cfg.dics.keepfilter   = 'yes'; cfg.dics.realfilter   = 'yes'; sourceAll =
> ft_sourceanalysis(cfg, freqAll); % source analysis cfg.grid.filter =
> sourceAll.avg.filter; cfg.dics.fixedori = 'yes'; cfg.keeptrials = 'yes';
> sourceAct  = ft_sourceanalysis(cfg, freqAct); sourceBl =
> ft_sourceanalysis(cfg, freqBl); % source statistics cfg = []; cfg.method
>    = 'montecarlo'; cfg.statistic   = 'ft_statfun_depsamplesT';
> cfg.parameter   = 'avg.pow'; cfg.correctm    = 'cluster'; cfg.clusteralpha
>     = 0.05; cfg.clusterstatistic = 'maxsum'; cfg.numrandomization = 1000;
> cfg.alpha       = 0.05; % note that this only implies single-sided testing
> cfg.tail        = 0; cfg.clustertail      = 0; cfg.uvar        = 1; % row
> of design matrix that contains unit variable (in this case: trials)
> cfg.ivar        = 2; % row of design matrix that contains independent
> variable (the conditions) design = [1:nTrials, 1:nTrials; ones(1, nTrials),
> 2*ones(1,nTrials)]'; cfg.design           = design'; stat =
> ft_sourcestatistics(cfg, sourceAct, sourceBl); *
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160727/04ae27fc/attachment.htm>

From sgj.umontreal at gmail.com  Wed Jul 27 23:07:14 2016
From: sgj.umontreal at gmail.com (sandra guerreiro jacinto)
Date: Wed, 27 Jul 2016 17:07:14 -0400
Subject: [FieldTrip] topoplot CSD data
Message-ID: <B8F8D108-8781-473B-A68C-F8DA2E314821@gmail.com>

I’m having trouble topoplot my data after a ft_scalpcurrentdensity procedure.

I get an error message :
«  Error using topoplot_common (line 267)
cfg.parameter=avg is not present in data structure »

Is that correct I take my individuals and make the mean over all subjects in order to create the avg?

here is my code:

    cfg.method       ='spline';
    cfg.elec         = ft_read_sens('standard_waveguard64.elc');
    cfg.trials       = 'all' ;
 
    cfg.conductivity =  0.33;
    cfg.lambda       = 1e-05;
    cfg.order        =  4;
    cfg.degree       = 14;
    ft_csd_GA_Checker_og = ft_scalpcurrentdensity(cfg, GA_Checker_og)
    
    ft_csd_GA_Checker_og.avg = squeeze(mean(ft_csd_GA_Checker_og.trial,1));

the last line was my turnaround. I just want to make sure the procedure is correct.

Thank you!
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160727/8bf6cbc0/attachment.htm>

From rleese12 at berkeley.edu  Thu Jul 28 07:43:44 2016
From: rleese12 at berkeley.edu (Nakyung Lee)
Date: Wed, 27 Jul 2016 22:43:44 -0700
Subject: [FieldTrip]  'ft_redefinetrial' returning only one trial
Message-ID: <CAJir=i-pff2xP=HQD7Yn9mJcu45FM1+CwHcMVkjH7DoKZQc=XA@mail.gmail.com>

Dear FieldTrip community,

I've been having a problem calling 'ft_redefinetrial'.
Basically with my raw data with one trial (simply 'data' here), I've been
trying to segment that one trial into smaller trials (so I can get rid of '
bad_times') by using the following code:

time = data.time{1,1};
bad_times = globals.bad_times_sorted; % a N*2 sorted double

cfg.begsample = [time(1); bad_times(:,2) + 1];
cfg.endsample = [bad_times(:,1) - 1; time(end)];

data_good = ft_redefinetrial(cfg, data);

However the code returns a data with only one trial.
(i.e. the resulting data_good consists of only one trial which correspond
to the time (time(1) : bad_times(1,1).)
The code is very simple and I didn't really expect it to behave this way.
Does anyone see why this is happening?
Any type of help would be appreciated.

Best regards,
Rachel Lee
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160727/b07ef84d/attachment.htm>

From icelandhouse at gmail.com  Thu Jul 28 09:20:34 2016
From: icelandhouse at gmail.com (Maris Skujevskis)
Date: Thu, 28 Jul 2016 09:20:34 +0200
Subject: [FieldTrip] Beamformer for S1 A1 responses with EEG
Message-ID: <CAKEvDieCL36r=uqfnvS48L5JS+6H2_p=MQ4hZW7U7zc7D=DsKA@mail.gmail.com>

Dear Fieldtrip community,

I am working on localizing primary sensory responses using the beamformer
technique. My subjects receive 'noisy' stimuli: tactile vibrations (0-100Hz
frequncy content) to both index fingers, OR 1-2kHz auditory noise stimuli
in both ears for 500 ms; I have 118 EEG channels and around 170 clean
trials for each modality per subject to work with. My results look ok at
the sensor level, but the sources look messy (for now...).

My question is: how accurately have you managed to
beamformer-source-localize primary somatosensory/auditory responses - say,
in a range from "not at all", "very vaguely/unreliably", "reasonably",
"quite accurately"?

I just want to know how successful you guys have been so I know what to
expect from EEG data, when to feel satisfied with the result I am getting.

Thanks a lot for your input!





On Wednesday, July 27, 2016, <fieldtrip-request at science.ru.nl> wrote:

> Send fieldtrip mailing list submissions to
>         fieldtrip at science.ru.nl <javascript:;>
>
> To subscribe or unsubscribe via the World Wide Web, visit
>         https://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 <javascript:;>
>
> You can reach the person managing the list at
>         fieldtrip-owner at science.ru.nl <javascript:;>
>
> When replying, please edit your Subject line so it is more specific
> than "Re: Contents of fieldtrip digest..."
>
>
> Today's Topics:
>
>    1. ft_databrowser error (Carmen Kung)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Wed, 27 Jul 2016 16:01:40 +1000
> From: Carmen Kung <carmen.kung at mq.edu.au <javascript:;>>
> To: <fieldtrip at science.ru.nl <javascript:;>>
> Subject: [FieldTrip] ft_databrowser error
> Message-ID: <d5ef871e-c3f5-fae8-4bcd-96e67d3fde96 at mq.edu.au <javascript:;>
> >
> Content-Type: text/plain; charset="utf-8"; Format="flowed"
>
> Dear fieldtripers,
>
> After running ft_definetrial and ft_preprocessing, we try to plot the
> data using ft_databrowser using the script at follow:
>
>
>  >> cfg = [];
>  >> ft_databrowser(cfg, data);
>
> But this is the error message we got:
>
> the input is raw data with 69 channels and 25 trials
> detected   0 visual artifacts
> Error using zeros
> Size inputs must be integers.
>
> Error in convert_event>artifact2artvec (line 179)
> artvec = zeros(length(artifact), endsample);
>
> Error in convert_event (line 103)
>      obj = artifact2artvec(obj,endsample);
>
> Error in ft_databrowser (line 501)
> artdata.trial{1}       = convert_event(artifact, 'boolvec', 'endsample',
> datendsample); % every artifact is a "channel"
>
>
> We did try to plot the raw *.cnt file (the cnt is recorded using curry
> 7) using ft_databrowser. It worked, but not the epoched data. This is
> the parameters we used for the cfg to run ft_definetrial and
> ft_preprocessing
>
>      cfg = [];
>      cfg.dataformat = 'ns_cnt';
>      cfg.headerformat= 'ns_cnt';
>      cfg.eventformat= 'ns_cnt';
>      cfg.trialdef.eventtype = 'stimtype';
>      cfg.trialdef.prestim = 0.5;
>      cfg.trialdef.poststim = 1.5;
>      cfg.trialdef.eventvalue = 114;
>      cfg.dataset = [dir filesep 'cnt' filesep subjectdata.subjectnr '_'
> subjectdata.initial '_' subjectdata.date '.cnt'];
>      cfg = ft_definetrial(cfg);
>      data = ft_preprocessing(cfg);
>
> The analysis is run on fieldtrip-20150522 and Matlab 2014a. Any help
> with this will be appreciated!
>
> Many thanks in advance,
> Carmen
>
> -------------- next part --------------
> An HTML attachment was scrubbed...
> URL: <
> http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160727/6df4adac/attachment-0001.html
> >
>
> ------------------------------
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl <javascript:;>
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
> End of fieldtrip Digest, Vol 68, Issue 28
> *****************************************
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160728/85c63583/attachment.htm>

From ruil3 at student.unimelb.edu.au  Thu Jul 28 09:58:07 2016
From: ruil3 at student.unimelb.edu.au (Rui Li)
Date: Thu, 28 Jul 2016 17:58:07 +1000
Subject: [FieldTrip] 'ft_redefinetrial' returning only one trial
In-Reply-To: <CAJir=i-pff2xP=HQD7Yn9mJcu45FM1+CwHcMVkjH7DoKZQc=XA@mail.gmail.com>
References: <CAJir=i-pff2xP=HQD7Yn9mJcu45FM1+CwHcMVkjH7DoKZQc=XA@mail.gmail.com>
Message-ID: <CALeb_wxz9vPh-BQnMebJ7Y--F7ve58fBouZJuDrWBRyfZFxSzw@mail.gmail.com>

Hi, Rachel

Probably because cfg.begsample and cfg.endsample should be sample points of
the begin and the end of the trails instead of the time;

I am not sure;

Regards,
Rui.

On Thu, Jul 28, 2016 at 3:43 PM, Nakyung Lee <rleese12 at berkeley.edu> wrote:

> Dear FieldTrip community,
>
> I've been having a problem calling 'ft_redefinetrial'.
> Basically with my raw data with one trial (simply 'data' here), I've been
> trying to segment that one trial into smaller trials (so I can get rid of '
> bad_times') by using the following code:
>
> time = data.time{1,1};
> bad_times = globals.bad_times_sorted; % a N*2 sorted double
>
> cfg.begsample = [time(1); bad_times(:,2) + 1];
> cfg.endsample = [bad_times(:,1) - 1; time(end)];
>
> data_good = ft_redefinetrial(cfg, data);
>
> However the code returns a data with only one trial.
> (i.e. the resulting data_good consists of only one trial which correspond
> to the time (time(1) : bad_times(1,1).)
> The code is very simple and I didn't really expect it to behave this way.
> Does anyone see why this is happening?
> Any type of help would be appreciated.
>
> Best regards,
> Rachel Lee
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160728/a1304ab0/attachment.htm>

From tineke.snijders at donders.ru.nl  Thu Jul 28 10:16:18 2016
From: tineke.snijders at donders.ru.nl (Snijders, T.M. (Tineke))
Date: Thu, 28 Jul 2016 08:16:18 +0000
Subject: [FieldTrip] topoplot CSD data
In-Reply-To: <B8F8D108-8781-473B-A68C-F8DA2E314821@gmail.com>
References: <B8F8D108-8781-473B-A68C-F8DA2E314821@gmail.com>
Message-ID: <815A9820E75FBC4F96B7CD3A8089D11C49E7619A@exprd04.hosting.ru.nl>

Hi Sandra,

I assume the input GA_Checker_og is a grand average where you have used cfg.keepindividual='yes', so you have the field .individual in the data instead of .avg.
So, you can either use cfg.keepindividual='no' when making your grand average, or I guess you can use ft_timelockanalysis after the ft_scalpcurrentdensity.

Cheers,
Tineke

________________________________
From: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl] on behalf of sandra guerreiro jacinto [sgj.umontreal at gmail.com]
Sent: Wednesday, July 27, 2016 11:07 PM
To: fieldtrip at science.ru.nl
Subject: [FieldTrip] topoplot CSD data

I’m having trouble topoplot my data after a ft_scalpcurrentdensity procedure.

I get an error message :
«  Error using topoplot_common (line 267)
cfg.parameter=avg is not present in data structure »

Is that correct I take my individuals and make the mean over all subjects in order to create the avg?

here is my code:

    cfg.method       ='spline';
    cfg.elec         = ft_read_sens('standard_waveguard64.elc');
    cfg.trials       = 'all' ;



    cfg.conductivity =  0.33;
    cfg.lambda       = 1e-05;
    cfg.order        =  4;
    cfg.degree       = 14;
    ft_csd_GA_Checker_og = ft_scalpcurrentdensity(cfg, GA_Checker_og)



    ft_csd_GA_Checker_og.avg = squeeze(mean(ft_csd_GA_Checker_og.trial,1));

the last line was my turnaround. I just want to make sure the procedure is correct.

Thank you!
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160728/2c1225cb/attachment.htm>

From icelandhouse at gmail.com  Thu Jul 28 17:28:14 2016
From: icelandhouse at gmail.com (Maris Skujevskis)
Date: Thu, 28 Jul 2016 17:28:14 +0200
Subject: [FieldTrip] Leadfield issues for EEG source reconstruction
Message-ID: <CAKEvDie6P1hK+etiEtwpAcOKb1R3Z2Ev++7Qb3u-=S0bXOg4cg@mail.gmail.com>

Dear Fieldtrip community,

The leadfields I have constructed for my EEG source reconstruction look
rather strange.
You can take a look at them here:
https://drive.google.com/folderview?id=0B9QSyDy3RhMIeFkxcm5kdmxOWVk&usp=drive_web

For a given electrode (red circle), the blue vectors represent the
direction and the strength of the leadfield. There are two issues:
(a) for some subjects there is an expected leadfield gradient' (closer
source points have larger vectors), while some others do not show this
pattern at all;
(b) some source points have disproportionately large/wrongly directed
vectors.

This is closely related to a previous fieldtrip discussion:
https://mailman.science.ru.nl/pipermail/fieldtrip/2015-March/009058.html ,
but in that discussion no conclusion/solution was reached.

Have you encountered these issues in your EEG source reconstruction and if
yes, how/did you manage to solve them?

Thanks a lot!
Maris
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160728/c7d3f2b5/attachment.htm>

From rleese12 at berkeley.edu  Thu Jul 28 18:01:57 2016
From: rleese12 at berkeley.edu (Nakyung Lee)
Date: Thu, 28 Jul 2016 09:01:57 -0700
Subject: [FieldTrip] 'ft_redefinetrial' returning only one trial
In-Reply-To: <CALeb_wxz9vPh-BQnMebJ7Y--F7ve58fBouZJuDrWBRyfZFxSzw@mail.gmail.com>
References: <CAJir=i-pff2xP=HQD7Yn9mJcu45FM1+CwHcMVkjH7DoKZQc=XA@mail.gmail.com>
 <CALeb_wxz9vPh-BQnMebJ7Y--F7ve58fBouZJuDrWBRyfZFxSzw@mail.gmail.com>
Message-ID: <CAJir=i-xwyE3KFR_0EBOr_7vubBLXMWbxYgmgo4k8=bUpi5c4g@mail.gmail.com>

Hi Rui,

In the code, the time (data.time{1,1}) is simply (1:NTime) (so it just
increments by 1).
Would it still matter?
Thank you for your reply.

Best,
Rachel

On Thu, Jul 28, 2016 at 12:58 AM, Rui Li <ruil3 at student.unimelb.edu.au>
wrote:

> Hi, Rachel
>
> Probably because cfg.begsample and cfg.endsample should be sample points
> of the begin and the end of the trails instead of the time;
>
> I am not sure;
>
> Regards,
> Rui.
>
> On Thu, Jul 28, 2016 at 3:43 PM, Nakyung Lee <rleese12 at berkeley.edu>
> wrote:
>
>> Dear FieldTrip community,
>>
>> I've been having a problem calling 'ft_redefinetrial'.
>> Basically with my raw data with one trial (simply 'data' here), I've
>> been trying to segment that one trial into smaller trials (so I can get rid
>> of 'bad_times') by using the following code:
>>
>> time = data.time{1,1};
>> bad_times = globals.bad_times_sorted; % a N*2 sorted double
>>
>> cfg.begsample = [time(1); bad_times(:,2) + 1];
>> cfg.endsample = [bad_times(:,1) - 1; time(end)];
>>
>> data_good = ft_redefinetrial(cfg, data);
>>
>> However the code returns a data with only one trial.
>> (i.e. the resulting data_good consists of only one trial which correspond
>> to the time (time(1) : bad_times(1,1).)
>> The code is very simple and I didn't really expect it to behave this way.
>> Does anyone see why this is happening?
>> Any type of help would be appreciated.
>>
>> Best regards,
>> Rachel Lee
>>
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160728/0d9bea57/attachment.htm>

From angela_rosink at live.nl  Thu Jul 28 19:42:30 2016
From: angela_rosink at live.nl (Angela Rosink)
Date: Thu, 28 Jul 2016 19:42:30 +0200
Subject: [FieldTrip] FW: ft_clusterplot
In-Reply-To: <DUB125-W198325EE91924C255FFD479D000@phx.gbl>
References: <DUB125-W198325EE91924C255FFD479D000@phx.gbl>
Message-ID: <DUB125-W1384CA7526542D3452CF0D9D000@phx.gbl>

Dear community,
My name is Angela and I am working in the UvA Sleeplab in Amsterdam on sleep and memory. Currently I am analysing EEG data and want to make time frequency plots with corresponding topoplots revealing statistical differences between conditions. I already got time frequency plots, but I'm having problems with creating the topoplots and statistics. 
I preprocessed my data, did time frequency analysis on it with ft_freqanalysis, grandaveraged the single TFs across conditions with ft_freqgrandaverage (and plotted those results) and performed cluster based permutation statistics on it with ft_freqstatistics. I tried using ft_clusterplot to assess topographies with highlighted clusters originating from ft_freqstatistics. 
When I called it, I got several results ranging from not being able to plot anything because dimensions were wrong, to 57 clusterplots. (why?)I got the message that dimord dimensions were exceeded, its not supporting chan_freq_time. Because I have a priori knowledge, I averaged over a frequency range with: cfg.frequency  = [5 8]; cfg.avgoverfreq  = 'yes';. Then I was able to plot, but giving strange results. (See attachtment 1-4). I tried cfg.zlim with maxmin and also without specifing it, without result.In order to solve the dimension problem I used ft_freqdescriptives, also shown at the example at your website, resulting in a lot of topographies which I cannot use. I tried to plot cfg.parameter = 'stat' and with cfg.parameter = 'raweffect', where stat is the outcome of ft_freqstatistics and stat.raweffect = grandavg1.powspctrm - grandavg3 as shown at http://www.fieldtriptoolbox.org/tutorial/cluster_permutation_freq at: Between trial experiments under: Plotting the results. But then again I'm getting an error: Error using ft_clusterplot (line 151), unsupported dimord chan_unknown_time.  Because the grandaveraged data with freqdescriptives is again 3D, chan_freq_time.
The cfg and data I use are as follows:>> display(cfg)
cfg = 
        alpha: 0.0250    parameter: 'raweffect'       layout: 'waveguard_layout_064ch2.lay'
>> display(stat)
stat = 
                   prob: [65x1x351 double]            posclusters: [1x2 struct]    posclusterslabelmat: [65x1x351 double]        posdistribution: [1x500 double]            negclusters: [1x3 struct]    negclusterslabelmat: [65x1x351 double]        negdistribution: [1x500 double]                cirange: [65x1x351 double]                   mask: [65x1x351 logical]                   stat: [65x1x351 double]                    ref: [65x1x351 double]                 dimord: 'chan_freq_time'                   freq: 6.4898                  label: {65x1 cell}                   time: [1x351 double]                    cfg: [1x1 struct]              raweffect: [65x35x351 double]
>> display(grandavg1)
grandavg1 = 
    powspctrm: [4-D double]        label: {65x1 cell}         freq: [1x35 double]         time: [1x351 double]       dimord: 'subj_chan_freq_time'          cfg: [1x1 struct]
>> display(grandavg3)
grandavg3 = 
    powspctrm: [4-D double]        label: {65x1 cell}         freq: [1x35 double]         time: [1x351 double]       dimord: 'subj_chan_freq_time'          cfg: [1x1 struct]
Can someone tell me if there is something wrong with the cfg settings I use or if I am doing something wrong at any other place?  Any help would be appreciated!
I also included my script starting from time frequency analysis. I used only 2 subjects per condition (condition 3 being control) only to try out my script, because I once already processed my data wrongly and I want to avoid that I have to redo all my data over and over. I'm not the best programmer, but it should give an idea of my most recent settings. 
All the best,Angela
 		 	   		   		 	   		  
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160728/25afcc6c/attachment.htm>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: 3.png
Type: image/png
Size: 154986 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160728/25afcc6c/attachment.png>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: 4.png
Type: image/png
Size: 120671 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160728/25afcc6c/attachment-0001.png>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: Cluster calculation.docx
Type: application/vnd.openxmlformats-officedocument.wordprocessingml.document
Size: 14663 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160728/25afcc6c/attachment.docx>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: 1.png
Type: image/png
Size: 166140 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160728/25afcc6c/attachment-0002.png>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: 2.png
Type: image/png
Size: 167393 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160728/25afcc6c/attachment-0003.png>

From elam4hcp at gmail.com  Thu Jul 28 23:43:07 2016
From: elam4hcp at gmail.com (Jennifer Elam)
Date: Thu, 28 Jul 2016 16:43:07 -0500
Subject: [FieldTrip] Register NOW for the 2016 HCP Course (Boston,
	28 August - September 1)!
Message-ID: <CAJbMWh6YXV9TH56BtiOj294a6tpCfzB-3bXHfStLCexWPe5Zaw@mail.gmail.com>

The 2016 HCP Course: “Exploring the Human Connectome”
<http://humanconnectome.org/courses/2016/exploring-the-human-connectome.php>
  starts in one month: August 28-September 1 in Boston!

There are still some open slots, but we encourage you to Register
<https://www.humanconnectome.org/courses/course-registration.php> today!

The HCP Course is the best place to learn directly from HCP investigators
and to explore HCP data and methods. This year's course will provide
hands-on experience in working with the new, multi-modal human cortical
parcellation (Glasser et al., Nature, July 20,
http://www.ncbi.nlm.nih.gov/pubmed/27437579) and with the “HCP-Style”
paradigm for data acquisition, analysis, and sharing (Glasser et al.,
Nature Neuroscience, in press).

The 2016 HCP Course curriculum (see the full Course Schedule
<https://www.humanconnectome.org/courses/2016/exploring-the-human-connectome.php#schedule>)
includes over *20 Lectures and 15 Practicals* and will be presented by 19
HCP investigators and staff
<https://www.humanconnectome.org/courses/2016/exploring-the-human-connectome.php#faculty>
and
and will be held over *five full days: August 28-September 1
(Sunday-Thursday) *at the Joseph B. Martin Conference Center at Harvard
Medical School <http://www.theconfcenter.hms.harvard.edu/>, in Boston,
Massachusetts, USA.

If you have any questions, please contact us at
hcpcourse at humanconnectome.org

Hope to see you in Boston!

Best,
2016 HCP Course Staff


Jennifer Elam, Ph.D.
Scientific Outreach, Human Connectome Project
Washington University School of Medicine
Department of Neuroscience, Box 8108
660 South Euclid Avenue
St. Louis, MO 63110
314-362-9387
elam at wustl.edu
www.humanconnectome.org
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160728/cec9dd61/attachment.htm>

From ruil3 at student.unimelb.edu.au  Fri Jul 29 06:19:31 2016
From: ruil3 at student.unimelb.edu.au (Rui Li)
Date: Fri, 29 Jul 2016 14:19:31 +1000
Subject: [FieldTrip] 'ft_redefinetrial' returning only one trial
In-Reply-To: <CAJir=i-xwyE3KFR_0EBOr_7vubBLXMWbxYgmgo4k8=bUpi5c4g@mail.gmail.com>
References: <CAJir=i-pff2xP=HQD7Yn9mJcu45FM1+CwHcMVkjH7DoKZQc=XA@mail.gmail.com>
 <CALeb_wxz9vPh-BQnMebJ7Y--F7ve58fBouZJuDrWBRyfZFxSzw@mail.gmail.com>
 <CAJir=i-xwyE3KFR_0EBOr_7vubBLXMWbxYgmgo4k8=bUpi5c4g@mail.gmail.com>
Message-ID: <CALeb_wx4xZap2QaT6s4vDH09n8cFnQOyO9BquWHAvaUuJM_KBA@mail.gmail.com>

hi,

cfg.begsample = [time(1); bad_times(:,2) + 1];
cfg.endsample = [bad_times(:,1) - 1; time(end)];

How about the rest three time samples: bad_times(:,2)+1, bad_times(:,1)-1
and time(end)?

Are they samples or the time?

Regards,
Rui.

On Fri, Jul 29, 2016 at 2:01 AM, Nakyung Lee <rleese12 at berkeley.edu> wrote:

> Hi Rui,
>
> In the code, the time (data.time{1,1}) is simply (1:NTime) (so it just
> increments by 1).
> Would it still matter?
> Thank you for your reply.
>
> Best,
> Rachel
>
> On Thu, Jul 28, 2016 at 12:58 AM, Rui Li <ruil3 at student.unimelb.edu.au>
> wrote:
>
>> Hi, Rachel
>>
>> Probably because cfg.begsample and cfg.endsample should be sample points
>> of the begin and the end of the trails instead of the time;
>>
>> I am not sure;
>>
>> Regards,
>> Rui.
>>
>> On Thu, Jul 28, 2016 at 3:43 PM, Nakyung Lee <rleese12 at berkeley.edu>
>> wrote:
>>
>>> Dear FieldTrip community,
>>>
>>> I've been having a problem calling 'ft_redefinetrial'.
>>> Basically with my raw data with one trial (simply 'data' here), I've
>>> been trying to segment that one trial into smaller trials (so I can get rid
>>> of 'bad_times') by using the following code:
>>>
>>> time = data.time{1,1};
>>> bad_times = globals.bad_times_sorted; % a N*2 sorted double
>>>
>>> cfg.begsample = [time(1); bad_times(:,2) + 1];
>>> cfg.endsample = [bad_times(:,1) - 1; time(end)];
>>>
>>> data_good = ft_redefinetrial(cfg, data);
>>>
>>> However the code returns a data with only one trial.
>>> (i.e. the resulting data_good consists of only one trial which
>>> correspond to the time (time(1) : bad_times(1,1).)
>>> The code is very simple and I didn't really expect it to behave this way.
>>> Does anyone see why this is happening?
>>> Any type of help would be appreciated.
>>>
>>> Best regards,
>>> Rachel Lee
>>>
>>>
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>
>>
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160729/6ec52215/attachment.htm>

From angela_rosink at live.nl  Fri Jul 29 10:45:31 2016
From: angela_rosink at live.nl (Angela Rosink)
Date: Fri, 29 Jul 2016 10:45:31 +0200
Subject: [FieldTrip] Unsupported dimord in ft_clusterplot
Message-ID: <DUB125-W883E6146361DFCA96C32AD9D010@phx.gbl>

Dear community,I noticed that my previous email had a wrong layout, therefore I'm posting my question again. My name is Angela and I am working in the UvA Sleeplab in Amsterdam on sleep and memory. Currently I am analysing EEG data and want to make time frequency plots with corresponding topoplots revealing statistical differences between conditions. I already got time frequency plots, but I'm having problems with creating the topoplots and statistics. I preprocessed my data, did time frequency analysis on it with ft_freqanalysis, grandaveraged the single TFs across conditions with ft_freqgrandaverage (and plotted those results) and performed cluster based permutation statistics on it with ft_freqstatistics. I tried using ft_clusterplot to assess topographies with highlighted clusters originating from ft_freqstatistics, but it's not working.When I call it, I got the message that dimord dimensions were exceeded, its not supporting chan_freq_time. Because I have a priori knowledge, I averaged over a frequency range with: cfg.frequency  = [5 8]; cfg.avgoverfreq  = 'yes'; during the ft_freqstatistics. Then I was able to plot, but giving strange results. (See on jumpshare.com: http://jmp.sh/qXfKbwY). I tried cfg.zlim with maxmin and also without specifing it, without result.In order to solve the dimension problem I used ft_freqdescriptives, also shown at the example at your website. I tried to plot cfg.parameter = 'stat' and with cfg.parameter = 'raweffect', where stat is the outcome of ft_freqstatistics and stat.raweffect = grandavg1.powspctrm - grandavg3.powspctrm as shown at http://www.fieldtriptoolbox.org/tutorial/cluster_permutation_freq at: Between trial experiments under: Plotting the results. But then again I'm getting an error: Error using ft_clusterplot (line 151), unsupported dimord chan_unknown_time.  Because the grandaveraged data with freqdescriptives is again 3D, chan_freq_time.The cfg and data I use are as follows:>> display(cfg)cfg =         alpha: 0.0250    parameter: 'raweffect'       layout: 'waveguard_layout_064ch2.lay'>> display(stat)stat =                    prob: [65x1x351 double]            posclusters: [1x2 struct]    posclusterslabelmat: [65x1x351 double]        posdistribution: [1x500 double]            negclusters: [1x3 struct]    negclusterslabelmat: [65x1x351 double]        negdistribution: [1x500 double]                cirange: [65x1x351 double]                   mask: [65x1x351 logical]                   stat: [65x1x351 double]                    ref: [65x1x351 double]                 dimord: 'chan_freq_time'                   freq: 6.4898                  label: {65x1 cell}                   time: [1x351 double]                    cfg: [1x1 struct]               raweffect: [65x35x351 double]>> display(grandavg1)grandavg1 =     powspctrm: [4-D double]        label: {65x1 cell}         freq: [1x35 double]         time: [1x351 double]       dimord: 'subj_chan_freq_time'          cfg: [1x1 struct]>> display(grandavg3)grandavg3 =     powspctrm: [4-D double]        label: {65x1 cell}         freq: [1x35 double]         time: [1x351 double]       dimord: 'subj_chan_freq_time'           cfg: [1x1 struct]Can someone tell me if there is something wrong with the cfg settings I use or if I am doing something wrong at any other place?  Any help would be appreciated!I also included my script starting from time frequency analysis. I used only 2 subjects per condition (condition 3 being control) only to try out my script, because I once already processed my data wrongly and I want to avoid that I have to redo all my data over and over. See on jumpshare.com: http://jmp.sh/qXfKbwY I'm not the best programmer, but it should give an idea of my most recent settings. All the best,Angela 		 	   		  
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160729/24857207/attachment.htm>

From rleese12 at berkeley.edu  Sat Jul 30 00:37:57 2016
From: rleese12 at berkeley.edu (Nakyung Lee)
Date: Fri, 29 Jul 2016 15:37:57 -0700
Subject: [FieldTrip] 'ft_redefinetrial' returning only one trial
In-Reply-To: <CALeb_wx4xZap2QaT6s4vDH09n8cFnQOyO9BquWHAvaUuJM_KBA@mail.gmail.com>
References: <CAJir=i-pff2xP=HQD7Yn9mJcu45FM1+CwHcMVkjH7DoKZQc=XA@mail.gmail.com>
 <CALeb_wxz9vPh-BQnMebJ7Y--F7ve58fBouZJuDrWBRyfZFxSzw@mail.gmail.com>
 <CAJir=i-xwyE3KFR_0EBOr_7vubBLXMWbxYgmgo4k8=bUpi5c4g@mail.gmail.com>
 <CALeb_wx4xZap2QaT6s4vDH09n8cFnQOyO9BquWHAvaUuJM_KBA@mail.gmail.com>
Message-ID: <CAJir=i_J1maFEc3+OnciTnXqo5vJ9eWxwyeezQMY2LNYnEuwuw@mail.gmail.com>

Hi Rui,

Again thank you for your reply.
They are samples as well.
Hence the elements of the first row of bad_times, which is 141000, 146000,
each represents the 141000th and 146000th indices of time and trial.
And since time is simply and array of consecutive integers (so it acts just
like indices) time(end) behaves just like a sample as well.

Best,
Rachel

On Thu, Jul 28, 2016 at 9:19 PM, Rui Li <ruil3 at student.unimelb.edu.au>
wrote:

> hi,
>
> cfg.begsample = [time(1); bad_times(:,2) + 1];
> cfg.endsample = [bad_times(:,1) - 1; time(end)];
>
> How about the rest three time samples: bad_times(:,2)+1, bad_times(:,1)-1
> and time(end)?
>
> Are they samples or the time?
>
> Regards,
> Rui.
>
> On Fri, Jul 29, 2016 at 2:01 AM, Nakyung Lee <rleese12 at berkeley.edu>
> wrote:
>
>> Hi Rui,
>>
>> In the code, the time (data.time{1,1}) is simply (1:NTime) (so it just
>> increments by 1).
>> Would it still matter?
>> Thank you for your reply.
>>
>> Best,
>> Rachel
>>
>> On Thu, Jul 28, 2016 at 12:58 AM, Rui Li <ruil3 at student.unimelb.edu.au>
>> wrote:
>>
>>> Hi, Rachel
>>>
>>> Probably because cfg.begsample and cfg.endsample should be sample points
>>> of the begin and the end of the trails instead of the time;
>>>
>>> I am not sure;
>>>
>>> Regards,
>>> Rui.
>>>
>>> On Thu, Jul 28, 2016 at 3:43 PM, Nakyung Lee <rleese12 at berkeley.edu>
>>> wrote:
>>>
>>>> Dear FieldTrip community,
>>>>
>>>> I've been having a problem calling 'ft_redefinetrial'.
>>>> Basically with my raw data with one trial (simply 'data' here), I've
>>>> been trying to segment that one trial into smaller trials (so I can get rid
>>>> of 'bad_times') by using the following code:
>>>>
>>>> time = data.time{1,1};
>>>> bad_times = globals.bad_times_sorted; % a N*2 sorted double
>>>>
>>>> cfg.begsample = [time(1); bad_times(:,2) + 1];
>>>> cfg.endsample = [bad_times(:,1) - 1; time(end)];
>>>>
>>>> data_good = ft_redefinetrial(cfg, data);
>>>>
>>>> However the code returns a data with only one trial.
>>>> (i.e. the resulting data_good consists of only one trial which
>>>> correspond to the time (time(1) : bad_times(1,1).)
>>>> The code is very simple and I didn't really expect it to behave this
>>>> way.
>>>> Does anyone see why this is happening?
>>>> Any type of help would be appreciated.
>>>>
>>>> Best regards,
>>>> Rachel Lee
>>>>
>>>>
>>>> _______________________________________________
>>>> fieldtrip mailing list
>>>> fieldtrip at donders.ru.nl
>>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>>
>>>
>>>
>>> _______________________________________________
>>> fieldtrip mailing list
>>> fieldtrip at donders.ru.nl
>>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>>
>>
>>
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl
>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160729/ecb9985a/attachment.htm>

From laxmi.shaw22 at gmail.com  Sun Jul 31 12:22:24 2016
From: laxmi.shaw22 at gmail.com (Laxmi Shaw)
Date: Sun, 31 Jul 2016 15:52:24 +0530
Subject: [FieldTrip] queries_related to_error
Message-ID: <CABWJU2QjWrJsjbANqnQ8UZcjQfrLQCqzQ8LzMM43AdNQcyAQFg@mail.gmail.com>

Dear Fieldtrip users,

Suddenly i got one error while compiling any fieldtrip function based
code.Please need your help to remove this error. I have attach the screen
shot of that matlab program.
[image: Inline image 1]
Your helps always been appreciated.


Regards
-- 
Laxmi Shaw
Research Scholar(PhD)
IIT Kharagpur
West Bengal
Ph no-08388837821
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160731/9c283250/attachment.htm>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: image.png
Type: image/png
Size: 103003 bytes
Desc: not available
URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/attachments/20160731/9c283250/attachment.png>