From josyjoyvarghese at gmail.com  Wed Jan  3 07:40:19 2018
From: josyjoyvarghese at gmail.com (josy joy)
Date: Wed, 3 Jan 2018 12:10:19 +0530
Subject: [FieldTrip] difficulty in importing data from eeg to fieldtrip
Message-ID: <CAOW5AWC2EiZa7pL6cLJGbXEsPqZWsVy9wUnGveZ6M9qnj9FQtA@mail.gmail.com>

Dear sir/mam

Im a fresher to the firldtrip but i do have matlab aand eeglab basic
experience.

i am working on eeg analysis using fieldtrip,now im facing the difficulty
in importing the eeg data from eeglab(.set format).

please solve my problem
thanks
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From a.stolk8 at gmail.com  Wed Jan  3 07:51:48 2018
From: a.stolk8 at gmail.com (Arjen Stolk)
Date: Tue, 2 Jan 2018 22:51:48 -0800
Subject: [FieldTrip] difficulty in importing data from eeg to fieldtrip
In-Reply-To: <CAOW5AWC2EiZa7pL6cLJGbXEsPqZWsVy9wUnGveZ6M9qnj9FQtA@mail.gmail.com>
References: <CAOW5AWC2EiZa7pL6cLJGbXEsPqZWsVy9wUnGveZ6M9qnj9FQtA@mail.gmail.com>
Message-ID: <CAAiwptQ_x7fNVa77cLdp=8J-TuVma713dO-THUJT4vSAn2DL0A@mail.gmail.com>

Hi Josy,

The following wiki page might provide a fruitful starting point for
converting data between fieldtrip and eeglab:
http://www.fieldtriptoolbox.org/getting_started/eeglab

Best,
Arjen

On Tue, Jan 2, 2018 at 10:40 PM, josy joy <josyjoyvarghese at gmail.com> wrote:

> Dear sir/mam
>
> Im a fresher to the firldtrip but i do have matlab aand eeglab basic
> experience.
>
> i am working on eeg analysis using fieldtrip,now im facing the difficulty
> in importing the eeg data from eeglab(.set format).
>
> please solve my problem
> thanks
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From justintracyfleming at gmail.com  Fri Jan  5 22:43:37 2018
From: justintracyfleming at gmail.com (Justin Fleming)
Date: Fri, 5 Jan 2018 16:43:37 -0500
Subject: [FieldTrip] Time-frequency analysis with varying length trials
Message-ID: <CACo=i5XqqiPJsqw4aD3kXRfi0wfhs6GGKHui=nZTL92iCeXEsA@mail.gmail.com>

Hello all,

I'm trying to do some exploratory spectral analysis on EEG data from a
reaction time experiment, in which the trial ends as soon as the subject
detects a target. The trails are up to 6 sec in length, but they average
closer to 2 sec.

My goal is to make time-frequency plots, using the multi-taper method,
aligned to the response (end of trial), rather than the beginning. I tried
the following approach first:
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From justintracyfleming at gmail.com  Fri Jan  5 22:52:00 2018
From: justintracyfleming at gmail.com (Justin Fleming)
Date: Fri, 5 Jan 2018 16:52:00 -0500
Subject: [FieldTrip] Time-frequency analysis with varying length trials
Message-ID: <CACo=i5WpVvJhUtVOKj8vc+-KVUPYLJG0BAnBaXUr1YVk9H38Cw@mail.gmail.com>

Hello all,

I'm trying to do some exploratory spectral analysis on EEG data from a
reaction time experiment, in which the trial ends as soon as the subject
detects a target. The trails are up to 6 sec in length, but they average
closer to 2-3 sec.

My goal is to make time-frequency plots, using the multi-taper method,
aligned to the end of the trial (subject response) rather than the
beginning. I tried the following approach first:

   - Flip each trial’s data in time, such that sample 1 is now the end of
   the trial
   - Nan-pad each trial so they all have the same number of samples (6 sec
   * 256 Hz = 1536 samples).
   - Perform multi-taper spectral analysis with ft_freqanalysis

It seems that FieldTrip isn’t ignoring the NaN’s when calculating the power
at each time point. Effectively, I’m limiting my data to the shortest trial
duration rather than plotting it out to the longest time point.

Any help on NaN removal with ft_freqanalysis, or if there’s a smarter way
to align time-frequency analyses to the ends of trials, would be much
appreciated!

Thanks,
-
Justin F.
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From fereshte.ramezani at gmail.com  Mon Jan  8 08:12:39 2018
From: fereshte.ramezani at gmail.com (Fereshte)
Date: Mon, 08 Jan 2018 07:12:39 +0000
Subject: [FieldTrip] Align a predefined grid source model to an exciting
	head model
Message-ID: <CAAdxBZqsiLcdKJ4=0UtdBkis=kTNs6XCTuNr9J4oz_3SkMi9OQ@mail.gmail.com>

Dear Experts,
How can I align a predefined grid source model to an existing head model? (
I have aligned the electrodes to  the headmodel manually but I'm not sure
how to align a dipole position on the headmodel).
Looking forward to hearing from you!
Regards,
Fereshte Ramezani
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From tzvetan.popov at uni-konstanz.de  Mon Jan  8 09:09:55 2018
From: tzvetan.popov at uni-konstanz.de (Tzvetan Popov)
Date: Mon, 8 Jan 2018 09:09:55 +0100
Subject: [FieldTrip] Align a predefined grid source model to an exciting
 head model
In-Reply-To: <CAAdxBZqsiLcdKJ4=0UtdBkis=kTNs6XCTuNr9J4oz_3SkMi9OQ@mail.gmail.com>
References: <CAAdxBZqsiLcdKJ4=0UtdBkis=kTNs6XCTuNr9J4oz_3SkMi9OQ@mail.gmail.com>
Message-ID: <120BD4FE-7395-4473-ABB6-EF59CEE4EB75@uni-konstanz.de>

Hi Fereshte,

this is the relevant tutorial that’d help you out: http://www.fieldtriptoolbox.org/tutorial/sourcemodel#subject-specific_grids_that_are_equivalent_across_subjects_in_normalized_space <http://www.fieldtriptoolbox.org/tutorial/sourcemodel#subject-specific_grids_that_are_equivalent_across_subjects_in_normalized_space>
good luck
tzvetan


> Am 08.01.2018 um 08:12 schrieb Fereshte <fereshte.ramezani at gmail.com>:
> 
> Dear Experts,
> How can I align a predefined grid source model to an existing head model? ( I have aligned the electrodes to  the headmodel manually but I'm not sure how to align a dipole position on the headmodel).
> Looking forward to hearing from you!
> Regards,
> Fereshte Ramezani 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From holmgren.jostein at gmail.com  Mon Jan  8 14:46:16 2018
From: holmgren.jostein at gmail.com (Jostein Holmgren)
Date: Mon, 8 Jan 2018 13:46:16 +0000
Subject: [FieldTrip] Post-doc position available @ Wellcome Centre for
 Integrative Neuroimaging, University of Oxford
Message-ID: <A26C2EA0-7106-4165-AD23-286AA24D13B4@gmail.com>

Dear All,

We are looking to recruit a talented post doc to join our team exploring EEG markers of depth of anaesthesia. Full details of the post are attached below. 

Please pass this email on to suitable candidates.

Best wishes,
Jostein

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

Jostein Holmgren
DPhil Student (PRS)
Nuffield Department of Clinical Neurosciences
Wellcome Centre for Integrative Neuroimaging, FMRIB Building
University of Oxford

-----------------------------------------------------------------------------------------------------
Postdoctoral Researcher in Signal Processing
Wellcome Centre for Integrative Neuroimaging (WIN), University of Oxford
Grade 7: £31,604 - £38,833 with a discretionary range to £42,418 p.a.

The successful candidate will develop and implement a new EEG depth of anaesthesia monitor that uses an individualised biomarker of perception loss called slow wave activity saturation (SWAS). The post holder will become a key member of the SWAS research team headed by Dr Katie Warnaby, and will lead software development and implementation of a prototype EEG monitoring system. 

You will have a PhD/DPhil in a relevant discipline, and possess sufficient specialist knowledge to work within the established research programme. Experience of EEG data analysis and developing real-time brain-computer and graphic user interfaces is highly desirable. 

To apply and for further details see https://www.recruit.ox.ac.uk/pls/hrisliverecruit/erq_jobspec_version_4.display_form <https://www.recruit.ox.ac.uk/pls/hrisliverecruit/erq_jobspec_version_4.display_form>. Please contact Katie Warnaby with informal enquiries on katie.warnaby at ndcn.ox.ac.uk <mailto:katie.warnaby at ndcn.ox.ac.uk>. 

Interviews will take place at the end of January for start as soon as possible after. The post is funded by the Medical Research Council (MRC) Development Pathway Funding Scheme. 

————————
Dr Katie Warnaby
Senior Research Scientist
Wellcome Centre for Integrative Neuroimaging @ FMRIB
University of Oxford

Tel: +44 1865 611 465
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From tom.marshall at psy.ox.ac.uk  Tue Jan  9 17:27:25 2018
From: tom.marshall at psy.ox.ac.uk (Tom Marshall)
Date: Tue, 9 Jan 2018 16:27:25 +0000
Subject: [FieldTrip] error in ft_prepare_headmodel
Message-ID: <39853797796B114D8DE552AC4996EA6835C4BD60@MBX11.ad.oak.ox.ac.uk>

Howdy 'Trippers,

I got a weird error when trying to create a template headmodel using ft_prepare_headmodel (basically just following the steps in the tutorial 'Creating a sourcemodel for source-reconstruction of MEG or EEG data').

After loading and segmenting the template brain I called ft_prepare_headmodel using the suggested parameters.

cfg          = [];
cfg.method   = 'singleshell';
template_headmodel = ft_prepare_headmodel(cfg, template_seg);

This gave the following error.

Error using ft_notification (line 314)
please specificy cfg.tissue and pass an appropriate segmented MRI as input data

Error in ft_error (line 39)
  ft_notification(varargin{:});

Error in ft_prepare_headmodel (line 354)
          ft_error('please specificy cfg.tissue and pass an appropriate segmented
          MRI as input data')

So I added cfg.tissue...

cfg          = [];
cfg.method   = 'singleshell';
cfg.tissue   = 'brain';
template_headmodel = ft_prepare_headmodel(cfg, template_seg);

...and this upset fieldtrip. After printing 'smoothing brain with a 5-voxel FWHM kernel', it hung for 10-15 minutes, then threw an error with lots of 'Missing symbol' statements (see below - there are a few hundred more, I just copypasted the last two).

Missing symbol '_vm_allocate' required by
'/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'
Missing symbol '_vm_deallocate' required by
'/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'.

Error in spm_smooth>smooth1 (line 105)
spm_conv_vol(P,Q,x,y,z,-[i,j,k]);

Error in spm_smooth (line 40)
    smooth1(P,Q,s,dtype);

Error in volumesmooth (line 18)
spm_smooth(output, output, fwhm);

Error in ft_datatype_segmentation (line 229)
          brain = volumesmooth(brain,    smooth,    'brain');

Error in prepare_mesh_segmentation (line 95)
    mri = ft_datatype_segmentation(mri, 'segmentationstyle', 'probabilistic',
    'hasbrain', 'yes');

Error in ft_prepare_mesh (line 147)
    bnd = prepare_mesh_segmentation(cfg, mri);

Error in ft_prepare_headmodel (line 337)
        geometry = ft_prepare_mesh(tmpcfg, data);

It seems like the problem is somewhere deep down in spm commands that fieldtrip is calling, so maybe nobody has a clue. I'm hoping somebody has seen this before and knows of a fix...

In case it's relevant: I'm running fieldtrip-20170726 in matlab R2017a on a mac.

And ideas?

Best,
Tom
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From jan.schoffelen at donders.ru.nl  Wed Jan 10 09:36:10 2018
From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs))
Date: Wed, 10 Jan 2018 08:36:10 +0000
Subject: [FieldTrip] error in ft_prepare_headmodel
In-Reply-To: <39853797796B114D8DE552AC4996EA6835C4BD60@MBX11.ad.oak.ox.ac.uk>
References: <39853797796B114D8DE552AC4996EA6835C4BD60@MBX11.ad.oak.ox.ac.uk>
Message-ID: <4BA0D72D-FC3B-4AF9-BDF2-08E60C01D689@donders.ru.nl>

Dear Tom,

To me, this looks like a platform/MATLAB version specific issue with the compiled mex-files. Anecdotally, MATLAB2017a on a Mac suffers from not knowing to handle the precompiled stuff that comes with FieldTrip/SPM. Either you could use a lower matlab version (e.g. 2016b, which as far as I know does not suffer from this), or you could try and recompile the affected mex-files from the original c-code with the matlab mex-command. See http://bit.ly/2DeuNlX for more info.

Best wishes,
JM


On 9 Jan 2018, at 17:27, Tom Marshall <tom.marshall at psy.ox.ac.uk<mailto:tom.marshall at psy.ox.ac.uk>> wrote:

Howdy 'Trippers,

I got a weird error when trying to create a template headmodel using ft_prepare_headmodel (basically just following the steps in the tutorial 'Creating a sourcemodel for source-reconstruction of MEG or EEG data').

After loading and segmenting the template brain I called ft_prepare_headmodel using the suggested parameters.

cfg          = [];
cfg.method   = 'singleshell';
template_headmodel = ft_prepare_headmodel(cfg, template_seg);

This gave the following error.

Error using ft_notification (line 314)
please specificy cfg.tissue and pass an appropriate segmented MRI as input data

Error in ft_error (line 39)
  ft_notification(varargin{:});

Error in ft_prepare_headmodel (line 354)
          ft_error('please specificy cfg.tissue and pass an appropriate segmented
          MRI as input data')

So I added cfg.tissue...

cfg          = [];
cfg.method   = 'singleshell';
cfg.tissue   = 'brain';
template_headmodel = ft_prepare_headmodel(cfg, template_seg);

...and this upset fieldtrip. After printing 'smoothing brain with a 5-voxel FWHM kernel', it hung for 10-15 minutes, then threw an error with lots of 'Missing symbol' statements (see below - there are a few hundred more, I just copypasted the last two).

Missing symbol '_vm_allocate' required by
'/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'
Missing symbol '_vm_deallocate' required by
'/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'.

Error in spm_smooth>smooth1 (line 105)
spm_conv_vol(P,Q,x,y,z,-[i,j,k]);

Error in spm_smooth (line 40)
    smooth1(P,Q,s,dtype);

Error in volumesmooth (line 18)
spm_smooth(output, output, fwhm);

Error in ft_datatype_segmentation (line 229)
          brain = volumesmooth(brain,    smooth,    'brain');

Error in prepare_mesh_segmentation (line 95)
    mri = ft_datatype_segmentation(mri, 'segmentationstyle', 'probabilistic',
    'hasbrain', 'yes');

Error in ft_prepare_mesh (line 147)
    bnd = prepare_mesh_segmentation(cfg, mri);

Error in ft_prepare_headmodel (line 337)
        geometry = ft_prepare_mesh(tmpcfg, data);

It seems like the problem is somewhere deep down in spm commands that fieldtrip is calling, so maybe nobody has a clue. I'm hoping somebody has seen this before and knows of a fix...

In case it's relevant: I'm running fieldtrip-20170726 in matlab R2017a on a mac.

And ideas?

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

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From fereshte.ramezani at gmail.com  Wed Jan 10 09:53:17 2018
From: fereshte.ramezani at gmail.com (Fereshte)
Date: Wed, 10 Jan 2018 08:53:17 +0000
Subject: [FieldTrip] Align a predefined grid source model to an exciting
 head model
In-Reply-To: <120BD4FE-7395-4473-ABB6-EF59CEE4EB75@uni-konstanz.de>
References: <CAAdxBZqsiLcdKJ4=0UtdBkis=kTNs6XCTuNr9J4oz_3SkMi9OQ@mail.gmail.com>
 <120BD4FE-7395-4473-ABB6-EF59CEE4EB75@uni-konstanz.de>
Message-ID: <CAAdxBZo4ybNv40gMR++VRKyopfHqEgKSkpThEjbqBYmTE9BfYw@mail.gmail.com>

Dear Txvetan,
Thank you for your answer. How does the filedtrip modify the head model
coordinate system if no coordinate is defined for the mri image given (to
make the FEM head model) by user?
Thanks in advance!
Regards,
Fereshte
On Mon, Jan 8, 2018 at 11:41 AM Tzvetan Popov <tzvetan.popov at uni-konstanz.de>
wrote:

> Hi Fereshte,
>
> this is the relevant tutorial that’d help you out:
> http://www.fieldtriptoolbox.org/tutorial/sourcemodel#subject-specific_grids_that_are_equivalent_across_subjects_in_normalized_space
> good luck
> tzvetan
>
>
> Am 08.01.2018 um 08:12 schrieb Fereshte <fereshte.ramezani at gmail.com>:
>
> Dear Experts,
> How can I align a predefined grid source model to an existing head model?
> ( I have aligned the electrodes to  the headmodel manually but I'm not sure
> how to align a dipole position on the headmodel).
> Looking forward to hearing from you!
> Regards,
> Fereshte Ramezani
>
> _______________________________________________
> 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
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From tzvetan.popov at uni-konstanz.de  Wed Jan 10 11:08:24 2018
From: tzvetan.popov at uni-konstanz.de (Tzvetan Popov)
Date: Wed, 10 Jan 2018 11:08:24 +0100
Subject: [FieldTrip] Align a predefined grid source model to an exciting
 head model
In-Reply-To: <CAAdxBZo4ybNv40gMR++VRKyopfHqEgKSkpThEjbqBYmTE9BfYw@mail.gmail.com>
References: <CAAdxBZqsiLcdKJ4=0UtdBkis=kTNs6XCTuNr9J4oz_3SkMi9OQ@mail.gmail.com>
 <120BD4FE-7395-4473-ABB6-EF59CEE4EB75@uni-konstanz.de>
 <CAAdxBZo4ybNv40gMR++VRKyopfHqEgKSkpThEjbqBYmTE9BfYw@mail.gmail.com>
Message-ID: <9C2C237B-72A7-46B3-BEE6-3662A4DAF503@uni-konstanz.de>

Hi,
I’m not sure I understood your question but if your mri is missing description of the coordsys but you know it, you could define it yourself by e.g. mri.coordsys = ’mni’. Alternatively you will be asked to define the directions of the x,y,z axes. Information about that can be found here:
http://www.fieldtriptoolbox.org/faq/how_are_the_different_head_and_mri_coordinate_systems_defined <http://www.fieldtriptoolbox.org/faq/how_are_the_different_head_and_mri_coordinate_systems_defined>

As such FieldTrip does not modify the head model coordsys at all. The head model is based on the coordsys defined by the input mri.
good luck
tzvetan


> Am 10.01.2018 um 09:53 schrieb Fereshte <fereshte.ramezani at gmail.com>:
> 
> Dear Txvetan,
> Thank you for your answer. How does the filedtrip modify the head model coordinate system if no coordinate is defined for the mri image given (to make the FEM head model) by user? 
> Thanks in advance!
> Regards,
> Fereshte 
> On Mon, Jan 8, 2018 at 11:41 AM Tzvetan Popov <tzvetan.popov at uni-konstanz.de <mailto:tzvetan.popov at uni-konstanz.de>> wrote:
> Hi Fereshte,
> 
> this is the relevant tutorial that’d help you out: http://www.fieldtriptoolbox.org/tutorial/sourcemodel#subject-specific_grids_that_are_equivalent_across_subjects_in_normalized_space <http://www.fieldtriptoolbox.org/tutorial/sourcemodel#subject-specific_grids_that_are_equivalent_across_subjects_in_normalized_space>
> good luck
> tzvetan
> 
> 
> 
>> Am 08.01.2018 um 08:12 schrieb Fereshte <fereshte.ramezani at gmail.com <mailto:fereshte.ramezani at gmail.com>>:
>> 
> 
>> Dear Experts,
>> How can I align a predefined grid source model to an existing head model? ( I have aligned the electrodes to  the headmodel manually but I'm not sure how to align a dipole position on the headmodel).
>> Looking forward to hearing from you!
>> Regards,
>> Fereshte Ramezani 
> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl <mailto:fieldtrip at donders.ru.nl>
>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip <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 <https://mailman.science.ru.nl/mailman/listinfo/fieldtrip>_______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From martin.bleichner at uni-oldenburg.de  Wed Jan 10 15:39:55 2018
From: martin.bleichner at uni-oldenburg.de (Martin Bleichner)
Date: Wed, 10 Jan 2018 15:39:55 +0100
Subject: [FieldTrip] 2nd International LSL Workshop (27.9-28.9.2018) - Save
	the Date
In-Reply-To: <CAPg9X1SEq_9ZWorE2bNOvwb=+vS45LmfYWiRUxWHOH1YqMMEwA@mail.gmail.com>
References: <CAPg9X1SCR_3Y0Kz+rJVGEGZkeQcHDUH0jPVvuJCLK2yVCO0eNA@mail.gmail.com>
 <CAPg9X1Qhsn-3xt=Kh60tSh3xe6s6o77PgukrAcM1bPmi-YFtFQ@mail.gmail.com>
 <2c8b685b-d7c4-e8f9-d00e-ec9fe96bd48b@gmail.com>
 <CAPg9X1SEq_9ZWorE2bNOvwb=+vS45LmfYWiRUxWHOH1YqMMEwA@mail.gmail.com>
Message-ID: <27e861b5-5224-61c5-d02c-3b70140acba2@uni-oldenburg.de>

Dear colleagues,

We are happy to announce the second international Lab Streaming Layer 
(LSL) workshop, which will take place September 27 - 28, 2018, at the 
Hanse Wissenschaftskolleg, in Delmenhorst, Germany. LSL is an 
open-source project enabling the synchronized streaming of time series 
data coming from different devices, such as EEG amplifiers, audio, 
video, eye tracking, keyboards, etc. LSL features near real-time access 
to data streams, time-synchronization, networking and centralized 
collection (https://github.com/sccn/labstreaminglayer).

Key LSL developers and expert users have confirmed attendance. The 
workshop will provide a general introduction to LSL. We will present how 
LSL can be used for a multitude of different experimental setups, using 
a variety of experimental software, hardware and operating systems. In a 
hands-on session, participants can learn to stream data from their own 
hardware or play with hardware provided by us and external partners. We 
will name pitfalls and discuss how to test and ensure the best possible 
timing accuracy when recording multimodal data. We will also provide a 
best practice guide and present different use cases of LSL. We will also 
use the workshop to discuss future software and hardware developments.

Participants are invited to contribute to the workshop by presenting 
their LSL use cases.

More information on the workshop will follow soon. For further 
enquiries, please contact: martin.bleichner at uol.de 
<mailto:martin.bleichner at uol.de>

Best,

Martin Bleichner

-- 
Dr. Martin Bleichner
Neuropsychology    Lab
Department of Psychology
University of Oldenburg
D-26111 Oldenburg
Germany

martin.bleichner at uni-oldenburg.de
Tel.: +49 (0)441 - 798-2940
http://www.uni-oldenburg.de/psychologie/neuropsychologie/team/martin-bleichner/

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From r.oostenveld at donders.ru.nl  Wed Jan 10 15:55:57 2018
From: r.oostenveld at donders.ru.nl (Robert Oostenveld)
Date: Wed, 10 Jan 2018 15:55:57 +0100
Subject: [FieldTrip] question on cluster-based statistics and source
	localization
In-Reply-To: <F96BCA30-0C1F-4C3B-9DE3-CDB22827049F@ulb.ac.be>
References: <F96BCA30-0C1F-4C3B-9DE3-CDB22827049F@ulb.ac.be>
Message-ID: <E1AC378D-E513-472B-A443-6E1439FE0A50@donders.ru.nl>

Hi Vincent,

Let me reply through the email list, where other people might learn something and/or want to chime in.

> On 10 Jan 2018, at 13:22, Vincent Wens <vwens at ulb.ac.be> wrote:
> 
> Dear Pr. Oostenveld,
> 
> I am Vincent Wens, a physicist working in the MEG unit at Erasme Hospital, Brussels. We've been recently trying to play with the cluster-based statistics that you developed and included in Fieldtrip, but hit a difficulty in our analysis pipeline and I wondered if you would be so kind to take a few minutes and provide advice on this? 

The cluster-based statistics is a method for statistical inference, i.e. statistical decision making based on a hypothesis and estimated probability distribution. The hypothesis H0 states that the data can be exchanged (between conditions). If it is very unlikely that the data can be exchanged (under H0), we decide that the data must be different somehow. The clusters provide evidence for the data being different, but the clusters are not the difference itself. The tip of an iceberg above the sea level provides evidence for there being an iceberg, but the tip is not the iceberg itself. 

An important FAQ is this http://www.fieldtriptoolbox.org/faq/how_not_to_interpret_results_from_a_cluster-based_permutation_test

Let me give the other commens in-line in your email below

> Globally, my question is how to go from sensor-level cluster statistics results to the source space.
> 
> More precisely: Assume we run the cluster statistics analysis on, say, N-channels time-frequency plots and obtain significance for the maximum cluster statistic.

So you obtain evidence that the channel level data is different. That logically implies that the cortical activity is different. Note that the other way arround would not hold per see; there can be different activity in the brain without it showing up as a difference in the scalp data.

> We thus find one (and possibly more) supra-threshold cluster(s) whose "spatio-spectral-temporal localization" can be assessed.

You could look at the visible tip (i.e. the cluster), you could also take a broader approach and look at the phenomenom under the tip (the iceberg).

> See for example the attached picture depicting the plot of those T-values within the significant cluster associated with an ERD. The next step would then be to source localize this,

You would not localize the cluster (you already have it, it is at the channel level). You localize the cortical activity that causes the data to appear different at the channel level. It’s the part of the iceberg under the sea level that causes the tip to appear above sea level.

> and our initial idea was to use the time and frequency region from this cluster as a prior on the time and frequency used for source projection. However the very complex shape of the cluster does not make this step so obvious. There are multiple possibilities that would come to mind, most of them absolutely ad-hoc, so I wondered your opinion on what would be the most rigorous, or at least least unacceptable way to go (or even just the most standard way, if there's one).

Based on the resulls (the multiplot), you should wonder whether there is only a single feature in the brain that is different or whether there are multiple. The hypothesis you started with was “is there any difference in this massive multiple-comparision space?” and the (only) answer you got to that question was “yes”. 

You now have the question “what is the difference”, which pertains to interpreting the data. That question has no binary answer and a statistical test based of a p-value being small enough (which gives you a "yes/no" answer) does not help.

I cannot offer specific advice on how to interpret your data, but recommend that you consider whether your true quest is for “the (one and only) effect” or “the effects” that causes the data in the two conditions to be different. Of course you can argue that the effect(s) show at certain frequency ranges and/or latencies and/or locations, and therefore you may decide to look for the interpretation of the effect(s) at or around those parts of the cluster. 

In general (not any more for this dataset) it is worthwile to consider that narrow a-priori hypotheses provide more valuable and specific information. This is something that we often rely on in sequential studies, where in the 2nd study we don’t repeat the full hypothesis of the 1st study (e.g. “is there any difference”), but a more specific sub-hypothesis that we generated on basis of the first study (e.g. is there a difference around this specific time-frequency range).

> Thanks in advance for your invaluable help, and still my best wishes for the New Year.

You’re welcome. Please follow up questions on the email discussion list.

best regards,
Robert


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From a.stolk8 at gmail.com  Wed Jan 10 17:16:09 2018
From: a.stolk8 at gmail.com (Arjen Stolk)
Date: Wed, 10 Jan 2018 08:16:09 -0800
Subject: [FieldTrip] error in ft_prepare_headmodel
In-Reply-To: <4BA0D72D-FC3B-4AF9-BDF2-08E60C01D689@donders.ru.nl>
References: <39853797796B114D8DE552AC4996EA6835C4BD60@MBX11.ad.oak.ox.ac.uk>
 <4BA0D72D-FC3B-4AF9-BDF2-08E60C01D689@donders.ru.nl>
Message-ID: <6131501D-762A-4258-B43E-4AB8FC3D7E57@gmail.com>

Hi Tom, 

As another work around, you could try using spm12 functionality. cfg.spmversion = ‘spm12’ if the function supports it, or by manually putting it on the path with ft_hastoolbox. There may be differences in the algorithm/outcome between versions, so you may want to be consistent in its use across subjects.

Best,
Arjen

> On Jan 10, 2018, at 12:36 AM, Schoffelen, J.M. (Jan Mathijs) <jan.schoffelen at donders.ru.nl> wrote:
> 
> Dear Tom,
> 
> To me, this looks like a platform/MATLAB version specific issue with the compiled mex-files. Anecdotally, MATLAB2017a on a Mac suffers from not knowing to handle the precompiled stuff that comes with FieldTrip/SPM. Either you could use a lower matlab version (e.g. 2016b, which as far as I know does not suffer from this), or you could try and recompile the affected mex-files from the original c-code with the matlab mex-command. See http://bit.ly/2DeuNlX for more info.
> 
> Best wishes,
> JM
> 
> 
>> On 9 Jan 2018, at 17:27, Tom Marshall <tom.marshall at psy.ox.ac.uk> wrote:
>> 
>> Howdy 'Trippers,
>> 
>> I got a weird error when trying to create a template headmodel using ft_prepare_headmodel (basically just following the steps in the tutorial 'Creating a sourcemodel for source-reconstruction of MEG or EEG data').
>> 
>> After loading and segmenting the template brain I called ft_prepare_headmodel using the suggested parameters.
>> 
>> cfg          = [];
>> cfg.method   = 'singleshell';
>> template_headmodel = ft_prepare_headmodel(cfg, template_seg);
>> 
>> This gave the following error.
>> 
>> Error using ft_notification (line 314)
>> please specificy cfg.tissue and pass an appropriate segmented MRI as input data
>> 
>> Error in ft_error (line 39)
>>   ft_notification(varargin{:});
>> 
>> Error in ft_prepare_headmodel (line 354)
>>           ft_error('please specificy cfg.tissue and pass an appropriate segmented
>>           MRI as input data')
>> 
>> So I added cfg.tissue...
>> 
>> cfg          = [];
>> cfg.method   = 'singleshell';
>> cfg.tissue   = 'brain';
>> template_headmodel = ft_prepare_headmodel(cfg, template_seg);
>> 
>> ...and this upset fieldtrip. After printing 'smoothing brain with a 5-voxel FWHM kernel', it hung for 10-15 minutes, then threw an error with lots of 'Missing symbol' statements (see below - there are a few hundred more, I just copypasted the last two).
>> 
>> Missing symbol '_vm_allocate' required by
>> '/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'
>> Missing symbol '_vm_deallocate' required by
>> '/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'.
>> 
>> Error in spm_smooth>smooth1 (line 105)
>> spm_conv_vol(P,Q,x,y,z,-[i,j,k]);
>> 
>> Error in spm_smooth (line 40)
>>     smooth1(P,Q,s,dtype);
>> 
>> Error in volumesmooth (line 18)
>> spm_smooth(output, output, fwhm);
>> 
>> Error in ft_datatype_segmentation (line 229)
>>           brain = volumesmooth(brain,    smooth,    'brain');
>> 
>> Error in prepare_mesh_segmentation (line 95)
>>     mri = ft_datatype_segmentation(mri, 'segmentationstyle', 'probabilistic',
>>     'hasbrain', 'yes');
>> 
>> Error in ft_prepare_mesh (line 147)
>>     bnd = prepare_mesh_segmentation(cfg, mri);
>> 
>> Error in ft_prepare_headmodel (line 337)
>>         geometry = ft_prepare_mesh(tmpcfg, data);
>> 
>> It seems like the problem is somewhere deep down in spm commands that fieldtrip is calling, so maybe nobody has a clue. I'm hoping somebody has seen this before and knows of a fix...
>> 
>> In case it's relevant: I'm running fieldtrip-20170726 in matlab R2017a on a mac.
>> 
>> And ideas?
>> 
>> Best,
>> Tom
>> _______________________________________________
>> 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
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From tom.marshall at psy.ox.ac.uk  Wed Jan 10 19:42:29 2018
From: tom.marshall at psy.ox.ac.uk (Tom Marshall)
Date: Wed, 10 Jan 2018 18:42:29 +0000
Subject: [FieldTrip] error in ft_prepare_headmodel
In-Reply-To: <6131501D-762A-4258-B43E-4AB8FC3D7E57@gmail.com>
References: <39853797796B114D8DE552AC4996EA6835C4BD60@MBX11.ad.oak.ox.ac.uk>
 <4BA0D72D-FC3B-4AF9-BDF2-08E60C01D689@donders.ru.nl>,
 <6131501D-762A-4258-B43E-4AB8FC3D7E57@gmail.com>
Message-ID: <39853797796B114D8DE552AC4996EA6835C4C11B@MBX11.ad.oak.ox.ac.uk>

Hi Arjen and JM,

Arjen - thanks for the golden tip!

As suggested, I explicitly added the SPM12 toolbox and called it in the cfg.

[status] = ft_hastoolbox('SPM12', 1, 0);

cfg                = [];
cfg.grid.warpmni   = 'yes';
cfg.grid.template  = template_grid;
cfg.grid.nonlinear = 'yes'; % use non-linear normalization
cfg.spmversion     = 'SPM12';
cfg.mri                = mri;
sourcemodel        = ft_prepare_sourcemodel(cfg);

However, this didn't totally solve the problem. At one point in ft_prepare_sourcemodel (line 636) ft_volumenormalise is called with a new cfg ('tmpcfg'). The choice to use SPM12 doesn't propagate to tmpcfg so fieldtrip adds SPM8 anyway when it calls ft_volumenormalise.

I fixed this by adding the following to ft_prepare_sourcemodel at line 633...

tmpcfg.spmversion = cfg.spmversion;

...and voila! A nice warped source model :)

Should I file this as a bug?

Best and thanks for the help,
Tom

________________________________
From: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl] on behalf of Arjen Stolk [a.stolk8 at gmail.com]
Sent: 10 January 2018 16:16
To: FieldTrip discussion list
Subject: Re: [FieldTrip] error in ft_prepare_headmodel

Hi Tom,

As another work around, you could try using spm12 functionality. cfg.spmversion = ‘spm12’ if the function supports it, or by manually putting it on the path with ft_hastoolbox. There may be differences in the algorithm/outcome between versions, so you may want to be consistent in its use across subjects.

Best,
Arjen

On Jan 10, 2018, at 12:36 AM, Schoffelen, J.M. (Jan Mathijs) <jan.schoffelen at donders.ru.nl<mailto:jan.schoffelen at donders.ru.nl>> wrote:

Dear Tom,

To me, this looks like a platform/MATLAB version specific issue with the compiled mex-files. Anecdotally, MATLAB2017a on a Mac suffers from not knowing to handle the precompiled stuff that comes with FieldTrip/SPM. Either you could use a lower matlab version (e.g. 2016b, which as far as I know does not suffer from this), or you could try and recompile the affected mex-files from the original c-code with the matlab mex-command. See http://bit.ly/2DeuNlX for more info.

Best wishes,
JM


On 9 Jan 2018, at 17:27, Tom Marshall <tom.marshall at psy.ox.ac.uk<mailto:tom.marshall at psy.ox.ac.uk>> wrote:

Howdy 'Trippers,

I got a weird error when trying to create a template headmodel using ft_prepare_headmodel (basically just following the steps in the tutorial 'Creating a sourcemodel for source-reconstruction of MEG or EEG data').

After loading and segmenting the template brain I called ft_prepare_headmodel using the suggested parameters.

cfg          = [];
cfg.method   = 'singleshell';
template_headmodel = ft_prepare_headmodel(cfg, template_seg);

This gave the following error.

Error using ft_notification (line 314)
please specificy cfg.tissue and pass an appropriate segmented MRI as input data

Error in ft_error (line 39)
  ft_notification(varargin{:});

Error in ft_prepare_headmodel (line 354)
          ft_error('please specificy cfg.tissue and pass an appropriate segmented
          MRI as input data')

So I added cfg.tissue...

cfg          = [];
cfg.method   = 'singleshell';
cfg.tissue   = 'brain';
template_headmodel = ft_prepare_headmodel(cfg, template_seg);

...and this upset fieldtrip. After printing 'smoothing brain with a 5-voxel FWHM kernel', it hung for 10-15 minutes, then threw an error with lots of 'Missing symbol' statements (see below - there are a few hundred more, I just copypasted the last two).

Missing symbol '_vm_allocate' required by
'/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'
Missing symbol '_vm_deallocate' required by
'/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'.

Error in spm_smooth>smooth1 (line 105)
spm_conv_vol(P,Q,x,y,z,-[i,j,k]);

Error in spm_smooth (line 40)
    smooth1(P,Q,s,dtype);

Error in volumesmooth (line 18)
spm_smooth(output, output, fwhm);

Error in ft_datatype_segmentation (line 229)
          brain = volumesmooth(brain,    smooth,    'brain');

Error in prepare_mesh_segmentation (line 95)
    mri = ft_datatype_segmentation(mri, 'segmentationstyle', 'probabilistic',
    'hasbrain', 'yes');

Error in ft_prepare_mesh (line 147)
    bnd = prepare_mesh_segmentation(cfg, mri);

Error in ft_prepare_headmodel (line 337)
        geometry = ft_prepare_mesh(tmpcfg, data);

It seems like the problem is somewhere deep down in spm commands that fieldtrip is calling, so maybe nobody has a clue. I'm hoping somebody has seen this before and knows of a fix...

In case it's relevant: I'm running fieldtrip-20170726 in matlab R2017a on a mac.

And ideas?

Best,
Tom
_______________________________________________
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
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From joseluisblues at gmail.com  Thu Jan 11 00:41:02 2018
From: joseluisblues at gmail.com (Jose)
Date: Wed, 10 Jan 2018 20:41:02 -0300
Subject: [FieldTrip] shrunk TFR topoplot
Message-ID: <CAH3cVdDVWKYSmGgL8U9At84dUREFy+RmCN6kLuYAjJvoP8Vcqg@mail.gmail.com>

dear list,

I'm trying to do a time-frequency plot with ft_topoplotTFR including first
an average across all conditions followed by specific conditions. I want to
highlight my sensors of interest for the first topoplot (the average across
all conditions), and I'm running in a rather annoying issue. When
highlighting the sensors the topoplot is slightly shrunk relative to the
other topoplots,

Has anybody run into this problem and find a workaround?

Thanks for any hints,

Jose

A snippet of my code is below,

%%%

    cfg = [ ];
    cfg.baseline = baselinePeriod;
    cfg.baselinetype = baselineType;
    cfg.xlim = TOI;
    cfg.ylim = YLimsFreq;
    cfg.zlim = ZLimsPower;
    cfg.marker = 'off';
    cfg.layout = 'biosemi64.lay';
    cfg.comment = 'no';
    cfg.interactive = 'no';
    % highlight
    cfg.highlight = 'on';
    cfg.highlightchannel = chan2use{i_chanSel};
    cfg.highlightcolor = [0 0 0];
    cfg.highlightsymbol = '.';
    cfg.highlightsize = 12;

    subplot(2,4,5); ft_topoplotTFR(cfg, datAll); colormap jet

    cfg = [ ];
    cfg.baseline = baselinePeriod;
    cfg.baselinetype = baselineType;
    cfg.xlim = TOI;
    cfg.ylim = YLimsFreq;
    cfg.zlim = ZLimsPower;
    cfg.marker = 'off';
    cfg.layout = 'biosemi64.lay';
    cfg.comment = 'no';
    cfg.interactive = 'no';
    subplot(2,4,6); ft_topoplotTFR(cfg, datCongr); colormap jet
    subplot(2,4,7); ft_topoplotTFR(cfg, datIncong); colormap jet
    subplot(2,4,8); ft_topoplotTFR(cfg, datNeutral); colormap jet

%%%
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From a.stolk8 at gmail.com  Thu Jan 11 07:49:44 2018
From: a.stolk8 at gmail.com (Arjen Stolk)
Date: Wed, 10 Jan 2018 22:49:44 -0800
Subject: [FieldTrip] error in ft_prepare_headmodel
In-Reply-To: <39853797796B114D8DE552AC4996EA6835C4C11B@MBX11.ad.oak.ox.ac.uk>
References: <39853797796B114D8DE552AC4996EA6835C4BD60@MBX11.ad.oak.ox.ac.uk>
 <4BA0D72D-FC3B-4AF9-BDF2-08E60C01D689@donders.ru.nl>
 <6131501D-762A-4258-B43E-4AB8FC3D7E57@gmail.com>
 <39853797796B114D8DE552AC4996EA6835C4C11B@MBX11.ad.oak.ox.ac.uk>
Message-ID: <CAAiwptTqisR_8ztKL86+kgYmYqS0tCtvqRRX3c95FnyNDtKCYw@mail.gmail.com>

Glad to see it worked, Tom. Full support for SPM12 has only recently been
completed, with JM laying the last hand on ft_volumenormalization a couple
of weeks ago. Therefore, the issue identified by you might be a missing
link that needs to be created still. Do you think you can you propose your
solution on github, for further joint discussion and implementation?

On Wed, Jan 10, 2018 at 10:42 AM, Tom Marshall <tom.marshall at psy.ox.ac.uk>
wrote:

> Hi Arjen and JM,
>
> Arjen - thanks for the golden tip!
>
> As suggested, I explicitly added the SPM12 toolbox and called it in the
> cfg.
>
>
>
>
>
>
>
>
>
>
>
> *[status] = ft_hastoolbox('SPM12', 1, 0); cfg                = [];
> cfg.grid.warpmni   = 'yes'; cfg.grid.template  = template_grid;
> cfg.grid.nonlinear = 'yes'; % use non-linear normalization
> cfg.spmversion     = 'SPM12'; cfg.mri                = mri;
> sourcemodel        = ft_prepare_sourcemodel(cfg); *However, this didn't
> totally solve the problem. At one point in ft_prepare_sourcemodel (line
> 636) ft_volumenormalise is called with a new cfg ('tmpcfg'). The choice to
> use SPM12 doesn't propagate to tmpcfg so fieldtrip adds SPM8 anyway when it
> calls ft_volumenormalise.
>
> I fixed this by adding the following to ft_prepare_sourcemodel at line
> 633...
>
>
> *tmpcfg.spmversion = cfg.spmversion; *
> ...and voila! A nice warped source model :)
>
> Should I file this as a bug?
>
> Best and thanks for the help,
> Tom
>
> ------------------------------
> *From:* fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl]
> on behalf of Arjen Stolk [a.stolk8 at gmail.com]
> *Sent:* 10 January 2018 16:16
> *To:* FieldTrip discussion list
> *Subject:* Re: [FieldTrip] error in ft_prepare_headmodel
>
> Hi Tom,
>
> As another work around, you could try using spm12 functionality.
> cfg.spmversion = ‘spm12’ if the function supports it, or by manually
> putting it on the path with ft_hastoolbox. There may be differences in the
> algorithm/outcome between versions, so you may want to be consistent in its
> use across subjects.
>
> Best,
> Arjen
>
> On Jan 10, 2018, at 12:36 AM, Schoffelen, J.M. (Jan Mathijs) <
> jan.schoffelen at donders.ru.nl> wrote:
>
> Dear Tom,
>
> To me, this looks like a platform/MATLAB version specific issue with the
> compiled mex-files. Anecdotally, MATLAB2017a on a Mac suffers from not
> knowing to handle the precompiled stuff that comes with FieldTrip/SPM.
> Either you could use a lower matlab version (e.g. 2016b, which as far as I
> know does not suffer from this), or you could try and recompile the
> affected mex-files from the original c-code with the matlab mex-command.
> See http://bit.ly/2DeuNlX for more info.
>
> Best wishes,
> JM
>
>
> On 9 Jan 2018, at 17:27, Tom Marshall <tom.marshall at psy.ox.ac.uk> wrote:
>
> Howdy 'Trippers,
>
> I got a weird error when trying to create a template headmodel using
> ft_prepare_headmodel (basically just following the steps in the tutorial
> 'Creating a sourcemodel for source-reconstruction of MEG or EEG data').
>
> After loading and segmenting the template brain I called
> ft_prepare_headmodel using the suggested parameters.
>
>
>
> *cfg          = []; cfg.method   = 'singleshell'; template_headmodel =
> ft_prepare_headmodel(cfg, template_seg);*
>
> This gave the following error.
>
>
>
>
>
>
>
>
>
> *Error using ft_notification (line 314) please specificy cfg.tissue and
> pass an appropriate segmented MRI as input data Error in ft_error (line 39)
>   ft_notification(varargin{:}); Error in ft_prepare_headmodel (line 354)
>           ft_error('please specificy cfg.tissue and pass an appropriate
> segmented           MRI as input data')*
>
> So I added cfg.tissue...
>
>
>
>
> *cfg          = []; cfg.method   = 'singleshell'; cfg.tissue   = 'brain';
> template_headmodel = ft_prepare_headmodel(cfg, template_seg);*
>
> ...and this upset fieldtrip. After printing *'smoothing brain with a
> 5-voxel FWHM kernel'*, it hung for 10-15 minutes, then threw an error
> with lots of 'Missing symbol' statements (see below - there are a few
> hundred more, I just copypasted the last two).
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
> *Missing symbol '_vm_allocate' required by
> '/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'
> Missing symbol '_vm_deallocate' required by
> '/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'.
> Error in spm_smooth>smooth1 (line 105) spm_conv_vol(P,Q,x,y,z,-[i,j,k]);
> Error in spm_smooth (line 40)     smooth1(P,Q,s,dtype); Error in
> volumesmooth (line 18) spm_smooth(output, output, fwhm); Error in
> ft_datatype_segmentation (line 229)           brain =
> volumesmooth(brain,    smooth,    'brain'); Error in
> prepare_mesh_segmentation (line 95)     mri = ft_datatype_segmentation(mri,
> 'segmentationstyle', 'probabilistic',     'hasbrain', 'yes'); Error in
> ft_prepare_mesh (line 147)     bnd = prepare_mesh_segmentation(cfg, mri);
> Error in ft_prepare_headmodel (line 337)         geometry =
> ft_prepare_mesh(tmpcfg, data); *
> It seems like the problem is somewhere deep down in spm commands that
> fieldtrip is calling, so maybe nobody has a clue. I'm hoping somebody has
> seen this before and knows of a fix...
>
> In case it's relevant: I'm running fieldtrip-20170726 in matlab R2017a on
> a mac.
>
> And ideas?
>
> Best,
> Tom
> _______________________________________________
> 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
>
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From Joachim.Gross at glasgow.ac.uk  Thu Jan 11 12:57:43 2018
From: Joachim.Gross at glasgow.ac.uk (Joachim Gross)
Date: Thu, 11 Jan 2018 11:57:43 +0000
Subject: [FieldTrip] Two Postdoc positions in Muenster, Germany
Message-ID: <A0FC7DEB-28C9-4A8E-A6F2-FF2AD80C7711@contoso.com>



The Institute for Biomagnetism and Biosignalanalysis at University of Muenster invites applications for a

Research associate/Postdoctoral scientist (f/m)
Ref.: 01689
Full-Time with 38,5 (hours/week)
(Germany salary grade: E 13 TV-L, 100%)

Two positions are intramurally funded and available for 2 years.

We are searching for trained and highly motivated scientists holding a PhD or MD degree and having experience in electrophysiology, cognitive neuroimaging or similar disciplines. The successful candidates are expected to have a strong publication record in international peer-reviewed journals.

The research project requires acquisition of MEG data and analysis of neuronal oscillations and their relationship to behaviour. Therefore, experience with MEG/EEG, programming and spectral analysis is essential.

The successful applicants will join a dynamic team of both experienced and junior researchers with many national and international collaborations and a sustained record of high-quality research output.

For more information please contact Prof Dr Joachim Gross, University of Muenster, Institute for Biomagnetism and Biosignalanalysis, 48149 Münster, Germany, Email:. Joachim.Gross(at)wwu(dot)de


Please send your application (including the above reference number) with all relevant information (CV, cover letter) by email (PDF-file, max. 5 MB) until 11.02.2018 to: bewerbung(at)ukmuenster(dot)de

Applications of women are specifically invited. In the case of similar qualifications, competence, and specific achievements, women will be considered on preferential terms within the framework of the legal possibilities. Handicapped candidates with equivalent qualifications will be given preference.


[University of Glasgow: The Times Scottish University of the Year 2018]
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From elam4hcp at gmail.com  Mon Jan 15 21:10:08 2018
From: elam4hcp at gmail.com (Jennifer Elam)
Date: Mon, 15 Jan 2018 14:10:08 -0600
Subject: [FieldTrip] Join us for HCP Course 2018 in Oxford, UK June 25-29!
Message-ID: <CAJbMWh6EONG62anxP+_ShBxhWNkPRyjPpg0HDBBoZNtORUcmBA@mail.gmail.com>

We are pleased to announce the *2018 HCP Course: "Exploring the Human
Connectome"
<http://store.humanconnectome.org/courses/2018/exploring-the-human-connectome.php>*,
to be held *June 25 – 29, 2018* at the Blavatnik School of Government
<https://www.bsg.ox.ac.uk/partner/contact-us>, at the University of Oxford
<http://www.ox.ac.uk/>, in Oxford, UK.
This 5-day intensive course will provide training in acquisition,
processing, analysis and visualization of whole brain imaging and
behavioral data using methods and tools developed by the WU-Minn-Oxford Human
Connectome Project (HCP) consortium.

The course is designed for investigators interested in:

   - using HCP-style data distributed by the Connectome Coordinating
   Facility (CCF) from the young adult (original) HCP and forthcoming projects
   - acquiring and analyzing HCP-style imaging and behavioral data at your
   own institution
   - processing your own non-HCP data using HCP pipelines and methods
   - using Connectome Workbench
   <https://www.humanconnectome.org/software/connectome-workbench.html> tools
   and sharing data using the BALSA <https://balsa.wustl.edu/> imaging
   database
   - learning HCP multimodal neuroimaging analysis methods, including those
   that combine MEG and MRI data
   - positioning yourself to capitalize on HCP-style data forthcoming from
   large-scale projects currently collecting data (e.g., Lifespan HCP
   development and aging and Connectomes Related to Human Disease projects)


Participants will learn how to acquire, analyze, visualize, and interpret
data from four major MR modalities (structural MR, resting-state fMRI,
diffusion imaging, task-evoked fMRI) plus magnetoencephalography (MEG) and
extensive behavioral data.  Lectures and labs will provide grounding in
neurobiological as well as methodological issues involved in interpreting
multimodal data, and will span the range from single-voxel/vertex to brain
network analysis approaches.

The course is open to students, postdocs, faculty, and industry
participants.  The course is aimed at both new and current users of HCP
data, methods, and tools, and will cover both basic and advanced topics.
Prior experience in human neuroimaging or in computational analysis of
brain networks is desirable, preferably including some familiarity with FSL
<https://fsl.fmrib.ox.ac.uk/fsl/fslwiki> and Freesurfer
<https://surfer.nmr.mgh.harvard.edu/> software.

For more info and to register visit the HCP Course 2018 website
<http://store.humanconnectome.org/courses/2018/exploring-the-human-connectome.php>.
New this year is the opportunity to add 6 nights of bed and
breakfast accommodation (Sun June 24 - Fri June 29) at nearby Worcester
College to your registration at a group, taxes included rate.
If you have any questions, please contact us at: hcpcourse at humanconnectome.
org

We look forward to seeing you in Oxford!

Best,
2018 HCP Course Organizers


-- 
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
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From bioeng.yoosofzadeh at gmail.com  Mon Jan 15 22:04:40 2018
From: bioeng.yoosofzadeh at gmail.com (Vahab Yousofzadeh)
Date: Mon, 15 Jan 2018 16:04:40 -0500
Subject: [FieldTrip] question on cluster-based statistics and source
Message-ID: <CAL5FLdKFs0rOBwkY29xTi7GZ_Kotdmjmdu9RCzkg34kSB0B24Q@mail.gmail.com>

Dear Vincent,

For cluster correction at source space, you would need to trick the
ft_prepare_neighbours because (as far as I know) it only works with
sensor-space data - so you just need to update the pos. with those
from the source model. Here's a piece of scripts:

s = timePost; % timePost is the output of ft_timelockanalysis.
s.grad.chanpos = headmodel_time.pos(headmodel_time.inside,:);
s.grad.chanori = s.grad.chanpos;
s.grad.chanunit(1:size(s.grad.chanpos,1)) = s.grad.chanunit(1);
s.grad.chantype(1:size(s.grad.chanpos,1)) = s.grad.chantype(1);
s.grad.tra    = ones(size(s.grad.chanpos,1),size(s.grad.tra,2));
for i=1:size(s.grad.chanpos,1)
    s.grad.label{i} = num2str(i);
    s.label{i} = num2str(i);
    s.grad.labelold =  num2str(i);
end
% prepare_neighbours determines what sensors may form clusters
cfg_neighb.method   = 'distance';
% cfg.method      = 'triangulation';
neighbours          = ft_prepare_neighbours(cfg_neighb, s);

%% inspecting random neighbours (#1200)
neighbours2 = [];
neighbours2 = neighbours(1200);
% neighbours2.neighblabel = neighbours2.neighblabel(1:20);
% plotting neighbours for inspection
cfg            = [];
cfg.neighbours = neighbours2;
ft_neighbourplot_source(cfg, s);

Now for cluster-correction, you need to have your source trials as
inputs, and do something like:

%% Cluster-correction
cfg = [];
cfg.parameter        = 'pow';
cfg.dim              = sourcemodel.dim;
cfg.method           = 'montecarlo';
% cfg.statistic        = 'ft_statfun_depsamplesT';
cfg.statistic        = 'depsamplesT';
% cfg.statistic         = 'indepsamplesT';
cfg.correctm         = 'cluster';
% cfg.correctm         = 'fdr';
cfg.clusteralpha     = 0.01;
cfg.clusterstatistic = 'max';
% cfg.correcttail = 'prob';
cfg.tail             = 0;
cfg.clustertail      = 0;
cfg.alpha            = 0.05;
cfg.numrandomization = 5000;
cfg.neighbours      = ft_prepare_neighbours(cfg_neighb, s);

ntrials                       = L;
design                        = zeros(2,2*ntrials);
design(1,1:ntrials)           = 1;
design(1,ntrials+1:2*ntrials) = 2;
design(2,1:ntrials)           = 1:ntrials;
design(2,ntrials+1:2*ntrials) = 1:ntrials;

cfg.design   = design;
cfg.ivar     = 1;
cfg.uvar     = 2;
stat         = ft_sourcestatistics(cfg,Source1,Source2);
stat.pos     = souremodel.pos;% keep positions for plotting later

and for plotting stats,

cfg              = [];
cfg.voxelcoord   = 'no';
cfg.parameter    = 'stat';
% cfg.interpmethod = 'nearest';
cfg.interpmethod = 'sphere_avg';
statint  = ft_sourceinterpolate(cfg, stat, template_mri);
cfg.parameter    = 'mask';
maskint  = ft_sourceinterpolate(cfg, stat, template_mri);

statint.mask = maskint.mask;

atlas = ft_read_atlas('ROI_MNI_V4.nii');

statint.coordsys  = 'mni';
cfg               = [];
cfg.method        = 'ortho';
% cfg.method = 'slice';
cfg.funparameter  = 'stat';
cfg.maskparameter = 'mask';
cfg.atlas         = atlas;
cfg.location      = 'max';
% cfg.funcolorlim   = [-5 5];
cfg.funcolormap   = 'jet';
% cfg.location = [x,y,z];
ft_sourceplot(cfg,statint);

Hope this helps, and let me know if you are running into issues.

Cheers,
Vahab

On Wed, Jan 10, 2018 at 9:55 AM,  <fieldtrip-request at science.ru.nl> wrote:
> Send fieldtrip mailing list submissions to
>         fieldtrip at science.ru.nl
>
> To subscribe or unsubscribe via the World Wide Web, visit
>         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
>
> You can reach the person managing the list at
>         fieldtrip-owner at science.ru.nl
>
> When replying, please edit your Subject line so it is more specific
> than "Re: Contents of fieldtrip digest..."
>
>
> Today's Topics:
>
>    1. 2nd International LSL Workshop (27.9-28.9.2018) - Save    the
>       Date (Martin Bleichner)
>    2. Re: question on cluster-based statistics and source
>       localization (Robert Oostenveld)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Wed, 10 Jan 2018 15:39:55 +0100
> From: Martin Bleichner <martin.bleichner at uni-oldenburg.de>
> To: lsl-l at mailman.ucsd.edu, eeglablist at sccn.ucsd.edu,
>         fieldtrip at science.ru.nl
> Subject: [FieldTrip] 2nd International LSL Workshop (27.9-28.9.2018) -
>         Save    the Date
> Message-ID: <27e861b5-5224-61c5-d02c-3b70140acba2 at uni-oldenburg.de>
> Content-Type: text/plain; charset="utf-8"; Format="flowed"
>
> Dear colleagues,
>
> We are happy to announce the second international Lab Streaming Layer
> (LSL) workshop, which will take place September 27 - 28, 2018, at the
> Hanse Wissenschaftskolleg, in Delmenhorst, Germany. LSL is an
> open-source project enabling the synchronized streaming of time series
> data coming from different devices, such as EEG amplifiers, audio,
> video, eye tracking, keyboards, etc. LSL features near real-time access
> to data streams, time-synchronization, networking and centralized
> collection (https://github.com/sccn/labstreaminglayer).
>
> Key LSL developers and expert users have confirmed attendance. The
> workshop will provide a general introduction to LSL. We will present how
> LSL can be used for a multitude of different experimental setups, using
> a variety of experimental software, hardware and?operating systems. In a
> hands-on session, participants can learn to stream data from their own
> hardware or play with hardware provided by us and external partners. We
> will name pitfalls and discuss how to test and ensure the best possible
> timing accuracy when recording multimodal data. We will also provide a
> best practice guide and present different use cases of LSL. We will also
> use the workshop to discuss future software and hardware developments.
>
> Participants are invited to contribute to the workshop by presenting
> their LSL use cases.
>
> More information on the workshop will follow soon. For further
> enquiries, please contact: martin.bleichner at uol.de
> <mailto:martin.bleichner at uol.de>
>
> Best,
>
> Martin Bleichner
>
> --
> Dr. Martin Bleichner
> Neuropsychology    Lab
> Department of Psychology
> University of Oldenburg
> D-26111 Oldenburg
> Germany
>
> martin.bleichner at uni-oldenburg.de
> Tel.: +49 (0)441 - 798-2940
> http://www.uni-oldenburg.de/psychologie/neuropsychologie/team/martin-bleichner/
>
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>
> ------------------------------
>
> Message: 2
> Date: Wed, 10 Jan 2018 15:55:57 +0100
> From: Robert Oostenveld <r.oostenveld at donders.ru.nl>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Cc: Vincent Wens <vwens at ulb.ac.be>
> Subject: Re: [FieldTrip] question on cluster-based statistics and
>         source  localization
> Message-ID: <E1AC378D-E513-472B-A443-6E1439FE0A50 at donders.ru.nl>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Vincent,
>
> Let me reply through the email list, where other people might learn something and/or want to chime in.
>
>> On 10 Jan 2018, at 13:22, Vincent Wens <vwens at ulb.ac.be> wrote:
>>
>> Dear Pr. Oostenveld,
>>
>> I am Vincent Wens, a physicist working in the MEG unit at Erasme Hospital, Brussels. We've been recently trying to play with the cluster-based statistics that you developed and included in Fieldtrip, but hit a difficulty in our analysis pipeline and I wondered if you would be so kind to take a few minutes and provide advice on this?
>
> The cluster-based statistics is a method for statistical inference, i.e. statistical decision making based on a hypothesis and estimated probability distribution. The hypothesis H0 states that the data can be exchanged (between conditions). If it is very unlikely that the data can be exchanged (under H0), we decide that the data must be different somehow. The clusters provide evidence for the data being different, but the clusters are not the difference itself. The tip of an iceberg above the sea level provides evidence for there being an iceberg, but the tip is not the iceberg itself.
>
> An important FAQ is this http://www.fieldtriptoolbox.org/faq/how_not_to_interpret_results_from_a_cluster-based_permutation_test
>
> Let me give the other commens in-line in your email below
>
>> Globally, my question is how to go from sensor-level cluster statistics results to the source space.
>>
>> More precisely: Assume we run the cluster statistics analysis on, say, N-channels time-frequency plots and obtain significance for the maximum cluster statistic.
>
> So you obtain evidence that the channel level data is different. That logically implies that the cortical activity is different. Note that the other way arround would not hold per see; there can be different activity in the brain without it showing up as a difference in the scalp data.
>
>> We thus find one (and possibly more) supra-threshold cluster(s) whose "spatio-spectral-temporal localization" can be assessed.
>
> You could look at the visible tip (i.e. the cluster), you could also take a broader approach and look at the phenomenom under the tip (the iceberg).
>
>> See for example the attached picture depicting the plot of those T-values within the significant cluster associated with an ERD. The next step would then be to source localize this,
>
> You would not localize the cluster (you already have it, it is at the channel level). You localize the cortical activity that causes the data to appear different at the channel level. It?s the part of the iceberg under the sea level that causes the tip to appear above sea level.
>
>> and our initial idea was to use the time and frequency region from this cluster as a prior on the time and frequency used for source projection. However the very complex shape of the cluster does not make this step so obvious. There are multiple possibilities that would come to mind, most of them absolutely ad-hoc, so I wondered your opinion on what would be the most rigorous, or at least least unacceptable way to go (or even just the most standard way, if there's one).
>
> Based on the resulls (the multiplot), you should wonder whether there is only a single feature in the brain that is different or whether there are multiple. The hypothesis you started with was ?is there any difference in this massive multiple-comparision space?? and the (only) answer you got to that question was ?yes?.
>
> You now have the question ?what is the difference?, which pertains to interpreting the data. That question has no binary answer and a statistical test based of a p-value being small enough (which gives you a "yes/no" answer) does not help.
>
> I cannot offer specific advice on how to interpret your data, but recommend that you consider whether your true quest is for ?the (one and only) effect? or ?the effects? that causes the data in the two conditions to be different. Of course you can argue that the effect(s) show at certain frequency ranges and/or latencies and/or locations, and therefore you may decide to look for the interpretation of the effect(s) at or around those parts of the cluster.
>
> In general (not any more for this dataset) it is worthwile to consider that narrow a-priori hypotheses provide more valuable and specific information. This is something that we often rely on in sequential studies, where in the 2nd study we don?t repeat the full hypothesis of the 1st study (e.g. ?is there any difference?), but a more specific sub-hypothesis that we generated on basis of the first study (e.g. is there a difference around this specific time-frequency range).
>
>> Thanks in advance for your invaluable help, and still my best wishes for the New Year.
>
> You?re welcome. Please follow up questions on the email discussion list.
>
> best regards,
> Robert
>
>
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>
> ------------------------------
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
> End of fieldtrip Digest, Vol 86, Issue 6
> ****************************************



From p.gaur at ulster.ac.uk  Tue Jan 16 15:26:53 2018
From: p.gaur at ulster.ac.uk (Gaur, Pramod)
Date: Tue, 16 Jan 2018 14:26:53 +0000
Subject: [FieldTrip] MEG UK 2018
Message-ID: <DB4PR06MB5855B4287245A8DBDC6C9DAB0EA0@DB4PR06MB585.eurprd06.prod.outlook.com>

Dear All,

The MEG UK 2018<http://meguk2018.co.uk/>, an annual conference focused on bringing together research groups working with magnetoencephalography (MEG) in the UK, will be held on  26-28 March 2018, at Ulster University, Magee Campus, Derry~Londonderry, Northern Ireland, UK. The conference is being organized by the Northern Ireland Functional Brain Mapping<https://www.ulster.ac.uk/research/institutes/computer-science/groups/intelligent-systems-research-centre/projects> (NIFBM) facility of the Intelligent Systems Research Centre (ISRC), a major research unit within the Faculty of Computing, Engineering and the Built Environment at Ulster's Magee campus.
More Details can be obtained from the MEG UK 2018 conference (http://meguk2018.co.uk/) website. We have secured very good deals for accommodation in local hotels as well as for local travel from Belfast airports by airporter.  Since number of places are limited, early registration and bookings are highly recommended.

Please register at the earliest to avoid disappointment.

Thanks,
MEG UK 2018



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From stephen.whitmarsh at gmail.com  Thu Jan 18 18:02:00 2018
From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh)
Date: Thu, 18 Jan 2018 18:02:00 +0100
Subject: [FieldTrip] question on cluster-based statistics and source
In-Reply-To: <CAL5FLdKFs0rOBwkY29xTi7GZ_Kotdmjmdu9RCzkg34kSB0B24Q@mail.gmail.com>
References: <CAL5FLdKFs0rOBwkY29xTi7GZ_Kotdmjmdu9RCzkg34kSB0B24Q@mail.gmail.com>
Message-ID: <CAFrxm=xt_cUZfL_MFbG8K27dKwOfmUaKg+mtmRsbMDRPHjhbEA@mail.gmail.com>

Hi there,

I just wanted to follow up and note that cluster-statistics are certainly
implemented for source-level reconstructed data (as a pointer to start,
see: http://www.fieldtriptoolbox.org/example/source_statistics)
I strongly suggest to use the functionality as intended in which most of
the typical user cases should be supported.

Best wishes,
Stephen




On 15 January 2018 at 22:04, Vahab Yousofzadeh <bioeng.yoosofzadeh at gmail.com
> wrote:

> Dear Vincent,
>
> For cluster correction at source space, you would need to trick the
> ft_prepare_neighbours because (as far as I know) it only works with
> sensor-space data - so you just need to update the pos. with those
> from the source model. Here's a piece of scripts:
>
> s = timePost; % timePost is the output of ft_timelockanalysis.
> s.grad.chanpos = headmodel_time.pos(headmodel_time.inside,:);
> s.grad.chanori = s.grad.chanpos;
> s.grad.chanunit(1:size(s.grad.chanpos,1)) = s.grad.chanunit(1);
> s.grad.chantype(1:size(s.grad.chanpos,1)) = s.grad.chantype(1);
> s.grad.tra    = ones(size(s.grad.chanpos,1),size(s.grad.tra,2));
> for i=1:size(s.grad.chanpos,1)
>     s.grad.label{i} = num2str(i);
>     s.label{i} = num2str(i);
>     s.grad.labelold =  num2str(i);
> end
> % prepare_neighbours determines what sensors may form clusters
> cfg_neighb.method   = 'distance';
> % cfg.method      = 'triangulation';
> neighbours          = ft_prepare_neighbours(cfg_neighb, s);
>
> %% inspecting random neighbours (#1200)
> neighbours2 = [];
> neighbours2 = neighbours(1200);
> % neighbours2.neighblabel = neighbours2.neighblabel(1:20);
> % plotting neighbours for inspection
> cfg            = [];
> cfg.neighbours = neighbours2;
> ft_neighbourplot_source(cfg, s);
>
> Now for cluster-correction, you need to have your source trials as
> inputs, and do something like:
>
> %% Cluster-correction
> cfg = [];
> cfg.parameter        = 'pow';
> cfg.dim              = sourcemodel.dim;
> cfg.method           = 'montecarlo';
> % cfg.statistic        = 'ft_statfun_depsamplesT';
> cfg.statistic        = 'depsamplesT';
> % cfg.statistic         = 'indepsamplesT';
> cfg.correctm         = 'cluster';
> % cfg.correctm         = 'fdr';
> cfg.clusteralpha     = 0.01;
> cfg.clusterstatistic = 'max';
> % cfg.correcttail = 'prob';
> cfg.tail             = 0;
> cfg.clustertail      = 0;
> cfg.alpha            = 0.05;
> cfg.numrandomization = 5000;
> cfg.neighbours      = ft_prepare_neighbours(cfg_neighb, s);
>
> ntrials                       = L;
> design                        = zeros(2,2*ntrials);
> design(1,1:ntrials)           = 1;
> design(1,ntrials+1:2*ntrials) = 2;
> design(2,1:ntrials)           = 1:ntrials;
> design(2,ntrials+1:2*ntrials) = 1:ntrials;
>
> cfg.design   = design;
> cfg.ivar     = 1;
> cfg.uvar     = 2;
> stat         = ft_sourcestatistics(cfg,Source1,Source2);
> stat.pos     = souremodel.pos;% keep positions for plotting later
>
> and for plotting stats,
>
> cfg              = [];
> cfg.voxelcoord   = 'no';
> cfg.parameter    = 'stat';
> % cfg.interpmethod = 'nearest';
> cfg.interpmethod = 'sphere_avg';
> statint  = ft_sourceinterpolate(cfg, stat, template_mri);
> cfg.parameter    = 'mask';
> maskint  = ft_sourceinterpolate(cfg, stat, template_mri);
>
> statint.mask = maskint.mask;
>
> atlas = ft_read_atlas('ROI_MNI_V4.nii');
>
> statint.coordsys  = 'mni';
> cfg               = [];
> cfg.method        = 'ortho';
> % cfg.method = 'slice';
> cfg.funparameter  = 'stat';
> cfg.maskparameter = 'mask';
> cfg.atlas         = atlas;
> cfg.location      = 'max';
> % cfg.funcolorlim   = [-5 5];
> cfg.funcolormap   = 'jet';
> % cfg.location = [x,y,z];
> ft_sourceplot(cfg,statint);
>
> Hope this helps, and let me know if you are running into issues.
>
> Cheers,
> Vahab
>
> On Wed, Jan 10, 2018 at 9:55 AM,  <fieldtrip-request at science.ru.nl> wrote:
> > Send fieldtrip mailing list submissions to
> >         fieldtrip at science.ru.nl
> >
> > To subscribe or unsubscribe via the World Wide Web, visit
> >         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
> >
> > You can reach the person managing the list at
> >         fieldtrip-owner at science.ru.nl
> >
> > When replying, please edit your Subject line so it is more specific
> > than "Re: Contents of fieldtrip digest..."
> >
> >
> > Today's Topics:
> >
> >    1. 2nd International LSL Workshop (27.9-28.9.2018) - Save    the
> >       Date (Martin Bleichner)
> >    2. Re: question on cluster-based statistics and source
> >       localization (Robert Oostenveld)
> >
> >
> > ----------------------------------------------------------------------
> >
> > Message: 1
> > Date: Wed, 10 Jan 2018 15:39:55 +0100
> > From: Martin Bleichner <martin.bleichner at uni-oldenburg.de>
> > To: lsl-l at mailman.ucsd.edu, eeglablist at sccn.ucsd.edu,
> >         fieldtrip at science.ru.nl
> > Subject: [FieldTrip] 2nd International LSL Workshop (27.9-28.9.2018) -
> >         Save    the Date
> > Message-ID: <27e861b5-5224-61c5-d02c-3b70140acba2 at uni-oldenburg.de>
> > Content-Type: text/plain; charset="utf-8"; Format="flowed"
> >
> > Dear colleagues,
> >
> > We are happy to announce the second international Lab Streaming Layer
> > (LSL) workshop, which will take place September 27 - 28, 2018, at the
> > Hanse Wissenschaftskolleg, in Delmenhorst, Germany. LSL is an
> > open-source project enabling the synchronized streaming of time series
> > data coming from different devices, such as EEG amplifiers, audio,
> > video, eye tracking, keyboards, etc. LSL features near real-time access
> > to data streams, time-synchronization, networking and centralized
> > collection (https://github.com/sccn/labstreaminglayer).
> >
> > Key LSL developers and expert users have confirmed attendance. The
> > workshop will provide a general introduction to LSL. We will present how
> > LSL can be used for a multitude of different experimental setups, using
> > a variety of experimental software, hardware and?operating systems. In a
> > hands-on session, participants can learn to stream data from their own
> > hardware or play with hardware provided by us and external partners. We
> > will name pitfalls and discuss how to test and ensure the best possible
> > timing accuracy when recording multimodal data. We will also provide a
> > best practice guide and present different use cases of LSL. We will also
> > use the workshop to discuss future software and hardware developments.
> >
> > Participants are invited to contribute to the workshop by presenting
> > their LSL use cases.
> >
> > More information on the workshop will follow soon. For further
> > enquiries, please contact: martin.bleichner at uol.de
> > <mailto:martin.bleichner at uol.de>
> >
> > Best,
> >
> > Martin Bleichner
> >
> > --
> > Dr. Martin Bleichner
> > Neuropsychology    Lab
> > Department of Psychology
> > University of Oldenburg
> > D-26111 Oldenburg
> > Germany
> >
> > martin.bleichner at uni-oldenburg.de
> > Tel.: +49 (0)441 - 798-2940
> > http://www.uni-oldenburg.de/psychologie/neuropsychologie/
> team/martin-bleichner/
> >
> > -------------- next part --------------
> > An HTML attachment was scrubbed...
> > URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/
> attachments/20180110/71ab956b/attachment-0001.html>
> >
> > ------------------------------
> >
> > Message: 2
> > Date: Wed, 10 Jan 2018 15:55:57 +0100
> > From: Robert Oostenveld <r.oostenveld at donders.ru.nl>
> > To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> > Cc: Vincent Wens <vwens at ulb.ac.be>
> > Subject: Re: [FieldTrip] question on cluster-based statistics and
> >         source  localization
> > Message-ID: <E1AC378D-E513-472B-A443-6E1439FE0A50 at donders.ru.nl>
> > Content-Type: text/plain; charset="utf-8"
> >
> > Hi Vincent,
> >
> > Let me reply through the email list, where other people might learn
> something and/or want to chime in.
> >
> >> On 10 Jan 2018, at 13:22, Vincent Wens <vwens at ulb.ac.be> wrote:
> >>
> >> Dear Pr. Oostenveld,
> >>
> >> I am Vincent Wens, a physicist working in the MEG unit at Erasme
> Hospital, Brussels. We've been recently trying to play with the
> cluster-based statistics that you developed and included in Fieldtrip, but
> hit a difficulty in our analysis pipeline and I wondered if you would be so
> kind to take a few minutes and provide advice on this?
> >
> > The cluster-based statistics is a method for statistical inference, i.e.
> statistical decision making based on a hypothesis and estimated probability
> distribution. The hypothesis H0 states that the data can be exchanged
> (between conditions). If it is very unlikely that the data can be exchanged
> (under H0), we decide that the data must be different somehow. The clusters
> provide evidence for the data being different, but the clusters are not the
> difference itself. The tip of an iceberg above the sea level provides
> evidence for there being an iceberg, but the tip is not the iceberg itself.
> >
> > An important FAQ is this http://www.fieldtriptoolbox.
> org/faq/how_not_to_interpret_results_from_a_cluster-based_permutation_test
> >
> > Let me give the other commens in-line in your email below
> >
> >> Globally, my question is how to go from sensor-level cluster statistics
> results to the source space.
> >>
> >> More precisely: Assume we run the cluster statistics analysis on, say,
> N-channels time-frequency plots and obtain significance for the maximum
> cluster statistic.
> >
> > So you obtain evidence that the channel level data is different. That
> logically implies that the cortical activity is different. Note that the
> other way arround would not hold per see; there can be different activity
> in the brain without it showing up as a difference in the scalp data.
> >
> >> We thus find one (and possibly more) supra-threshold cluster(s) whose
> "spatio-spectral-temporal localization" can be assessed.
> >
> > You could look at the visible tip (i.e. the cluster), you could also
> take a broader approach and look at the phenomenom under the tip (the
> iceberg).
> >
> >> See for example the attached picture depicting the plot of those
> T-values within the significant cluster associated with an ERD. The next
> step would then be to source localize this,
> >
> > You would not localize the cluster (you already have it, it is at the
> channel level). You localize the cortical activity that causes the data to
> appear different at the channel level. It?s the part of the iceberg under
> the sea level that causes the tip to appear above sea level.
> >
> >> and our initial idea was to use the time and frequency region from this
> cluster as a prior on the time and frequency used for source projection.
> However the very complex shape of the cluster does not make this step so
> obvious. There are multiple possibilities that would come to mind, most of
> them absolutely ad-hoc, so I wondered your opinion on what would be the
> most rigorous, or at least least unacceptable way to go (or even just the
> most standard way, if there's one).
> >
> > Based on the resulls (the multiplot), you should wonder whether there is
> only a single feature in the brain that is different or whether there are
> multiple. The hypothesis you started with was ?is there any difference in
> this massive multiple-comparision space?? and the (only) answer you got to
> that question was ?yes?.
> >
> > You now have the question ?what is the difference?, which pertains to
> interpreting the data. That question has no binary answer and a statistical
> test based of a p-value being small enough (which gives you a "yes/no"
> answer) does not help.
> >
> > I cannot offer specific advice on how to interpret your data, but
> recommend that you consider whether your true quest is for ?the (one and
> only) effect? or ?the effects? that causes the data in the two conditions
> to be different. Of course you can argue that the effect(s) show at certain
> frequency ranges and/or latencies and/or locations, and therefore you may
> decide to look for the interpretation of the effect(s) at or around those
> parts of the cluster.
> >
> > In general (not any more for this dataset) it is worthwile to consider
> that narrow a-priori hypotheses provide more valuable and specific
> information. This is something that we often rely on in sequential studies,
> where in the 2nd study we don?t repeat the full hypothesis of the 1st study
> (e.g. ?is there any difference?), but a more specific sub-hypothesis that
> we generated on basis of the first study (e.g. is there a difference around
> this specific time-frequency range).
> >
> >> Thanks in advance for your invaluable help, and still my best wishes
> for the New Year.
> >
> > You?re welcome. Please follow up questions on the email discussion list.
> >
> > best regards,
> > Robert
> >
> >
> > -------------- next part --------------
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> > -------------- next part --------------
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> > Size: 191076 bytes
> > Desc: not available
> > URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/
> attachments/20180110/dedffb0b/attachment.png>
> >
> > ------------------------------
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >
> > End of fieldtrip Digest, Vol 86, Issue 6
> > ****************************************
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From urieduardo at gmail.com  Fri Jan 19 14:44:37 2018
From: urieduardo at gmail.com (=?UTF-8?Q?Uri_Eduardo_Ram=C3=ADrez_Pasos?=)
Date: Fri, 19 Jan 2018 14:44:37 +0100
Subject: [FieldTrip] Interpolation using Talairach atlas
Message-ID: <CADO6phi=rEuFOvJgmhoEUBJnDF+wTZeV7A8bLbA5RF4TkZxhEg@mail.gmail.com>

Dear fieldtrippers,

I'm following the Salzburg tutorial (
http://www.fieldtriptoolbox.org/tutorial/salzburg) but using only templates
(i.e., no subject MRIs) and the Talairach (with 'tal' coordinates) atlas
from AFNI.

However, when I run

    atlas =
ft_read_atlas('~/Documents/MATLAB/fieldtrip-20170618/template/atlas/afni/TTatlas+tlrc.HEAD');

    cfg=[];
    cfg.method='lcmv';
    cfg.grid=template_grid;
    cfg.grid.filter=sourceavg.avg.filter;
    cfg.vol=vol;
    sourcepreS1=ft_sourceanalysis(cfg, avgpre);
    sourcepstS1=ft_sourceanalysis(cfg, avgpst);

    cfg = [];
    cfg.parameter = 'avg.pow';
    cfg.operation = '((x1-x2)./x2)*100';
    S1bl=ft_math(cfg,sourcepstS1,sourcepreS1);

    templatefile =
'~/Documents/MATLAB/fieldtrip-20170618/external/spm8/templates/T1.nii';
    template_mri = ft_read_mri(templatefile);
    cfg              = [];
    cfg.voxelcoord   = 'no';
    cfg.parameter    = 'pow';
    cfg.interpmethod = 'nearest';
    source_int  = ft_sourceinterpolate(cfg, S1bl, template_mri);
    %%
    cfg=[];
    parcel = ft_sourceparcellate(cfg, source_int, atlas);

I get the following error

Index exceeds matrix dimensions.

Error in ft_sourceparcellate (line 172)
  fprintf('%d of the labeled positions are inside the brain\n',
  sum(source.inside(seg(:)~=0)));

This is probably due to the spm8 template having too few 'pos' values. Do
you know of other mri template that would work with the AFNI atlas?

Best regards,
Eduardo Ramirez, PhD student
University of Würzburg
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From tonyvazhangottu at gmail.com  Mon Jan 22 05:29:42 2018
From: tonyvazhangottu at gmail.com (TONY CHACKO)
Date: Mon, 22 Jan 2018 09:59:42 +0530
Subject: [FieldTrip] (no subject)
Message-ID: <CAC0bWAbyc0k2M3iV+7GJEheJ3JrRNbrc0Yn88+QLG-Gh=rJ8Zg@mail.gmail.com>

 Dear all,
I am a new comer in fieldtrip software for my eeg project , I'm having
basic doubts.
I want to show all the events on my continuous data without segmenting the
data
and also I need to show my data in 50s-100s time.also i need to see my
results in matlab plots

Please help
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From Mariam.Kostandyan at UGent.be  Mon Jan 22 12:11:52 2018
From: Mariam.Kostandyan at UGent.be (Mariam Kostandyan)
Date: Mon, 22 Jan 2018 11:11:52 +0000
Subject: [FieldTrip] error Conversion to struct in ft_prepare_neighbours
Message-ID: <1516619979417.866@UGent.be>

Dear all,

I am quite new to the FieldTrip. I want to use it to check for the inter-electrode distances using the ft_prepare_neighbours function. My script looks like this:

cfg.method        = 'distance';
cfg.neighbourdist = 4;
cfg.channel       = {'FP1', 'FP2', 'F7', 'F3', 'FZ', 'F4', 'F8', 'FT9', 'FC5', 'FT10', 'T7', 'C3', 'CZ', 'C4', 'T8', 'TP9', 'CP5', 'CP6', 'TP10', 'P9', 'P7', 'P3', 'PZ', 'P4', 'P8', 'P10', 'O1', 'OZ', 'O2'};
cfg.feedback      = 'yes';
cfg.elec  = {'FP1', 'FP2', 'F7', 'F3', 'FZ', 'F4', 'F8', 'FT9', 'FC5', 'FT10', 'T7', 'C3', 'CZ', 'C4', 'T8', 'TP9', 'CP5', 'CP6', 'TP10', 'P9', 'P7', 'P3', 'PZ', 'P4', 'P8', 'P10', 'O1', 'OZ', 'O2'};
cfg.elecfile = 'sub03_Mariam_cues.set';
neighbours = ft_prepare_neighbours(cfg, 'sub03_Mariam_cues.set');


When I run it I get error messages:


Error using struct
Conversion to struct from cell is not possible.

Error in ft_checkconfig (line 248)
  cfg.elec = ft_datatype_sens(struct(cfg.elec));

Error in ft_preamble_trackconfig (line 37)
cfg = ft_checkconfig(cfg, 'trackconfig', 'on');

Error in ft_preamble (line 85)
evalin('caller', full_cmd);

Error in ft_neighbourplot (line 65)
ft_preamble trackconfig


How can I fix it? I would appreciate any help.


Best,

Mariam


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

Mariam Kostandyan
PhD student
University of Gent
Department of Experimental Psychology
Henri Dunantlaan 2, 9000 Gent, Belgium
----------------------

Room 140.021
Tel.: +32 9 264 6398
E-mail: Mariam.Kostandyan at UGent.be<mailto:Mariam.Kostandyan at UGent.be>
E-mail: kostandyan.m at gmail.com<mailto:kostandyan.m at gmail.com>
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From jan.schoffelen at donders.ru.nl  Mon Jan 22 13:51:35 2018
From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs))
Date: Mon, 22 Jan 2018 12:51:35 +0000
Subject: [FieldTrip] error Conversion to struct in ft_prepare_neighbours
In-Reply-To: <1516619979417.866@UGent.be>
References: <1516619979417.866@UGent.be>
Message-ID: <E3412ADA-DF6E-45AE-AF51-F28C0621D758@donders.ru.nl>

Dear Mariam,

Perhaps it will work if you remove the ‘elec’-field from the cfg.

Best wishes,
Jan-Mathijs

On 22 Jan 2018, at 12:11, Mariam Kostandyan <Mariam.Kostandyan at UGent.be<mailto:Mariam.Kostandyan at UGent.be>> wrote:

Dear all,

I am quite new to the FieldTrip. I want to use it to check for the inter-electrode distances using the ft_prepare_neighbours function. My script looks like this:

cfg.method        = 'distance';
cfg.neighbourdist = 4;
cfg.channel       = {'FP1', 'FP2', 'F7', 'F3', 'FZ', 'F4', 'F8', 'FT9', 'FC5', 'FT10', 'T7', 'C3', 'CZ', 'C4', 'T8', 'TP9', 'CP5', 'CP6', 'TP10', 'P9', 'P7', 'P3', 'PZ', 'P4', 'P8', 'P10', 'O1', 'OZ', 'O2'};
cfg.feedback      = 'yes';
cfg.elec  = {'FP1', 'FP2', 'F7', 'F3', 'FZ', 'F4', 'F8', 'FT9', 'FC5', 'FT10', 'T7', 'C3', 'CZ', 'C4', 'T8', 'TP9', 'CP5', 'CP6', 'TP10', 'P9', 'P7', 'P3', 'PZ', 'P4', 'P8', 'P10', 'O1', 'OZ', 'O2'};
cfg.elecfile = 'sub03_Mariam_cues.set';
neighbours = ft_prepare_neighbours(cfg, 'sub03_Mariam_cues.set');

When I run it I get error messages:

Error using struct
Conversion to struct from cell is not possible.

Error in ft_checkconfig (line 248)
  cfg.elec = ft_datatype_sens(struct(cfg.elec));

Error in ft_preamble_trackconfig (line 37)
cfg = ft_checkconfig(cfg, 'trackconfig', 'on');

Error in ft_preamble (line 85)
evalin('caller', full_cmd);

Error in ft_neighbourplot (line 65)
ft_preamble trackconfig

How can I fix it? I would appreciate any help.

Best,
Mariam

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

Mariam Kostandyan
PhD student
University of Gent
Department of Experimental Psychology
Henri Dunantlaan 2, 9000 Gent, Belgium
----------------------

Room 140.021
Tel.: +32 9 264 6398
E-mail: Mariam.Kostandyan at UGent.be<mailto:Mariam.Kostandyan at UGent.be>
E-mail: kostandyan.m at gmail.com<mailto:kostandyan.m at gmail.com>
_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From Heidi.SolbergOkland at mrc-cbu.cam.ac.uk  Mon Jan 22 14:15:58 2018
From: Heidi.SolbergOkland at mrc-cbu.cam.ac.uk (Heidi Solberg Okland)
Date: Mon, 22 Jan 2018 13:15:58 +0000
Subject: [FieldTrip] Reject trials based on standard deviation
Message-ID: <9327C18D1181184A833D66FF65A9D9E10139717943@wsr-ex-101.mrc-cbsu.local>

Dear Fieldtrippers,

I'm currently working on an MEG dataset and have so far done automatic rejection of bad channels using Maxfilter and then done ICA-based artefact reduction (eyeblinks and heartbeat) in MNE Python. I now have my data in Fieldtrip trial structures. What is left is to remove trials that are outliers/noisy because the subject moved/coughed/etc. I have tried to use ft_visinspect with variance as metric, but the issue I have is that the variance is displayed in actual units (e.g. 1e10^23) rather than in terms of standard deviations. This is problematic, as my trial rejection will be based on my subjective decisions that some trials look like outliers and not others. What I would like instead is to just do something like "discard trials where the amplitude is more than X standard deviations above or below the mean", which is reproducible. Is this way of rejecting trials implemented in FT? I have seen the tutorial on automatic artefact rejection, but it looks more like something that would be useful for removing e.g. eyeblinks.

Best wishes,
Heidi


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

Heidi Solberg Økland
PhD candidate, Language group

Tel: 01223 273721
MRC Cognition & Brain Sciences Unit
University of Cambridge
15 Chaucer Road
Cambridge
CB2 7EF

Web: http://www.mrc-cbu.cam.ac.uk<http://www.mrc-cbu.cam.ac.uk/>

Social media:
[facebook-flat-logo-01]<https://en-gb.facebook.com/MRCCBU/>   [twiiter-flat-logo-02] <https://mobile.twitter.com/mrccbu?lang=en>

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From Mariam.Kostandyan at UGent.be  Mon Jan 22 14:22:16 2018
From: Mariam.Kostandyan at UGent.be (Mariam Kostandyan)
Date: Mon, 22 Jan 2018 13:22:16 +0000
Subject: [FieldTrip] error Conversion to struct in ft_prepare_neighbours
In-Reply-To: <E3412ADA-DF6E-45AE-AF51-F28C0621D758@donders.ru.nl>
References: <1516619979417.866@UGent.be>,
 <E3412ADA-DF6E-45AE-AF51-F28C0621D758@donders.ru.nl>
Message-ID: <1516627803115.4133@UGent.be>

Dear Jan-Mathijs,


I guess it partially worked since it started reading the .set file but still outputed an error:


>>  cfg.method        = 'distance';
cfg.neighbourdist = 4;
cfg.channel       = {'FP1', 'FP2', 'F7', 'F3', 'FZ', 'F4', 'F8', 'FT9', 'FC5', 'FT10', 'T7', 'C3', 'CZ', 'C4', 'T8', 'TP9', 'CP5', 'CP6', 'TP10', 'P9', 'P7', 'P3', 'PZ', 'P4', 'P8', 'P10', 'O1', 'OZ', 'O2'};
cfg.feedback      = 'yes';
cfg.elecfile = 'sub03_Mariam_cues.set';
neighbours = ft_prepare_neighbours(cfg, 'sub03_Mariam_cues.set');
reading electrodes from file 'sub03_Mariam_cues.set'
Attempt to reference field of non-structure array.

Error in ft_prepare_neighbours (line 176)
    [dataidx, sensidx] = match_str(data.label, label);


Is it the .set file that has electrodes as a non-structure array?


Best,

Mariam


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

Mariam Kostandyan
PhD student
University of Gent
Department of Experimental Psychology
Henri Dunantlaan 2, 9000 Gent, Belgium
----------------------

Room 140.021
Tel.: +32 9 264 6398
E-mail: Mariam.Kostandyan at UGent.be<mailto:Mariam.Kostandyan at UGent.be>
E-mail: kostandyan.m at gmail.com<mailto:kostandyan.m at gmail.com>
________________________________
От: fieldtrip-bounces at science.ru.nl <fieldtrip-bounces at science.ru.nl> от имени Schoffelen, J.M. (Jan Mathijs) <jan.schoffelen at donders.ru.nl>
Отправлено: 22 января 2018 г. 13:51
Кому: FieldTrip discussion list
Тема: Re: [FieldTrip] error Conversion to struct in ft_prepare_neighbours

Dear Mariam,

Perhaps it will work if you remove the 'elec'-field from the cfg.

Best wishes,
Jan-Mathijs

On 22 Jan 2018, at 12:11, Mariam Kostandyan <Mariam.Kostandyan at UGent.be<mailto:Mariam.Kostandyan at UGent.be>> wrote:

Dear all,

I am quite new to the FieldTrip. I want to use it to check for the inter-electrode distances using the ft_prepare_neighbours function. My script looks like this:

cfg.method        = 'distance';
cfg.neighbourdist = 4;
cfg.channel       = {'FP1', 'FP2', 'F7', 'F3', 'FZ', 'F4', 'F8', 'FT9', 'FC5', 'FT10', 'T7', 'C3', 'CZ', 'C4', 'T8', 'TP9', 'CP5', 'CP6', 'TP10', 'P9', 'P7', 'P3', 'PZ', 'P4', 'P8', 'P10', 'O1', 'OZ', 'O2'};
cfg.feedback      = 'yes';
cfg.elec  = {'FP1', 'FP2', 'F7', 'F3', 'FZ', 'F4', 'F8', 'FT9', 'FC5', 'FT10', 'T7', 'C3', 'CZ', 'C4', 'T8', 'TP9', 'CP5', 'CP6', 'TP10', 'P9', 'P7', 'P3', 'PZ', 'P4', 'P8', 'P10', 'O1', 'OZ', 'O2'};
cfg.elecfile = 'sub03_Mariam_cues.set';
neighbours = ft_prepare_neighbours(cfg, 'sub03_Mariam_cues.set');

When I run it I get error messages:

Error using struct
Conversion to struct from cell is not possible.

Error in ft_checkconfig (line 248)
  cfg.elec = ft_datatype_sens(struct(cfg.elec));

Error in ft_preamble_trackconfig (line 37)
cfg = ft_checkconfig(cfg, 'trackconfig', 'on');

Error in ft_preamble (line 85)
evalin('caller', full_cmd);

Error in ft_neighbourplot (line 65)
ft_preamble trackconfig

How can I fix it? I would appreciate any help.

Best,
Mariam

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

Mariam Kostandyan
PhD student
University of Gent
Department of Experimental Psychology
Henri Dunantlaan 2, 9000 Gent, Belgium
----------------------

Room 140.021
Tel.: +32 9 264 6398
E-mail: Mariam.Kostandyan at UGent.be<mailto:Mariam.Kostandyan at UGent.be>
E-mail: kostandyan.m at gmail.com<mailto:kostandyan.m at gmail.com>
_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From stephen.whitmarsh at gmail.com  Mon Jan 22 17:06:47 2018
From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh)
Date: Mon, 22 Jan 2018 17:06:47 +0100
Subject: [FieldTrip] Reject trials based on standard deviation
In-Reply-To: <9327C18D1181184A833D66FF65A9D9E10139717943@wsr-ex-101.mrc-cbsu.local>
References: <9327C18D1181184A833D66FF65A9D9E10139717943@wsr-ex-101.mrc-cbsu.local>
Message-ID: <CAFrxm=ymv4xFdT+X5tLwz3T2yPwaAFEVaQxyi+_ZXxXpneDNnA@mail.gmail.com>

Hi Heidi,

I guess you could just e.g. zscore your data before the (semi)automatic
artefact *detection*, and apply those artefact definitions on your original
data in the artefact *rejection*.

Cheers,
Stephen

On 22 January 2018 at 14:15, Heidi Solberg Okland <
Heidi.SolbergOkland at mrc-cbu.cam.ac.uk> wrote:

> Dear Fieldtrippers,
>
>
>
> I’m currently working on an MEG dataset and have so far done automatic
> rejection of bad channels using Maxfilter and then done ICA-based artefact
> reduction (eyeblinks and heartbeat) in MNE Python. I now have my data in
> Fieldtrip trial structures. What is left is to remove trials that are
> outliers/noisy because the subject moved/coughed/etc. I have tried to use
> ft_visinspect with variance as metric, but the issue I have is that the
> variance is displayed in actual units (e.g. 1e10^23) rather than in terms
> of standard deviations. This is problematic, as my trial rejection will be
> based on my subjective decisions that some trials look like outliers and
> not others. What I would like instead is to just do something like “discard
> trials where the amplitude is more than X standard deviations above or
> below the mean”, which is reproducible. Is this way of rejecting trials
> implemented in FT? I have seen the tutorial on automatic artefact
> rejection, but it looks more like something that would be useful for
> removing e.g. eyeblinks.
>
>
>
> Best wishes,
>
> Heidi
>
>
>
>
>
> ----------------------------------------------------------
>
>
>
> Heidi Solberg Økland
>
> PhD candidate, Language group
>
>
>
> Tel: 01223 273721
>
> MRC Cognition & Brain Sciences Unit
>
> University of Cambridge
> 15 Chaucer Road
> Cambridge
>
> CB2 7EF
>
>
>
> Web: http://www.mrc-cbu.cam.ac.uk
>
>
>
> Social media:
>
> [image: facebook-flat-logo-01] <https://en-gb.facebook.com/MRCCBU/>   [image:
> twiiter-flat-logo-02] <https://mobile.twitter.com/mrccbu?lang=en>
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From rosemary.southwell.14 at ucl.ac.uk  Mon Jan 22 21:50:38 2018
From: rosemary.southwell.14 at ucl.ac.uk (Rosy Southwell)
Date: Mon, 22 Jan 2018 20:50:38 +0000
Subject: [FieldTrip] Source activation vs baseline on MNE output
Message-ID: <CADxBig50beESaNN6of6Zx7cLfbR8h9-9wDcgenGVHhWPywsK5A@mail.gmail.com>

Dear Fieldtrip Community,

I am working on EEG source analysis for auditory evoked responses to long
(3-second) stimuli. My data are evoked responses baseline corrected in the
interval [-1 0], and am interested in source activity in the window [0.5
1.5] relative to stimulus onset.

I have used MNE to estimate source activity over a latency of [-1 1.5]; see
code [1] below. Although I have two conditions of interest which I will
later contrast using ft_statfun_depsamplesT, I am first interested in
seeing which areas are activated by each condition. In order to extract
sound-evoked activity from ongoing activity, I would like to visualise the
source activity for each condition as an activation relative to baseline,
expressed as a T-statistic. I have ensured that my baseline window and
activation window are of equal duration and non-overlapping.

I have attempted to use ft_statfun_actvsblT for computing this statistic
(see code [2] below), but receive the error "Inappropriate dimord for the
statistics function FT_STATFUN_ACTVSBLT." From reading the function, I
understand that this method requires time-frequency data with
dimord 'chan_freq_time'. However my data is evoked, time-domain only.

My questions are
a) Is it even appropriate to express such "time-dimension-only" source
results as an activation relative to baseline?

b) If so, how would I best compute this in Fieldtrip?

c) if not, do you have a recommendation of how to quantify the degree of
activation for a single condition?

All the best,

Rosy Southwell
PhD Candidate
Chait Lab
Ear Institute, University College London.

%% CODE
% [1.] source analysis
  cfg = [];
            cfg.method = 'mne';
            cfg.latency = [-1 1.5];
            cfg.elec = elec;
            cfg.grid = sourcemodel_cortex;
            cfg.headmodel = headmodel;
            cfg.mne.prewhiten = 'yes';
            cfg.mne.lambda    = 3;
            cfg.mne.scalesourcecov = 'yes';
            [source] = ft_sourceanalysis(cfg, data);

% [2.] T-statistic of activation vs baseline

cfg=[];
cfg.method      = 'analytic';
cfg.statistic   = 'ft_statfun_actvsblT';
cfg.parameter   = 'pow';
cfg.correctm    = 'no';
cfg.alpha       = 0.025;
cfg.tail        = 0;
nsubj=20;
cfg.design(1,:) = [ones(1,nsubj) 2*ones(1,nsubj)];
cfg.design(2,:) = [1:nsubj 1:nsubj ];
cfg.ivar        = 1; % row of design matrix that contains independent
variable (the conditions)
cfg.uvar        = 2; % row of design matrix that contains unit variable (in
this case: subjects)

stat_RvR = ft_sourcestatistics(cfg,source_ac_all{:},source_bl_all{:});
% where source_ac_all, source_bl_all are 1*20 cell array of structs for
each subject
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From luca.turella at unitn.it  Tue Jan 23 18:27:59 2018
From: luca.turella at unitn.it (Luca Turella)
Date: Tue, 23 Jan 2018 18:27:59 +0100
Subject: [FieldTrip] Postdoctoral position - MEG and Visual Imagery @ CIMeC
 University of Trento, Italy
Message-ID: <CALvsWdV99L2NJ=FrVacWkWqrLNV+J2Hmmmn3Mynwb23QyNXNgw@mail.gmail.com>

A postdoctoral position will be available soon at the Center for Mind/Brain
Sciences (CIMeC, http://www.cimec.unitn.it/en) at the University of Trento
(Italy). The topic of investigation will cover the neural dynamics
underlying visual imagery adopting MEG. The position is supported by the
ERC Advanced Grant “Perceptual Awareness in the Reorganizing Brain” (PI
Carlo Marzi).


Candidates should have a Ph.D. degree in a field related to Cognitive
Neuroscience or related areas. The ideal candidate should have previous
experience in EEG/MEG data acquisition and analysis and good programming
skills in Matlab and Fieldtrip. Knowledge of the Italian language is not
required.


The salary will be proportional to the level of experience and the starting
date of the appointment is negotiable, but within the next 6 months.
Applications will be considered until the position is filled. The contract
will have a duration of 1 year, and can be extended by another year.
Applications should be sent to angelika.lingnau at rhul.ac.uk, including a CV,
statement of research interests, and contact details of two referees.
Potential candidates are also encouraged to send informal inquiries to
angelika.lingnau at rhul.ac.uk.


CIMeC offers an international and vibrant research setting with access to
state-of-the-art neuroimaging methodologies, including a research-only MR
scanner, MEG, EEG and TMS, as well as behavioural, eye tracking and motion
tracking laboratories. English is the official language of the CIMeC, where
a large proportion of the faculty, post-docs and students come from a wide
range of countries outside of Italy.


The University of Trento consistently ranks as a top Italian university in
both national Research Assessment Evaluations (RAE) and University Surveys.
In the latest RAE, the University of Trento as a whole ranks 2nd among
medium-sized universities.


-- 
Luca Turella, PhD
Assistant Professor
CIMeC - Center for Mind/Brain Sciences
University of Trento
Mattarello (TN), Via Delle Regole 101
Tel.+39 0461-28 3098
http://www.unitn.it/cimec



Legal Disclaimer
This electronic message contains information that is confidential. The
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Questo messaggio Email contiene informazioni confidenziali riservate ai
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From jorn at artinis.com  Fri Jan 26 16:07:02 2018
From: jorn at artinis.com (=?iso-8859-1?Q?J=F6rn_M._Horschig?=)
Date: Fri, 26 Jan 2018 16:07:02 +0100
Subject: [FieldTrip] ARTscientific: NIRS symposium in Thailand
Message-ID: <007101d396b7$5256acf0$f70406d0$@artinis.com>

Dear fieldtrippers,

 

On June 27-30, we from Artinis Medical Systems are organizing a
scientific symposium revolving around near-infrared spectroscopy (NIRS)
for neuro- and sports research. We would like to invite you to register
for the ARTscientific symposium in the beautiful and luxurious Wyndham
Grand Phuket Kalim Bay in Thailand. In this 2.5-day symposium, we will
create an open platform for both experienced and novice researchers to
share experiences, discuss NIRS and enjoy several hands-on workshops. We
are arranging an interesting line-up of keynote speakers, who will
provide valuable insight into NIRS and brain research. 

 

Next to providing a NIRS playground we will organize poster and
presentation sessions, so you will get the chance to present and discuss
your research. To sum it all up social wining and dining will be
organized in one of the most extraordinary places in Thailand.

The registration: Get an early bird ticket

The amount of rooms in the hotel are limited, so get yours quickly and
benefit until February 28th from the early bird discount! Additional
information on e.g. the program workshops or the location can be found
on our website: http://www.artinis.com/artscientific-2018/.  

If you have any questions, suggestions or requests for the symposium,
please do not hesitate to contact us at symposium at artinis.com.

 

With best regards,

The Artinis team

 

--
Jörn M. Horschig, PhD
Software Engineer & Project Leader NeuroGuard XS

  

A  Einsteinweg 17
    6662PW Elst 
    The Netherlands
T  +31 481 350 980
I    <http://www.artinis.com/> www.artinis.com

The information in this e-mail is confidential and intended solely for
the person to whom it is addressed. If this message is not addressed to
you, please be aware that you have no authorization to read this e-mail,
to copy it, to furnish it to any person other than the addressee, or to
use or misuse its content in any way whatsoever. Should you have
received this e-mail by mistake, please bring this to the attention of
the sender, after which you are kindly requested to destroy the original
message.

 

 <http://eepurl.com/bTlr_L> Sign up for our NIRS newsletter

 

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From i.charest at bham.ac.uk  Fri Jan 26 16:25:41 2018
From: i.charest at bham.ac.uk (Ian Charest (School of Psychology))
Date: Fri, 26 Jan 2018 15:25:41 +0000
Subject: [FieldTrip] Postdoc position on the neurocognitive mechanisms of
 conscious access
Message-ID: <97F95B166F2157409BE1EC68292F25AC436368A6@EX13.adf.bham.ac.uk>

Dear FieldTrip discussions list,

see below for details of a 3 year ERC funded postdoctoral position in Birmingham, UK.


https://goo.gl/6PuHwj


Best wishes,

Ian Charest
Lecturer, School of Psychology,
University of Birmingham, UK
iancharest.com

_________________________

Advert:
The School of Psychology at the University of Birmingham is looking for a bright and motivated Post-doctoral scientist to join the Charest Laboratory (iancharest.com). The Postdoc position to be filled is part of a project recently funded by a European Research Council Starting Grant entitled: "Spatio-Temporal Attention and Representation Tracking: the precise neural architecture of conscious object perception" (START).

The Project:
START is an ambitious programme of work that will make use of cutting-edge multivariate pattern analyses (MVPA) techniques to reveal the brain mechanisms that are critical for consciously perceiving visual objects in tasks that manipulate conscious access to visual information. The ability to consciously recognise faces, objects, or sounds is crucial for adaptive behaviour and survival. Yet, how our conscious experience of the world emerges in our brain remains unknown. The overall aim of the START programme is to fill an important gap in our understanding of consciousness by elucidating the neural underpinnings of conscious access. How does the brain select relevant information among distractors, and keep this information in mind? Why does our ability to consciously recognise salient objects sometimes fail under pressure and exhibit variability across days and individuals? START will try to address these important questions by precisely tracking where in the brain and when in time the representations critical for conscious access are established, by using novel approaches of Representational Similarity Analyses which combines the strengths of EEG, fMRI, and Deep Convolutional Neuronal Networks. This project will provide new insights on the precise spatio-temporal dynamics of conscious access, the mechanisms governing it, and the idiosyncratic subtleties behind the meanderings of consciousness.

The candidate:
The successful candidate will have (or be in the process of obtaining) a PhD in cognitive neuroscience or a related field. Previous experience with psychophysical tasks that manipulate conscious access in vision is desirable. Given the nature of the project, experience with fMRI, EEG/MEG and data analysis is required. Experience in using matlab or python (and Psychtoolbox or PsychoPy) is also a requirement. The successful applicant will have experience with multivariate pattern analyses (Representational Similarity Analysis, Fisher linear discriminants, etc) of neuroimaging data. This post will require designing experiments, collecting and analysing data associated with the project, preparing manuscripts for publication, presenting results at national and international conferences and the possible supervision of research assistants and students.

The School:
The School of Psychology at the University of Birmingham (http://www.birmingham.ac.uk/schools/psychology/index.aspx<https://www.findaphd.com/common/clickCount.aspx?theid=92145&type=184&DID=148&url=http%3a%2f%2fwww.birmingham.ac.uk%2fschools%2fpsychology%2findex.aspx>) is one of the largest and most successful in the UK, currently ranked in the top 5 Schools in the country (REF 2014). The School is soon to move to new accommodation in the form of a fully refurbished, purpose-designed space and a new-build Centre for Human Brain Health that will house our new MRI, MEG, EEG, NIRS, sleep lab, and the recently appointed Chair in Translational Neuroscience. The University of Birmingham is an equal opportunities employer. The School of Psychology has a Bronze Athena SWAN award and strives to maintain a flexible and supportive environment that enables its staff to flourish.

For informal enquiries about the project please contact Dr. Ian Charest (i.charest at bham.ac.uk). Please follow the following link for more details and to apply: https://goo.gl/6PuHwj


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From dr.nivethida at gmail.com  Wed Jan 31 10:47:36 2018
From: dr.nivethida at gmail.com (nivethida t)
Date: Wed, 31 Jan 2018 15:17:36 +0530
Subject: [FieldTrip] Opening for PhD position at Department of Neurology,
	NIMHANS, India
Message-ID: <CAMBnzx4eSs5XCenx8Njh3f69Ynv9-w3Zmj5nzx1tcPzikveqQg@mail.gmail.com>

Applications are invited for a prospective PhD candidate at the Department
of Neurology, National Institute of Mental Health and Neuro Sciences
(NIMHANS), Bengaluru, India.


The candidate will work on a Wellcome Trust/DBT India Alliance funded
project involving Transcranial magnetic stimulation (TMS), EEG and MEG
studies in patients with Parkinson’s disease.


Candidates with strong technical background (Master’s degree in basic
sciences/ engineering/ neuroscience) and prior knowledge of MATLAB are
eligible to apply. Experience with EEG/MEG signal processing is a plus.


Admission to the PhD program at the institute is subjected to the candidate
qualifying the NIMHANS online entrance test and interview. The entrance
test may be waived if the applicant has cleared any of the
DBT/UGC/CSIR/ICMR qualifying exams.


For further details on the PhD admission procedure, please refer to the
prospectus on the institute’s website (
http://www.nimhans.ac.in/sites/default/files/NIMHANS_Prospectus%202018-19%20Final%20%281%29.pdf)
.


Application deadline for July admission: 4th February, 2018



-- 
Dr. Nivethida Thirugnanasambandam, MBBS, MTech, PhD
Extramural Research Faculty,
Wellcome Trust/DBT India Alliance Clinical Research Fellow (Intermediate),
Department of Neurology,
National Institute of Mental Health and Neuro Sciences (NIMHANS),
Hosur Road, P B 2900, Bengaluru 560 029,
Karnataka, India
Ph: +91-80-26995143
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From r.oostenveld at donders.ru.nl  Wed Jan 31 12:44:49 2018
From: r.oostenveld at donders.ru.nl (Robert Oostenveld)
Date: Wed, 31 Jan 2018 12:44:49 +0100
Subject: [FieldTrip] MEG/EEG FieldTrip toolkit course in Nijmegen:
	pre-registration now open
Message-ID: <24B65D6F-F33A-4981-BEE2-CB06C3DC8327@donders.ru.nl>

Dear all,

On 9-13 April 2018 we will host the yearly “Advanced MEG/EEG data analysis toolkit" at the Donders Institute in Nijmegen. The course is aimed at researchers that have already performed  MEG/EEG data acquisition and have a good understanding of their own experimental design. Furthermore, we expect that you know the basics of MATLAB and that you already have some experience with MEG/EEG preprocessing and analysis. 

This intense 5-day toolkit course will teach you advanced MEG and EEG data analysis methods. We will cover preprocessing, frequency analysis, source reconstruction, connectivity and various statistical methods. The toolkit will consist of a number of lectures, followed by hands-on sessions in which you will be tutored through the complete analysis of a MEG data set using the FieldTrip toolbox. There will be plenty of opportunity to interact and ask questions about your research and data. On the final day you will have the opportunity to work on your own dataset under supervision of skilled tutors.

We can only host a limited number of participants. From past experience we expect the course to be oversubscribed, hence we will start with pre-registration. The final selection of the participants will be based on the motivation, background experience and research interests that are provided in the registration form. The deadline for pre-registration is March 1, 2018.

More information, including the link to register and last years program can be found at http://www.ru.nl/donders/agenda/donders-tool-kits/vm-tool-kits/donders-meg-eeg-tool-kit/ <http://www.ru.nl/donders/agenda/donders-tool-kits/vm-tool-kits/donders-meg-eeg-tool-kit/>. Please note that this year we added an extra day to have more hands-on time and to better deal with EEG specific topics. 

best regards,
Robert

-----------------------------------------------------------
Robert Oostenveld, PhD

Senior Researcher & MEG Physicist
Donders Institute for Brain, Cognition and Behaviour
Radboud University, Nijmegen, The Netherlands

Visiting Professor
NatMEG - the Swedish National MEG facility
Karolinska Institute, Stockholm, Sweden

tel.: +31 (0)24 3619695
e-mail: r.oostenveld at donders.ru.nl
web: http://www.ru.nl/donders
skype: r.oostenveld
-----------------------------------------------------------

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From davide.tabarelli at unitn.it  Wed Jan 31 17:56:45 2018
From: davide.tabarelli at unitn.it (Davide Tabarelli)
Date: Wed, 31 Jan 2018 17:56:45 +0100
Subject: [FieldTrip] Subject level non parametric statistics for coherence
	with external stimulus
Message-ID: <FD9AA208-D908-4CA2-A3AD-CD9AE61E5EC7@unitn.it>

Dear Fieldtrip users,

I’m trying to calculate a statistical map for coherence differences between two conditions at a source level for a single subject, but I have some problems with channel combinations.

I have calculated common LCMV filters for my subject and computed source time series, that I have stored in a ft_timelock structure.
I have also successfully calculated coherence between the stimulus function and all dipoles for both conditions A and B using ft_freqanalysis and ft_connectivityanalysis.
Now I would like to compute a non parametric statistical map for the coherence difference between A and B using the approach of Maris & Schoffelen & Fries 2007.

I’m trying to use the “ft_statfun_indepsamplesZcoh” statistics as follow:

cfg=[]; 
cfg.parameter = 'fourierspctrm’; 
cfg.frequency = 5.5;
cfg.statistic = 'ft_statfun_indepsamplesZcoh’; 
cfg.method = 'montecarlo’; 
cfg.numrandomization = 1000;
cfg.design = design;
stat = ft_freqstatistics(icfg, fourier_conditionA, fourier_conditionA);

I realized this will compute the statistics for all the possible combination of channels, thus between stimulus and sources and between all pairs of sources … that is computationally non effordable (at least for me).

There is a way to tell ft_freqstatistics to use only some combination when computing the significance of coherence differences?

Or am I doing something wrong?

Thank you all !

D.

—
Davide Tabarelli, Ph.D.
Center for Mind Brain Sciences (CIMeC)
University of Trento,
Via delle Regole, 101
38123 Mattarello (TN)
Tel: +39 (0)461 283644
Italy






From josyjoyvarghese at gmail.com  Wed Jan  3 07:40:19 2018
From: josyjoyvarghese at gmail.com (josy joy)
Date: Wed, 3 Jan 2018 12:10:19 +0530
Subject: [FieldTrip] difficulty in importing data from eeg to fieldtrip
Message-ID: <CAOW5AWC2EiZa7pL6cLJGbXEsPqZWsVy9wUnGveZ6M9qnj9FQtA@mail.gmail.com>

Dear sir/mam

Im a fresher to the firldtrip but i do have matlab aand eeglab basic
experience.

i am working on eeg analysis using fieldtrip,now im facing the difficulty
in importing the eeg data from eeglab(.set format).

please solve my problem
thanks
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From a.stolk8 at gmail.com  Wed Jan  3 07:51:48 2018
From: a.stolk8 at gmail.com (Arjen Stolk)
Date: Tue, 2 Jan 2018 22:51:48 -0800
Subject: [FieldTrip] difficulty in importing data from eeg to fieldtrip
In-Reply-To: <CAOW5AWC2EiZa7pL6cLJGbXEsPqZWsVy9wUnGveZ6M9qnj9FQtA@mail.gmail.com>
References: <CAOW5AWC2EiZa7pL6cLJGbXEsPqZWsVy9wUnGveZ6M9qnj9FQtA@mail.gmail.com>
Message-ID: <CAAiwptQ_x7fNVa77cLdp=8J-TuVma713dO-THUJT4vSAn2DL0A@mail.gmail.com>

Hi Josy,

The following wiki page might provide a fruitful starting point for
converting data between fieldtrip and eeglab:
http://www.fieldtriptoolbox.org/getting_started/eeglab

Best,
Arjen

On Tue, Jan 2, 2018 at 10:40 PM, josy joy <josyjoyvarghese at gmail.com> wrote:

> Dear sir/mam
>
> Im a fresher to the firldtrip but i do have matlab aand eeglab basic
> experience.
>
> i am working on eeg analysis using fieldtrip,now im facing the difficulty
> in importing the eeg data from eeglab(.set format).
>
> please solve my problem
> thanks
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From justintracyfleming at gmail.com  Fri Jan  5 22:43:37 2018
From: justintracyfleming at gmail.com (Justin Fleming)
Date: Fri, 5 Jan 2018 16:43:37 -0500
Subject: [FieldTrip] Time-frequency analysis with varying length trials
Message-ID: <CACo=i5XqqiPJsqw4aD3kXRfi0wfhs6GGKHui=nZTL92iCeXEsA@mail.gmail.com>

Hello all,

I'm trying to do some exploratory spectral analysis on EEG data from a
reaction time experiment, in which the trial ends as soon as the subject
detects a target. The trails are up to 6 sec in length, but they average
closer to 2 sec.

My goal is to make time-frequency plots, using the multi-taper method,
aligned to the response (end of trial), rather than the beginning. I tried
the following approach first:
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From justintracyfleming at gmail.com  Fri Jan  5 22:52:00 2018
From: justintracyfleming at gmail.com (Justin Fleming)
Date: Fri, 5 Jan 2018 16:52:00 -0500
Subject: [FieldTrip] Time-frequency analysis with varying length trials
Message-ID: <CACo=i5WpVvJhUtVOKj8vc+-KVUPYLJG0BAnBaXUr1YVk9H38Cw@mail.gmail.com>

Hello all,

I'm trying to do some exploratory spectral analysis on EEG data from a
reaction time experiment, in which the trial ends as soon as the subject
detects a target. The trails are up to 6 sec in length, but they average
closer to 2-3 sec.

My goal is to make time-frequency plots, using the multi-taper method,
aligned to the end of the trial (subject response) rather than the
beginning. I tried the following approach first:

   - Flip each trial’s data in time, such that sample 1 is now the end of
   the trial
   - Nan-pad each trial so they all have the same number of samples (6 sec
   * 256 Hz = 1536 samples).
   - Perform multi-taper spectral analysis with ft_freqanalysis

It seems that FieldTrip isn’t ignoring the NaN’s when calculating the power
at each time point. Effectively, I’m limiting my data to the shortest trial
duration rather than plotting it out to the longest time point.

Any help on NaN removal with ft_freqanalysis, or if there’s a smarter way
to align time-frequency analyses to the ends of trials, would be much
appreciated!

Thanks,
-
Justin F.
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From fereshte.ramezani at gmail.com  Mon Jan  8 08:12:39 2018
From: fereshte.ramezani at gmail.com (Fereshte)
Date: Mon, 08 Jan 2018 07:12:39 +0000
Subject: [FieldTrip] Align a predefined grid source model to an exciting
	head model
Message-ID: <CAAdxBZqsiLcdKJ4=0UtdBkis=kTNs6XCTuNr9J4oz_3SkMi9OQ@mail.gmail.com>

Dear Experts,
How can I align a predefined grid source model to an existing head model? (
I have aligned the electrodes to  the headmodel manually but I'm not sure
how to align a dipole position on the headmodel).
Looking forward to hearing from you!
Regards,
Fereshte Ramezani
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From tzvetan.popov at uni-konstanz.de  Mon Jan  8 09:09:55 2018
From: tzvetan.popov at uni-konstanz.de (Tzvetan Popov)
Date: Mon, 8 Jan 2018 09:09:55 +0100
Subject: [FieldTrip] Align a predefined grid source model to an exciting
 head model
In-Reply-To: <CAAdxBZqsiLcdKJ4=0UtdBkis=kTNs6XCTuNr9J4oz_3SkMi9OQ@mail.gmail.com>
References: <CAAdxBZqsiLcdKJ4=0UtdBkis=kTNs6XCTuNr9J4oz_3SkMi9OQ@mail.gmail.com>
Message-ID: <120BD4FE-7395-4473-ABB6-EF59CEE4EB75@uni-konstanz.de>

Hi Fereshte,

this is the relevant tutorial that’d help you out: http://www.fieldtriptoolbox.org/tutorial/sourcemodel#subject-specific_grids_that_are_equivalent_across_subjects_in_normalized_space <http://www.fieldtriptoolbox.org/tutorial/sourcemodel#subject-specific_grids_that_are_equivalent_across_subjects_in_normalized_space>
good luck
tzvetan


> Am 08.01.2018 um 08:12 schrieb Fereshte <fereshte.ramezani at gmail.com>:
> 
> Dear Experts,
> How can I align a predefined grid source model to an existing head model? ( I have aligned the electrodes to  the headmodel manually but I'm not sure how to align a dipole position on the headmodel).
> Looking forward to hearing from you!
> Regards,
> Fereshte Ramezani 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From holmgren.jostein at gmail.com  Mon Jan  8 14:46:16 2018
From: holmgren.jostein at gmail.com (Jostein Holmgren)
Date: Mon, 8 Jan 2018 13:46:16 +0000
Subject: [FieldTrip] Post-doc position available @ Wellcome Centre for
 Integrative Neuroimaging, University of Oxford
Message-ID: <A26C2EA0-7106-4165-AD23-286AA24D13B4@gmail.com>

Dear All,

We are looking to recruit a talented post doc to join our team exploring EEG markers of depth of anaesthesia. Full details of the post are attached below. 

Please pass this email on to suitable candidates.

Best wishes,
Jostein

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

Jostein Holmgren
DPhil Student (PRS)
Nuffield Department of Clinical Neurosciences
Wellcome Centre for Integrative Neuroimaging, FMRIB Building
University of Oxford

-----------------------------------------------------------------------------------------------------
Postdoctoral Researcher in Signal Processing
Wellcome Centre for Integrative Neuroimaging (WIN), University of Oxford
Grade 7: £31,604 - £38,833 with a discretionary range to £42,418 p.a.

The successful candidate will develop and implement a new EEG depth of anaesthesia monitor that uses an individualised biomarker of perception loss called slow wave activity saturation (SWAS). The post holder will become a key member of the SWAS research team headed by Dr Katie Warnaby, and will lead software development and implementation of a prototype EEG monitoring system. 

You will have a PhD/DPhil in a relevant discipline, and possess sufficient specialist knowledge to work within the established research programme. Experience of EEG data analysis and developing real-time brain-computer and graphic user interfaces is highly desirable. 

To apply and for further details see https://www.recruit.ox.ac.uk/pls/hrisliverecruit/erq_jobspec_version_4.display_form <https://www.recruit.ox.ac.uk/pls/hrisliverecruit/erq_jobspec_version_4.display_form>. Please contact Katie Warnaby with informal enquiries on katie.warnaby at ndcn.ox.ac.uk <mailto:katie.warnaby at ndcn.ox.ac.uk>. 

Interviews will take place at the end of January for start as soon as possible after. The post is funded by the Medical Research Council (MRC) Development Pathway Funding Scheme. 

————————
Dr Katie Warnaby
Senior Research Scientist
Wellcome Centre for Integrative Neuroimaging @ FMRIB
University of Oxford

Tel: +44 1865 611 465
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From tom.marshall at psy.ox.ac.uk  Tue Jan  9 17:27:25 2018
From: tom.marshall at psy.ox.ac.uk (Tom Marshall)
Date: Tue, 9 Jan 2018 16:27:25 +0000
Subject: [FieldTrip] error in ft_prepare_headmodel
Message-ID: <39853797796B114D8DE552AC4996EA6835C4BD60@MBX11.ad.oak.ox.ac.uk>

Howdy 'Trippers,

I got a weird error when trying to create a template headmodel using ft_prepare_headmodel (basically just following the steps in the tutorial 'Creating a sourcemodel for source-reconstruction of MEG or EEG data').

After loading and segmenting the template brain I called ft_prepare_headmodel using the suggested parameters.

cfg          = [];
cfg.method   = 'singleshell';
template_headmodel = ft_prepare_headmodel(cfg, template_seg);

This gave the following error.

Error using ft_notification (line 314)
please specificy cfg.tissue and pass an appropriate segmented MRI as input data

Error in ft_error (line 39)
  ft_notification(varargin{:});

Error in ft_prepare_headmodel (line 354)
          ft_error('please specificy cfg.tissue and pass an appropriate segmented
          MRI as input data')

So I added cfg.tissue...

cfg          = [];
cfg.method   = 'singleshell';
cfg.tissue   = 'brain';
template_headmodel = ft_prepare_headmodel(cfg, template_seg);

...and this upset fieldtrip. After printing 'smoothing brain with a 5-voxel FWHM kernel', it hung for 10-15 minutes, then threw an error with lots of 'Missing symbol' statements (see below - there are a few hundred more, I just copypasted the last two).

Missing symbol '_vm_allocate' required by
'/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'
Missing symbol '_vm_deallocate' required by
'/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'.

Error in spm_smooth>smooth1 (line 105)
spm_conv_vol(P,Q,x,y,z,-[i,j,k]);

Error in spm_smooth (line 40)
    smooth1(P,Q,s,dtype);

Error in volumesmooth (line 18)
spm_smooth(output, output, fwhm);

Error in ft_datatype_segmentation (line 229)
          brain = volumesmooth(brain,    smooth,    'brain');

Error in prepare_mesh_segmentation (line 95)
    mri = ft_datatype_segmentation(mri, 'segmentationstyle', 'probabilistic',
    'hasbrain', 'yes');

Error in ft_prepare_mesh (line 147)
    bnd = prepare_mesh_segmentation(cfg, mri);

Error in ft_prepare_headmodel (line 337)
        geometry = ft_prepare_mesh(tmpcfg, data);

It seems like the problem is somewhere deep down in spm commands that fieldtrip is calling, so maybe nobody has a clue. I'm hoping somebody has seen this before and knows of a fix...

In case it's relevant: I'm running fieldtrip-20170726 in matlab R2017a on a mac.

And ideas?

Best,
Tom
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From jan.schoffelen at donders.ru.nl  Wed Jan 10 09:36:10 2018
From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs))
Date: Wed, 10 Jan 2018 08:36:10 +0000
Subject: [FieldTrip] error in ft_prepare_headmodel
In-Reply-To: <39853797796B114D8DE552AC4996EA6835C4BD60@MBX11.ad.oak.ox.ac.uk>
References: <39853797796B114D8DE552AC4996EA6835C4BD60@MBX11.ad.oak.ox.ac.uk>
Message-ID: <4BA0D72D-FC3B-4AF9-BDF2-08E60C01D689@donders.ru.nl>

Dear Tom,

To me, this looks like a platform/MATLAB version specific issue with the compiled mex-files. Anecdotally, MATLAB2017a on a Mac suffers from not knowing to handle the precompiled stuff that comes with FieldTrip/SPM. Either you could use a lower matlab version (e.g. 2016b, which as far as I know does not suffer from this), or you could try and recompile the affected mex-files from the original c-code with the matlab mex-command. See http://bit.ly/2DeuNlX for more info.

Best wishes,
JM


On 9 Jan 2018, at 17:27, Tom Marshall <tom.marshall at psy.ox.ac.uk<mailto:tom.marshall at psy.ox.ac.uk>> wrote:

Howdy 'Trippers,

I got a weird error when trying to create a template headmodel using ft_prepare_headmodel (basically just following the steps in the tutorial 'Creating a sourcemodel for source-reconstruction of MEG or EEG data').

After loading and segmenting the template brain I called ft_prepare_headmodel using the suggested parameters.

cfg          = [];
cfg.method   = 'singleshell';
template_headmodel = ft_prepare_headmodel(cfg, template_seg);

This gave the following error.

Error using ft_notification (line 314)
please specificy cfg.tissue and pass an appropriate segmented MRI as input data

Error in ft_error (line 39)
  ft_notification(varargin{:});

Error in ft_prepare_headmodel (line 354)
          ft_error('please specificy cfg.tissue and pass an appropriate segmented
          MRI as input data')

So I added cfg.tissue...

cfg          = [];
cfg.method   = 'singleshell';
cfg.tissue   = 'brain';
template_headmodel = ft_prepare_headmodel(cfg, template_seg);

...and this upset fieldtrip. After printing 'smoothing brain with a 5-voxel FWHM kernel', it hung for 10-15 minutes, then threw an error with lots of 'Missing symbol' statements (see below - there are a few hundred more, I just copypasted the last two).

Missing symbol '_vm_allocate' required by
'/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'
Missing symbol '_vm_deallocate' required by
'/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'.

Error in spm_smooth>smooth1 (line 105)
spm_conv_vol(P,Q,x,y,z,-[i,j,k]);

Error in spm_smooth (line 40)
    smooth1(P,Q,s,dtype);

Error in volumesmooth (line 18)
spm_smooth(output, output, fwhm);

Error in ft_datatype_segmentation (line 229)
          brain = volumesmooth(brain,    smooth,    'brain');

Error in prepare_mesh_segmentation (line 95)
    mri = ft_datatype_segmentation(mri, 'segmentationstyle', 'probabilistic',
    'hasbrain', 'yes');

Error in ft_prepare_mesh (line 147)
    bnd = prepare_mesh_segmentation(cfg, mri);

Error in ft_prepare_headmodel (line 337)
        geometry = ft_prepare_mesh(tmpcfg, data);

It seems like the problem is somewhere deep down in spm commands that fieldtrip is calling, so maybe nobody has a clue. I'm hoping somebody has seen this before and knows of a fix...

In case it's relevant: I'm running fieldtrip-20170726 in matlab R2017a on a mac.

And ideas?

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

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From fereshte.ramezani at gmail.com  Wed Jan 10 09:53:17 2018
From: fereshte.ramezani at gmail.com (Fereshte)
Date: Wed, 10 Jan 2018 08:53:17 +0000
Subject: [FieldTrip] Align a predefined grid source model to an exciting
 head model
In-Reply-To: <120BD4FE-7395-4473-ABB6-EF59CEE4EB75@uni-konstanz.de>
References: <CAAdxBZqsiLcdKJ4=0UtdBkis=kTNs6XCTuNr9J4oz_3SkMi9OQ@mail.gmail.com>
 <120BD4FE-7395-4473-ABB6-EF59CEE4EB75@uni-konstanz.de>
Message-ID: <CAAdxBZo4ybNv40gMR++VRKyopfHqEgKSkpThEjbqBYmTE9BfYw@mail.gmail.com>

Dear Txvetan,
Thank you for your answer. How does the filedtrip modify the head model
coordinate system if no coordinate is defined for the mri image given (to
make the FEM head model) by user?
Thanks in advance!
Regards,
Fereshte
On Mon, Jan 8, 2018 at 11:41 AM Tzvetan Popov <tzvetan.popov at uni-konstanz.de>
wrote:

> Hi Fereshte,
>
> this is the relevant tutorial that’d help you out:
> http://www.fieldtriptoolbox.org/tutorial/sourcemodel#subject-specific_grids_that_are_equivalent_across_subjects_in_normalized_space
> good luck
> tzvetan
>
>
> Am 08.01.2018 um 08:12 schrieb Fereshte <fereshte.ramezani at gmail.com>:
>
> Dear Experts,
> How can I align a predefined grid source model to an existing head model?
> ( I have aligned the electrodes to  the headmodel manually but I'm not sure
> how to align a dipole position on the headmodel).
> Looking forward to hearing from you!
> Regards,
> Fereshte Ramezani
>
> _______________________________________________
> 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
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From tzvetan.popov at uni-konstanz.de  Wed Jan 10 11:08:24 2018
From: tzvetan.popov at uni-konstanz.de (Tzvetan Popov)
Date: Wed, 10 Jan 2018 11:08:24 +0100
Subject: [FieldTrip] Align a predefined grid source model to an exciting
 head model
In-Reply-To: <CAAdxBZo4ybNv40gMR++VRKyopfHqEgKSkpThEjbqBYmTE9BfYw@mail.gmail.com>
References: <CAAdxBZqsiLcdKJ4=0UtdBkis=kTNs6XCTuNr9J4oz_3SkMi9OQ@mail.gmail.com>
 <120BD4FE-7395-4473-ABB6-EF59CEE4EB75@uni-konstanz.de>
 <CAAdxBZo4ybNv40gMR++VRKyopfHqEgKSkpThEjbqBYmTE9BfYw@mail.gmail.com>
Message-ID: <9C2C237B-72A7-46B3-BEE6-3662A4DAF503@uni-konstanz.de>

Hi,
I’m not sure I understood your question but if your mri is missing description of the coordsys but you know it, you could define it yourself by e.g. mri.coordsys = ’mni’. Alternatively you will be asked to define the directions of the x,y,z axes. Information about that can be found here:
http://www.fieldtriptoolbox.org/faq/how_are_the_different_head_and_mri_coordinate_systems_defined <http://www.fieldtriptoolbox.org/faq/how_are_the_different_head_and_mri_coordinate_systems_defined>

As such FieldTrip does not modify the head model coordsys at all. The head model is based on the coordsys defined by the input mri.
good luck
tzvetan


> Am 10.01.2018 um 09:53 schrieb Fereshte <fereshte.ramezani at gmail.com>:
> 
> Dear Txvetan,
> Thank you for your answer. How does the filedtrip modify the head model coordinate system if no coordinate is defined for the mri image given (to make the FEM head model) by user? 
> Thanks in advance!
> Regards,
> Fereshte 
> On Mon, Jan 8, 2018 at 11:41 AM Tzvetan Popov <tzvetan.popov at uni-konstanz.de <mailto:tzvetan.popov at uni-konstanz.de>> wrote:
> Hi Fereshte,
> 
> this is the relevant tutorial that’d help you out: http://www.fieldtriptoolbox.org/tutorial/sourcemodel#subject-specific_grids_that_are_equivalent_across_subjects_in_normalized_space <http://www.fieldtriptoolbox.org/tutorial/sourcemodel#subject-specific_grids_that_are_equivalent_across_subjects_in_normalized_space>
> good luck
> tzvetan
> 
> 
> 
>> Am 08.01.2018 um 08:12 schrieb Fereshte <fereshte.ramezani at gmail.com <mailto:fereshte.ramezani at gmail.com>>:
>> 
> 
>> Dear Experts,
>> How can I align a predefined grid source model to an existing head model? ( I have aligned the electrodes to  the headmodel manually but I'm not sure how to align a dipole position on the headmodel).
>> Looking forward to hearing from you!
>> Regards,
>> Fereshte Ramezani 
> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl <mailto:fieldtrip at donders.ru.nl>
>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip <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 <https://mailman.science.ru.nl/mailman/listinfo/fieldtrip>_______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From martin.bleichner at uni-oldenburg.de  Wed Jan 10 15:39:55 2018
From: martin.bleichner at uni-oldenburg.de (Martin Bleichner)
Date: Wed, 10 Jan 2018 15:39:55 +0100
Subject: [FieldTrip] 2nd International LSL Workshop (27.9-28.9.2018) - Save
	the Date
In-Reply-To: <CAPg9X1SEq_9ZWorE2bNOvwb=+vS45LmfYWiRUxWHOH1YqMMEwA@mail.gmail.com>
References: <CAPg9X1SCR_3Y0Kz+rJVGEGZkeQcHDUH0jPVvuJCLK2yVCO0eNA@mail.gmail.com>
 <CAPg9X1Qhsn-3xt=Kh60tSh3xe6s6o77PgukrAcM1bPmi-YFtFQ@mail.gmail.com>
 <2c8b685b-d7c4-e8f9-d00e-ec9fe96bd48b@gmail.com>
 <CAPg9X1SEq_9ZWorE2bNOvwb=+vS45LmfYWiRUxWHOH1YqMMEwA@mail.gmail.com>
Message-ID: <27e861b5-5224-61c5-d02c-3b70140acba2@uni-oldenburg.de>

Dear colleagues,

We are happy to announce the second international Lab Streaming Layer 
(LSL) workshop, which will take place September 27 - 28, 2018, at the 
Hanse Wissenschaftskolleg, in Delmenhorst, Germany. LSL is an 
open-source project enabling the synchronized streaming of time series 
data coming from different devices, such as EEG amplifiers, audio, 
video, eye tracking, keyboards, etc. LSL features near real-time access 
to data streams, time-synchronization, networking and centralized 
collection (https://github.com/sccn/labstreaminglayer).

Key LSL developers and expert users have confirmed attendance. The 
workshop will provide a general introduction to LSL. We will present how 
LSL can be used for a multitude of different experimental setups, using 
a variety of experimental software, hardware and operating systems. In a 
hands-on session, participants can learn to stream data from their own 
hardware or play with hardware provided by us and external partners. We 
will name pitfalls and discuss how to test and ensure the best possible 
timing accuracy when recording multimodal data. We will also provide a 
best practice guide and present different use cases of LSL. We will also 
use the workshop to discuss future software and hardware developments.

Participants are invited to contribute to the workshop by presenting 
their LSL use cases.

More information on the workshop will follow soon. For further 
enquiries, please contact: martin.bleichner at uol.de 
<mailto:martin.bleichner at uol.de>

Best,

Martin Bleichner

-- 
Dr. Martin Bleichner
Neuropsychology    Lab
Department of Psychology
University of Oldenburg
D-26111 Oldenburg
Germany

martin.bleichner at uni-oldenburg.de
Tel.: +49 (0)441 - 798-2940
http://www.uni-oldenburg.de/psychologie/neuropsychologie/team/martin-bleichner/

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From r.oostenveld at donders.ru.nl  Wed Jan 10 15:55:57 2018
From: r.oostenveld at donders.ru.nl (Robert Oostenveld)
Date: Wed, 10 Jan 2018 15:55:57 +0100
Subject: [FieldTrip] question on cluster-based statistics and source
	localization
In-Reply-To: <F96BCA30-0C1F-4C3B-9DE3-CDB22827049F@ulb.ac.be>
References: <F96BCA30-0C1F-4C3B-9DE3-CDB22827049F@ulb.ac.be>
Message-ID: <E1AC378D-E513-472B-A443-6E1439FE0A50@donders.ru.nl>

Hi Vincent,

Let me reply through the email list, where other people might learn something and/or want to chime in.

> On 10 Jan 2018, at 13:22, Vincent Wens <vwens at ulb.ac.be> wrote:
> 
> Dear Pr. Oostenveld,
> 
> I am Vincent Wens, a physicist working in the MEG unit at Erasme Hospital, Brussels. We've been recently trying to play with the cluster-based statistics that you developed and included in Fieldtrip, but hit a difficulty in our analysis pipeline and I wondered if you would be so kind to take a few minutes and provide advice on this? 

The cluster-based statistics is a method for statistical inference, i.e. statistical decision making based on a hypothesis and estimated probability distribution. The hypothesis H0 states that the data can be exchanged (between conditions). If it is very unlikely that the data can be exchanged (under H0), we decide that the data must be different somehow. The clusters provide evidence for the data being different, but the clusters are not the difference itself. The tip of an iceberg above the sea level provides evidence for there being an iceberg, but the tip is not the iceberg itself. 

An important FAQ is this http://www.fieldtriptoolbox.org/faq/how_not_to_interpret_results_from_a_cluster-based_permutation_test

Let me give the other commens in-line in your email below

> Globally, my question is how to go from sensor-level cluster statistics results to the source space.
> 
> More precisely: Assume we run the cluster statistics analysis on, say, N-channels time-frequency plots and obtain significance for the maximum cluster statistic.

So you obtain evidence that the channel level data is different. That logically implies that the cortical activity is different. Note that the other way arround would not hold per see; there can be different activity in the brain without it showing up as a difference in the scalp data.

> We thus find one (and possibly more) supra-threshold cluster(s) whose "spatio-spectral-temporal localization" can be assessed.

You could look at the visible tip (i.e. the cluster), you could also take a broader approach and look at the phenomenom under the tip (the iceberg).

> See for example the attached picture depicting the plot of those T-values within the significant cluster associated with an ERD. The next step would then be to source localize this,

You would not localize the cluster (you already have it, it is at the channel level). You localize the cortical activity that causes the data to appear different at the channel level. It’s the part of the iceberg under the sea level that causes the tip to appear above sea level.

> and our initial idea was to use the time and frequency region from this cluster as a prior on the time and frequency used for source projection. However the very complex shape of the cluster does not make this step so obvious. There are multiple possibilities that would come to mind, most of them absolutely ad-hoc, so I wondered your opinion on what would be the most rigorous, or at least least unacceptable way to go (or even just the most standard way, if there's one).

Based on the resulls (the multiplot), you should wonder whether there is only a single feature in the brain that is different or whether there are multiple. The hypothesis you started with was “is there any difference in this massive multiple-comparision space?” and the (only) answer you got to that question was “yes”. 

You now have the question “what is the difference”, which pertains to interpreting the data. That question has no binary answer and a statistical test based of a p-value being small enough (which gives you a "yes/no" answer) does not help.

I cannot offer specific advice on how to interpret your data, but recommend that you consider whether your true quest is for “the (one and only) effect” or “the effects” that causes the data in the two conditions to be different. Of course you can argue that the effect(s) show at certain frequency ranges and/or latencies and/or locations, and therefore you may decide to look for the interpretation of the effect(s) at or around those parts of the cluster. 

In general (not any more for this dataset) it is worthwile to consider that narrow a-priori hypotheses provide more valuable and specific information. This is something that we often rely on in sequential studies, where in the 2nd study we don’t repeat the full hypothesis of the 1st study (e.g. “is there any difference”), but a more specific sub-hypothesis that we generated on basis of the first study (e.g. is there a difference around this specific time-frequency range).

> Thanks in advance for your invaluable help, and still my best wishes for the New Year.

You’re welcome. Please follow up questions on the email discussion list.

best regards,
Robert


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From a.stolk8 at gmail.com  Wed Jan 10 17:16:09 2018
From: a.stolk8 at gmail.com (Arjen Stolk)
Date: Wed, 10 Jan 2018 08:16:09 -0800
Subject: [FieldTrip] error in ft_prepare_headmodel
In-Reply-To: <4BA0D72D-FC3B-4AF9-BDF2-08E60C01D689@donders.ru.nl>
References: <39853797796B114D8DE552AC4996EA6835C4BD60@MBX11.ad.oak.ox.ac.uk>
 <4BA0D72D-FC3B-4AF9-BDF2-08E60C01D689@donders.ru.nl>
Message-ID: <6131501D-762A-4258-B43E-4AB8FC3D7E57@gmail.com>

Hi Tom, 

As another work around, you could try using spm12 functionality. cfg.spmversion = ‘spm12’ if the function supports it, or by manually putting it on the path with ft_hastoolbox. There may be differences in the algorithm/outcome between versions, so you may want to be consistent in its use across subjects.

Best,
Arjen

> On Jan 10, 2018, at 12:36 AM, Schoffelen, J.M. (Jan Mathijs) <jan.schoffelen at donders.ru.nl> wrote:
> 
> Dear Tom,
> 
> To me, this looks like a platform/MATLAB version specific issue with the compiled mex-files. Anecdotally, MATLAB2017a on a Mac suffers from not knowing to handle the precompiled stuff that comes with FieldTrip/SPM. Either you could use a lower matlab version (e.g. 2016b, which as far as I know does not suffer from this), or you could try and recompile the affected mex-files from the original c-code with the matlab mex-command. See http://bit.ly/2DeuNlX for more info.
> 
> Best wishes,
> JM
> 
> 
>> On 9 Jan 2018, at 17:27, Tom Marshall <tom.marshall at psy.ox.ac.uk> wrote:
>> 
>> Howdy 'Trippers,
>> 
>> I got a weird error when trying to create a template headmodel using ft_prepare_headmodel (basically just following the steps in the tutorial 'Creating a sourcemodel for source-reconstruction of MEG or EEG data').
>> 
>> After loading and segmenting the template brain I called ft_prepare_headmodel using the suggested parameters.
>> 
>> cfg          = [];
>> cfg.method   = 'singleshell';
>> template_headmodel = ft_prepare_headmodel(cfg, template_seg);
>> 
>> This gave the following error.
>> 
>> Error using ft_notification (line 314)
>> please specificy cfg.tissue and pass an appropriate segmented MRI as input data
>> 
>> Error in ft_error (line 39)
>>   ft_notification(varargin{:});
>> 
>> Error in ft_prepare_headmodel (line 354)
>>           ft_error('please specificy cfg.tissue and pass an appropriate segmented
>>           MRI as input data')
>> 
>> So I added cfg.tissue...
>> 
>> cfg          = [];
>> cfg.method   = 'singleshell';
>> cfg.tissue   = 'brain';
>> template_headmodel = ft_prepare_headmodel(cfg, template_seg);
>> 
>> ...and this upset fieldtrip. After printing 'smoothing brain with a 5-voxel FWHM kernel', it hung for 10-15 minutes, then threw an error with lots of 'Missing symbol' statements (see below - there are a few hundred more, I just copypasted the last two).
>> 
>> Missing symbol '_vm_allocate' required by
>> '/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'
>> Missing symbol '_vm_deallocate' required by
>> '/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'.
>> 
>> Error in spm_smooth>smooth1 (line 105)
>> spm_conv_vol(P,Q,x,y,z,-[i,j,k]);
>> 
>> Error in spm_smooth (line 40)
>>     smooth1(P,Q,s,dtype);
>> 
>> Error in volumesmooth (line 18)
>> spm_smooth(output, output, fwhm);
>> 
>> Error in ft_datatype_segmentation (line 229)
>>           brain = volumesmooth(brain,    smooth,    'brain');
>> 
>> Error in prepare_mesh_segmentation (line 95)
>>     mri = ft_datatype_segmentation(mri, 'segmentationstyle', 'probabilistic',
>>     'hasbrain', 'yes');
>> 
>> Error in ft_prepare_mesh (line 147)
>>     bnd = prepare_mesh_segmentation(cfg, mri);
>> 
>> Error in ft_prepare_headmodel (line 337)
>>         geometry = ft_prepare_mesh(tmpcfg, data);
>> 
>> It seems like the problem is somewhere deep down in spm commands that fieldtrip is calling, so maybe nobody has a clue. I'm hoping somebody has seen this before and knows of a fix...
>> 
>> In case it's relevant: I'm running fieldtrip-20170726 in matlab R2017a on a mac.
>> 
>> And ideas?
>> 
>> Best,
>> Tom
>> _______________________________________________
>> 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
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From tom.marshall at psy.ox.ac.uk  Wed Jan 10 19:42:29 2018
From: tom.marshall at psy.ox.ac.uk (Tom Marshall)
Date: Wed, 10 Jan 2018 18:42:29 +0000
Subject: [FieldTrip] error in ft_prepare_headmodel
In-Reply-To: <6131501D-762A-4258-B43E-4AB8FC3D7E57@gmail.com>
References: <39853797796B114D8DE552AC4996EA6835C4BD60@MBX11.ad.oak.ox.ac.uk>
 <4BA0D72D-FC3B-4AF9-BDF2-08E60C01D689@donders.ru.nl>,
 <6131501D-762A-4258-B43E-4AB8FC3D7E57@gmail.com>
Message-ID: <39853797796B114D8DE552AC4996EA6835C4C11B@MBX11.ad.oak.ox.ac.uk>

Hi Arjen and JM,

Arjen - thanks for the golden tip!

As suggested, I explicitly added the SPM12 toolbox and called it in the cfg.

[status] = ft_hastoolbox('SPM12', 1, 0);

cfg                = [];
cfg.grid.warpmni   = 'yes';
cfg.grid.template  = template_grid;
cfg.grid.nonlinear = 'yes'; % use non-linear normalization
cfg.spmversion     = 'SPM12';
cfg.mri                = mri;
sourcemodel        = ft_prepare_sourcemodel(cfg);

However, this didn't totally solve the problem. At one point in ft_prepare_sourcemodel (line 636) ft_volumenormalise is called with a new cfg ('tmpcfg'). The choice to use SPM12 doesn't propagate to tmpcfg so fieldtrip adds SPM8 anyway when it calls ft_volumenormalise.

I fixed this by adding the following to ft_prepare_sourcemodel at line 633...

tmpcfg.spmversion = cfg.spmversion;

...and voila! A nice warped source model :)

Should I file this as a bug?

Best and thanks for the help,
Tom

________________________________
From: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl] on behalf of Arjen Stolk [a.stolk8 at gmail.com]
Sent: 10 January 2018 16:16
To: FieldTrip discussion list
Subject: Re: [FieldTrip] error in ft_prepare_headmodel

Hi Tom,

As another work around, you could try using spm12 functionality. cfg.spmversion = ‘spm12’ if the function supports it, or by manually putting it on the path with ft_hastoolbox. There may be differences in the algorithm/outcome between versions, so you may want to be consistent in its use across subjects.

Best,
Arjen

On Jan 10, 2018, at 12:36 AM, Schoffelen, J.M. (Jan Mathijs) <jan.schoffelen at donders.ru.nl<mailto:jan.schoffelen at donders.ru.nl>> wrote:

Dear Tom,

To me, this looks like a platform/MATLAB version specific issue with the compiled mex-files. Anecdotally, MATLAB2017a on a Mac suffers from not knowing to handle the precompiled stuff that comes with FieldTrip/SPM. Either you could use a lower matlab version (e.g. 2016b, which as far as I know does not suffer from this), or you could try and recompile the affected mex-files from the original c-code with the matlab mex-command. See http://bit.ly/2DeuNlX for more info.

Best wishes,
JM


On 9 Jan 2018, at 17:27, Tom Marshall <tom.marshall at psy.ox.ac.uk<mailto:tom.marshall at psy.ox.ac.uk>> wrote:

Howdy 'Trippers,

I got a weird error when trying to create a template headmodel using ft_prepare_headmodel (basically just following the steps in the tutorial 'Creating a sourcemodel for source-reconstruction of MEG or EEG data').

After loading and segmenting the template brain I called ft_prepare_headmodel using the suggested parameters.

cfg          = [];
cfg.method   = 'singleshell';
template_headmodel = ft_prepare_headmodel(cfg, template_seg);

This gave the following error.

Error using ft_notification (line 314)
please specificy cfg.tissue and pass an appropriate segmented MRI as input data

Error in ft_error (line 39)
  ft_notification(varargin{:});

Error in ft_prepare_headmodel (line 354)
          ft_error('please specificy cfg.tissue and pass an appropriate segmented
          MRI as input data')

So I added cfg.tissue...

cfg          = [];
cfg.method   = 'singleshell';
cfg.tissue   = 'brain';
template_headmodel = ft_prepare_headmodel(cfg, template_seg);

...and this upset fieldtrip. After printing 'smoothing brain with a 5-voxel FWHM kernel', it hung for 10-15 minutes, then threw an error with lots of 'Missing symbol' statements (see below - there are a few hundred more, I just copypasted the last two).

Missing symbol '_vm_allocate' required by
'/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'
Missing symbol '_vm_deallocate' required by
'/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'.

Error in spm_smooth>smooth1 (line 105)
spm_conv_vol(P,Q,x,y,z,-[i,j,k]);

Error in spm_smooth (line 40)
    smooth1(P,Q,s,dtype);

Error in volumesmooth (line 18)
spm_smooth(output, output, fwhm);

Error in ft_datatype_segmentation (line 229)
          brain = volumesmooth(brain,    smooth,    'brain');

Error in prepare_mesh_segmentation (line 95)
    mri = ft_datatype_segmentation(mri, 'segmentationstyle', 'probabilistic',
    'hasbrain', 'yes');

Error in ft_prepare_mesh (line 147)
    bnd = prepare_mesh_segmentation(cfg, mri);

Error in ft_prepare_headmodel (line 337)
        geometry = ft_prepare_mesh(tmpcfg, data);

It seems like the problem is somewhere deep down in spm commands that fieldtrip is calling, so maybe nobody has a clue. I'm hoping somebody has seen this before and knows of a fix...

In case it's relevant: I'm running fieldtrip-20170726 in matlab R2017a on a mac.

And ideas?

Best,
Tom
_______________________________________________
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
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From joseluisblues at gmail.com  Thu Jan 11 00:41:02 2018
From: joseluisblues at gmail.com (Jose)
Date: Wed, 10 Jan 2018 20:41:02 -0300
Subject: [FieldTrip] shrunk TFR topoplot
Message-ID: <CAH3cVdDVWKYSmGgL8U9At84dUREFy+RmCN6kLuYAjJvoP8Vcqg@mail.gmail.com>

dear list,

I'm trying to do a time-frequency plot with ft_topoplotTFR including first
an average across all conditions followed by specific conditions. I want to
highlight my sensors of interest for the first topoplot (the average across
all conditions), and I'm running in a rather annoying issue. When
highlighting the sensors the topoplot is slightly shrunk relative to the
other topoplots,

Has anybody run into this problem and find a workaround?

Thanks for any hints,

Jose

A snippet of my code is below,

%%%

    cfg = [ ];
    cfg.baseline = baselinePeriod;
    cfg.baselinetype = baselineType;
    cfg.xlim = TOI;
    cfg.ylim = YLimsFreq;
    cfg.zlim = ZLimsPower;
    cfg.marker = 'off';
    cfg.layout = 'biosemi64.lay';
    cfg.comment = 'no';
    cfg.interactive = 'no';
    % highlight
    cfg.highlight = 'on';
    cfg.highlightchannel = chan2use{i_chanSel};
    cfg.highlightcolor = [0 0 0];
    cfg.highlightsymbol = '.';
    cfg.highlightsize = 12;

    subplot(2,4,5); ft_topoplotTFR(cfg, datAll); colormap jet

    cfg = [ ];
    cfg.baseline = baselinePeriod;
    cfg.baselinetype = baselineType;
    cfg.xlim = TOI;
    cfg.ylim = YLimsFreq;
    cfg.zlim = ZLimsPower;
    cfg.marker = 'off';
    cfg.layout = 'biosemi64.lay';
    cfg.comment = 'no';
    cfg.interactive = 'no';
    subplot(2,4,6); ft_topoplotTFR(cfg, datCongr); colormap jet
    subplot(2,4,7); ft_topoplotTFR(cfg, datIncong); colormap jet
    subplot(2,4,8); ft_topoplotTFR(cfg, datNeutral); colormap jet

%%%
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From a.stolk8 at gmail.com  Thu Jan 11 07:49:44 2018
From: a.stolk8 at gmail.com (Arjen Stolk)
Date: Wed, 10 Jan 2018 22:49:44 -0800
Subject: [FieldTrip] error in ft_prepare_headmodel
In-Reply-To: <39853797796B114D8DE552AC4996EA6835C4C11B@MBX11.ad.oak.ox.ac.uk>
References: <39853797796B114D8DE552AC4996EA6835C4BD60@MBX11.ad.oak.ox.ac.uk>
 <4BA0D72D-FC3B-4AF9-BDF2-08E60C01D689@donders.ru.nl>
 <6131501D-762A-4258-B43E-4AB8FC3D7E57@gmail.com>
 <39853797796B114D8DE552AC4996EA6835C4C11B@MBX11.ad.oak.ox.ac.uk>
Message-ID: <CAAiwptTqisR_8ztKL86+kgYmYqS0tCtvqRRX3c95FnyNDtKCYw@mail.gmail.com>

Glad to see it worked, Tom. Full support for SPM12 has only recently been
completed, with JM laying the last hand on ft_volumenormalization a couple
of weeks ago. Therefore, the issue identified by you might be a missing
link that needs to be created still. Do you think you can you propose your
solution on github, for further joint discussion and implementation?

On Wed, Jan 10, 2018 at 10:42 AM, Tom Marshall <tom.marshall at psy.ox.ac.uk>
wrote:

> Hi Arjen and JM,
>
> Arjen - thanks for the golden tip!
>
> As suggested, I explicitly added the SPM12 toolbox and called it in the
> cfg.
>
>
>
>
>
>
>
>
>
>
>
> *[status] = ft_hastoolbox('SPM12', 1, 0); cfg                = [];
> cfg.grid.warpmni   = 'yes'; cfg.grid.template  = template_grid;
> cfg.grid.nonlinear = 'yes'; % use non-linear normalization
> cfg.spmversion     = 'SPM12'; cfg.mri                = mri;
> sourcemodel        = ft_prepare_sourcemodel(cfg); *However, this didn't
> totally solve the problem. At one point in ft_prepare_sourcemodel (line
> 636) ft_volumenormalise is called with a new cfg ('tmpcfg'). The choice to
> use SPM12 doesn't propagate to tmpcfg so fieldtrip adds SPM8 anyway when it
> calls ft_volumenormalise.
>
> I fixed this by adding the following to ft_prepare_sourcemodel at line
> 633...
>
>
> *tmpcfg.spmversion = cfg.spmversion; *
> ...and voila! A nice warped source model :)
>
> Should I file this as a bug?
>
> Best and thanks for the help,
> Tom
>
> ------------------------------
> *From:* fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl]
> on behalf of Arjen Stolk [a.stolk8 at gmail.com]
> *Sent:* 10 January 2018 16:16
> *To:* FieldTrip discussion list
> *Subject:* Re: [FieldTrip] error in ft_prepare_headmodel
>
> Hi Tom,
>
> As another work around, you could try using spm12 functionality.
> cfg.spmversion = ‘spm12’ if the function supports it, or by manually
> putting it on the path with ft_hastoolbox. There may be differences in the
> algorithm/outcome between versions, so you may want to be consistent in its
> use across subjects.
>
> Best,
> Arjen
>
> On Jan 10, 2018, at 12:36 AM, Schoffelen, J.M. (Jan Mathijs) <
> jan.schoffelen at donders.ru.nl> wrote:
>
> Dear Tom,
>
> To me, this looks like a platform/MATLAB version specific issue with the
> compiled mex-files. Anecdotally, MATLAB2017a on a Mac suffers from not
> knowing to handle the precompiled stuff that comes with FieldTrip/SPM.
> Either you could use a lower matlab version (e.g. 2016b, which as far as I
> know does not suffer from this), or you could try and recompile the
> affected mex-files from the original c-code with the matlab mex-command.
> See http://bit.ly/2DeuNlX for more info.
>
> Best wishes,
> JM
>
>
> On 9 Jan 2018, at 17:27, Tom Marshall <tom.marshall at psy.ox.ac.uk> wrote:
>
> Howdy 'Trippers,
>
> I got a weird error when trying to create a template headmodel using
> ft_prepare_headmodel (basically just following the steps in the tutorial
> 'Creating a sourcemodel for source-reconstruction of MEG or EEG data').
>
> After loading and segmenting the template brain I called
> ft_prepare_headmodel using the suggested parameters.
>
>
>
> *cfg          = []; cfg.method   = 'singleshell'; template_headmodel =
> ft_prepare_headmodel(cfg, template_seg);*
>
> This gave the following error.
>
>
>
>
>
>
>
>
>
> *Error using ft_notification (line 314) please specificy cfg.tissue and
> pass an appropriate segmented MRI as input data Error in ft_error (line 39)
>   ft_notification(varargin{:}); Error in ft_prepare_headmodel (line 354)
>           ft_error('please specificy cfg.tissue and pass an appropriate
> segmented           MRI as input data')*
>
> So I added cfg.tissue...
>
>
>
>
> *cfg          = []; cfg.method   = 'singleshell'; cfg.tissue   = 'brain';
> template_headmodel = ft_prepare_headmodel(cfg, template_seg);*
>
> ...and this upset fieldtrip. After printing *'smoothing brain with a
> 5-voxel FWHM kernel'*, it hung for 10-15 minutes, then threw an error
> with lots of 'Missing symbol' statements (see below - there are a few
> hundred more, I just copypasted the last two).
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
> *Missing symbol '_vm_allocate' required by
> '/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'
> Missing symbol '_vm_deallocate' required by
> '/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'.
> Error in spm_smooth>smooth1 (line 105) spm_conv_vol(P,Q,x,y,z,-[i,j,k]);
> Error in spm_smooth (line 40)     smooth1(P,Q,s,dtype); Error in
> volumesmooth (line 18) spm_smooth(output, output, fwhm); Error in
> ft_datatype_segmentation (line 229)           brain =
> volumesmooth(brain,    smooth,    'brain'); Error in
> prepare_mesh_segmentation (line 95)     mri = ft_datatype_segmentation(mri,
> 'segmentationstyle', 'probabilistic',     'hasbrain', 'yes'); Error in
> ft_prepare_mesh (line 147)     bnd = prepare_mesh_segmentation(cfg, mri);
> Error in ft_prepare_headmodel (line 337)         geometry =
> ft_prepare_mesh(tmpcfg, data); *
> It seems like the problem is somewhere deep down in spm commands that
> fieldtrip is calling, so maybe nobody has a clue. I'm hoping somebody has
> seen this before and knows of a fix...
>
> In case it's relevant: I'm running fieldtrip-20170726 in matlab R2017a on
> a mac.
>
> And ideas?
>
> Best,
> Tom
> _______________________________________________
> 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
>
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From Joachim.Gross at glasgow.ac.uk  Thu Jan 11 12:57:43 2018
From: Joachim.Gross at glasgow.ac.uk (Joachim Gross)
Date: Thu, 11 Jan 2018 11:57:43 +0000
Subject: [FieldTrip] Two Postdoc positions in Muenster, Germany
Message-ID: <A0FC7DEB-28C9-4A8E-A6F2-FF2AD80C7711@contoso.com>



The Institute for Biomagnetism and Biosignalanalysis at University of Muenster invites applications for a

Research associate/Postdoctoral scientist (f/m)
Ref.: 01689
Full-Time with 38,5 (hours/week)
(Germany salary grade: E 13 TV-L, 100%)

Two positions are intramurally funded and available for 2 years.

We are searching for trained and highly motivated scientists holding a PhD or MD degree and having experience in electrophysiology, cognitive neuroimaging or similar disciplines. The successful candidates are expected to have a strong publication record in international peer-reviewed journals.

The research project requires acquisition of MEG data and analysis of neuronal oscillations and their relationship to behaviour. Therefore, experience with MEG/EEG, programming and spectral analysis is essential.

The successful applicants will join a dynamic team of both experienced and junior researchers with many national and international collaborations and a sustained record of high-quality research output.

For more information please contact Prof Dr Joachim Gross, University of Muenster, Institute for Biomagnetism and Biosignalanalysis, 48149 Münster, Germany, Email:. Joachim.Gross(at)wwu(dot)de


Please send your application (including the above reference number) with all relevant information (CV, cover letter) by email (PDF-file, max. 5 MB) until 11.02.2018 to: bewerbung(at)ukmuenster(dot)de

Applications of women are specifically invited. In the case of similar qualifications, competence, and specific achievements, women will be considered on preferential terms within the framework of the legal possibilities. Handicapped candidates with equivalent qualifications will be given preference.


[University of Glasgow: The Times Scottish University of the Year 2018]
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From elam4hcp at gmail.com  Mon Jan 15 21:10:08 2018
From: elam4hcp at gmail.com (Jennifer Elam)
Date: Mon, 15 Jan 2018 14:10:08 -0600
Subject: [FieldTrip] Join us for HCP Course 2018 in Oxford, UK June 25-29!
Message-ID: <CAJbMWh6EONG62anxP+_ShBxhWNkPRyjPpg0HDBBoZNtORUcmBA@mail.gmail.com>

We are pleased to announce the *2018 HCP Course: "Exploring the Human
Connectome"
<http://store.humanconnectome.org/courses/2018/exploring-the-human-connectome.php>*,
to be held *June 25 – 29, 2018* at the Blavatnik School of Government
<https://www.bsg.ox.ac.uk/partner/contact-us>, at the University of Oxford
<http://www.ox.ac.uk/>, in Oxford, UK.
This 5-day intensive course will provide training in acquisition,
processing, analysis and visualization of whole brain imaging and
behavioral data using methods and tools developed by the WU-Minn-Oxford Human
Connectome Project (HCP) consortium.

The course is designed for investigators interested in:

   - using HCP-style data distributed by the Connectome Coordinating
   Facility (CCF) from the young adult (original) HCP and forthcoming projects
   - acquiring and analyzing HCP-style imaging and behavioral data at your
   own institution
   - processing your own non-HCP data using HCP pipelines and methods
   - using Connectome Workbench
   <https://www.humanconnectome.org/software/connectome-workbench.html> tools
   and sharing data using the BALSA <https://balsa.wustl.edu/> imaging
   database
   - learning HCP multimodal neuroimaging analysis methods, including those
   that combine MEG and MRI data
   - positioning yourself to capitalize on HCP-style data forthcoming from
   large-scale projects currently collecting data (e.g., Lifespan HCP
   development and aging and Connectomes Related to Human Disease projects)


Participants will learn how to acquire, analyze, visualize, and interpret
data from four major MR modalities (structural MR, resting-state fMRI,
diffusion imaging, task-evoked fMRI) plus magnetoencephalography (MEG) and
extensive behavioral data.  Lectures and labs will provide grounding in
neurobiological as well as methodological issues involved in interpreting
multimodal data, and will span the range from single-voxel/vertex to brain
network analysis approaches.

The course is open to students, postdocs, faculty, and industry
participants.  The course is aimed at both new and current users of HCP
data, methods, and tools, and will cover both basic and advanced topics.
Prior experience in human neuroimaging or in computational analysis of
brain networks is desirable, preferably including some familiarity with FSL
<https://fsl.fmrib.ox.ac.uk/fsl/fslwiki> and Freesurfer
<https://surfer.nmr.mgh.harvard.edu/> software.

For more info and to register visit the HCP Course 2018 website
<http://store.humanconnectome.org/courses/2018/exploring-the-human-connectome.php>.
New this year is the opportunity to add 6 nights of bed and
breakfast accommodation (Sun June 24 - Fri June 29) at nearby Worcester
College to your registration at a group, taxes included rate.
If you have any questions, please contact us at: hcpcourse at humanconnectome.
org

We look forward to seeing you in Oxford!

Best,
2018 HCP Course Organizers


-- 
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
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From bioeng.yoosofzadeh at gmail.com  Mon Jan 15 22:04:40 2018
From: bioeng.yoosofzadeh at gmail.com (Vahab Yousofzadeh)
Date: Mon, 15 Jan 2018 16:04:40 -0500
Subject: [FieldTrip] question on cluster-based statistics and source
Message-ID: <CAL5FLdKFs0rOBwkY29xTi7GZ_Kotdmjmdu9RCzkg34kSB0B24Q@mail.gmail.com>

Dear Vincent,

For cluster correction at source space, you would need to trick the
ft_prepare_neighbours because (as far as I know) it only works with
sensor-space data - so you just need to update the pos. with those
from the source model. Here's a piece of scripts:

s = timePost; % timePost is the output of ft_timelockanalysis.
s.grad.chanpos = headmodel_time.pos(headmodel_time.inside,:);
s.grad.chanori = s.grad.chanpos;
s.grad.chanunit(1:size(s.grad.chanpos,1)) = s.grad.chanunit(1);
s.grad.chantype(1:size(s.grad.chanpos,1)) = s.grad.chantype(1);
s.grad.tra    = ones(size(s.grad.chanpos,1),size(s.grad.tra,2));
for i=1:size(s.grad.chanpos,1)
    s.grad.label{i} = num2str(i);
    s.label{i} = num2str(i);
    s.grad.labelold =  num2str(i);
end
% prepare_neighbours determines what sensors may form clusters
cfg_neighb.method   = 'distance';
% cfg.method      = 'triangulation';
neighbours          = ft_prepare_neighbours(cfg_neighb, s);

%% inspecting random neighbours (#1200)
neighbours2 = [];
neighbours2 = neighbours(1200);
% neighbours2.neighblabel = neighbours2.neighblabel(1:20);
% plotting neighbours for inspection
cfg            = [];
cfg.neighbours = neighbours2;
ft_neighbourplot_source(cfg, s);

Now for cluster-correction, you need to have your source trials as
inputs, and do something like:

%% Cluster-correction
cfg = [];
cfg.parameter        = 'pow';
cfg.dim              = sourcemodel.dim;
cfg.method           = 'montecarlo';
% cfg.statistic        = 'ft_statfun_depsamplesT';
cfg.statistic        = 'depsamplesT';
% cfg.statistic         = 'indepsamplesT';
cfg.correctm         = 'cluster';
% cfg.correctm         = 'fdr';
cfg.clusteralpha     = 0.01;
cfg.clusterstatistic = 'max';
% cfg.correcttail = 'prob';
cfg.tail             = 0;
cfg.clustertail      = 0;
cfg.alpha            = 0.05;
cfg.numrandomization = 5000;
cfg.neighbours      = ft_prepare_neighbours(cfg_neighb, s);

ntrials                       = L;
design                        = zeros(2,2*ntrials);
design(1,1:ntrials)           = 1;
design(1,ntrials+1:2*ntrials) = 2;
design(2,1:ntrials)           = 1:ntrials;
design(2,ntrials+1:2*ntrials) = 1:ntrials;

cfg.design   = design;
cfg.ivar     = 1;
cfg.uvar     = 2;
stat         = ft_sourcestatistics(cfg,Source1,Source2);
stat.pos     = souremodel.pos;% keep positions for plotting later

and for plotting stats,

cfg              = [];
cfg.voxelcoord   = 'no';
cfg.parameter    = 'stat';
% cfg.interpmethod = 'nearest';
cfg.interpmethod = 'sphere_avg';
statint  = ft_sourceinterpolate(cfg, stat, template_mri);
cfg.parameter    = 'mask';
maskint  = ft_sourceinterpolate(cfg, stat, template_mri);

statint.mask = maskint.mask;

atlas = ft_read_atlas('ROI_MNI_V4.nii');

statint.coordsys  = 'mni';
cfg               = [];
cfg.method        = 'ortho';
% cfg.method = 'slice';
cfg.funparameter  = 'stat';
cfg.maskparameter = 'mask';
cfg.atlas         = atlas;
cfg.location      = 'max';
% cfg.funcolorlim   = [-5 5];
cfg.funcolormap   = 'jet';
% cfg.location = [x,y,z];
ft_sourceplot(cfg,statint);

Hope this helps, and let me know if you are running into issues.

Cheers,
Vahab

On Wed, Jan 10, 2018 at 9:55 AM,  <fieldtrip-request at science.ru.nl> wrote:
> Send fieldtrip mailing list submissions to
>         fieldtrip at science.ru.nl
>
> To subscribe or unsubscribe via the World Wide Web, visit
>         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
>
> You can reach the person managing the list at
>         fieldtrip-owner at science.ru.nl
>
> When replying, please edit your Subject line so it is more specific
> than "Re: Contents of fieldtrip digest..."
>
>
> Today's Topics:
>
>    1. 2nd International LSL Workshop (27.9-28.9.2018) - Save    the
>       Date (Martin Bleichner)
>    2. Re: question on cluster-based statistics and source
>       localization (Robert Oostenveld)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Wed, 10 Jan 2018 15:39:55 +0100
> From: Martin Bleichner <martin.bleichner at uni-oldenburg.de>
> To: lsl-l at mailman.ucsd.edu, eeglablist at sccn.ucsd.edu,
>         fieldtrip at science.ru.nl
> Subject: [FieldTrip] 2nd International LSL Workshop (27.9-28.9.2018) -
>         Save    the Date
> Message-ID: <27e861b5-5224-61c5-d02c-3b70140acba2 at uni-oldenburg.de>
> Content-Type: text/plain; charset="utf-8"; Format="flowed"
>
> Dear colleagues,
>
> We are happy to announce the second international Lab Streaming Layer
> (LSL) workshop, which will take place September 27 - 28, 2018, at the
> Hanse Wissenschaftskolleg, in Delmenhorst, Germany. LSL is an
> open-source project enabling the synchronized streaming of time series
> data coming from different devices, such as EEG amplifiers, audio,
> video, eye tracking, keyboards, etc. LSL features near real-time access
> to data streams, time-synchronization, networking and centralized
> collection (https://github.com/sccn/labstreaminglayer).
>
> Key LSL developers and expert users have confirmed attendance. The
> workshop will provide a general introduction to LSL. We will present how
> LSL can be used for a multitude of different experimental setups, using
> a variety of experimental software, hardware and?operating systems. In a
> hands-on session, participants can learn to stream data from their own
> hardware or play with hardware provided by us and external partners. We
> will name pitfalls and discuss how to test and ensure the best possible
> timing accuracy when recording multimodal data. We will also provide a
> best practice guide and present different use cases of LSL. We will also
> use the workshop to discuss future software and hardware developments.
>
> Participants are invited to contribute to the workshop by presenting
> their LSL use cases.
>
> More information on the workshop will follow soon. For further
> enquiries, please contact: martin.bleichner at uol.de
> <mailto:martin.bleichner at uol.de>
>
> Best,
>
> Martin Bleichner
>
> --
> Dr. Martin Bleichner
> Neuropsychology    Lab
> Department of Psychology
> University of Oldenburg
> D-26111 Oldenburg
> Germany
>
> martin.bleichner at uni-oldenburg.de
> Tel.: +49 (0)441 - 798-2940
> http://www.uni-oldenburg.de/psychologie/neuropsychologie/team/martin-bleichner/
>
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>
> ------------------------------
>
> Message: 2
> Date: Wed, 10 Jan 2018 15:55:57 +0100
> From: Robert Oostenveld <r.oostenveld at donders.ru.nl>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Cc: Vincent Wens <vwens at ulb.ac.be>
> Subject: Re: [FieldTrip] question on cluster-based statistics and
>         source  localization
> Message-ID: <E1AC378D-E513-472B-A443-6E1439FE0A50 at donders.ru.nl>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Vincent,
>
> Let me reply through the email list, where other people might learn something and/or want to chime in.
>
>> On 10 Jan 2018, at 13:22, Vincent Wens <vwens at ulb.ac.be> wrote:
>>
>> Dear Pr. Oostenveld,
>>
>> I am Vincent Wens, a physicist working in the MEG unit at Erasme Hospital, Brussels. We've been recently trying to play with the cluster-based statistics that you developed and included in Fieldtrip, but hit a difficulty in our analysis pipeline and I wondered if you would be so kind to take a few minutes and provide advice on this?
>
> The cluster-based statistics is a method for statistical inference, i.e. statistical decision making based on a hypothesis and estimated probability distribution. The hypothesis H0 states that the data can be exchanged (between conditions). If it is very unlikely that the data can be exchanged (under H0), we decide that the data must be different somehow. The clusters provide evidence for the data being different, but the clusters are not the difference itself. The tip of an iceberg above the sea level provides evidence for there being an iceberg, but the tip is not the iceberg itself.
>
> An important FAQ is this http://www.fieldtriptoolbox.org/faq/how_not_to_interpret_results_from_a_cluster-based_permutation_test
>
> Let me give the other commens in-line in your email below
>
>> Globally, my question is how to go from sensor-level cluster statistics results to the source space.
>>
>> More precisely: Assume we run the cluster statistics analysis on, say, N-channels time-frequency plots and obtain significance for the maximum cluster statistic.
>
> So you obtain evidence that the channel level data is different. That logically implies that the cortical activity is different. Note that the other way arround would not hold per see; there can be different activity in the brain without it showing up as a difference in the scalp data.
>
>> We thus find one (and possibly more) supra-threshold cluster(s) whose "spatio-spectral-temporal localization" can be assessed.
>
> You could look at the visible tip (i.e. the cluster), you could also take a broader approach and look at the phenomenom under the tip (the iceberg).
>
>> See for example the attached picture depicting the plot of those T-values within the significant cluster associated with an ERD. The next step would then be to source localize this,
>
> You would not localize the cluster (you already have it, it is at the channel level). You localize the cortical activity that causes the data to appear different at the channel level. It?s the part of the iceberg under the sea level that causes the tip to appear above sea level.
>
>> and our initial idea was to use the time and frequency region from this cluster as a prior on the time and frequency used for source projection. However the very complex shape of the cluster does not make this step so obvious. There are multiple possibilities that would come to mind, most of them absolutely ad-hoc, so I wondered your opinion on what would be the most rigorous, or at least least unacceptable way to go (or even just the most standard way, if there's one).
>
> Based on the resulls (the multiplot), you should wonder whether there is only a single feature in the brain that is different or whether there are multiple. The hypothesis you started with was ?is there any difference in this massive multiple-comparision space?? and the (only) answer you got to that question was ?yes?.
>
> You now have the question ?what is the difference?, which pertains to interpreting the data. That question has no binary answer and a statistical test based of a p-value being small enough (which gives you a "yes/no" answer) does not help.
>
> I cannot offer specific advice on how to interpret your data, but recommend that you consider whether your true quest is for ?the (one and only) effect? or ?the effects? that causes the data in the two conditions to be different. Of course you can argue that the effect(s) show at certain frequency ranges and/or latencies and/or locations, and therefore you may decide to look for the interpretation of the effect(s) at or around those parts of the cluster.
>
> In general (not any more for this dataset) it is worthwile to consider that narrow a-priori hypotheses provide more valuable and specific information. This is something that we often rely on in sequential studies, where in the 2nd study we don?t repeat the full hypothesis of the 1st study (e.g. ?is there any difference?), but a more specific sub-hypothesis that we generated on basis of the first study (e.g. is there a difference around this specific time-frequency range).
>
>> Thanks in advance for your invaluable help, and still my best wishes for the New Year.
>
> You?re welcome. Please follow up questions on the email discussion list.
>
> best regards,
> Robert
>
>
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>
> ------------------------------
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
> End of fieldtrip Digest, Vol 86, Issue 6
> ****************************************



From p.gaur at ulster.ac.uk  Tue Jan 16 15:26:53 2018
From: p.gaur at ulster.ac.uk (Gaur, Pramod)
Date: Tue, 16 Jan 2018 14:26:53 +0000
Subject: [FieldTrip] MEG UK 2018
Message-ID: <DB4PR06MB5855B4287245A8DBDC6C9DAB0EA0@DB4PR06MB585.eurprd06.prod.outlook.com>

Dear All,

The MEG UK 2018<http://meguk2018.co.uk/>, an annual conference focused on bringing together research groups working with magnetoencephalography (MEG) in the UK, will be held on  26-28 March 2018, at Ulster University, Magee Campus, Derry~Londonderry, Northern Ireland, UK. The conference is being organized by the Northern Ireland Functional Brain Mapping<https://www.ulster.ac.uk/research/institutes/computer-science/groups/intelligent-systems-research-centre/projects> (NIFBM) facility of the Intelligent Systems Research Centre (ISRC), a major research unit within the Faculty of Computing, Engineering and the Built Environment at Ulster's Magee campus.
More Details can be obtained from the MEG UK 2018 conference (http://meguk2018.co.uk/) website. We have secured very good deals for accommodation in local hotels as well as for local travel from Belfast airports by airporter.  Since number of places are limited, early registration and bookings are highly recommended.

Please register at the earliest to avoid disappointment.

Thanks,
MEG UK 2018



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From stephen.whitmarsh at gmail.com  Thu Jan 18 18:02:00 2018
From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh)
Date: Thu, 18 Jan 2018 18:02:00 +0100
Subject: [FieldTrip] question on cluster-based statistics and source
In-Reply-To: <CAL5FLdKFs0rOBwkY29xTi7GZ_Kotdmjmdu9RCzkg34kSB0B24Q@mail.gmail.com>
References: <CAL5FLdKFs0rOBwkY29xTi7GZ_Kotdmjmdu9RCzkg34kSB0B24Q@mail.gmail.com>
Message-ID: <CAFrxm=xt_cUZfL_MFbG8K27dKwOfmUaKg+mtmRsbMDRPHjhbEA@mail.gmail.com>

Hi there,

I just wanted to follow up and note that cluster-statistics are certainly
implemented for source-level reconstructed data (as a pointer to start,
see: http://www.fieldtriptoolbox.org/example/source_statistics)
I strongly suggest to use the functionality as intended in which most of
the typical user cases should be supported.

Best wishes,
Stephen




On 15 January 2018 at 22:04, Vahab Yousofzadeh <bioeng.yoosofzadeh at gmail.com
> wrote:

> Dear Vincent,
>
> For cluster correction at source space, you would need to trick the
> ft_prepare_neighbours because (as far as I know) it only works with
> sensor-space data - so you just need to update the pos. with those
> from the source model. Here's a piece of scripts:
>
> s = timePost; % timePost is the output of ft_timelockanalysis.
> s.grad.chanpos = headmodel_time.pos(headmodel_time.inside,:);
> s.grad.chanori = s.grad.chanpos;
> s.grad.chanunit(1:size(s.grad.chanpos,1)) = s.grad.chanunit(1);
> s.grad.chantype(1:size(s.grad.chanpos,1)) = s.grad.chantype(1);
> s.grad.tra    = ones(size(s.grad.chanpos,1),size(s.grad.tra,2));
> for i=1:size(s.grad.chanpos,1)
>     s.grad.label{i} = num2str(i);
>     s.label{i} = num2str(i);
>     s.grad.labelold =  num2str(i);
> end
> % prepare_neighbours determines what sensors may form clusters
> cfg_neighb.method   = 'distance';
> % cfg.method      = 'triangulation';
> neighbours          = ft_prepare_neighbours(cfg_neighb, s);
>
> %% inspecting random neighbours (#1200)
> neighbours2 = [];
> neighbours2 = neighbours(1200);
> % neighbours2.neighblabel = neighbours2.neighblabel(1:20);
> % plotting neighbours for inspection
> cfg            = [];
> cfg.neighbours = neighbours2;
> ft_neighbourplot_source(cfg, s);
>
> Now for cluster-correction, you need to have your source trials as
> inputs, and do something like:
>
> %% Cluster-correction
> cfg = [];
> cfg.parameter        = 'pow';
> cfg.dim              = sourcemodel.dim;
> cfg.method           = 'montecarlo';
> % cfg.statistic        = 'ft_statfun_depsamplesT';
> cfg.statistic        = 'depsamplesT';
> % cfg.statistic         = 'indepsamplesT';
> cfg.correctm         = 'cluster';
> % cfg.correctm         = 'fdr';
> cfg.clusteralpha     = 0.01;
> cfg.clusterstatistic = 'max';
> % cfg.correcttail = 'prob';
> cfg.tail             = 0;
> cfg.clustertail      = 0;
> cfg.alpha            = 0.05;
> cfg.numrandomization = 5000;
> cfg.neighbours      = ft_prepare_neighbours(cfg_neighb, s);
>
> ntrials                       = L;
> design                        = zeros(2,2*ntrials);
> design(1,1:ntrials)           = 1;
> design(1,ntrials+1:2*ntrials) = 2;
> design(2,1:ntrials)           = 1:ntrials;
> design(2,ntrials+1:2*ntrials) = 1:ntrials;
>
> cfg.design   = design;
> cfg.ivar     = 1;
> cfg.uvar     = 2;
> stat         = ft_sourcestatistics(cfg,Source1,Source2);
> stat.pos     = souremodel.pos;% keep positions for plotting later
>
> and for plotting stats,
>
> cfg              = [];
> cfg.voxelcoord   = 'no';
> cfg.parameter    = 'stat';
> % cfg.interpmethod = 'nearest';
> cfg.interpmethod = 'sphere_avg';
> statint  = ft_sourceinterpolate(cfg, stat, template_mri);
> cfg.parameter    = 'mask';
> maskint  = ft_sourceinterpolate(cfg, stat, template_mri);
>
> statint.mask = maskint.mask;
>
> atlas = ft_read_atlas('ROI_MNI_V4.nii');
>
> statint.coordsys  = 'mni';
> cfg               = [];
> cfg.method        = 'ortho';
> % cfg.method = 'slice';
> cfg.funparameter  = 'stat';
> cfg.maskparameter = 'mask';
> cfg.atlas         = atlas;
> cfg.location      = 'max';
> % cfg.funcolorlim   = [-5 5];
> cfg.funcolormap   = 'jet';
> % cfg.location = [x,y,z];
> ft_sourceplot(cfg,statint);
>
> Hope this helps, and let me know if you are running into issues.
>
> Cheers,
> Vahab
>
> On Wed, Jan 10, 2018 at 9:55 AM,  <fieldtrip-request at science.ru.nl> wrote:
> > Send fieldtrip mailing list submissions to
> >         fieldtrip at science.ru.nl
> >
> > To subscribe or unsubscribe via the World Wide Web, visit
> >         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
> >
> > You can reach the person managing the list at
> >         fieldtrip-owner at science.ru.nl
> >
> > When replying, please edit your Subject line so it is more specific
> > than "Re: Contents of fieldtrip digest..."
> >
> >
> > Today's Topics:
> >
> >    1. 2nd International LSL Workshop (27.9-28.9.2018) - Save    the
> >       Date (Martin Bleichner)
> >    2. Re: question on cluster-based statistics and source
> >       localization (Robert Oostenveld)
> >
> >
> > ----------------------------------------------------------------------
> >
> > Message: 1
> > Date: Wed, 10 Jan 2018 15:39:55 +0100
> > From: Martin Bleichner <martin.bleichner at uni-oldenburg.de>
> > To: lsl-l at mailman.ucsd.edu, eeglablist at sccn.ucsd.edu,
> >         fieldtrip at science.ru.nl
> > Subject: [FieldTrip] 2nd International LSL Workshop (27.9-28.9.2018) -
> >         Save    the Date
> > Message-ID: <27e861b5-5224-61c5-d02c-3b70140acba2 at uni-oldenburg.de>
> > Content-Type: text/plain; charset="utf-8"; Format="flowed"
> >
> > Dear colleagues,
> >
> > We are happy to announce the second international Lab Streaming Layer
> > (LSL) workshop, which will take place September 27 - 28, 2018, at the
> > Hanse Wissenschaftskolleg, in Delmenhorst, Germany. LSL is an
> > open-source project enabling the synchronized streaming of time series
> > data coming from different devices, such as EEG amplifiers, audio,
> > video, eye tracking, keyboards, etc. LSL features near real-time access
> > to data streams, time-synchronization, networking and centralized
> > collection (https://github.com/sccn/labstreaminglayer).
> >
> > Key LSL developers and expert users have confirmed attendance. The
> > workshop will provide a general introduction to LSL. We will present how
> > LSL can be used for a multitude of different experimental setups, using
> > a variety of experimental software, hardware and?operating systems. In a
> > hands-on session, participants can learn to stream data from their own
> > hardware or play with hardware provided by us and external partners. We
> > will name pitfalls and discuss how to test and ensure the best possible
> > timing accuracy when recording multimodal data. We will also provide a
> > best practice guide and present different use cases of LSL. We will also
> > use the workshop to discuss future software and hardware developments.
> >
> > Participants are invited to contribute to the workshop by presenting
> > their LSL use cases.
> >
> > More information on the workshop will follow soon. For further
> > enquiries, please contact: martin.bleichner at uol.de
> > <mailto:martin.bleichner at uol.de>
> >
> > Best,
> >
> > Martin Bleichner
> >
> > --
> > Dr. Martin Bleichner
> > Neuropsychology    Lab
> > Department of Psychology
> > University of Oldenburg
> > D-26111 Oldenburg
> > Germany
> >
> > martin.bleichner at uni-oldenburg.de
> > Tel.: +49 (0)441 - 798-2940
> > http://www.uni-oldenburg.de/psychologie/neuropsychologie/
> team/martin-bleichner/
> >
> > -------------- next part --------------
> > An HTML attachment was scrubbed...
> > URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/
> attachments/20180110/71ab956b/attachment-0001.html>
> >
> > ------------------------------
> >
> > Message: 2
> > Date: Wed, 10 Jan 2018 15:55:57 +0100
> > From: Robert Oostenveld <r.oostenveld at donders.ru.nl>
> > To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> > Cc: Vincent Wens <vwens at ulb.ac.be>
> > Subject: Re: [FieldTrip] question on cluster-based statistics and
> >         source  localization
> > Message-ID: <E1AC378D-E513-472B-A443-6E1439FE0A50 at donders.ru.nl>
> > Content-Type: text/plain; charset="utf-8"
> >
> > Hi Vincent,
> >
> > Let me reply through the email list, where other people might learn
> something and/or want to chime in.
> >
> >> On 10 Jan 2018, at 13:22, Vincent Wens <vwens at ulb.ac.be> wrote:
> >>
> >> Dear Pr. Oostenveld,
> >>
> >> I am Vincent Wens, a physicist working in the MEG unit at Erasme
> Hospital, Brussels. We've been recently trying to play with the
> cluster-based statistics that you developed and included in Fieldtrip, but
> hit a difficulty in our analysis pipeline and I wondered if you would be so
> kind to take a few minutes and provide advice on this?
> >
> > The cluster-based statistics is a method for statistical inference, i.e.
> statistical decision making based on a hypothesis and estimated probability
> distribution. The hypothesis H0 states that the data can be exchanged
> (between conditions). If it is very unlikely that the data can be exchanged
> (under H0), we decide that the data must be different somehow. The clusters
> provide evidence for the data being different, but the clusters are not the
> difference itself. The tip of an iceberg above the sea level provides
> evidence for there being an iceberg, but the tip is not the iceberg itself.
> >
> > An important FAQ is this http://www.fieldtriptoolbox.
> org/faq/how_not_to_interpret_results_from_a_cluster-based_permutation_test
> >
> > Let me give the other commens in-line in your email below
> >
> >> Globally, my question is how to go from sensor-level cluster statistics
> results to the source space.
> >>
> >> More precisely: Assume we run the cluster statistics analysis on, say,
> N-channels time-frequency plots and obtain significance for the maximum
> cluster statistic.
> >
> > So you obtain evidence that the channel level data is different. That
> logically implies that the cortical activity is different. Note that the
> other way arround would not hold per see; there can be different activity
> in the brain without it showing up as a difference in the scalp data.
> >
> >> We thus find one (and possibly more) supra-threshold cluster(s) whose
> "spatio-spectral-temporal localization" can be assessed.
> >
> > You could look at the visible tip (i.e. the cluster), you could also
> take a broader approach and look at the phenomenom under the tip (the
> iceberg).
> >
> >> See for example the attached picture depicting the plot of those
> T-values within the significant cluster associated with an ERD. The next
> step would then be to source localize this,
> >
> > You would not localize the cluster (you already have it, it is at the
> channel level). You localize the cortical activity that causes the data to
> appear different at the channel level. It?s the part of the iceberg under
> the sea level that causes the tip to appear above sea level.
> >
> >> and our initial idea was to use the time and frequency region from this
> cluster as a prior on the time and frequency used for source projection.
> However the very complex shape of the cluster does not make this step so
> obvious. There are multiple possibilities that would come to mind, most of
> them absolutely ad-hoc, so I wondered your opinion on what would be the
> most rigorous, or at least least unacceptable way to go (or even just the
> most standard way, if there's one).
> >
> > Based on the resulls (the multiplot), you should wonder whether there is
> only a single feature in the brain that is different or whether there are
> multiple. The hypothesis you started with was ?is there any difference in
> this massive multiple-comparision space?? and the (only) answer you got to
> that question was ?yes?.
> >
> > You now have the question ?what is the difference?, which pertains to
> interpreting the data. That question has no binary answer and a statistical
> test based of a p-value being small enough (which gives you a "yes/no"
> answer) does not help.
> >
> > I cannot offer specific advice on how to interpret your data, but
> recommend that you consider whether your true quest is for ?the (one and
> only) effect? or ?the effects? that causes the data in the two conditions
> to be different. Of course you can argue that the effect(s) show at certain
> frequency ranges and/or latencies and/or locations, and therefore you may
> decide to look for the interpretation of the effect(s) at or around those
> parts of the cluster.
> >
> > In general (not any more for this dataset) it is worthwile to consider
> that narrow a-priori hypotheses provide more valuable and specific
> information. This is something that we often rely on in sequential studies,
> where in the 2nd study we don?t repeat the full hypothesis of the 1st study
> (e.g. ?is there any difference?), but a more specific sub-hypothesis that
> we generated on basis of the first study (e.g. is there a difference around
> this specific time-frequency range).
> >
> >> Thanks in advance for your invaluable help, and still my best wishes
> for the New Year.
> >
> > You?re welcome. Please follow up questions on the email discussion list.
> >
> > best regards,
> > Robert
> >
> >
> > -------------- next part --------------
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> > Size: 191076 bytes
> > Desc: not available
> > URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/
> attachments/20180110/dedffb0b/attachment.png>
> >
> > ------------------------------
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >
> > End of fieldtrip Digest, Vol 86, Issue 6
> > ****************************************
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From urieduardo at gmail.com  Fri Jan 19 14:44:37 2018
From: urieduardo at gmail.com (=?UTF-8?Q?Uri_Eduardo_Ram=C3=ADrez_Pasos?=)
Date: Fri, 19 Jan 2018 14:44:37 +0100
Subject: [FieldTrip] Interpolation using Talairach atlas
Message-ID: <CADO6phi=rEuFOvJgmhoEUBJnDF+wTZeV7A8bLbA5RF4TkZxhEg@mail.gmail.com>

Dear fieldtrippers,

I'm following the Salzburg tutorial (
http://www.fieldtriptoolbox.org/tutorial/salzburg) but using only templates
(i.e., no subject MRIs) and the Talairach (with 'tal' coordinates) atlas
from AFNI.

However, when I run

    atlas =
ft_read_atlas('~/Documents/MATLAB/fieldtrip-20170618/template/atlas/afni/TTatlas+tlrc.HEAD');

    cfg=[];
    cfg.method='lcmv';
    cfg.grid=template_grid;
    cfg.grid.filter=sourceavg.avg.filter;
    cfg.vol=vol;
    sourcepreS1=ft_sourceanalysis(cfg, avgpre);
    sourcepstS1=ft_sourceanalysis(cfg, avgpst);

    cfg = [];
    cfg.parameter = 'avg.pow';
    cfg.operation = '((x1-x2)./x2)*100';
    S1bl=ft_math(cfg,sourcepstS1,sourcepreS1);

    templatefile =
'~/Documents/MATLAB/fieldtrip-20170618/external/spm8/templates/T1.nii';
    template_mri = ft_read_mri(templatefile);
    cfg              = [];
    cfg.voxelcoord   = 'no';
    cfg.parameter    = 'pow';
    cfg.interpmethod = 'nearest';
    source_int  = ft_sourceinterpolate(cfg, S1bl, template_mri);
    %%
    cfg=[];
    parcel = ft_sourceparcellate(cfg, source_int, atlas);

I get the following error

Index exceeds matrix dimensions.

Error in ft_sourceparcellate (line 172)
  fprintf('%d of the labeled positions are inside the brain\n',
  sum(source.inside(seg(:)~=0)));

This is probably due to the spm8 template having too few 'pos' values. Do
you know of other mri template that would work with the AFNI atlas?

Best regards,
Eduardo Ramirez, PhD student
University of Würzburg
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From tonyvazhangottu at gmail.com  Mon Jan 22 05:29:42 2018
From: tonyvazhangottu at gmail.com (TONY CHACKO)
Date: Mon, 22 Jan 2018 09:59:42 +0530
Subject: [FieldTrip] (no subject)
Message-ID: <CAC0bWAbyc0k2M3iV+7GJEheJ3JrRNbrc0Yn88+QLG-Gh=rJ8Zg@mail.gmail.com>

 Dear all,
I am a new comer in fieldtrip software for my eeg project , I'm having
basic doubts.
I want to show all the events on my continuous data without segmenting the
data
and also I need to show my data in 50s-100s time.also i need to see my
results in matlab plots

Please help
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From Mariam.Kostandyan at UGent.be  Mon Jan 22 12:11:52 2018
From: Mariam.Kostandyan at UGent.be (Mariam Kostandyan)
Date: Mon, 22 Jan 2018 11:11:52 +0000
Subject: [FieldTrip] error Conversion to struct in ft_prepare_neighbours
Message-ID: <1516619979417.866@UGent.be>

Dear all,

I am quite new to the FieldTrip. I want to use it to check for the inter-electrode distances using the ft_prepare_neighbours function. My script looks like this:

cfg.method        = 'distance';
cfg.neighbourdist = 4;
cfg.channel       = {'FP1', 'FP2', 'F7', 'F3', 'FZ', 'F4', 'F8', 'FT9', 'FC5', 'FT10', 'T7', 'C3', 'CZ', 'C4', 'T8', 'TP9', 'CP5', 'CP6', 'TP10', 'P9', 'P7', 'P3', 'PZ', 'P4', 'P8', 'P10', 'O1', 'OZ', 'O2'};
cfg.feedback      = 'yes';
cfg.elec  = {'FP1', 'FP2', 'F7', 'F3', 'FZ', 'F4', 'F8', 'FT9', 'FC5', 'FT10', 'T7', 'C3', 'CZ', 'C4', 'T8', 'TP9', 'CP5', 'CP6', 'TP10', 'P9', 'P7', 'P3', 'PZ', 'P4', 'P8', 'P10', 'O1', 'OZ', 'O2'};
cfg.elecfile = 'sub03_Mariam_cues.set';
neighbours = ft_prepare_neighbours(cfg, 'sub03_Mariam_cues.set');


When I run it I get error messages:


Error using struct
Conversion to struct from cell is not possible.

Error in ft_checkconfig (line 248)
  cfg.elec = ft_datatype_sens(struct(cfg.elec));

Error in ft_preamble_trackconfig (line 37)
cfg = ft_checkconfig(cfg, 'trackconfig', 'on');

Error in ft_preamble (line 85)
evalin('caller', full_cmd);

Error in ft_neighbourplot (line 65)
ft_preamble trackconfig


How can I fix it? I would appreciate any help.


Best,

Mariam


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

Mariam Kostandyan
PhD student
University of Gent
Department of Experimental Psychology
Henri Dunantlaan 2, 9000 Gent, Belgium
----------------------

Room 140.021
Tel.: +32 9 264 6398
E-mail: Mariam.Kostandyan at UGent.be<mailto:Mariam.Kostandyan at UGent.be>
E-mail: kostandyan.m at gmail.com<mailto:kostandyan.m at gmail.com>
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From jan.schoffelen at donders.ru.nl  Mon Jan 22 13:51:35 2018
From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs))
Date: Mon, 22 Jan 2018 12:51:35 +0000
Subject: [FieldTrip] error Conversion to struct in ft_prepare_neighbours
In-Reply-To: <1516619979417.866@UGent.be>
References: <1516619979417.866@UGent.be>
Message-ID: <E3412ADA-DF6E-45AE-AF51-F28C0621D758@donders.ru.nl>

Dear Mariam,

Perhaps it will work if you remove the ‘elec’-field from the cfg.

Best wishes,
Jan-Mathijs

On 22 Jan 2018, at 12:11, Mariam Kostandyan <Mariam.Kostandyan at UGent.be<mailto:Mariam.Kostandyan at UGent.be>> wrote:

Dear all,

I am quite new to the FieldTrip. I want to use it to check for the inter-electrode distances using the ft_prepare_neighbours function. My script looks like this:

cfg.method        = 'distance';
cfg.neighbourdist = 4;
cfg.channel       = {'FP1', 'FP2', 'F7', 'F3', 'FZ', 'F4', 'F8', 'FT9', 'FC5', 'FT10', 'T7', 'C3', 'CZ', 'C4', 'T8', 'TP9', 'CP5', 'CP6', 'TP10', 'P9', 'P7', 'P3', 'PZ', 'P4', 'P8', 'P10', 'O1', 'OZ', 'O2'};
cfg.feedback      = 'yes';
cfg.elec  = {'FP1', 'FP2', 'F7', 'F3', 'FZ', 'F4', 'F8', 'FT9', 'FC5', 'FT10', 'T7', 'C3', 'CZ', 'C4', 'T8', 'TP9', 'CP5', 'CP6', 'TP10', 'P9', 'P7', 'P3', 'PZ', 'P4', 'P8', 'P10', 'O1', 'OZ', 'O2'};
cfg.elecfile = 'sub03_Mariam_cues.set';
neighbours = ft_prepare_neighbours(cfg, 'sub03_Mariam_cues.set');

When I run it I get error messages:

Error using struct
Conversion to struct from cell is not possible.

Error in ft_checkconfig (line 248)
  cfg.elec = ft_datatype_sens(struct(cfg.elec));

Error in ft_preamble_trackconfig (line 37)
cfg = ft_checkconfig(cfg, 'trackconfig', 'on');

Error in ft_preamble (line 85)
evalin('caller', full_cmd);

Error in ft_neighbourplot (line 65)
ft_preamble trackconfig

How can I fix it? I would appreciate any help.

Best,
Mariam

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

Mariam Kostandyan
PhD student
University of Gent
Department of Experimental Psychology
Henri Dunantlaan 2, 9000 Gent, Belgium
----------------------

Room 140.021
Tel.: +32 9 264 6398
E-mail: Mariam.Kostandyan at UGent.be<mailto:Mariam.Kostandyan at UGent.be>
E-mail: kostandyan.m at gmail.com<mailto:kostandyan.m at gmail.com>
_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From Heidi.SolbergOkland at mrc-cbu.cam.ac.uk  Mon Jan 22 14:15:58 2018
From: Heidi.SolbergOkland at mrc-cbu.cam.ac.uk (Heidi Solberg Okland)
Date: Mon, 22 Jan 2018 13:15:58 +0000
Subject: [FieldTrip] Reject trials based on standard deviation
Message-ID: <9327C18D1181184A833D66FF65A9D9E10139717943@wsr-ex-101.mrc-cbsu.local>

Dear Fieldtrippers,

I'm currently working on an MEG dataset and have so far done automatic rejection of bad channels using Maxfilter and then done ICA-based artefact reduction (eyeblinks and heartbeat) in MNE Python. I now have my data in Fieldtrip trial structures. What is left is to remove trials that are outliers/noisy because the subject moved/coughed/etc. I have tried to use ft_visinspect with variance as metric, but the issue I have is that the variance is displayed in actual units (e.g. 1e10^23) rather than in terms of standard deviations. This is problematic, as my trial rejection will be based on my subjective decisions that some trials look like outliers and not others. What I would like instead is to just do something like "discard trials where the amplitude is more than X standard deviations above or below the mean", which is reproducible. Is this way of rejecting trials implemented in FT? I have seen the tutorial on automatic artefact rejection, but it looks more like something that would be useful for removing e.g. eyeblinks.

Best wishes,
Heidi


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

Heidi Solberg Økland
PhD candidate, Language group

Tel: 01223 273721
MRC Cognition & Brain Sciences Unit
University of Cambridge
15 Chaucer Road
Cambridge
CB2 7EF

Web: http://www.mrc-cbu.cam.ac.uk<http://www.mrc-cbu.cam.ac.uk/>

Social media:
[facebook-flat-logo-01]<https://en-gb.facebook.com/MRCCBU/>   [twiiter-flat-logo-02] <https://mobile.twitter.com/mrccbu?lang=en>

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From Mariam.Kostandyan at UGent.be  Mon Jan 22 14:22:16 2018
From: Mariam.Kostandyan at UGent.be (Mariam Kostandyan)
Date: Mon, 22 Jan 2018 13:22:16 +0000
Subject: [FieldTrip] error Conversion to struct in ft_prepare_neighbours
In-Reply-To: <E3412ADA-DF6E-45AE-AF51-F28C0621D758@donders.ru.nl>
References: <1516619979417.866@UGent.be>,
 <E3412ADA-DF6E-45AE-AF51-F28C0621D758@donders.ru.nl>
Message-ID: <1516627803115.4133@UGent.be>

Dear Jan-Mathijs,


I guess it partially worked since it started reading the .set file but still outputed an error:


>>  cfg.method        = 'distance';
cfg.neighbourdist = 4;
cfg.channel       = {'FP1', 'FP2', 'F7', 'F3', 'FZ', 'F4', 'F8', 'FT9', 'FC5', 'FT10', 'T7', 'C3', 'CZ', 'C4', 'T8', 'TP9', 'CP5', 'CP6', 'TP10', 'P9', 'P7', 'P3', 'PZ', 'P4', 'P8', 'P10', 'O1', 'OZ', 'O2'};
cfg.feedback      = 'yes';
cfg.elecfile = 'sub03_Mariam_cues.set';
neighbours = ft_prepare_neighbours(cfg, 'sub03_Mariam_cues.set');
reading electrodes from file 'sub03_Mariam_cues.set'
Attempt to reference field of non-structure array.

Error in ft_prepare_neighbours (line 176)
    [dataidx, sensidx] = match_str(data.label, label);


Is it the .set file that has electrodes as a non-structure array?


Best,

Mariam


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

Mariam Kostandyan
PhD student
University of Gent
Department of Experimental Psychology
Henri Dunantlaan 2, 9000 Gent, Belgium
----------------------

Room 140.021
Tel.: +32 9 264 6398
E-mail: Mariam.Kostandyan at UGent.be<mailto:Mariam.Kostandyan at UGent.be>
E-mail: kostandyan.m at gmail.com<mailto:kostandyan.m at gmail.com>
________________________________
От: fieldtrip-bounces at science.ru.nl <fieldtrip-bounces at science.ru.nl> от имени Schoffelen, J.M. (Jan Mathijs) <jan.schoffelen at donders.ru.nl>
Отправлено: 22 января 2018 г. 13:51
Кому: FieldTrip discussion list
Тема: Re: [FieldTrip] error Conversion to struct in ft_prepare_neighbours

Dear Mariam,

Perhaps it will work if you remove the 'elec'-field from the cfg.

Best wishes,
Jan-Mathijs

On 22 Jan 2018, at 12:11, Mariam Kostandyan <Mariam.Kostandyan at UGent.be<mailto:Mariam.Kostandyan at UGent.be>> wrote:

Dear all,

I am quite new to the FieldTrip. I want to use it to check for the inter-electrode distances using the ft_prepare_neighbours function. My script looks like this:

cfg.method        = 'distance';
cfg.neighbourdist = 4;
cfg.channel       = {'FP1', 'FP2', 'F7', 'F3', 'FZ', 'F4', 'F8', 'FT9', 'FC5', 'FT10', 'T7', 'C3', 'CZ', 'C4', 'T8', 'TP9', 'CP5', 'CP6', 'TP10', 'P9', 'P7', 'P3', 'PZ', 'P4', 'P8', 'P10', 'O1', 'OZ', 'O2'};
cfg.feedback      = 'yes';
cfg.elec  = {'FP1', 'FP2', 'F7', 'F3', 'FZ', 'F4', 'F8', 'FT9', 'FC5', 'FT10', 'T7', 'C3', 'CZ', 'C4', 'T8', 'TP9', 'CP5', 'CP6', 'TP10', 'P9', 'P7', 'P3', 'PZ', 'P4', 'P8', 'P10', 'O1', 'OZ', 'O2'};
cfg.elecfile = 'sub03_Mariam_cues.set';
neighbours = ft_prepare_neighbours(cfg, 'sub03_Mariam_cues.set');

When I run it I get error messages:

Error using struct
Conversion to struct from cell is not possible.

Error in ft_checkconfig (line 248)
  cfg.elec = ft_datatype_sens(struct(cfg.elec));

Error in ft_preamble_trackconfig (line 37)
cfg = ft_checkconfig(cfg, 'trackconfig', 'on');

Error in ft_preamble (line 85)
evalin('caller', full_cmd);

Error in ft_neighbourplot (line 65)
ft_preamble trackconfig

How can I fix it? I would appreciate any help.

Best,
Mariam

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

Mariam Kostandyan
PhD student
University of Gent
Department of Experimental Psychology
Henri Dunantlaan 2, 9000 Gent, Belgium
----------------------

Room 140.021
Tel.: +32 9 264 6398
E-mail: Mariam.Kostandyan at UGent.be<mailto:Mariam.Kostandyan at UGent.be>
E-mail: kostandyan.m at gmail.com<mailto:kostandyan.m at gmail.com>
_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From stephen.whitmarsh at gmail.com  Mon Jan 22 17:06:47 2018
From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh)
Date: Mon, 22 Jan 2018 17:06:47 +0100
Subject: [FieldTrip] Reject trials based on standard deviation
In-Reply-To: <9327C18D1181184A833D66FF65A9D9E10139717943@wsr-ex-101.mrc-cbsu.local>
References: <9327C18D1181184A833D66FF65A9D9E10139717943@wsr-ex-101.mrc-cbsu.local>
Message-ID: <CAFrxm=ymv4xFdT+X5tLwz3T2yPwaAFEVaQxyi+_ZXxXpneDNnA@mail.gmail.com>

Hi Heidi,

I guess you could just e.g. zscore your data before the (semi)automatic
artefact *detection*, and apply those artefact definitions on your original
data in the artefact *rejection*.

Cheers,
Stephen

On 22 January 2018 at 14:15, Heidi Solberg Okland <
Heidi.SolbergOkland at mrc-cbu.cam.ac.uk> wrote:

> Dear Fieldtrippers,
>
>
>
> I’m currently working on an MEG dataset and have so far done automatic
> rejection of bad channels using Maxfilter and then done ICA-based artefact
> reduction (eyeblinks and heartbeat) in MNE Python. I now have my data in
> Fieldtrip trial structures. What is left is to remove trials that are
> outliers/noisy because the subject moved/coughed/etc. I have tried to use
> ft_visinspect with variance as metric, but the issue I have is that the
> variance is displayed in actual units (e.g. 1e10^23) rather than in terms
> of standard deviations. This is problematic, as my trial rejection will be
> based on my subjective decisions that some trials look like outliers and
> not others. What I would like instead is to just do something like “discard
> trials where the amplitude is more than X standard deviations above or
> below the mean”, which is reproducible. Is this way of rejecting trials
> implemented in FT? I have seen the tutorial on automatic artefact
> rejection, but it looks more like something that would be useful for
> removing e.g. eyeblinks.
>
>
>
> Best wishes,
>
> Heidi
>
>
>
>
>
> ----------------------------------------------------------
>
>
>
> Heidi Solberg Økland
>
> PhD candidate, Language group
>
>
>
> Tel: 01223 273721
>
> MRC Cognition & Brain Sciences Unit
>
> University of Cambridge
> 15 Chaucer Road
> Cambridge
>
> CB2 7EF
>
>
>
> Web: http://www.mrc-cbu.cam.ac.uk
>
>
>
> Social media:
>
> [image: facebook-flat-logo-01] <https://en-gb.facebook.com/MRCCBU/>   [image:
> twiiter-flat-logo-02] <https://mobile.twitter.com/mrccbu?lang=en>
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From rosemary.southwell.14 at ucl.ac.uk  Mon Jan 22 21:50:38 2018
From: rosemary.southwell.14 at ucl.ac.uk (Rosy Southwell)
Date: Mon, 22 Jan 2018 20:50:38 +0000
Subject: [FieldTrip] Source activation vs baseline on MNE output
Message-ID: <CADxBig50beESaNN6of6Zx7cLfbR8h9-9wDcgenGVHhWPywsK5A@mail.gmail.com>

Dear Fieldtrip Community,

I am working on EEG source analysis for auditory evoked responses to long
(3-second) stimuli. My data are evoked responses baseline corrected in the
interval [-1 0], and am interested in source activity in the window [0.5
1.5] relative to stimulus onset.

I have used MNE to estimate source activity over a latency of [-1 1.5]; see
code [1] below. Although I have two conditions of interest which I will
later contrast using ft_statfun_depsamplesT, I am first interested in
seeing which areas are activated by each condition. In order to extract
sound-evoked activity from ongoing activity, I would like to visualise the
source activity for each condition as an activation relative to baseline,
expressed as a T-statistic. I have ensured that my baseline window and
activation window are of equal duration and non-overlapping.

I have attempted to use ft_statfun_actvsblT for computing this statistic
(see code [2] below), but receive the error "Inappropriate dimord for the
statistics function FT_STATFUN_ACTVSBLT." From reading the function, I
understand that this method requires time-frequency data with
dimord 'chan_freq_time'. However my data is evoked, time-domain only.

My questions are
a) Is it even appropriate to express such "time-dimension-only" source
results as an activation relative to baseline?

b) If so, how would I best compute this in Fieldtrip?

c) if not, do you have a recommendation of how to quantify the degree of
activation for a single condition?

All the best,

Rosy Southwell
PhD Candidate
Chait Lab
Ear Institute, University College London.

%% CODE
% [1.] source analysis
  cfg = [];
            cfg.method = 'mne';
            cfg.latency = [-1 1.5];
            cfg.elec = elec;
            cfg.grid = sourcemodel_cortex;
            cfg.headmodel = headmodel;
            cfg.mne.prewhiten = 'yes';
            cfg.mne.lambda    = 3;
            cfg.mne.scalesourcecov = 'yes';
            [source] = ft_sourceanalysis(cfg, data);

% [2.] T-statistic of activation vs baseline

cfg=[];
cfg.method      = 'analytic';
cfg.statistic   = 'ft_statfun_actvsblT';
cfg.parameter   = 'pow';
cfg.correctm    = 'no';
cfg.alpha       = 0.025;
cfg.tail        = 0;
nsubj=20;
cfg.design(1,:) = [ones(1,nsubj) 2*ones(1,nsubj)];
cfg.design(2,:) = [1:nsubj 1:nsubj ];
cfg.ivar        = 1; % row of design matrix that contains independent
variable (the conditions)
cfg.uvar        = 2; % row of design matrix that contains unit variable (in
this case: subjects)

stat_RvR = ft_sourcestatistics(cfg,source_ac_all{:},source_bl_all{:});
% where source_ac_all, source_bl_all are 1*20 cell array of structs for
each subject
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From luca.turella at unitn.it  Tue Jan 23 18:27:59 2018
From: luca.turella at unitn.it (Luca Turella)
Date: Tue, 23 Jan 2018 18:27:59 +0100
Subject: [FieldTrip] Postdoctoral position - MEG and Visual Imagery @ CIMeC
 University of Trento, Italy
Message-ID: <CALvsWdV99L2NJ=FrVacWkWqrLNV+J2Hmmmn3Mynwb23QyNXNgw@mail.gmail.com>

A postdoctoral position will be available soon at the Center for Mind/Brain
Sciences (CIMeC, http://www.cimec.unitn.it/en) at the University of Trento
(Italy). The topic of investigation will cover the neural dynamics
underlying visual imagery adopting MEG. The position is supported by the
ERC Advanced Grant “Perceptual Awareness in the Reorganizing Brain” (PI
Carlo Marzi).


Candidates should have a Ph.D. degree in a field related to Cognitive
Neuroscience or related areas. The ideal candidate should have previous
experience in EEG/MEG data acquisition and analysis and good programming
skills in Matlab and Fieldtrip. Knowledge of the Italian language is not
required.


The salary will be proportional to the level of experience and the starting
date of the appointment is negotiable, but within the next 6 months.
Applications will be considered until the position is filled. The contract
will have a duration of 1 year, and can be extended by another year.
Applications should be sent to angelika.lingnau at rhul.ac.uk, including a CV,
statement of research interests, and contact details of two referees.
Potential candidates are also encouraged to send informal inquiries to
angelika.lingnau at rhul.ac.uk.


CIMeC offers an international and vibrant research setting with access to
state-of-the-art neuroimaging methodologies, including a research-only MR
scanner, MEG, EEG and TMS, as well as behavioural, eye tracking and motion
tracking laboratories. English is the official language of the CIMeC, where
a large proportion of the faculty, post-docs and students come from a wide
range of countries outside of Italy.


The University of Trento consistently ranks as a top Italian university in
both national Research Assessment Evaluations (RAE) and University Surveys.
In the latest RAE, the University of Trento as a whole ranks 2nd among
medium-sized universities.


-- 
Luca Turella, PhD
Assistant Professor
CIMeC - Center for Mind/Brain Sciences
University of Trento
Mattarello (TN), Via Delle Regole 101
Tel.+39 0461-28 3098
http://www.unitn.it/cimec



Legal Disclaimer
This electronic message contains information that is confidential. The
information is intended for the use of the addressee only. If you are not
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note that any disclosure, copy, distribution or use of the contents of this
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Questo messaggio Email contiene informazioni confidenziali riservate ai
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From jorn at artinis.com  Fri Jan 26 16:07:02 2018
From: jorn at artinis.com (=?iso-8859-1?Q?J=F6rn_M._Horschig?=)
Date: Fri, 26 Jan 2018 16:07:02 +0100
Subject: [FieldTrip] ARTscientific: NIRS symposium in Thailand
Message-ID: <007101d396b7$5256acf0$f70406d0$@artinis.com>

Dear fieldtrippers,

 

On June 27-30, we from Artinis Medical Systems are organizing a
scientific symposium revolving around near-infrared spectroscopy (NIRS)
for neuro- and sports research. We would like to invite you to register
for the ARTscientific symposium in the beautiful and luxurious Wyndham
Grand Phuket Kalim Bay in Thailand. In this 2.5-day symposium, we will
create an open platform for both experienced and novice researchers to
share experiences, discuss NIRS and enjoy several hands-on workshops. We
are arranging an interesting line-up of keynote speakers, who will
provide valuable insight into NIRS and brain research. 

 

Next to providing a NIRS playground we will organize poster and
presentation sessions, so you will get the chance to present and discuss
your research. To sum it all up social wining and dining will be
organized in one of the most extraordinary places in Thailand.

The registration: Get an early bird ticket

The amount of rooms in the hotel are limited, so get yours quickly and
benefit until February 28th from the early bird discount! Additional
information on e.g. the program workshops or the location can be found
on our website: http://www.artinis.com/artscientific-2018/.  

If you have any questions, suggestions or requests for the symposium,
please do not hesitate to contact us at symposium at artinis.com.

 

With best regards,

The Artinis team

 

--
Jörn M. Horschig, PhD
Software Engineer & Project Leader NeuroGuard XS

  

A  Einsteinweg 17
    6662PW Elst 
    The Netherlands
T  +31 481 350 980
I    <http://www.artinis.com/> www.artinis.com

The information in this e-mail is confidential and intended solely for
the person to whom it is addressed. If this message is not addressed to
you, please be aware that you have no authorization to read this e-mail,
to copy it, to furnish it to any person other than the addressee, or to
use or misuse its content in any way whatsoever. Should you have
received this e-mail by mistake, please bring this to the attention of
the sender, after which you are kindly requested to destroy the original
message.

 

 <http://eepurl.com/bTlr_L> Sign up for our NIRS newsletter

 

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From i.charest at bham.ac.uk  Fri Jan 26 16:25:41 2018
From: i.charest at bham.ac.uk (Ian Charest (School of Psychology))
Date: Fri, 26 Jan 2018 15:25:41 +0000
Subject: [FieldTrip] Postdoc position on the neurocognitive mechanisms of
 conscious access
Message-ID: <97F95B166F2157409BE1EC68292F25AC436368A6@EX13.adf.bham.ac.uk>

Dear FieldTrip discussions list,

see below for details of a 3 year ERC funded postdoctoral position in Birmingham, UK.


https://goo.gl/6PuHwj


Best wishes,

Ian Charest
Lecturer, School of Psychology,
University of Birmingham, UK
iancharest.com

_________________________

Advert:
The School of Psychology at the University of Birmingham is looking for a bright and motivated Post-doctoral scientist to join the Charest Laboratory (iancharest.com). The Postdoc position to be filled is part of a project recently funded by a European Research Council Starting Grant entitled: "Spatio-Temporal Attention and Representation Tracking: the precise neural architecture of conscious object perception" (START).

The Project:
START is an ambitious programme of work that will make use of cutting-edge multivariate pattern analyses (MVPA) techniques to reveal the brain mechanisms that are critical for consciously perceiving visual objects in tasks that manipulate conscious access to visual information. The ability to consciously recognise faces, objects, or sounds is crucial for adaptive behaviour and survival. Yet, how our conscious experience of the world emerges in our brain remains unknown. The overall aim of the START programme is to fill an important gap in our understanding of consciousness by elucidating the neural underpinnings of conscious access. How does the brain select relevant information among distractors, and keep this information in mind? Why does our ability to consciously recognise salient objects sometimes fail under pressure and exhibit variability across days and individuals? START will try to address these important questions by precisely tracking where in the brain and when in time the representations critical for conscious access are established, by using novel approaches of Representational Similarity Analyses which combines the strengths of EEG, fMRI, and Deep Convolutional Neuronal Networks. This project will provide new insights on the precise spatio-temporal dynamics of conscious access, the mechanisms governing it, and the idiosyncratic subtleties behind the meanderings of consciousness.

The candidate:
The successful candidate will have (or be in the process of obtaining) a PhD in cognitive neuroscience or a related field. Previous experience with psychophysical tasks that manipulate conscious access in vision is desirable. Given the nature of the project, experience with fMRI, EEG/MEG and data analysis is required. Experience in using matlab or python (and Psychtoolbox or PsychoPy) is also a requirement. The successful applicant will have experience with multivariate pattern analyses (Representational Similarity Analysis, Fisher linear discriminants, etc) of neuroimaging data. This post will require designing experiments, collecting and analysing data associated with the project, preparing manuscripts for publication, presenting results at national and international conferences and the possible supervision of research assistants and students.

The School:
The School of Psychology at the University of Birmingham (http://www.birmingham.ac.uk/schools/psychology/index.aspx<https://www.findaphd.com/common/clickCount.aspx?theid=92145&type=184&DID=148&url=http%3a%2f%2fwww.birmingham.ac.uk%2fschools%2fpsychology%2findex.aspx>) is one of the largest and most successful in the UK, currently ranked in the top 5 Schools in the country (REF 2014). The School is soon to move to new accommodation in the form of a fully refurbished, purpose-designed space and a new-build Centre for Human Brain Health that will house our new MRI, MEG, EEG, NIRS, sleep lab, and the recently appointed Chair in Translational Neuroscience. The University of Birmingham is an equal opportunities employer. The School of Psychology has a Bronze Athena SWAN award and strives to maintain a flexible and supportive environment that enables its staff to flourish.

For informal enquiries about the project please contact Dr. Ian Charest (i.charest at bham.ac.uk). Please follow the following link for more details and to apply: https://goo.gl/6PuHwj


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From dr.nivethida at gmail.com  Wed Jan 31 10:47:36 2018
From: dr.nivethida at gmail.com (nivethida t)
Date: Wed, 31 Jan 2018 15:17:36 +0530
Subject: [FieldTrip] Opening for PhD position at Department of Neurology,
	NIMHANS, India
Message-ID: <CAMBnzx4eSs5XCenx8Njh3f69Ynv9-w3Zmj5nzx1tcPzikveqQg@mail.gmail.com>

Applications are invited for a prospective PhD candidate at the Department
of Neurology, National Institute of Mental Health and Neuro Sciences
(NIMHANS), Bengaluru, India.


The candidate will work on a Wellcome Trust/DBT India Alliance funded
project involving Transcranial magnetic stimulation (TMS), EEG and MEG
studies in patients with Parkinson’s disease.


Candidates with strong technical background (Master’s degree in basic
sciences/ engineering/ neuroscience) and prior knowledge of MATLAB are
eligible to apply. Experience with EEG/MEG signal processing is a plus.


Admission to the PhD program at the institute is subjected to the candidate
qualifying the NIMHANS online entrance test and interview. The entrance
test may be waived if the applicant has cleared any of the
DBT/UGC/CSIR/ICMR qualifying exams.


For further details on the PhD admission procedure, please refer to the
prospectus on the institute’s website (
http://www.nimhans.ac.in/sites/default/files/NIMHANS_Prospectus%202018-19%20Final%20%281%29.pdf)
.


Application deadline for July admission: 4th February, 2018



-- 
Dr. Nivethida Thirugnanasambandam, MBBS, MTech, PhD
Extramural Research Faculty,
Wellcome Trust/DBT India Alliance Clinical Research Fellow (Intermediate),
Department of Neurology,
National Institute of Mental Health and Neuro Sciences (NIMHANS),
Hosur Road, P B 2900, Bengaluru 560 029,
Karnataka, India
Ph: +91-80-26995143
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From r.oostenveld at donders.ru.nl  Wed Jan 31 12:44:49 2018
From: r.oostenveld at donders.ru.nl (Robert Oostenveld)
Date: Wed, 31 Jan 2018 12:44:49 +0100
Subject: [FieldTrip] MEG/EEG FieldTrip toolkit course in Nijmegen:
	pre-registration now open
Message-ID: <24B65D6F-F33A-4981-BEE2-CB06C3DC8327@donders.ru.nl>

Dear all,

On 9-13 April 2018 we will host the yearly “Advanced MEG/EEG data analysis toolkit" at the Donders Institute in Nijmegen. The course is aimed at researchers that have already performed  MEG/EEG data acquisition and have a good understanding of their own experimental design. Furthermore, we expect that you know the basics of MATLAB and that you already have some experience with MEG/EEG preprocessing and analysis. 

This intense 5-day toolkit course will teach you advanced MEG and EEG data analysis methods. We will cover preprocessing, frequency analysis, source reconstruction, connectivity and various statistical methods. The toolkit will consist of a number of lectures, followed by hands-on sessions in which you will be tutored through the complete analysis of a MEG data set using the FieldTrip toolbox. There will be plenty of opportunity to interact and ask questions about your research and data. On the final day you will have the opportunity to work on your own dataset under supervision of skilled tutors.

We can only host a limited number of participants. From past experience we expect the course to be oversubscribed, hence we will start with pre-registration. The final selection of the participants will be based on the motivation, background experience and research interests that are provided in the registration form. The deadline for pre-registration is March 1, 2018.

More information, including the link to register and last years program can be found at http://www.ru.nl/donders/agenda/donders-tool-kits/vm-tool-kits/donders-meg-eeg-tool-kit/ <http://www.ru.nl/donders/agenda/donders-tool-kits/vm-tool-kits/donders-meg-eeg-tool-kit/>. Please note that this year we added an extra day to have more hands-on time and to better deal with EEG specific topics. 

best regards,
Robert

-----------------------------------------------------------
Robert Oostenveld, PhD

Senior Researcher & MEG Physicist
Donders Institute for Brain, Cognition and Behaviour
Radboud University, Nijmegen, The Netherlands

Visiting Professor
NatMEG - the Swedish National MEG facility
Karolinska Institute, Stockholm, Sweden

tel.: +31 (0)24 3619695
e-mail: r.oostenveld at donders.ru.nl
web: http://www.ru.nl/donders
skype: r.oostenveld
-----------------------------------------------------------

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From davide.tabarelli at unitn.it  Wed Jan 31 17:56:45 2018
From: davide.tabarelli at unitn.it (Davide Tabarelli)
Date: Wed, 31 Jan 2018 17:56:45 +0100
Subject: [FieldTrip] Subject level non parametric statistics for coherence
	with external stimulus
Message-ID: <FD9AA208-D908-4CA2-A3AD-CD9AE61E5EC7@unitn.it>

Dear Fieldtrip users,

I’m trying to calculate a statistical map for coherence differences between two conditions at a source level for a single subject, but I have some problems with channel combinations.

I have calculated common LCMV filters for my subject and computed source time series, that I have stored in a ft_timelock structure.
I have also successfully calculated coherence between the stimulus function and all dipoles for both conditions A and B using ft_freqanalysis and ft_connectivityanalysis.
Now I would like to compute a non parametric statistical map for the coherence difference between A and B using the approach of Maris & Schoffelen & Fries 2007.

I’m trying to use the “ft_statfun_indepsamplesZcoh” statistics as follow:

cfg=[]; 
cfg.parameter = 'fourierspctrm’; 
cfg.frequency = 5.5;
cfg.statistic = 'ft_statfun_indepsamplesZcoh’; 
cfg.method = 'montecarlo’; 
cfg.numrandomization = 1000;
cfg.design = design;
stat = ft_freqstatistics(icfg, fourier_conditionA, fourier_conditionA);

I realized this will compute the statistics for all the possible combination of channels, thus between stimulus and sources and between all pairs of sources … that is computationally non effordable (at least for me).

There is a way to tell ft_freqstatistics to use only some combination when computing the significance of coherence differences?

Or am I doing something wrong?

Thank you all !

D.

—
Davide Tabarelli, Ph.D.
Center for Mind Brain Sciences (CIMeC)
University of Trento,
Via delle Regole, 101
38123 Mattarello (TN)
Tel: +39 (0)461 283644
Italy






From josyjoyvarghese at gmail.com  Wed Jan  3 07:40:19 2018
From: josyjoyvarghese at gmail.com (josy joy)
Date: Wed, 3 Jan 2018 12:10:19 +0530
Subject: [FieldTrip] difficulty in importing data from eeg to fieldtrip
Message-ID: <CAOW5AWC2EiZa7pL6cLJGbXEsPqZWsVy9wUnGveZ6M9qnj9FQtA@mail.gmail.com>

Dear sir/mam

Im a fresher to the firldtrip but i do have matlab aand eeglab basic
experience.

i am working on eeg analysis using fieldtrip,now im facing the difficulty
in importing the eeg data from eeglab(.set format).

please solve my problem
thanks
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From a.stolk8 at gmail.com  Wed Jan  3 07:51:48 2018
From: a.stolk8 at gmail.com (Arjen Stolk)
Date: Tue, 2 Jan 2018 22:51:48 -0800
Subject: [FieldTrip] difficulty in importing data from eeg to fieldtrip
In-Reply-To: <CAOW5AWC2EiZa7pL6cLJGbXEsPqZWsVy9wUnGveZ6M9qnj9FQtA@mail.gmail.com>
References: <CAOW5AWC2EiZa7pL6cLJGbXEsPqZWsVy9wUnGveZ6M9qnj9FQtA@mail.gmail.com>
Message-ID: <CAAiwptQ_x7fNVa77cLdp=8J-TuVma713dO-THUJT4vSAn2DL0A@mail.gmail.com>

Hi Josy,

The following wiki page might provide a fruitful starting point for
converting data between fieldtrip and eeglab:
http://www.fieldtriptoolbox.org/getting_started/eeglab

Best,
Arjen

On Tue, Jan 2, 2018 at 10:40 PM, josy joy <josyjoyvarghese at gmail.com> wrote:

> Dear sir/mam
>
> Im a fresher to the firldtrip but i do have matlab aand eeglab basic
> experience.
>
> i am working on eeg analysis using fieldtrip,now im facing the difficulty
> in importing the eeg data from eeglab(.set format).
>
> please solve my problem
> thanks
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From justintracyfleming at gmail.com  Fri Jan  5 22:43:37 2018
From: justintracyfleming at gmail.com (Justin Fleming)
Date: Fri, 5 Jan 2018 16:43:37 -0500
Subject: [FieldTrip] Time-frequency analysis with varying length trials
Message-ID: <CACo=i5XqqiPJsqw4aD3kXRfi0wfhs6GGKHui=nZTL92iCeXEsA@mail.gmail.com>

Hello all,

I'm trying to do some exploratory spectral analysis on EEG data from a
reaction time experiment, in which the trial ends as soon as the subject
detects a target. The trails are up to 6 sec in length, but they average
closer to 2 sec.

My goal is to make time-frequency plots, using the multi-taper method,
aligned to the response (end of trial), rather than the beginning. I tried
the following approach first:
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From justintracyfleming at gmail.com  Fri Jan  5 22:52:00 2018
From: justintracyfleming at gmail.com (Justin Fleming)
Date: Fri, 5 Jan 2018 16:52:00 -0500
Subject: [FieldTrip] Time-frequency analysis with varying length trials
Message-ID: <CACo=i5WpVvJhUtVOKj8vc+-KVUPYLJG0BAnBaXUr1YVk9H38Cw@mail.gmail.com>

Hello all,

I'm trying to do some exploratory spectral analysis on EEG data from a
reaction time experiment, in which the trial ends as soon as the subject
detects a target. The trails are up to 6 sec in length, but they average
closer to 2-3 sec.

My goal is to make time-frequency plots, using the multi-taper method,
aligned to the end of the trial (subject response) rather than the
beginning. I tried the following approach first:

   - Flip each trial’s data in time, such that sample 1 is now the end of
   the trial
   - Nan-pad each trial so they all have the same number of samples (6 sec
   * 256 Hz = 1536 samples).
   - Perform multi-taper spectral analysis with ft_freqanalysis

It seems that FieldTrip isn’t ignoring the NaN’s when calculating the power
at each time point. Effectively, I’m limiting my data to the shortest trial
duration rather than plotting it out to the longest time point.

Any help on NaN removal with ft_freqanalysis, or if there’s a smarter way
to align time-frequency analyses to the ends of trials, would be much
appreciated!

Thanks,
-
Justin F.
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From fereshte.ramezani at gmail.com  Mon Jan  8 08:12:39 2018
From: fereshte.ramezani at gmail.com (Fereshte)
Date: Mon, 08 Jan 2018 07:12:39 +0000
Subject: [FieldTrip] Align a predefined grid source model to an exciting
	head model
Message-ID: <CAAdxBZqsiLcdKJ4=0UtdBkis=kTNs6XCTuNr9J4oz_3SkMi9OQ@mail.gmail.com>

Dear Experts,
How can I align a predefined grid source model to an existing head model? (
I have aligned the electrodes to  the headmodel manually but I'm not sure
how to align a dipole position on the headmodel).
Looking forward to hearing from you!
Regards,
Fereshte Ramezani
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From tzvetan.popov at uni-konstanz.de  Mon Jan  8 09:09:55 2018
From: tzvetan.popov at uni-konstanz.de (Tzvetan Popov)
Date: Mon, 8 Jan 2018 09:09:55 +0100
Subject: [FieldTrip] Align a predefined grid source model to an exciting
 head model
In-Reply-To: <CAAdxBZqsiLcdKJ4=0UtdBkis=kTNs6XCTuNr9J4oz_3SkMi9OQ@mail.gmail.com>
References: <CAAdxBZqsiLcdKJ4=0UtdBkis=kTNs6XCTuNr9J4oz_3SkMi9OQ@mail.gmail.com>
Message-ID: <120BD4FE-7395-4473-ABB6-EF59CEE4EB75@uni-konstanz.de>

Hi Fereshte,

this is the relevant tutorial that’d help you out: http://www.fieldtriptoolbox.org/tutorial/sourcemodel#subject-specific_grids_that_are_equivalent_across_subjects_in_normalized_space <http://www.fieldtriptoolbox.org/tutorial/sourcemodel#subject-specific_grids_that_are_equivalent_across_subjects_in_normalized_space>
good luck
tzvetan


> Am 08.01.2018 um 08:12 schrieb Fereshte <fereshte.ramezani at gmail.com>:
> 
> Dear Experts,
> How can I align a predefined grid source model to an existing head model? ( I have aligned the electrodes to  the headmodel manually but I'm not sure how to align a dipole position on the headmodel).
> Looking forward to hearing from you!
> Regards,
> Fereshte Ramezani 
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From holmgren.jostein at gmail.com  Mon Jan  8 14:46:16 2018
From: holmgren.jostein at gmail.com (Jostein Holmgren)
Date: Mon, 8 Jan 2018 13:46:16 +0000
Subject: [FieldTrip] Post-doc position available @ Wellcome Centre for
 Integrative Neuroimaging, University of Oxford
Message-ID: <A26C2EA0-7106-4165-AD23-286AA24D13B4@gmail.com>

Dear All,

We are looking to recruit a talented post doc to join our team exploring EEG markers of depth of anaesthesia. Full details of the post are attached below. 

Please pass this email on to suitable candidates.

Best wishes,
Jostein

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

Jostein Holmgren
DPhil Student (PRS)
Nuffield Department of Clinical Neurosciences
Wellcome Centre for Integrative Neuroimaging, FMRIB Building
University of Oxford

-----------------------------------------------------------------------------------------------------
Postdoctoral Researcher in Signal Processing
Wellcome Centre for Integrative Neuroimaging (WIN), University of Oxford
Grade 7: £31,604 - £38,833 with a discretionary range to £42,418 p.a.

The successful candidate will develop and implement a new EEG depth of anaesthesia monitor that uses an individualised biomarker of perception loss called slow wave activity saturation (SWAS). The post holder will become a key member of the SWAS research team headed by Dr Katie Warnaby, and will lead software development and implementation of a prototype EEG monitoring system. 

You will have a PhD/DPhil in a relevant discipline, and possess sufficient specialist knowledge to work within the established research programme. Experience of EEG data analysis and developing real-time brain-computer and graphic user interfaces is highly desirable. 

To apply and for further details see https://www.recruit.ox.ac.uk/pls/hrisliverecruit/erq_jobspec_version_4.display_form <https://www.recruit.ox.ac.uk/pls/hrisliverecruit/erq_jobspec_version_4.display_form>. Please contact Katie Warnaby with informal enquiries on katie.warnaby at ndcn.ox.ac.uk <mailto:katie.warnaby at ndcn.ox.ac.uk>. 

Interviews will take place at the end of January for start as soon as possible after. The post is funded by the Medical Research Council (MRC) Development Pathway Funding Scheme. 

————————
Dr Katie Warnaby
Senior Research Scientist
Wellcome Centre for Integrative Neuroimaging @ FMRIB
University of Oxford

Tel: +44 1865 611 465
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From tom.marshall at psy.ox.ac.uk  Tue Jan  9 17:27:25 2018
From: tom.marshall at psy.ox.ac.uk (Tom Marshall)
Date: Tue, 9 Jan 2018 16:27:25 +0000
Subject: [FieldTrip] error in ft_prepare_headmodel
Message-ID: <39853797796B114D8DE552AC4996EA6835C4BD60@MBX11.ad.oak.ox.ac.uk>

Howdy 'Trippers,

I got a weird error when trying to create a template headmodel using ft_prepare_headmodel (basically just following the steps in the tutorial 'Creating a sourcemodel for source-reconstruction of MEG or EEG data').

After loading and segmenting the template brain I called ft_prepare_headmodel using the suggested parameters.

cfg          = [];
cfg.method   = 'singleshell';
template_headmodel = ft_prepare_headmodel(cfg, template_seg);

This gave the following error.

Error using ft_notification (line 314)
please specificy cfg.tissue and pass an appropriate segmented MRI as input data

Error in ft_error (line 39)
  ft_notification(varargin{:});

Error in ft_prepare_headmodel (line 354)
          ft_error('please specificy cfg.tissue and pass an appropriate segmented
          MRI as input data')

So I added cfg.tissue...

cfg          = [];
cfg.method   = 'singleshell';
cfg.tissue   = 'brain';
template_headmodel = ft_prepare_headmodel(cfg, template_seg);

...and this upset fieldtrip. After printing 'smoothing brain with a 5-voxel FWHM kernel', it hung for 10-15 minutes, then threw an error with lots of 'Missing symbol' statements (see below - there are a few hundred more, I just copypasted the last two).

Missing symbol '_vm_allocate' required by
'/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'
Missing symbol '_vm_deallocate' required by
'/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'.

Error in spm_smooth>smooth1 (line 105)
spm_conv_vol(P,Q,x,y,z,-[i,j,k]);

Error in spm_smooth (line 40)
    smooth1(P,Q,s,dtype);

Error in volumesmooth (line 18)
spm_smooth(output, output, fwhm);

Error in ft_datatype_segmentation (line 229)
          brain = volumesmooth(brain,    smooth,    'brain');

Error in prepare_mesh_segmentation (line 95)
    mri = ft_datatype_segmentation(mri, 'segmentationstyle', 'probabilistic',
    'hasbrain', 'yes');

Error in ft_prepare_mesh (line 147)
    bnd = prepare_mesh_segmentation(cfg, mri);

Error in ft_prepare_headmodel (line 337)
        geometry = ft_prepare_mesh(tmpcfg, data);

It seems like the problem is somewhere deep down in spm commands that fieldtrip is calling, so maybe nobody has a clue. I'm hoping somebody has seen this before and knows of a fix...

In case it's relevant: I'm running fieldtrip-20170726 in matlab R2017a on a mac.

And ideas?

Best,
Tom
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From jan.schoffelen at donders.ru.nl  Wed Jan 10 09:36:10 2018
From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs))
Date: Wed, 10 Jan 2018 08:36:10 +0000
Subject: [FieldTrip] error in ft_prepare_headmodel
In-Reply-To: <39853797796B114D8DE552AC4996EA6835C4BD60@MBX11.ad.oak.ox.ac.uk>
References: <39853797796B114D8DE552AC4996EA6835C4BD60@MBX11.ad.oak.ox.ac.uk>
Message-ID: <4BA0D72D-FC3B-4AF9-BDF2-08E60C01D689@donders.ru.nl>

Dear Tom,

To me, this looks like a platform/MATLAB version specific issue with the compiled mex-files. Anecdotally, MATLAB2017a on a Mac suffers from not knowing to handle the precompiled stuff that comes with FieldTrip/SPM. Either you could use a lower matlab version (e.g. 2016b, which as far as I know does not suffer from this), or you could try and recompile the affected mex-files from the original c-code with the matlab mex-command. See http://bit.ly/2DeuNlX for more info.

Best wishes,
JM


On 9 Jan 2018, at 17:27, Tom Marshall <tom.marshall at psy.ox.ac.uk<mailto:tom.marshall at psy.ox.ac.uk>> wrote:

Howdy 'Trippers,

I got a weird error when trying to create a template headmodel using ft_prepare_headmodel (basically just following the steps in the tutorial 'Creating a sourcemodel for source-reconstruction of MEG or EEG data').

After loading and segmenting the template brain I called ft_prepare_headmodel using the suggested parameters.

cfg          = [];
cfg.method   = 'singleshell';
template_headmodel = ft_prepare_headmodel(cfg, template_seg);

This gave the following error.

Error using ft_notification (line 314)
please specificy cfg.tissue and pass an appropriate segmented MRI as input data

Error in ft_error (line 39)
  ft_notification(varargin{:});

Error in ft_prepare_headmodel (line 354)
          ft_error('please specificy cfg.tissue and pass an appropriate segmented
          MRI as input data')

So I added cfg.tissue...

cfg          = [];
cfg.method   = 'singleshell';
cfg.tissue   = 'brain';
template_headmodel = ft_prepare_headmodel(cfg, template_seg);

...and this upset fieldtrip. After printing 'smoothing brain with a 5-voxel FWHM kernel', it hung for 10-15 minutes, then threw an error with lots of 'Missing symbol' statements (see below - there are a few hundred more, I just copypasted the last two).

Missing symbol '_vm_allocate' required by
'/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'
Missing symbol '_vm_deallocate' required by
'/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'.

Error in spm_smooth>smooth1 (line 105)
spm_conv_vol(P,Q,x,y,z,-[i,j,k]);

Error in spm_smooth (line 40)
    smooth1(P,Q,s,dtype);

Error in volumesmooth (line 18)
spm_smooth(output, output, fwhm);

Error in ft_datatype_segmentation (line 229)
          brain = volumesmooth(brain,    smooth,    'brain');

Error in prepare_mesh_segmentation (line 95)
    mri = ft_datatype_segmentation(mri, 'segmentationstyle', 'probabilistic',
    'hasbrain', 'yes');

Error in ft_prepare_mesh (line 147)
    bnd = prepare_mesh_segmentation(cfg, mri);

Error in ft_prepare_headmodel (line 337)
        geometry = ft_prepare_mesh(tmpcfg, data);

It seems like the problem is somewhere deep down in spm commands that fieldtrip is calling, so maybe nobody has a clue. I'm hoping somebody has seen this before and knows of a fix...

In case it's relevant: I'm running fieldtrip-20170726 in matlab R2017a on a mac.

And ideas?

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

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From fereshte.ramezani at gmail.com  Wed Jan 10 09:53:17 2018
From: fereshte.ramezani at gmail.com (Fereshte)
Date: Wed, 10 Jan 2018 08:53:17 +0000
Subject: [FieldTrip] Align a predefined grid source model to an exciting
 head model
In-Reply-To: <120BD4FE-7395-4473-ABB6-EF59CEE4EB75@uni-konstanz.de>
References: <CAAdxBZqsiLcdKJ4=0UtdBkis=kTNs6XCTuNr9J4oz_3SkMi9OQ@mail.gmail.com>
 <120BD4FE-7395-4473-ABB6-EF59CEE4EB75@uni-konstanz.de>
Message-ID: <CAAdxBZo4ybNv40gMR++VRKyopfHqEgKSkpThEjbqBYmTE9BfYw@mail.gmail.com>

Dear Txvetan,
Thank you for your answer. How does the filedtrip modify the head model
coordinate system if no coordinate is defined for the mri image given (to
make the FEM head model) by user?
Thanks in advance!
Regards,
Fereshte
On Mon, Jan 8, 2018 at 11:41 AM Tzvetan Popov <tzvetan.popov at uni-konstanz.de>
wrote:

> Hi Fereshte,
>
> this is the relevant tutorial that’d help you out:
> http://www.fieldtriptoolbox.org/tutorial/sourcemodel#subject-specific_grids_that_are_equivalent_across_subjects_in_normalized_space
> good luck
> tzvetan
>
>
> Am 08.01.2018 um 08:12 schrieb Fereshte <fereshte.ramezani at gmail.com>:
>
> Dear Experts,
> How can I align a predefined grid source model to an existing head model?
> ( I have aligned the electrodes to  the headmodel manually but I'm not sure
> how to align a dipole position on the headmodel).
> Looking forward to hearing from you!
> Regards,
> Fereshte Ramezani
>
> _______________________________________________
> 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
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From tzvetan.popov at uni-konstanz.de  Wed Jan 10 11:08:24 2018
From: tzvetan.popov at uni-konstanz.de (Tzvetan Popov)
Date: Wed, 10 Jan 2018 11:08:24 +0100
Subject: [FieldTrip] Align a predefined grid source model to an exciting
 head model
In-Reply-To: <CAAdxBZo4ybNv40gMR++VRKyopfHqEgKSkpThEjbqBYmTE9BfYw@mail.gmail.com>
References: <CAAdxBZqsiLcdKJ4=0UtdBkis=kTNs6XCTuNr9J4oz_3SkMi9OQ@mail.gmail.com>
 <120BD4FE-7395-4473-ABB6-EF59CEE4EB75@uni-konstanz.de>
 <CAAdxBZo4ybNv40gMR++VRKyopfHqEgKSkpThEjbqBYmTE9BfYw@mail.gmail.com>
Message-ID: <9C2C237B-72A7-46B3-BEE6-3662A4DAF503@uni-konstanz.de>

Hi,
I’m not sure I understood your question but if your mri is missing description of the coordsys but you know it, you could define it yourself by e.g. mri.coordsys = ’mni’. Alternatively you will be asked to define the directions of the x,y,z axes. Information about that can be found here:
http://www.fieldtriptoolbox.org/faq/how_are_the_different_head_and_mri_coordinate_systems_defined <http://www.fieldtriptoolbox.org/faq/how_are_the_different_head_and_mri_coordinate_systems_defined>

As such FieldTrip does not modify the head model coordsys at all. The head model is based on the coordsys defined by the input mri.
good luck
tzvetan


> Am 10.01.2018 um 09:53 schrieb Fereshte <fereshte.ramezani at gmail.com>:
> 
> Dear Txvetan,
> Thank you for your answer. How does the filedtrip modify the head model coordinate system if no coordinate is defined for the mri image given (to make the FEM head model) by user? 
> Thanks in advance!
> Regards,
> Fereshte 
> On Mon, Jan 8, 2018 at 11:41 AM Tzvetan Popov <tzvetan.popov at uni-konstanz.de <mailto:tzvetan.popov at uni-konstanz.de>> wrote:
> Hi Fereshte,
> 
> this is the relevant tutorial that’d help you out: http://www.fieldtriptoolbox.org/tutorial/sourcemodel#subject-specific_grids_that_are_equivalent_across_subjects_in_normalized_space <http://www.fieldtriptoolbox.org/tutorial/sourcemodel#subject-specific_grids_that_are_equivalent_across_subjects_in_normalized_space>
> good luck
> tzvetan
> 
> 
> 
>> Am 08.01.2018 um 08:12 schrieb Fereshte <fereshte.ramezani at gmail.com <mailto:fereshte.ramezani at gmail.com>>:
>> 
> 
>> Dear Experts,
>> How can I align a predefined grid source model to an existing head model? ( I have aligned the electrodes to  the headmodel manually but I'm not sure how to align a dipole position on the headmodel).
>> Looking forward to hearing from you!
>> Regards,
>> Fereshte Ramezani 
> 
>> _______________________________________________
>> fieldtrip mailing list
>> fieldtrip at donders.ru.nl <mailto:fieldtrip at donders.ru.nl>
>> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip <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 <https://mailman.science.ru.nl/mailman/listinfo/fieldtrip>_______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From martin.bleichner at uni-oldenburg.de  Wed Jan 10 15:39:55 2018
From: martin.bleichner at uni-oldenburg.de (Martin Bleichner)
Date: Wed, 10 Jan 2018 15:39:55 +0100
Subject: [FieldTrip] 2nd International LSL Workshop (27.9-28.9.2018) - Save
	the Date
In-Reply-To: <CAPg9X1SEq_9ZWorE2bNOvwb=+vS45LmfYWiRUxWHOH1YqMMEwA@mail.gmail.com>
References: <CAPg9X1SCR_3Y0Kz+rJVGEGZkeQcHDUH0jPVvuJCLK2yVCO0eNA@mail.gmail.com>
 <CAPg9X1Qhsn-3xt=Kh60tSh3xe6s6o77PgukrAcM1bPmi-YFtFQ@mail.gmail.com>
 <2c8b685b-d7c4-e8f9-d00e-ec9fe96bd48b@gmail.com>
 <CAPg9X1SEq_9ZWorE2bNOvwb=+vS45LmfYWiRUxWHOH1YqMMEwA@mail.gmail.com>
Message-ID: <27e861b5-5224-61c5-d02c-3b70140acba2@uni-oldenburg.de>

Dear colleagues,

We are happy to announce the second international Lab Streaming Layer 
(LSL) workshop, which will take place September 27 - 28, 2018, at the 
Hanse Wissenschaftskolleg, in Delmenhorst, Germany. LSL is an 
open-source project enabling the synchronized streaming of time series 
data coming from different devices, such as EEG amplifiers, audio, 
video, eye tracking, keyboards, etc. LSL features near real-time access 
to data streams, time-synchronization, networking and centralized 
collection (https://github.com/sccn/labstreaminglayer).

Key LSL developers and expert users have confirmed attendance. The 
workshop will provide a general introduction to LSL. We will present how 
LSL can be used for a multitude of different experimental setups, using 
a variety of experimental software, hardware and operating systems. In a 
hands-on session, participants can learn to stream data from their own 
hardware or play with hardware provided by us and external partners. We 
will name pitfalls and discuss how to test and ensure the best possible 
timing accuracy when recording multimodal data. We will also provide a 
best practice guide and present different use cases of LSL. We will also 
use the workshop to discuss future software and hardware developments.

Participants are invited to contribute to the workshop by presenting 
their LSL use cases.

More information on the workshop will follow soon. For further 
enquiries, please contact: martin.bleichner at uol.de 
<mailto:martin.bleichner at uol.de>

Best,

Martin Bleichner

-- 
Dr. Martin Bleichner
Neuropsychology    Lab
Department of Psychology
University of Oldenburg
D-26111 Oldenburg
Germany

martin.bleichner at uni-oldenburg.de
Tel.: +49 (0)441 - 798-2940
http://www.uni-oldenburg.de/psychologie/neuropsychologie/team/martin-bleichner/

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From r.oostenveld at donders.ru.nl  Wed Jan 10 15:55:57 2018
From: r.oostenveld at donders.ru.nl (Robert Oostenveld)
Date: Wed, 10 Jan 2018 15:55:57 +0100
Subject: [FieldTrip] question on cluster-based statistics and source
	localization
In-Reply-To: <F96BCA30-0C1F-4C3B-9DE3-CDB22827049F@ulb.ac.be>
References: <F96BCA30-0C1F-4C3B-9DE3-CDB22827049F@ulb.ac.be>
Message-ID: <E1AC378D-E513-472B-A443-6E1439FE0A50@donders.ru.nl>

Hi Vincent,

Let me reply through the email list, where other people might learn something and/or want to chime in.

> On 10 Jan 2018, at 13:22, Vincent Wens <vwens at ulb.ac.be> wrote:
> 
> Dear Pr. Oostenveld,
> 
> I am Vincent Wens, a physicist working in the MEG unit at Erasme Hospital, Brussels. We've been recently trying to play with the cluster-based statistics that you developed and included in Fieldtrip, but hit a difficulty in our analysis pipeline and I wondered if you would be so kind to take a few minutes and provide advice on this? 

The cluster-based statistics is a method for statistical inference, i.e. statistical decision making based on a hypothesis and estimated probability distribution. The hypothesis H0 states that the data can be exchanged (between conditions). If it is very unlikely that the data can be exchanged (under H0), we decide that the data must be different somehow. The clusters provide evidence for the data being different, but the clusters are not the difference itself. The tip of an iceberg above the sea level provides evidence for there being an iceberg, but the tip is not the iceberg itself. 

An important FAQ is this http://www.fieldtriptoolbox.org/faq/how_not_to_interpret_results_from_a_cluster-based_permutation_test

Let me give the other commens in-line in your email below

> Globally, my question is how to go from sensor-level cluster statistics results to the source space.
> 
> More precisely: Assume we run the cluster statistics analysis on, say, N-channels time-frequency plots and obtain significance for the maximum cluster statistic.

So you obtain evidence that the channel level data is different. That logically implies that the cortical activity is different. Note that the other way arround would not hold per see; there can be different activity in the brain without it showing up as a difference in the scalp data.

> We thus find one (and possibly more) supra-threshold cluster(s) whose "spatio-spectral-temporal localization" can be assessed.

You could look at the visible tip (i.e. the cluster), you could also take a broader approach and look at the phenomenom under the tip (the iceberg).

> See for example the attached picture depicting the plot of those T-values within the significant cluster associated with an ERD. The next step would then be to source localize this,

You would not localize the cluster (you already have it, it is at the channel level). You localize the cortical activity that causes the data to appear different at the channel level. It’s the part of the iceberg under the sea level that causes the tip to appear above sea level.

> and our initial idea was to use the time and frequency region from this cluster as a prior on the time and frequency used for source projection. However the very complex shape of the cluster does not make this step so obvious. There are multiple possibilities that would come to mind, most of them absolutely ad-hoc, so I wondered your opinion on what would be the most rigorous, or at least least unacceptable way to go (or even just the most standard way, if there's one).

Based on the resulls (the multiplot), you should wonder whether there is only a single feature in the brain that is different or whether there are multiple. The hypothesis you started with was “is there any difference in this massive multiple-comparision space?” and the (only) answer you got to that question was “yes”. 

You now have the question “what is the difference”, which pertains to interpreting the data. That question has no binary answer and a statistical test based of a p-value being small enough (which gives you a "yes/no" answer) does not help.

I cannot offer specific advice on how to interpret your data, but recommend that you consider whether your true quest is for “the (one and only) effect” or “the effects” that causes the data in the two conditions to be different. Of course you can argue that the effect(s) show at certain frequency ranges and/or latencies and/or locations, and therefore you may decide to look for the interpretation of the effect(s) at or around those parts of the cluster. 

In general (not any more for this dataset) it is worthwile to consider that narrow a-priori hypotheses provide more valuable and specific information. This is something that we often rely on in sequential studies, where in the 2nd study we don’t repeat the full hypothesis of the 1st study (e.g. “is there any difference”), but a more specific sub-hypothesis that we generated on basis of the first study (e.g. is there a difference around this specific time-frequency range).

> Thanks in advance for your invaluable help, and still my best wishes for the New Year.

You’re welcome. Please follow up questions on the email discussion list.

best regards,
Robert


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From a.stolk8 at gmail.com  Wed Jan 10 17:16:09 2018
From: a.stolk8 at gmail.com (Arjen Stolk)
Date: Wed, 10 Jan 2018 08:16:09 -0800
Subject: [FieldTrip] error in ft_prepare_headmodel
In-Reply-To: <4BA0D72D-FC3B-4AF9-BDF2-08E60C01D689@donders.ru.nl>
References: <39853797796B114D8DE552AC4996EA6835C4BD60@MBX11.ad.oak.ox.ac.uk>
 <4BA0D72D-FC3B-4AF9-BDF2-08E60C01D689@donders.ru.nl>
Message-ID: <6131501D-762A-4258-B43E-4AB8FC3D7E57@gmail.com>

Hi Tom, 

As another work around, you could try using spm12 functionality. cfg.spmversion = ‘spm12’ if the function supports it, or by manually putting it on the path with ft_hastoolbox. There may be differences in the algorithm/outcome between versions, so you may want to be consistent in its use across subjects.

Best,
Arjen

> On Jan 10, 2018, at 12:36 AM, Schoffelen, J.M. (Jan Mathijs) <jan.schoffelen at donders.ru.nl> wrote:
> 
> Dear Tom,
> 
> To me, this looks like a platform/MATLAB version specific issue with the compiled mex-files. Anecdotally, MATLAB2017a on a Mac suffers from not knowing to handle the precompiled stuff that comes with FieldTrip/SPM. Either you could use a lower matlab version (e.g. 2016b, which as far as I know does not suffer from this), or you could try and recompile the affected mex-files from the original c-code with the matlab mex-command. See http://bit.ly/2DeuNlX for more info.
> 
> Best wishes,
> JM
> 
> 
>> On 9 Jan 2018, at 17:27, Tom Marshall <tom.marshall at psy.ox.ac.uk> wrote:
>> 
>> Howdy 'Trippers,
>> 
>> I got a weird error when trying to create a template headmodel using ft_prepare_headmodel (basically just following the steps in the tutorial 'Creating a sourcemodel for source-reconstruction of MEG or EEG data').
>> 
>> After loading and segmenting the template brain I called ft_prepare_headmodel using the suggested parameters.
>> 
>> cfg          = [];
>> cfg.method   = 'singleshell';
>> template_headmodel = ft_prepare_headmodel(cfg, template_seg);
>> 
>> This gave the following error.
>> 
>> Error using ft_notification (line 314)
>> please specificy cfg.tissue and pass an appropriate segmented MRI as input data
>> 
>> Error in ft_error (line 39)
>>   ft_notification(varargin{:});
>> 
>> Error in ft_prepare_headmodel (line 354)
>>           ft_error('please specificy cfg.tissue and pass an appropriate segmented
>>           MRI as input data')
>> 
>> So I added cfg.tissue...
>> 
>> cfg          = [];
>> cfg.method   = 'singleshell';
>> cfg.tissue   = 'brain';
>> template_headmodel = ft_prepare_headmodel(cfg, template_seg);
>> 
>> ...and this upset fieldtrip. After printing 'smoothing brain with a 5-voxel FWHM kernel', it hung for 10-15 minutes, then threw an error with lots of 'Missing symbol' statements (see below - there are a few hundred more, I just copypasted the last two).
>> 
>> Missing symbol '_vm_allocate' required by
>> '/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'
>> Missing symbol '_vm_deallocate' required by
>> '/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'.
>> 
>> Error in spm_smooth>smooth1 (line 105)
>> spm_conv_vol(P,Q,x,y,z,-[i,j,k]);
>> 
>> Error in spm_smooth (line 40)
>>     smooth1(P,Q,s,dtype);
>> 
>> Error in volumesmooth (line 18)
>> spm_smooth(output, output, fwhm);
>> 
>> Error in ft_datatype_segmentation (line 229)
>>           brain = volumesmooth(brain,    smooth,    'brain');
>> 
>> Error in prepare_mesh_segmentation (line 95)
>>     mri = ft_datatype_segmentation(mri, 'segmentationstyle', 'probabilistic',
>>     'hasbrain', 'yes');
>> 
>> Error in ft_prepare_mesh (line 147)
>>     bnd = prepare_mesh_segmentation(cfg, mri);
>> 
>> Error in ft_prepare_headmodel (line 337)
>>         geometry = ft_prepare_mesh(tmpcfg, data);
>> 
>> It seems like the problem is somewhere deep down in spm commands that fieldtrip is calling, so maybe nobody has a clue. I'm hoping somebody has seen this before and knows of a fix...
>> 
>> In case it's relevant: I'm running fieldtrip-20170726 in matlab R2017a on a mac.
>> 
>> And ideas?
>> 
>> Best,
>> Tom
>> _______________________________________________
>> 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
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From tom.marshall at psy.ox.ac.uk  Wed Jan 10 19:42:29 2018
From: tom.marshall at psy.ox.ac.uk (Tom Marshall)
Date: Wed, 10 Jan 2018 18:42:29 +0000
Subject: [FieldTrip] error in ft_prepare_headmodel
In-Reply-To: <6131501D-762A-4258-B43E-4AB8FC3D7E57@gmail.com>
References: <39853797796B114D8DE552AC4996EA6835C4BD60@MBX11.ad.oak.ox.ac.uk>
 <4BA0D72D-FC3B-4AF9-BDF2-08E60C01D689@donders.ru.nl>,
 <6131501D-762A-4258-B43E-4AB8FC3D7E57@gmail.com>
Message-ID: <39853797796B114D8DE552AC4996EA6835C4C11B@MBX11.ad.oak.ox.ac.uk>

Hi Arjen and JM,

Arjen - thanks for the golden tip!

As suggested, I explicitly added the SPM12 toolbox and called it in the cfg.

[status] = ft_hastoolbox('SPM12', 1, 0);

cfg                = [];
cfg.grid.warpmni   = 'yes';
cfg.grid.template  = template_grid;
cfg.grid.nonlinear = 'yes'; % use non-linear normalization
cfg.spmversion     = 'SPM12';
cfg.mri                = mri;
sourcemodel        = ft_prepare_sourcemodel(cfg);

However, this didn't totally solve the problem. At one point in ft_prepare_sourcemodel (line 636) ft_volumenormalise is called with a new cfg ('tmpcfg'). The choice to use SPM12 doesn't propagate to tmpcfg so fieldtrip adds SPM8 anyway when it calls ft_volumenormalise.

I fixed this by adding the following to ft_prepare_sourcemodel at line 633...

tmpcfg.spmversion = cfg.spmversion;

...and voila! A nice warped source model :)

Should I file this as a bug?

Best and thanks for the help,
Tom

________________________________
From: fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl] on behalf of Arjen Stolk [a.stolk8 at gmail.com]
Sent: 10 January 2018 16:16
To: FieldTrip discussion list
Subject: Re: [FieldTrip] error in ft_prepare_headmodel

Hi Tom,

As another work around, you could try using spm12 functionality. cfg.spmversion = ‘spm12’ if the function supports it, or by manually putting it on the path with ft_hastoolbox. There may be differences in the algorithm/outcome between versions, so you may want to be consistent in its use across subjects.

Best,
Arjen

On Jan 10, 2018, at 12:36 AM, Schoffelen, J.M. (Jan Mathijs) <jan.schoffelen at donders.ru.nl<mailto:jan.schoffelen at donders.ru.nl>> wrote:

Dear Tom,

To me, this looks like a platform/MATLAB version specific issue with the compiled mex-files. Anecdotally, MATLAB2017a on a Mac suffers from not knowing to handle the precompiled stuff that comes with FieldTrip/SPM. Either you could use a lower matlab version (e.g. 2016b, which as far as I know does not suffer from this), or you could try and recompile the affected mex-files from the original c-code with the matlab mex-command. See http://bit.ly/2DeuNlX for more info.

Best wishes,
JM


On 9 Jan 2018, at 17:27, Tom Marshall <tom.marshall at psy.ox.ac.uk<mailto:tom.marshall at psy.ox.ac.uk>> wrote:

Howdy 'Trippers,

I got a weird error when trying to create a template headmodel using ft_prepare_headmodel (basically just following the steps in the tutorial 'Creating a sourcemodel for source-reconstruction of MEG or EEG data').

After loading and segmenting the template brain I called ft_prepare_headmodel using the suggested parameters.

cfg          = [];
cfg.method   = 'singleshell';
template_headmodel = ft_prepare_headmodel(cfg, template_seg);

This gave the following error.

Error using ft_notification (line 314)
please specificy cfg.tissue and pass an appropriate segmented MRI as input data

Error in ft_error (line 39)
  ft_notification(varargin{:});

Error in ft_prepare_headmodel (line 354)
          ft_error('please specificy cfg.tissue and pass an appropriate segmented
          MRI as input data')

So I added cfg.tissue...

cfg          = [];
cfg.method   = 'singleshell';
cfg.tissue   = 'brain';
template_headmodel = ft_prepare_headmodel(cfg, template_seg);

...and this upset fieldtrip. After printing 'smoothing brain with a 5-voxel FWHM kernel', it hung for 10-15 minutes, then threw an error with lots of 'Missing symbol' statements (see below - there are a few hundred more, I just copypasted the last two).

Missing symbol '_vm_allocate' required by
'/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'
Missing symbol '_vm_deallocate' required by
'/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'.

Error in spm_smooth>smooth1 (line 105)
spm_conv_vol(P,Q,x,y,z,-[i,j,k]);

Error in spm_smooth (line 40)
    smooth1(P,Q,s,dtype);

Error in volumesmooth (line 18)
spm_smooth(output, output, fwhm);

Error in ft_datatype_segmentation (line 229)
          brain = volumesmooth(brain,    smooth,    'brain');

Error in prepare_mesh_segmentation (line 95)
    mri = ft_datatype_segmentation(mri, 'segmentationstyle', 'probabilistic',
    'hasbrain', 'yes');

Error in ft_prepare_mesh (line 147)
    bnd = prepare_mesh_segmentation(cfg, mri);

Error in ft_prepare_headmodel (line 337)
        geometry = ft_prepare_mesh(tmpcfg, data);

It seems like the problem is somewhere deep down in spm commands that fieldtrip is calling, so maybe nobody has a clue. I'm hoping somebody has seen this before and knows of a fix...

In case it's relevant: I'm running fieldtrip-20170726 in matlab R2017a on a mac.

And ideas?

Best,
Tom
_______________________________________________
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
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From joseluisblues at gmail.com  Thu Jan 11 00:41:02 2018
From: joseluisblues at gmail.com (Jose)
Date: Wed, 10 Jan 2018 20:41:02 -0300
Subject: [FieldTrip] shrunk TFR topoplot
Message-ID: <CAH3cVdDVWKYSmGgL8U9At84dUREFy+RmCN6kLuYAjJvoP8Vcqg@mail.gmail.com>

dear list,

I'm trying to do a time-frequency plot with ft_topoplotTFR including first
an average across all conditions followed by specific conditions. I want to
highlight my sensors of interest for the first topoplot (the average across
all conditions), and I'm running in a rather annoying issue. When
highlighting the sensors the topoplot is slightly shrunk relative to the
other topoplots,

Has anybody run into this problem and find a workaround?

Thanks for any hints,

Jose

A snippet of my code is below,

%%%

    cfg = [ ];
    cfg.baseline = baselinePeriod;
    cfg.baselinetype = baselineType;
    cfg.xlim = TOI;
    cfg.ylim = YLimsFreq;
    cfg.zlim = ZLimsPower;
    cfg.marker = 'off';
    cfg.layout = 'biosemi64.lay';
    cfg.comment = 'no';
    cfg.interactive = 'no';
    % highlight
    cfg.highlight = 'on';
    cfg.highlightchannel = chan2use{i_chanSel};
    cfg.highlightcolor = [0 0 0];
    cfg.highlightsymbol = '.';
    cfg.highlightsize = 12;

    subplot(2,4,5); ft_topoplotTFR(cfg, datAll); colormap jet

    cfg = [ ];
    cfg.baseline = baselinePeriod;
    cfg.baselinetype = baselineType;
    cfg.xlim = TOI;
    cfg.ylim = YLimsFreq;
    cfg.zlim = ZLimsPower;
    cfg.marker = 'off';
    cfg.layout = 'biosemi64.lay';
    cfg.comment = 'no';
    cfg.interactive = 'no';
    subplot(2,4,6); ft_topoplotTFR(cfg, datCongr); colormap jet
    subplot(2,4,7); ft_topoplotTFR(cfg, datIncong); colormap jet
    subplot(2,4,8); ft_topoplotTFR(cfg, datNeutral); colormap jet

%%%
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From a.stolk8 at gmail.com  Thu Jan 11 07:49:44 2018
From: a.stolk8 at gmail.com (Arjen Stolk)
Date: Wed, 10 Jan 2018 22:49:44 -0800
Subject: [FieldTrip] error in ft_prepare_headmodel
In-Reply-To: <39853797796B114D8DE552AC4996EA6835C4C11B@MBX11.ad.oak.ox.ac.uk>
References: <39853797796B114D8DE552AC4996EA6835C4BD60@MBX11.ad.oak.ox.ac.uk>
 <4BA0D72D-FC3B-4AF9-BDF2-08E60C01D689@donders.ru.nl>
 <6131501D-762A-4258-B43E-4AB8FC3D7E57@gmail.com>
 <39853797796B114D8DE552AC4996EA6835C4C11B@MBX11.ad.oak.ox.ac.uk>
Message-ID: <CAAiwptTqisR_8ztKL86+kgYmYqS0tCtvqRRX3c95FnyNDtKCYw@mail.gmail.com>

Glad to see it worked, Tom. Full support for SPM12 has only recently been
completed, with JM laying the last hand on ft_volumenormalization a couple
of weeks ago. Therefore, the issue identified by you might be a missing
link that needs to be created still. Do you think you can you propose your
solution on github, for further joint discussion and implementation?

On Wed, Jan 10, 2018 at 10:42 AM, Tom Marshall <tom.marshall at psy.ox.ac.uk>
wrote:

> Hi Arjen and JM,
>
> Arjen - thanks for the golden tip!
>
> As suggested, I explicitly added the SPM12 toolbox and called it in the
> cfg.
>
>
>
>
>
>
>
>
>
>
>
> *[status] = ft_hastoolbox('SPM12', 1, 0); cfg                = [];
> cfg.grid.warpmni   = 'yes'; cfg.grid.template  = template_grid;
> cfg.grid.nonlinear = 'yes'; % use non-linear normalization
> cfg.spmversion     = 'SPM12'; cfg.mri                = mri;
> sourcemodel        = ft_prepare_sourcemodel(cfg); *However, this didn't
> totally solve the problem. At one point in ft_prepare_sourcemodel (line
> 636) ft_volumenormalise is called with a new cfg ('tmpcfg'). The choice to
> use SPM12 doesn't propagate to tmpcfg so fieldtrip adds SPM8 anyway when it
> calls ft_volumenormalise.
>
> I fixed this by adding the following to ft_prepare_sourcemodel at line
> 633...
>
>
> *tmpcfg.spmversion = cfg.spmversion; *
> ...and voila! A nice warped source model :)
>
> Should I file this as a bug?
>
> Best and thanks for the help,
> Tom
>
> ------------------------------
> *From:* fieldtrip-bounces at science.ru.nl [fieldtrip-bounces at science.ru.nl]
> on behalf of Arjen Stolk [a.stolk8 at gmail.com]
> *Sent:* 10 January 2018 16:16
> *To:* FieldTrip discussion list
> *Subject:* Re: [FieldTrip] error in ft_prepare_headmodel
>
> Hi Tom,
>
> As another work around, you could try using spm12 functionality.
> cfg.spmversion = ‘spm12’ if the function supports it, or by manually
> putting it on the path with ft_hastoolbox. There may be differences in the
> algorithm/outcome between versions, so you may want to be consistent in its
> use across subjects.
>
> Best,
> Arjen
>
> On Jan 10, 2018, at 12:36 AM, Schoffelen, J.M. (Jan Mathijs) <
> jan.schoffelen at donders.ru.nl> wrote:
>
> Dear Tom,
>
> To me, this looks like a platform/MATLAB version specific issue with the
> compiled mex-files. Anecdotally, MATLAB2017a on a Mac suffers from not
> knowing to handle the precompiled stuff that comes with FieldTrip/SPM.
> Either you could use a lower matlab version (e.g. 2016b, which as far as I
> know does not suffer from this), or you could try and recompile the
> affected mex-files from the original c-code with the matlab mex-command.
> See http://bit.ly/2DeuNlX for more info.
>
> Best wishes,
> JM
>
>
> On 9 Jan 2018, at 17:27, Tom Marshall <tom.marshall at psy.ox.ac.uk> wrote:
>
> Howdy 'Trippers,
>
> I got a weird error when trying to create a template headmodel using
> ft_prepare_headmodel (basically just following the steps in the tutorial
> 'Creating a sourcemodel for source-reconstruction of MEG or EEG data').
>
> After loading and segmenting the template brain I called
> ft_prepare_headmodel using the suggested parameters.
>
>
>
> *cfg          = []; cfg.method   = 'singleshell'; template_headmodel =
> ft_prepare_headmodel(cfg, template_seg);*
>
> This gave the following error.
>
>
>
>
>
>
>
>
>
> *Error using ft_notification (line 314) please specificy cfg.tissue and
> pass an appropriate segmented MRI as input data Error in ft_error (line 39)
>   ft_notification(varargin{:}); Error in ft_prepare_headmodel (line 354)
>           ft_error('please specificy cfg.tissue and pass an appropriate
> segmented           MRI as input data')*
>
> So I added cfg.tissue...
>
>
>
>
> *cfg          = []; cfg.method   = 'singleshell'; cfg.tissue   = 'brain';
> template_headmodel = ft_prepare_headmodel(cfg, template_seg);*
>
> ...and this upset fieldtrip. After printing *'smoothing brain with a
> 5-voxel FWHM kernel'*, it hung for 10-15 minutes, then threw an error
> with lots of 'Missing symbol' statements (see below - there are a few
> hundred more, I just copypasted the last two).
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
>
> *Missing symbol '_vm_allocate' required by
> '/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'
> Missing symbol '_vm_deallocate' required by
> '/usr/lib/closure/libclosured.dylib->/usr/lib/system/libdyld.dylib->/usr/lib/system/libsystem_platform.dylib->/usr/lib/system/libsystem_pthread.dylib->/usr/lib/system/libcache.dylib->/usr/lib/libgcc_s.1.dylib->/Users/marshall/Documents/MATLAB/fieldtrip-20170726/external/spm8/spm_conv_vol.mexmaci64'.
> Error in spm_smooth>smooth1 (line 105) spm_conv_vol(P,Q,x,y,z,-[i,j,k]);
> Error in spm_smooth (line 40)     smooth1(P,Q,s,dtype); Error in
> volumesmooth (line 18) spm_smooth(output, output, fwhm); Error in
> ft_datatype_segmentation (line 229)           brain =
> volumesmooth(brain,    smooth,    'brain'); Error in
> prepare_mesh_segmentation (line 95)     mri = ft_datatype_segmentation(mri,
> 'segmentationstyle', 'probabilistic',     'hasbrain', 'yes'); Error in
> ft_prepare_mesh (line 147)     bnd = prepare_mesh_segmentation(cfg, mri);
> Error in ft_prepare_headmodel (line 337)         geometry =
> ft_prepare_mesh(tmpcfg, data); *
> It seems like the problem is somewhere deep down in spm commands that
> fieldtrip is calling, so maybe nobody has a clue. I'm hoping somebody has
> seen this before and knows of a fix...
>
> In case it's relevant: I'm running fieldtrip-20170726 in matlab R2017a on
> a mac.
>
> And ideas?
>
> Best,
> Tom
> _______________________________________________
> 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
>
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From Joachim.Gross at glasgow.ac.uk  Thu Jan 11 12:57:43 2018
From: Joachim.Gross at glasgow.ac.uk (Joachim Gross)
Date: Thu, 11 Jan 2018 11:57:43 +0000
Subject: [FieldTrip] Two Postdoc positions in Muenster, Germany
Message-ID: <A0FC7DEB-28C9-4A8E-A6F2-FF2AD80C7711@contoso.com>



The Institute for Biomagnetism and Biosignalanalysis at University of Muenster invites applications for a

Research associate/Postdoctoral scientist (f/m)
Ref.: 01689
Full-Time with 38,5 (hours/week)
(Germany salary grade: E 13 TV-L, 100%)

Two positions are intramurally funded and available for 2 years.

We are searching for trained and highly motivated scientists holding a PhD or MD degree and having experience in electrophysiology, cognitive neuroimaging or similar disciplines. The successful candidates are expected to have a strong publication record in international peer-reviewed journals.

The research project requires acquisition of MEG data and analysis of neuronal oscillations and their relationship to behaviour. Therefore, experience with MEG/EEG, programming and spectral analysis is essential.

The successful applicants will join a dynamic team of both experienced and junior researchers with many national and international collaborations and a sustained record of high-quality research output.

For more information please contact Prof Dr Joachim Gross, University of Muenster, Institute for Biomagnetism and Biosignalanalysis, 48149 Münster, Germany, Email:. Joachim.Gross(at)wwu(dot)de


Please send your application (including the above reference number) with all relevant information (CV, cover letter) by email (PDF-file, max. 5 MB) until 11.02.2018 to: bewerbung(at)ukmuenster(dot)de

Applications of women are specifically invited. In the case of similar qualifications, competence, and specific achievements, women will be considered on preferential terms within the framework of the legal possibilities. Handicapped candidates with equivalent qualifications will be given preference.


[University of Glasgow: The Times Scottish University of the Year 2018]
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From elam4hcp at gmail.com  Mon Jan 15 21:10:08 2018
From: elam4hcp at gmail.com (Jennifer Elam)
Date: Mon, 15 Jan 2018 14:10:08 -0600
Subject: [FieldTrip] Join us for HCP Course 2018 in Oxford, UK June 25-29!
Message-ID: <CAJbMWh6EONG62anxP+_ShBxhWNkPRyjPpg0HDBBoZNtORUcmBA@mail.gmail.com>

We are pleased to announce the *2018 HCP Course: "Exploring the Human
Connectome"
<http://store.humanconnectome.org/courses/2018/exploring-the-human-connectome.php>*,
to be held *June 25 – 29, 2018* at the Blavatnik School of Government
<https://www.bsg.ox.ac.uk/partner/contact-us>, at the University of Oxford
<http://www.ox.ac.uk/>, in Oxford, UK.
This 5-day intensive course will provide training in acquisition,
processing, analysis and visualization of whole brain imaging and
behavioral data using methods and tools developed by the WU-Minn-Oxford Human
Connectome Project (HCP) consortium.

The course is designed for investigators interested in:

   - using HCP-style data distributed by the Connectome Coordinating
   Facility (CCF) from the young adult (original) HCP and forthcoming projects
   - acquiring and analyzing HCP-style imaging and behavioral data at your
   own institution
   - processing your own non-HCP data using HCP pipelines and methods
   - using Connectome Workbench
   <https://www.humanconnectome.org/software/connectome-workbench.html> tools
   and sharing data using the BALSA <https://balsa.wustl.edu/> imaging
   database
   - learning HCP multimodal neuroimaging analysis methods, including those
   that combine MEG and MRI data
   - positioning yourself to capitalize on HCP-style data forthcoming from
   large-scale projects currently collecting data (e.g., Lifespan HCP
   development and aging and Connectomes Related to Human Disease projects)


Participants will learn how to acquire, analyze, visualize, and interpret
data from four major MR modalities (structural MR, resting-state fMRI,
diffusion imaging, task-evoked fMRI) plus magnetoencephalography (MEG) and
extensive behavioral data.  Lectures and labs will provide grounding in
neurobiological as well as methodological issues involved in interpreting
multimodal data, and will span the range from single-voxel/vertex to brain
network analysis approaches.

The course is open to students, postdocs, faculty, and industry
participants.  The course is aimed at both new and current users of HCP
data, methods, and tools, and will cover both basic and advanced topics.
Prior experience in human neuroimaging or in computational analysis of
brain networks is desirable, preferably including some familiarity with FSL
<https://fsl.fmrib.ox.ac.uk/fsl/fslwiki> and Freesurfer
<https://surfer.nmr.mgh.harvard.edu/> software.

For more info and to register visit the HCP Course 2018 website
<http://store.humanconnectome.org/courses/2018/exploring-the-human-connectome.php>.
New this year is the opportunity to add 6 nights of bed and
breakfast accommodation (Sun June 24 - Fri June 29) at nearby Worcester
College to your registration at a group, taxes included rate.
If you have any questions, please contact us at: hcpcourse at humanconnectome.
org

We look forward to seeing you in Oxford!

Best,
2018 HCP Course Organizers


-- 
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
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From bioeng.yoosofzadeh at gmail.com  Mon Jan 15 22:04:40 2018
From: bioeng.yoosofzadeh at gmail.com (Vahab Yousofzadeh)
Date: Mon, 15 Jan 2018 16:04:40 -0500
Subject: [FieldTrip] question on cluster-based statistics and source
Message-ID: <CAL5FLdKFs0rOBwkY29xTi7GZ_Kotdmjmdu9RCzkg34kSB0B24Q@mail.gmail.com>

Dear Vincent,

For cluster correction at source space, you would need to trick the
ft_prepare_neighbours because (as far as I know) it only works with
sensor-space data - so you just need to update the pos. with those
from the source model. Here's a piece of scripts:

s = timePost; % timePost is the output of ft_timelockanalysis.
s.grad.chanpos = headmodel_time.pos(headmodel_time.inside,:);
s.grad.chanori = s.grad.chanpos;
s.grad.chanunit(1:size(s.grad.chanpos,1)) = s.grad.chanunit(1);
s.grad.chantype(1:size(s.grad.chanpos,1)) = s.grad.chantype(1);
s.grad.tra    = ones(size(s.grad.chanpos,1),size(s.grad.tra,2));
for i=1:size(s.grad.chanpos,1)
    s.grad.label{i} = num2str(i);
    s.label{i} = num2str(i);
    s.grad.labelold =  num2str(i);
end
% prepare_neighbours determines what sensors may form clusters
cfg_neighb.method   = 'distance';
% cfg.method      = 'triangulation';
neighbours          = ft_prepare_neighbours(cfg_neighb, s);

%% inspecting random neighbours (#1200)
neighbours2 = [];
neighbours2 = neighbours(1200);
% neighbours2.neighblabel = neighbours2.neighblabel(1:20);
% plotting neighbours for inspection
cfg            = [];
cfg.neighbours = neighbours2;
ft_neighbourplot_source(cfg, s);

Now for cluster-correction, you need to have your source trials as
inputs, and do something like:

%% Cluster-correction
cfg = [];
cfg.parameter        = 'pow';
cfg.dim              = sourcemodel.dim;
cfg.method           = 'montecarlo';
% cfg.statistic        = 'ft_statfun_depsamplesT';
cfg.statistic        = 'depsamplesT';
% cfg.statistic         = 'indepsamplesT';
cfg.correctm         = 'cluster';
% cfg.correctm         = 'fdr';
cfg.clusteralpha     = 0.01;
cfg.clusterstatistic = 'max';
% cfg.correcttail = 'prob';
cfg.tail             = 0;
cfg.clustertail      = 0;
cfg.alpha            = 0.05;
cfg.numrandomization = 5000;
cfg.neighbours      = ft_prepare_neighbours(cfg_neighb, s);

ntrials                       = L;
design                        = zeros(2,2*ntrials);
design(1,1:ntrials)           = 1;
design(1,ntrials+1:2*ntrials) = 2;
design(2,1:ntrials)           = 1:ntrials;
design(2,ntrials+1:2*ntrials) = 1:ntrials;

cfg.design   = design;
cfg.ivar     = 1;
cfg.uvar     = 2;
stat         = ft_sourcestatistics(cfg,Source1,Source2);
stat.pos     = souremodel.pos;% keep positions for plotting later

and for plotting stats,

cfg              = [];
cfg.voxelcoord   = 'no';
cfg.parameter    = 'stat';
% cfg.interpmethod = 'nearest';
cfg.interpmethod = 'sphere_avg';
statint  = ft_sourceinterpolate(cfg, stat, template_mri);
cfg.parameter    = 'mask';
maskint  = ft_sourceinterpolate(cfg, stat, template_mri);

statint.mask = maskint.mask;

atlas = ft_read_atlas('ROI_MNI_V4.nii');

statint.coordsys  = 'mni';
cfg               = [];
cfg.method        = 'ortho';
% cfg.method = 'slice';
cfg.funparameter  = 'stat';
cfg.maskparameter = 'mask';
cfg.atlas         = atlas;
cfg.location      = 'max';
% cfg.funcolorlim   = [-5 5];
cfg.funcolormap   = 'jet';
% cfg.location = [x,y,z];
ft_sourceplot(cfg,statint);

Hope this helps, and let me know if you are running into issues.

Cheers,
Vahab

On Wed, Jan 10, 2018 at 9:55 AM,  <fieldtrip-request at science.ru.nl> wrote:
> Send fieldtrip mailing list submissions to
>         fieldtrip at science.ru.nl
>
> To subscribe or unsubscribe via the World Wide Web, visit
>         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
>
> You can reach the person managing the list at
>         fieldtrip-owner at science.ru.nl
>
> When replying, please edit your Subject line so it is more specific
> than "Re: Contents of fieldtrip digest..."
>
>
> Today's Topics:
>
>    1. 2nd International LSL Workshop (27.9-28.9.2018) - Save    the
>       Date (Martin Bleichner)
>    2. Re: question on cluster-based statistics and source
>       localization (Robert Oostenveld)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Wed, 10 Jan 2018 15:39:55 +0100
> From: Martin Bleichner <martin.bleichner at uni-oldenburg.de>
> To: lsl-l at mailman.ucsd.edu, eeglablist at sccn.ucsd.edu,
>         fieldtrip at science.ru.nl
> Subject: [FieldTrip] 2nd International LSL Workshop (27.9-28.9.2018) -
>         Save    the Date
> Message-ID: <27e861b5-5224-61c5-d02c-3b70140acba2 at uni-oldenburg.de>
> Content-Type: text/plain; charset="utf-8"; Format="flowed"
>
> Dear colleagues,
>
> We are happy to announce the second international Lab Streaming Layer
> (LSL) workshop, which will take place September 27 - 28, 2018, at the
> Hanse Wissenschaftskolleg, in Delmenhorst, Germany. LSL is an
> open-source project enabling the synchronized streaming of time series
> data coming from different devices, such as EEG amplifiers, audio,
> video, eye tracking, keyboards, etc. LSL features near real-time access
> to data streams, time-synchronization, networking and centralized
> collection (https://github.com/sccn/labstreaminglayer).
>
> Key LSL developers and expert users have confirmed attendance. The
> workshop will provide a general introduction to LSL. We will present how
> LSL can be used for a multitude of different experimental setups, using
> a variety of experimental software, hardware and?operating systems. In a
> hands-on session, participants can learn to stream data from their own
> hardware or play with hardware provided by us and external partners. We
> will name pitfalls and discuss how to test and ensure the best possible
> timing accuracy when recording multimodal data. We will also provide a
> best practice guide and present different use cases of LSL. We will also
> use the workshop to discuss future software and hardware developments.
>
> Participants are invited to contribute to the workshop by presenting
> their LSL use cases.
>
> More information on the workshop will follow soon. For further
> enquiries, please contact: martin.bleichner at uol.de
> <mailto:martin.bleichner at uol.de>
>
> Best,
>
> Martin Bleichner
>
> --
> Dr. Martin Bleichner
> Neuropsychology    Lab
> Department of Psychology
> University of Oldenburg
> D-26111 Oldenburg
> Germany
>
> martin.bleichner at uni-oldenburg.de
> Tel.: +49 (0)441 - 798-2940
> http://www.uni-oldenburg.de/psychologie/neuropsychologie/team/martin-bleichner/
>
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>
> ------------------------------
>
> Message: 2
> Date: Wed, 10 Jan 2018 15:55:57 +0100
> From: Robert Oostenveld <r.oostenveld at donders.ru.nl>
> To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> Cc: Vincent Wens <vwens at ulb.ac.be>
> Subject: Re: [FieldTrip] question on cluster-based statistics and
>         source  localization
> Message-ID: <E1AC378D-E513-472B-A443-6E1439FE0A50 at donders.ru.nl>
> Content-Type: text/plain; charset="utf-8"
>
> Hi Vincent,
>
> Let me reply through the email list, where other people might learn something and/or want to chime in.
>
>> On 10 Jan 2018, at 13:22, Vincent Wens <vwens at ulb.ac.be> wrote:
>>
>> Dear Pr. Oostenveld,
>>
>> I am Vincent Wens, a physicist working in the MEG unit at Erasme Hospital, Brussels. We've been recently trying to play with the cluster-based statistics that you developed and included in Fieldtrip, but hit a difficulty in our analysis pipeline and I wondered if you would be so kind to take a few minutes and provide advice on this?
>
> The cluster-based statistics is a method for statistical inference, i.e. statistical decision making based on a hypothesis and estimated probability distribution. The hypothesis H0 states that the data can be exchanged (between conditions). If it is very unlikely that the data can be exchanged (under H0), we decide that the data must be different somehow. The clusters provide evidence for the data being different, but the clusters are not the difference itself. The tip of an iceberg above the sea level provides evidence for there being an iceberg, but the tip is not the iceberg itself.
>
> An important FAQ is this http://www.fieldtriptoolbox.org/faq/how_not_to_interpret_results_from_a_cluster-based_permutation_test
>
> Let me give the other commens in-line in your email below
>
>> Globally, my question is how to go from sensor-level cluster statistics results to the source space.
>>
>> More precisely: Assume we run the cluster statistics analysis on, say, N-channels time-frequency plots and obtain significance for the maximum cluster statistic.
>
> So you obtain evidence that the channel level data is different. That logically implies that the cortical activity is different. Note that the other way arround would not hold per see; there can be different activity in the brain without it showing up as a difference in the scalp data.
>
>> We thus find one (and possibly more) supra-threshold cluster(s) whose "spatio-spectral-temporal localization" can be assessed.
>
> You could look at the visible tip (i.e. the cluster), you could also take a broader approach and look at the phenomenom under the tip (the iceberg).
>
>> See for example the attached picture depicting the plot of those T-values within the significant cluster associated with an ERD. The next step would then be to source localize this,
>
> You would not localize the cluster (you already have it, it is at the channel level). You localize the cortical activity that causes the data to appear different at the channel level. It?s the part of the iceberg under the sea level that causes the tip to appear above sea level.
>
>> and our initial idea was to use the time and frequency region from this cluster as a prior on the time and frequency used for source projection. However the very complex shape of the cluster does not make this step so obvious. There are multiple possibilities that would come to mind, most of them absolutely ad-hoc, so I wondered your opinion on what would be the most rigorous, or at least least unacceptable way to go (or even just the most standard way, if there's one).
>
> Based on the resulls (the multiplot), you should wonder whether there is only a single feature in the brain that is different or whether there are multiple. The hypothesis you started with was ?is there any difference in this massive multiple-comparision space?? and the (only) answer you got to that question was ?yes?.
>
> You now have the question ?what is the difference?, which pertains to interpreting the data. That question has no binary answer and a statistical test based of a p-value being small enough (which gives you a "yes/no" answer) does not help.
>
> I cannot offer specific advice on how to interpret your data, but recommend that you consider whether your true quest is for ?the (one and only) effect? or ?the effects? that causes the data in the two conditions to be different. Of course you can argue that the effect(s) show at certain frequency ranges and/or latencies and/or locations, and therefore you may decide to look for the interpretation of the effect(s) at or around those parts of the cluster.
>
> In general (not any more for this dataset) it is worthwile to consider that narrow a-priori hypotheses provide more valuable and specific information. This is something that we often rely on in sequential studies, where in the 2nd study we don?t repeat the full hypothesis of the 1st study (e.g. ?is there any difference?), but a more specific sub-hypothesis that we generated on basis of the first study (e.g. is there a difference around this specific time-frequency range).
>
>> Thanks in advance for your invaluable help, and still my best wishes for the New Year.
>
> You?re welcome. Please follow up questions on the email discussion list.
>
> best regards,
> Robert
>
>
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>
> ------------------------------
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
> End of fieldtrip Digest, Vol 86, Issue 6
> ****************************************



From p.gaur at ulster.ac.uk  Tue Jan 16 15:26:53 2018
From: p.gaur at ulster.ac.uk (Gaur, Pramod)
Date: Tue, 16 Jan 2018 14:26:53 +0000
Subject: [FieldTrip] MEG UK 2018
Message-ID: <DB4PR06MB5855B4287245A8DBDC6C9DAB0EA0@DB4PR06MB585.eurprd06.prod.outlook.com>

Dear All,

The MEG UK 2018<http://meguk2018.co.uk/>, an annual conference focused on bringing together research groups working with magnetoencephalography (MEG) in the UK, will be held on  26-28 March 2018, at Ulster University, Magee Campus, Derry~Londonderry, Northern Ireland, UK. The conference is being organized by the Northern Ireland Functional Brain Mapping<https://www.ulster.ac.uk/research/institutes/computer-science/groups/intelligent-systems-research-centre/projects> (NIFBM) facility of the Intelligent Systems Research Centre (ISRC), a major research unit within the Faculty of Computing, Engineering and the Built Environment at Ulster's Magee campus.
More Details can be obtained from the MEG UK 2018 conference (http://meguk2018.co.uk/) website. We have secured very good deals for accommodation in local hotels as well as for local travel from Belfast airports by airporter.  Since number of places are limited, early registration and bookings are highly recommended.

Please register at the earliest to avoid disappointment.

Thanks,
MEG UK 2018



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From stephen.whitmarsh at gmail.com  Thu Jan 18 18:02:00 2018
From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh)
Date: Thu, 18 Jan 2018 18:02:00 +0100
Subject: [FieldTrip] question on cluster-based statistics and source
In-Reply-To: <CAL5FLdKFs0rOBwkY29xTi7GZ_Kotdmjmdu9RCzkg34kSB0B24Q@mail.gmail.com>
References: <CAL5FLdKFs0rOBwkY29xTi7GZ_Kotdmjmdu9RCzkg34kSB0B24Q@mail.gmail.com>
Message-ID: <CAFrxm=xt_cUZfL_MFbG8K27dKwOfmUaKg+mtmRsbMDRPHjhbEA@mail.gmail.com>

Hi there,

I just wanted to follow up and note that cluster-statistics are certainly
implemented for source-level reconstructed data (as a pointer to start,
see: http://www.fieldtriptoolbox.org/example/source_statistics)
I strongly suggest to use the functionality as intended in which most of
the typical user cases should be supported.

Best wishes,
Stephen




On 15 January 2018 at 22:04, Vahab Yousofzadeh <bioeng.yoosofzadeh at gmail.com
> wrote:

> Dear Vincent,
>
> For cluster correction at source space, you would need to trick the
> ft_prepare_neighbours because (as far as I know) it only works with
> sensor-space data - so you just need to update the pos. with those
> from the source model. Here's a piece of scripts:
>
> s = timePost; % timePost is the output of ft_timelockanalysis.
> s.grad.chanpos = headmodel_time.pos(headmodel_time.inside,:);
> s.grad.chanori = s.grad.chanpos;
> s.grad.chanunit(1:size(s.grad.chanpos,1)) = s.grad.chanunit(1);
> s.grad.chantype(1:size(s.grad.chanpos,1)) = s.grad.chantype(1);
> s.grad.tra    = ones(size(s.grad.chanpos,1),size(s.grad.tra,2));
> for i=1:size(s.grad.chanpos,1)
>     s.grad.label{i} = num2str(i);
>     s.label{i} = num2str(i);
>     s.grad.labelold =  num2str(i);
> end
> % prepare_neighbours determines what sensors may form clusters
> cfg_neighb.method   = 'distance';
> % cfg.method      = 'triangulation';
> neighbours          = ft_prepare_neighbours(cfg_neighb, s);
>
> %% inspecting random neighbours (#1200)
> neighbours2 = [];
> neighbours2 = neighbours(1200);
> % neighbours2.neighblabel = neighbours2.neighblabel(1:20);
> % plotting neighbours for inspection
> cfg            = [];
> cfg.neighbours = neighbours2;
> ft_neighbourplot_source(cfg, s);
>
> Now for cluster-correction, you need to have your source trials as
> inputs, and do something like:
>
> %% Cluster-correction
> cfg = [];
> cfg.parameter        = 'pow';
> cfg.dim              = sourcemodel.dim;
> cfg.method           = 'montecarlo';
> % cfg.statistic        = 'ft_statfun_depsamplesT';
> cfg.statistic        = 'depsamplesT';
> % cfg.statistic         = 'indepsamplesT';
> cfg.correctm         = 'cluster';
> % cfg.correctm         = 'fdr';
> cfg.clusteralpha     = 0.01;
> cfg.clusterstatistic = 'max';
> % cfg.correcttail = 'prob';
> cfg.tail             = 0;
> cfg.clustertail      = 0;
> cfg.alpha            = 0.05;
> cfg.numrandomization = 5000;
> cfg.neighbours      = ft_prepare_neighbours(cfg_neighb, s);
>
> ntrials                       = L;
> design                        = zeros(2,2*ntrials);
> design(1,1:ntrials)           = 1;
> design(1,ntrials+1:2*ntrials) = 2;
> design(2,1:ntrials)           = 1:ntrials;
> design(2,ntrials+1:2*ntrials) = 1:ntrials;
>
> cfg.design   = design;
> cfg.ivar     = 1;
> cfg.uvar     = 2;
> stat         = ft_sourcestatistics(cfg,Source1,Source2);
> stat.pos     = souremodel.pos;% keep positions for plotting later
>
> and for plotting stats,
>
> cfg              = [];
> cfg.voxelcoord   = 'no';
> cfg.parameter    = 'stat';
> % cfg.interpmethod = 'nearest';
> cfg.interpmethod = 'sphere_avg';
> statint  = ft_sourceinterpolate(cfg, stat, template_mri);
> cfg.parameter    = 'mask';
> maskint  = ft_sourceinterpolate(cfg, stat, template_mri);
>
> statint.mask = maskint.mask;
>
> atlas = ft_read_atlas('ROI_MNI_V4.nii');
>
> statint.coordsys  = 'mni';
> cfg               = [];
> cfg.method        = 'ortho';
> % cfg.method = 'slice';
> cfg.funparameter  = 'stat';
> cfg.maskparameter = 'mask';
> cfg.atlas         = atlas;
> cfg.location      = 'max';
> % cfg.funcolorlim   = [-5 5];
> cfg.funcolormap   = 'jet';
> % cfg.location = [x,y,z];
> ft_sourceplot(cfg,statint);
>
> Hope this helps, and let me know if you are running into issues.
>
> Cheers,
> Vahab
>
> On Wed, Jan 10, 2018 at 9:55 AM,  <fieldtrip-request at science.ru.nl> wrote:
> > Send fieldtrip mailing list submissions to
> >         fieldtrip at science.ru.nl
> >
> > To subscribe or unsubscribe via the World Wide Web, visit
> >         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
> >
> > You can reach the person managing the list at
> >         fieldtrip-owner at science.ru.nl
> >
> > When replying, please edit your Subject line so it is more specific
> > than "Re: Contents of fieldtrip digest..."
> >
> >
> > Today's Topics:
> >
> >    1. 2nd International LSL Workshop (27.9-28.9.2018) - Save    the
> >       Date (Martin Bleichner)
> >    2. Re: question on cluster-based statistics and source
> >       localization (Robert Oostenveld)
> >
> >
> > ----------------------------------------------------------------------
> >
> > Message: 1
> > Date: Wed, 10 Jan 2018 15:39:55 +0100
> > From: Martin Bleichner <martin.bleichner at uni-oldenburg.de>
> > To: lsl-l at mailman.ucsd.edu, eeglablist at sccn.ucsd.edu,
> >         fieldtrip at science.ru.nl
> > Subject: [FieldTrip] 2nd International LSL Workshop (27.9-28.9.2018) -
> >         Save    the Date
> > Message-ID: <27e861b5-5224-61c5-d02c-3b70140acba2 at uni-oldenburg.de>
> > Content-Type: text/plain; charset="utf-8"; Format="flowed"
> >
> > Dear colleagues,
> >
> > We are happy to announce the second international Lab Streaming Layer
> > (LSL) workshop, which will take place September 27 - 28, 2018, at the
> > Hanse Wissenschaftskolleg, in Delmenhorst, Germany. LSL is an
> > open-source project enabling the synchronized streaming of time series
> > data coming from different devices, such as EEG amplifiers, audio,
> > video, eye tracking, keyboards, etc. LSL features near real-time access
> > to data streams, time-synchronization, networking and centralized
> > collection (https://github.com/sccn/labstreaminglayer).
> >
> > Key LSL developers and expert users have confirmed attendance. The
> > workshop will provide a general introduction to LSL. We will present how
> > LSL can be used for a multitude of different experimental setups, using
> > a variety of experimental software, hardware and?operating systems. In a
> > hands-on session, participants can learn to stream data from their own
> > hardware or play with hardware provided by us and external partners. We
> > will name pitfalls and discuss how to test and ensure the best possible
> > timing accuracy when recording multimodal data. We will also provide a
> > best practice guide and present different use cases of LSL. We will also
> > use the workshop to discuss future software and hardware developments.
> >
> > Participants are invited to contribute to the workshop by presenting
> > their LSL use cases.
> >
> > More information on the workshop will follow soon. For further
> > enquiries, please contact: martin.bleichner at uol.de
> > <mailto:martin.bleichner at uol.de>
> >
> > Best,
> >
> > Martin Bleichner
> >
> > --
> > Dr. Martin Bleichner
> > Neuropsychology    Lab
> > Department of Psychology
> > University of Oldenburg
> > D-26111 Oldenburg
> > Germany
> >
> > martin.bleichner at uni-oldenburg.de
> > Tel.: +49 (0)441 - 798-2940
> > http://www.uni-oldenburg.de/psychologie/neuropsychologie/
> team/martin-bleichner/
> >
> > -------------- next part --------------
> > An HTML attachment was scrubbed...
> > URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/
> attachments/20180110/71ab956b/attachment-0001.html>
> >
> > ------------------------------
> >
> > Message: 2
> > Date: Wed, 10 Jan 2018 15:55:57 +0100
> > From: Robert Oostenveld <r.oostenveld at donders.ru.nl>
> > To: FieldTrip discussion list <fieldtrip at science.ru.nl>
> > Cc: Vincent Wens <vwens at ulb.ac.be>
> > Subject: Re: [FieldTrip] question on cluster-based statistics and
> >         source  localization
> > Message-ID: <E1AC378D-E513-472B-A443-6E1439FE0A50 at donders.ru.nl>
> > Content-Type: text/plain; charset="utf-8"
> >
> > Hi Vincent,
> >
> > Let me reply through the email list, where other people might learn
> something and/or want to chime in.
> >
> >> On 10 Jan 2018, at 13:22, Vincent Wens <vwens at ulb.ac.be> wrote:
> >>
> >> Dear Pr. Oostenveld,
> >>
> >> I am Vincent Wens, a physicist working in the MEG unit at Erasme
> Hospital, Brussels. We've been recently trying to play with the
> cluster-based statistics that you developed and included in Fieldtrip, but
> hit a difficulty in our analysis pipeline and I wondered if you would be so
> kind to take a few minutes and provide advice on this?
> >
> > The cluster-based statistics is a method for statistical inference, i.e.
> statistical decision making based on a hypothesis and estimated probability
> distribution. The hypothesis H0 states that the data can be exchanged
> (between conditions). If it is very unlikely that the data can be exchanged
> (under H0), we decide that the data must be different somehow. The clusters
> provide evidence for the data being different, but the clusters are not the
> difference itself. The tip of an iceberg above the sea level provides
> evidence for there being an iceberg, but the tip is not the iceberg itself.
> >
> > An important FAQ is this http://www.fieldtriptoolbox.
> org/faq/how_not_to_interpret_results_from_a_cluster-based_permutation_test
> >
> > Let me give the other commens in-line in your email below
> >
> >> Globally, my question is how to go from sensor-level cluster statistics
> results to the source space.
> >>
> >> More precisely: Assume we run the cluster statistics analysis on, say,
> N-channels time-frequency plots and obtain significance for the maximum
> cluster statistic.
> >
> > So you obtain evidence that the channel level data is different. That
> logically implies that the cortical activity is different. Note that the
> other way arround would not hold per see; there can be different activity
> in the brain without it showing up as a difference in the scalp data.
> >
> >> We thus find one (and possibly more) supra-threshold cluster(s) whose
> "spatio-spectral-temporal localization" can be assessed.
> >
> > You could look at the visible tip (i.e. the cluster), you could also
> take a broader approach and look at the phenomenom under the tip (the
> iceberg).
> >
> >> See for example the attached picture depicting the plot of those
> T-values within the significant cluster associated with an ERD. The next
> step would then be to source localize this,
> >
> > You would not localize the cluster (you already have it, it is at the
> channel level). You localize the cortical activity that causes the data to
> appear different at the channel level. It?s the part of the iceberg under
> the sea level that causes the tip to appear above sea level.
> >
> >> and our initial idea was to use the time and frequency region from this
> cluster as a prior on the time and frequency used for source projection.
> However the very complex shape of the cluster does not make this step so
> obvious. There are multiple possibilities that would come to mind, most of
> them absolutely ad-hoc, so I wondered your opinion on what would be the
> most rigorous, or at least least unacceptable way to go (or even just the
> most standard way, if there's one).
> >
> > Based on the resulls (the multiplot), you should wonder whether there is
> only a single feature in the brain that is different or whether there are
> multiple. The hypothesis you started with was ?is there any difference in
> this massive multiple-comparision space?? and the (only) answer you got to
> that question was ?yes?.
> >
> > You now have the question ?what is the difference?, which pertains to
> interpreting the data. That question has no binary answer and a statistical
> test based of a p-value being small enough (which gives you a "yes/no"
> answer) does not help.
> >
> > I cannot offer specific advice on how to interpret your data, but
> recommend that you consider whether your true quest is for ?the (one and
> only) effect? or ?the effects? that causes the data in the two conditions
> to be different. Of course you can argue that the effect(s) show at certain
> frequency ranges and/or latencies and/or locations, and therefore you may
> decide to look for the interpretation of the effect(s) at or around those
> parts of the cluster.
> >
> > In general (not any more for this dataset) it is worthwile to consider
> that narrow a-priori hypotheses provide more valuable and specific
> information. This is something that we often rely on in sequential studies,
> where in the 2nd study we don?t repeat the full hypothesis of the 1st study
> (e.g. ?is there any difference?), but a more specific sub-hypothesis that
> we generated on basis of the first study (e.g. is there a difference around
> this specific time-frequency range).
> >
> >> Thanks in advance for your invaluable help, and still my best wishes
> for the New Year.
> >
> > You?re welcome. Please follow up questions on the email discussion list.
> >
> > best regards,
> > Robert
> >
> >
> > -------------- next part --------------
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> > Desc: not available
> > URL: <http://mailman.science.ru.nl/pipermail/fieldtrip/
> attachments/20180110/dedffb0b/attachment.png>
> >
> > ------------------------------
> >
> > _______________________________________________
> > fieldtrip mailing list
> > fieldtrip at donders.ru.nl
> > https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
> >
> > End of fieldtrip Digest, Vol 86, Issue 6
> > ****************************************
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From urieduardo at gmail.com  Fri Jan 19 14:44:37 2018
From: urieduardo at gmail.com (=?UTF-8?Q?Uri_Eduardo_Ram=C3=ADrez_Pasos?=)
Date: Fri, 19 Jan 2018 14:44:37 +0100
Subject: [FieldTrip] Interpolation using Talairach atlas
Message-ID: <CADO6phi=rEuFOvJgmhoEUBJnDF+wTZeV7A8bLbA5RF4TkZxhEg@mail.gmail.com>

Dear fieldtrippers,

I'm following the Salzburg tutorial (
http://www.fieldtriptoolbox.org/tutorial/salzburg) but using only templates
(i.e., no subject MRIs) and the Talairach (with 'tal' coordinates) atlas
from AFNI.

However, when I run

    atlas =
ft_read_atlas('~/Documents/MATLAB/fieldtrip-20170618/template/atlas/afni/TTatlas+tlrc.HEAD');

    cfg=[];
    cfg.method='lcmv';
    cfg.grid=template_grid;
    cfg.grid.filter=sourceavg.avg.filter;
    cfg.vol=vol;
    sourcepreS1=ft_sourceanalysis(cfg, avgpre);
    sourcepstS1=ft_sourceanalysis(cfg, avgpst);

    cfg = [];
    cfg.parameter = 'avg.pow';
    cfg.operation = '((x1-x2)./x2)*100';
    S1bl=ft_math(cfg,sourcepstS1,sourcepreS1);

    templatefile =
'~/Documents/MATLAB/fieldtrip-20170618/external/spm8/templates/T1.nii';
    template_mri = ft_read_mri(templatefile);
    cfg              = [];
    cfg.voxelcoord   = 'no';
    cfg.parameter    = 'pow';
    cfg.interpmethod = 'nearest';
    source_int  = ft_sourceinterpolate(cfg, S1bl, template_mri);
    %%
    cfg=[];
    parcel = ft_sourceparcellate(cfg, source_int, atlas);

I get the following error

Index exceeds matrix dimensions.

Error in ft_sourceparcellate (line 172)
  fprintf('%d of the labeled positions are inside the brain\n',
  sum(source.inside(seg(:)~=0)));

This is probably due to the spm8 template having too few 'pos' values. Do
you know of other mri template that would work with the AFNI atlas?

Best regards,
Eduardo Ramirez, PhD student
University of Würzburg
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From tonyvazhangottu at gmail.com  Mon Jan 22 05:29:42 2018
From: tonyvazhangottu at gmail.com (TONY CHACKO)
Date: Mon, 22 Jan 2018 09:59:42 +0530
Subject: [FieldTrip] (no subject)
Message-ID: <CAC0bWAbyc0k2M3iV+7GJEheJ3JrRNbrc0Yn88+QLG-Gh=rJ8Zg@mail.gmail.com>

 Dear all,
I am a new comer in fieldtrip software for my eeg project , I'm having
basic doubts.
I want to show all the events on my continuous data without segmenting the
data
and also I need to show my data in 50s-100s time.also i need to see my
results in matlab plots

Please help
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From Mariam.Kostandyan at UGent.be  Mon Jan 22 12:11:52 2018
From: Mariam.Kostandyan at UGent.be (Mariam Kostandyan)
Date: Mon, 22 Jan 2018 11:11:52 +0000
Subject: [FieldTrip] error Conversion to struct in ft_prepare_neighbours
Message-ID: <1516619979417.866@UGent.be>

Dear all,

I am quite new to the FieldTrip. I want to use it to check for the inter-electrode distances using the ft_prepare_neighbours function. My script looks like this:

cfg.method        = 'distance';
cfg.neighbourdist = 4;
cfg.channel       = {'FP1', 'FP2', 'F7', 'F3', 'FZ', 'F4', 'F8', 'FT9', 'FC5', 'FT10', 'T7', 'C3', 'CZ', 'C4', 'T8', 'TP9', 'CP5', 'CP6', 'TP10', 'P9', 'P7', 'P3', 'PZ', 'P4', 'P8', 'P10', 'O1', 'OZ', 'O2'};
cfg.feedback      = 'yes';
cfg.elec  = {'FP1', 'FP2', 'F7', 'F3', 'FZ', 'F4', 'F8', 'FT9', 'FC5', 'FT10', 'T7', 'C3', 'CZ', 'C4', 'T8', 'TP9', 'CP5', 'CP6', 'TP10', 'P9', 'P7', 'P3', 'PZ', 'P4', 'P8', 'P10', 'O1', 'OZ', 'O2'};
cfg.elecfile = 'sub03_Mariam_cues.set';
neighbours = ft_prepare_neighbours(cfg, 'sub03_Mariam_cues.set');


When I run it I get error messages:


Error using struct
Conversion to struct from cell is not possible.

Error in ft_checkconfig (line 248)
  cfg.elec = ft_datatype_sens(struct(cfg.elec));

Error in ft_preamble_trackconfig (line 37)
cfg = ft_checkconfig(cfg, 'trackconfig', 'on');

Error in ft_preamble (line 85)
evalin('caller', full_cmd);

Error in ft_neighbourplot (line 65)
ft_preamble trackconfig


How can I fix it? I would appreciate any help.


Best,

Mariam


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

Mariam Kostandyan
PhD student
University of Gent
Department of Experimental Psychology
Henri Dunantlaan 2, 9000 Gent, Belgium
----------------------

Room 140.021
Tel.: +32 9 264 6398
E-mail: Mariam.Kostandyan at UGent.be<mailto:Mariam.Kostandyan at UGent.be>
E-mail: kostandyan.m at gmail.com<mailto:kostandyan.m at gmail.com>
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From jan.schoffelen at donders.ru.nl  Mon Jan 22 13:51:35 2018
From: jan.schoffelen at donders.ru.nl (Schoffelen, J.M. (Jan Mathijs))
Date: Mon, 22 Jan 2018 12:51:35 +0000
Subject: [FieldTrip] error Conversion to struct in ft_prepare_neighbours
In-Reply-To: <1516619979417.866@UGent.be>
References: <1516619979417.866@UGent.be>
Message-ID: <E3412ADA-DF6E-45AE-AF51-F28C0621D758@donders.ru.nl>

Dear Mariam,

Perhaps it will work if you remove the ‘elec’-field from the cfg.

Best wishes,
Jan-Mathijs

On 22 Jan 2018, at 12:11, Mariam Kostandyan <Mariam.Kostandyan at UGent.be<mailto:Mariam.Kostandyan at UGent.be>> wrote:

Dear all,

I am quite new to the FieldTrip. I want to use it to check for the inter-electrode distances using the ft_prepare_neighbours function. My script looks like this:

cfg.method        = 'distance';
cfg.neighbourdist = 4;
cfg.channel       = {'FP1', 'FP2', 'F7', 'F3', 'FZ', 'F4', 'F8', 'FT9', 'FC5', 'FT10', 'T7', 'C3', 'CZ', 'C4', 'T8', 'TP9', 'CP5', 'CP6', 'TP10', 'P9', 'P7', 'P3', 'PZ', 'P4', 'P8', 'P10', 'O1', 'OZ', 'O2'};
cfg.feedback      = 'yes';
cfg.elec  = {'FP1', 'FP2', 'F7', 'F3', 'FZ', 'F4', 'F8', 'FT9', 'FC5', 'FT10', 'T7', 'C3', 'CZ', 'C4', 'T8', 'TP9', 'CP5', 'CP6', 'TP10', 'P9', 'P7', 'P3', 'PZ', 'P4', 'P8', 'P10', 'O1', 'OZ', 'O2'};
cfg.elecfile = 'sub03_Mariam_cues.set';
neighbours = ft_prepare_neighbours(cfg, 'sub03_Mariam_cues.set');

When I run it I get error messages:

Error using struct
Conversion to struct from cell is not possible.

Error in ft_checkconfig (line 248)
  cfg.elec = ft_datatype_sens(struct(cfg.elec));

Error in ft_preamble_trackconfig (line 37)
cfg = ft_checkconfig(cfg, 'trackconfig', 'on');

Error in ft_preamble (line 85)
evalin('caller', full_cmd);

Error in ft_neighbourplot (line 65)
ft_preamble trackconfig

How can I fix it? I would appreciate any help.

Best,
Mariam

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

Mariam Kostandyan
PhD student
University of Gent
Department of Experimental Psychology
Henri Dunantlaan 2, 9000 Gent, Belgium
----------------------

Room 140.021
Tel.: +32 9 264 6398
E-mail: Mariam.Kostandyan at UGent.be<mailto:Mariam.Kostandyan at UGent.be>
E-mail: kostandyan.m at gmail.com<mailto:kostandyan.m at gmail.com>
_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From Heidi.SolbergOkland at mrc-cbu.cam.ac.uk  Mon Jan 22 14:15:58 2018
From: Heidi.SolbergOkland at mrc-cbu.cam.ac.uk (Heidi Solberg Okland)
Date: Mon, 22 Jan 2018 13:15:58 +0000
Subject: [FieldTrip] Reject trials based on standard deviation
Message-ID: <9327C18D1181184A833D66FF65A9D9E10139717943@wsr-ex-101.mrc-cbsu.local>

Dear Fieldtrippers,

I'm currently working on an MEG dataset and have so far done automatic rejection of bad channels using Maxfilter and then done ICA-based artefact reduction (eyeblinks and heartbeat) in MNE Python. I now have my data in Fieldtrip trial structures. What is left is to remove trials that are outliers/noisy because the subject moved/coughed/etc. I have tried to use ft_visinspect with variance as metric, but the issue I have is that the variance is displayed in actual units (e.g. 1e10^23) rather than in terms of standard deviations. This is problematic, as my trial rejection will be based on my subjective decisions that some trials look like outliers and not others. What I would like instead is to just do something like "discard trials where the amplitude is more than X standard deviations above or below the mean", which is reproducible. Is this way of rejecting trials implemented in FT? I have seen the tutorial on automatic artefact rejection, but it looks more like something that would be useful for removing e.g. eyeblinks.

Best wishes,
Heidi


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

Heidi Solberg Økland
PhD candidate, Language group

Tel: 01223 273721
MRC Cognition & Brain Sciences Unit
University of Cambridge
15 Chaucer Road
Cambridge
CB2 7EF

Web: http://www.mrc-cbu.cam.ac.uk<http://www.mrc-cbu.cam.ac.uk/>

Social media:
[facebook-flat-logo-01]<https://en-gb.facebook.com/MRCCBU/>   [twiiter-flat-logo-02] <https://mobile.twitter.com/mrccbu?lang=en>

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From Mariam.Kostandyan at UGent.be  Mon Jan 22 14:22:16 2018
From: Mariam.Kostandyan at UGent.be (Mariam Kostandyan)
Date: Mon, 22 Jan 2018 13:22:16 +0000
Subject: [FieldTrip] error Conversion to struct in ft_prepare_neighbours
In-Reply-To: <E3412ADA-DF6E-45AE-AF51-F28C0621D758@donders.ru.nl>
References: <1516619979417.866@UGent.be>,
 <E3412ADA-DF6E-45AE-AF51-F28C0621D758@donders.ru.nl>
Message-ID: <1516627803115.4133@UGent.be>

Dear Jan-Mathijs,


I guess it partially worked since it started reading the .set file but still outputed an error:


>>  cfg.method        = 'distance';
cfg.neighbourdist = 4;
cfg.channel       = {'FP1', 'FP2', 'F7', 'F3', 'FZ', 'F4', 'F8', 'FT9', 'FC5', 'FT10', 'T7', 'C3', 'CZ', 'C4', 'T8', 'TP9', 'CP5', 'CP6', 'TP10', 'P9', 'P7', 'P3', 'PZ', 'P4', 'P8', 'P10', 'O1', 'OZ', 'O2'};
cfg.feedback      = 'yes';
cfg.elecfile = 'sub03_Mariam_cues.set';
neighbours = ft_prepare_neighbours(cfg, 'sub03_Mariam_cues.set');
reading electrodes from file 'sub03_Mariam_cues.set'
Attempt to reference field of non-structure array.

Error in ft_prepare_neighbours (line 176)
    [dataidx, sensidx] = match_str(data.label, label);


Is it the .set file that has electrodes as a non-structure array?


Best,

Mariam


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

Mariam Kostandyan
PhD student
University of Gent
Department of Experimental Psychology
Henri Dunantlaan 2, 9000 Gent, Belgium
----------------------

Room 140.021
Tel.: +32 9 264 6398
E-mail: Mariam.Kostandyan at UGent.be<mailto:Mariam.Kostandyan at UGent.be>
E-mail: kostandyan.m at gmail.com<mailto:kostandyan.m at gmail.com>
________________________________
От: fieldtrip-bounces at science.ru.nl <fieldtrip-bounces at science.ru.nl> от имени Schoffelen, J.M. (Jan Mathijs) <jan.schoffelen at donders.ru.nl>
Отправлено: 22 января 2018 г. 13:51
Кому: FieldTrip discussion list
Тема: Re: [FieldTrip] error Conversion to struct in ft_prepare_neighbours

Dear Mariam,

Perhaps it will work if you remove the 'elec'-field from the cfg.

Best wishes,
Jan-Mathijs

On 22 Jan 2018, at 12:11, Mariam Kostandyan <Mariam.Kostandyan at UGent.be<mailto:Mariam.Kostandyan at UGent.be>> wrote:

Dear all,

I am quite new to the FieldTrip. I want to use it to check for the inter-electrode distances using the ft_prepare_neighbours function. My script looks like this:

cfg.method        = 'distance';
cfg.neighbourdist = 4;
cfg.channel       = {'FP1', 'FP2', 'F7', 'F3', 'FZ', 'F4', 'F8', 'FT9', 'FC5', 'FT10', 'T7', 'C3', 'CZ', 'C4', 'T8', 'TP9', 'CP5', 'CP6', 'TP10', 'P9', 'P7', 'P3', 'PZ', 'P4', 'P8', 'P10', 'O1', 'OZ', 'O2'};
cfg.feedback      = 'yes';
cfg.elec  = {'FP1', 'FP2', 'F7', 'F3', 'FZ', 'F4', 'F8', 'FT9', 'FC5', 'FT10', 'T7', 'C3', 'CZ', 'C4', 'T8', 'TP9', 'CP5', 'CP6', 'TP10', 'P9', 'P7', 'P3', 'PZ', 'P4', 'P8', 'P10', 'O1', 'OZ', 'O2'};
cfg.elecfile = 'sub03_Mariam_cues.set';
neighbours = ft_prepare_neighbours(cfg, 'sub03_Mariam_cues.set');

When I run it I get error messages:

Error using struct
Conversion to struct from cell is not possible.

Error in ft_checkconfig (line 248)
  cfg.elec = ft_datatype_sens(struct(cfg.elec));

Error in ft_preamble_trackconfig (line 37)
cfg = ft_checkconfig(cfg, 'trackconfig', 'on');

Error in ft_preamble (line 85)
evalin('caller', full_cmd);

Error in ft_neighbourplot (line 65)
ft_preamble trackconfig

How can I fix it? I would appreciate any help.

Best,
Mariam

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

Mariam Kostandyan
PhD student
University of Gent
Department of Experimental Psychology
Henri Dunantlaan 2, 9000 Gent, Belgium
----------------------

Room 140.021
Tel.: +32 9 264 6398
E-mail: Mariam.Kostandyan at UGent.be<mailto:Mariam.Kostandyan at UGent.be>
E-mail: kostandyan.m at gmail.com<mailto:kostandyan.m at gmail.com>
_______________________________________________
fieldtrip mailing list
fieldtrip at donders.ru.nl<mailto:fieldtrip at donders.ru.nl>
https://mailman.science.ru.nl/mailman/listinfo/fieldtrip

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From stephen.whitmarsh at gmail.com  Mon Jan 22 17:06:47 2018
From: stephen.whitmarsh at gmail.com (Stephen Whitmarsh)
Date: Mon, 22 Jan 2018 17:06:47 +0100
Subject: [FieldTrip] Reject trials based on standard deviation
In-Reply-To: <9327C18D1181184A833D66FF65A9D9E10139717943@wsr-ex-101.mrc-cbsu.local>
References: <9327C18D1181184A833D66FF65A9D9E10139717943@wsr-ex-101.mrc-cbsu.local>
Message-ID: <CAFrxm=ymv4xFdT+X5tLwz3T2yPwaAFEVaQxyi+_ZXxXpneDNnA@mail.gmail.com>

Hi Heidi,

I guess you could just e.g. zscore your data before the (semi)automatic
artefact *detection*, and apply those artefact definitions on your original
data in the artefact *rejection*.

Cheers,
Stephen

On 22 January 2018 at 14:15, Heidi Solberg Okland <
Heidi.SolbergOkland at mrc-cbu.cam.ac.uk> wrote:

> Dear Fieldtrippers,
>
>
>
> I’m currently working on an MEG dataset and have so far done automatic
> rejection of bad channels using Maxfilter and then done ICA-based artefact
> reduction (eyeblinks and heartbeat) in MNE Python. I now have my data in
> Fieldtrip trial structures. What is left is to remove trials that are
> outliers/noisy because the subject moved/coughed/etc. I have tried to use
> ft_visinspect with variance as metric, but the issue I have is that the
> variance is displayed in actual units (e.g. 1e10^23) rather than in terms
> of standard deviations. This is problematic, as my trial rejection will be
> based on my subjective decisions that some trials look like outliers and
> not others. What I would like instead is to just do something like “discard
> trials where the amplitude is more than X standard deviations above or
> below the mean”, which is reproducible. Is this way of rejecting trials
> implemented in FT? I have seen the tutorial on automatic artefact
> rejection, but it looks more like something that would be useful for
> removing e.g. eyeblinks.
>
>
>
> Best wishes,
>
> Heidi
>
>
>
>
>
> ----------------------------------------------------------
>
>
>
> Heidi Solberg Økland
>
> PhD candidate, Language group
>
>
>
> Tel: 01223 273721
>
> MRC Cognition & Brain Sciences Unit
>
> University of Cambridge
> 15 Chaucer Road
> Cambridge
>
> CB2 7EF
>
>
>
> Web: http://www.mrc-cbu.cam.ac.uk
>
>
>
> Social media:
>
> [image: facebook-flat-logo-01] <https://en-gb.facebook.com/MRCCBU/>   [image:
> twiiter-flat-logo-02] <https://mobile.twitter.com/mrccbu?lang=en>
>
>
>
> _______________________________________________
> fieldtrip mailing list
> fieldtrip at donders.ru.nl
> https://mailman.science.ru.nl/mailman/listinfo/fieldtrip
>
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From rosemary.southwell.14 at ucl.ac.uk  Mon Jan 22 21:50:38 2018
From: rosemary.southwell.14 at ucl.ac.uk (Rosy Southwell)
Date: Mon, 22 Jan 2018 20:50:38 +0000
Subject: [FieldTrip] Source activation vs baseline on MNE output
Message-ID: <CADxBig50beESaNN6of6Zx7cLfbR8h9-9wDcgenGVHhWPywsK5A@mail.gmail.com>

Dear Fieldtrip Community,

I am working on EEG source analysis for auditory evoked responses to long
(3-second) stimuli. My data are evoked responses baseline corrected in the
interval [-1 0], and am interested in source activity in the window [0.5
1.5] relative to stimulus onset.

I have used MNE to estimate source activity over a latency of [-1 1.5]; see
code [1] below. Although I have two conditions of interest which I will
later contrast using ft_statfun_depsamplesT, I am first interested in
seeing which areas are activated by each condition. In order to extract
sound-evoked activity from ongoing activity, I would like to visualise the
source activity for each condition as an activation relative to baseline,
expressed as a T-statistic. I have ensured that my baseline window and
activation window are of equal duration and non-overlapping.

I have attempted to use ft_statfun_actvsblT for computing this statistic
(see code [2] below), but receive the error "Inappropriate dimord for the
statistics function FT_STATFUN_ACTVSBLT." From reading the function, I
understand that this method requires time-frequency data with
dimord 'chan_freq_time'. However my data is evoked, time-domain only.

My questions are
a) Is it even appropriate to express such "time-dimension-only" source
results as an activation relative to baseline?

b) If so, how would I best compute this in Fieldtrip?

c) if not, do you have a recommendation of how to quantify the degree of
activation for a single condition?

All the best,

Rosy Southwell
PhD Candidate
Chait Lab
Ear Institute, University College London.

%% CODE
% [1.] source analysis
  cfg = [];
            cfg.method = 'mne';
            cfg.latency = [-1 1.5];
            cfg.elec = elec;
            cfg.grid = sourcemodel_cortex;
            cfg.headmodel = headmodel;
            cfg.mne.prewhiten = 'yes';
            cfg.mne.lambda    = 3;
            cfg.mne.scalesourcecov = 'yes';
            [source] = ft_sourceanalysis(cfg, data);

% [2.] T-statistic of activation vs baseline

cfg=[];
cfg.method      = 'analytic';
cfg.statistic   = 'ft_statfun_actvsblT';
cfg.parameter   = 'pow';
cfg.correctm    = 'no';
cfg.alpha       = 0.025;
cfg.tail        = 0;
nsubj=20;
cfg.design(1,:) = [ones(1,nsubj) 2*ones(1,nsubj)];
cfg.design(2,:) = [1:nsubj 1:nsubj ];
cfg.ivar        = 1; % row of design matrix that contains independent
variable (the conditions)
cfg.uvar        = 2; % row of design matrix that contains unit variable (in
this case: subjects)

stat_RvR = ft_sourcestatistics(cfg,source_ac_all{:},source_bl_all{:});
% where source_ac_all, source_bl_all are 1*20 cell array of structs for
each subject
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From luca.turella at unitn.it  Tue Jan 23 18:27:59 2018
From: luca.turella at unitn.it (Luca Turella)
Date: Tue, 23 Jan 2018 18:27:59 +0100
Subject: [FieldTrip] Postdoctoral position - MEG and Visual Imagery @ CIMeC
 University of Trento, Italy
Message-ID: <CALvsWdV99L2NJ=FrVacWkWqrLNV+J2Hmmmn3Mynwb23QyNXNgw@mail.gmail.com>

A postdoctoral position will be available soon at the Center for Mind/Brain
Sciences (CIMeC, http://www.cimec.unitn.it/en) at the University of Trento
(Italy). The topic of investigation will cover the neural dynamics
underlying visual imagery adopting MEG. The position is supported by the
ERC Advanced Grant “Perceptual Awareness in the Reorganizing Brain” (PI
Carlo Marzi).


Candidates should have a Ph.D. degree in a field related to Cognitive
Neuroscience or related areas. The ideal candidate should have previous
experience in EEG/MEG data acquisition and analysis and good programming
skills in Matlab and Fieldtrip. Knowledge of the Italian language is not
required.


The salary will be proportional to the level of experience and the starting
date of the appointment is negotiable, but within the next 6 months.
Applications will be considered until the position is filled. The contract
will have a duration of 1 year, and can be extended by another year.
Applications should be sent to angelika.lingnau at rhul.ac.uk, including a CV,
statement of research interests, and contact details of two referees.
Potential candidates are also encouraged to send informal inquiries to
angelika.lingnau at rhul.ac.uk.


CIMeC offers an international and vibrant research setting with access to
state-of-the-art neuroimaging methodologies, including a research-only MR
scanner, MEG, EEG and TMS, as well as behavioural, eye tracking and motion
tracking laboratories. English is the official language of the CIMeC, where
a large proportion of the faculty, post-docs and students come from a wide
range of countries outside of Italy.


The University of Trento consistently ranks as a top Italian university in
both national Research Assessment Evaluations (RAE) and University Surveys.
In the latest RAE, the University of Trento as a whole ranks 2nd among
medium-sized universities.


-- 
Luca Turella, PhD
Assistant Professor
CIMeC - Center for Mind/Brain Sciences
University of Trento
Mattarello (TN), Via Delle Regole 101
Tel.+39 0461-28 3098
http://www.unitn.it/cimec



Legal Disclaimer
This electronic message contains information that is confidential. The
information is intended for the use of the addressee only. If you are not
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note that any disclosure, copy, distribution or use of the contents of this
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Questo messaggio Email contiene informazioni confidenziali riservate ai
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From jorn at artinis.com  Fri Jan 26 16:07:02 2018
From: jorn at artinis.com (=?iso-8859-1?Q?J=F6rn_M._Horschig?=)
Date: Fri, 26 Jan 2018 16:07:02 +0100
Subject: [FieldTrip] ARTscientific: NIRS symposium in Thailand
Message-ID: <007101d396b7$5256acf0$f70406d0$@artinis.com>

Dear fieldtrippers,

 

On June 27-30, we from Artinis Medical Systems are organizing a
scientific symposium revolving around near-infrared spectroscopy (NIRS)
for neuro- and sports research. We would like to invite you to register
for the ARTscientific symposium in the beautiful and luxurious Wyndham
Grand Phuket Kalim Bay in Thailand. In this 2.5-day symposium, we will
create an open platform for both experienced and novice researchers to
share experiences, discuss NIRS and enjoy several hands-on workshops. We
are arranging an interesting line-up of keynote speakers, who will
provide valuable insight into NIRS and brain research. 

 

Next to providing a NIRS playground we will organize poster and
presentation sessions, so you will get the chance to present and discuss
your research. To sum it all up social wining and dining will be
organized in one of the most extraordinary places in Thailand.

The registration: Get an early bird ticket

The amount of rooms in the hotel are limited, so get yours quickly and
benefit until February 28th from the early bird discount! Additional
information on e.g. the program workshops or the location can be found
on our website: http://www.artinis.com/artscientific-2018/.  

If you have any questions, suggestions or requests for the symposium,
please do not hesitate to contact us at symposium at artinis.com.

 

With best regards,

The Artinis team

 

--
Jörn M. Horschig, PhD
Software Engineer & Project Leader NeuroGuard XS

  

A  Einsteinweg 17
    6662PW Elst 
    The Netherlands
T  +31 481 350 980
I    <http://www.artinis.com/> www.artinis.com

The information in this e-mail is confidential and intended solely for
the person to whom it is addressed. If this message is not addressed to
you, please be aware that you have no authorization to read this e-mail,
to copy it, to furnish it to any person other than the addressee, or to
use or misuse its content in any way whatsoever. Should you have
received this e-mail by mistake, please bring this to the attention of
the sender, after which you are kindly requested to destroy the original
message.

 

 <http://eepurl.com/bTlr_L> Sign up for our NIRS newsletter

 

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From i.charest at bham.ac.uk  Fri Jan 26 16:25:41 2018
From: i.charest at bham.ac.uk (Ian Charest (School of Psychology))
Date: Fri, 26 Jan 2018 15:25:41 +0000
Subject: [FieldTrip] Postdoc position on the neurocognitive mechanisms of
 conscious access
Message-ID: <97F95B166F2157409BE1EC68292F25AC436368A6@EX13.adf.bham.ac.uk>

Dear FieldTrip discussions list,

see below for details of a 3 year ERC funded postdoctoral position in Birmingham, UK.


https://goo.gl/6PuHwj


Best wishes,

Ian Charest
Lecturer, School of Psychology,
University of Birmingham, UK
iancharest.com

_________________________

Advert:
The School of Psychology at the University of Birmingham is looking for a bright and motivated Post-doctoral scientist to join the Charest Laboratory (iancharest.com). The Postdoc position to be filled is part of a project recently funded by a European Research Council Starting Grant entitled: "Spatio-Temporal Attention and Representation Tracking: the precise neural architecture of conscious object perception" (START).

The Project:
START is an ambitious programme of work that will make use of cutting-edge multivariate pattern analyses (MVPA) techniques to reveal the brain mechanisms that are critical for consciously perceiving visual objects in tasks that manipulate conscious access to visual information. The ability to consciously recognise faces, objects, or sounds is crucial for adaptive behaviour and survival. Yet, how our conscious experience of the world emerges in our brain remains unknown. The overall aim of the START programme is to fill an important gap in our understanding of consciousness by elucidating the neural underpinnings of conscious access. How does the brain select relevant information among distractors, and keep this information in mind? Why does our ability to consciously recognise salient objects sometimes fail under pressure and exhibit variability across days and individuals? START will try to address these important questions by precisely tracking where in the brain and when in time the representations critical for conscious access are established, by using novel approaches of Representational Similarity Analyses which combines the strengths of EEG, fMRI, and Deep Convolutional Neuronal Networks. This project will provide new insights on the precise spatio-temporal dynamics of conscious access, the mechanisms governing it, and the idiosyncratic subtleties behind the meanderings of consciousness.

The candidate:
The successful candidate will have (or be in the process of obtaining) a PhD in cognitive neuroscience or a related field. Previous experience with psychophysical tasks that manipulate conscious access in vision is desirable. Given the nature of the project, experience with fMRI, EEG/MEG and data analysis is required. Experience in using matlab or python (and Psychtoolbox or PsychoPy) is also a requirement. The successful applicant will have experience with multivariate pattern analyses (Representational Similarity Analysis, Fisher linear discriminants, etc) of neuroimaging data. This post will require designing experiments, collecting and analysing data associated with the project, preparing manuscripts for publication, presenting results at national and international conferences and the possible supervision of research assistants and students.

The School:
The School of Psychology at the University of Birmingham (http://www.birmingham.ac.uk/schools/psychology/index.aspx<https://www.findaphd.com/common/clickCount.aspx?theid=92145&type=184&DID=148&url=http%3a%2f%2fwww.birmingham.ac.uk%2fschools%2fpsychology%2findex.aspx>) is one of the largest and most successful in the UK, currently ranked in the top 5 Schools in the country (REF 2014). The School is soon to move to new accommodation in the form of a fully refurbished, purpose-designed space and a new-build Centre for Human Brain Health that will house our new MRI, MEG, EEG, NIRS, sleep lab, and the recently appointed Chair in Translational Neuroscience. The University of Birmingham is an equal opportunities employer. The School of Psychology has a Bronze Athena SWAN award and strives to maintain a flexible and supportive environment that enables its staff to flourish.

For informal enquiries about the project please contact Dr. Ian Charest (i.charest at bham.ac.uk). Please follow the following link for more details and to apply: https://goo.gl/6PuHwj


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From dr.nivethida at gmail.com  Wed Jan 31 10:47:36 2018
From: dr.nivethida at gmail.com (nivethida t)
Date: Wed, 31 Jan 2018 15:17:36 +0530
Subject: [FieldTrip] Opening for PhD position at Department of Neurology,
	NIMHANS, India
Message-ID: <CAMBnzx4eSs5XCenx8Njh3f69Ynv9-w3Zmj5nzx1tcPzikveqQg@mail.gmail.com>

Applications are invited for a prospective PhD candidate at the Department
of Neurology, National Institute of Mental Health and Neuro Sciences
(NIMHANS), Bengaluru, India.


The candidate will work on a Wellcome Trust/DBT India Alliance funded
project involving Transcranial magnetic stimulation (TMS), EEG and MEG
studies in patients with Parkinson’s disease.


Candidates with strong technical background (Master’s degree in basic
sciences/ engineering/ neuroscience) and prior knowledge of MATLAB are
eligible to apply. Experience with EEG/MEG signal processing is a plus.


Admission to the PhD program at the institute is subjected to the candidate
qualifying the NIMHANS online entrance test and interview. The entrance
test may be waived if the applicant has cleared any of the
DBT/UGC/CSIR/ICMR qualifying exams.


For further details on the PhD admission procedure, please refer to the
prospectus on the institute’s website (
http://www.nimhans.ac.in/sites/default/files/NIMHANS_Prospectus%202018-19%20Final%20%281%29.pdf)
.


Application deadline for July admission: 4th February, 2018



-- 
Dr. Nivethida Thirugnanasambandam, MBBS, MTech, PhD
Extramural Research Faculty,
Wellcome Trust/DBT India Alliance Clinical Research Fellow (Intermediate),
Department of Neurology,
National Institute of Mental Health and Neuro Sciences (NIMHANS),
Hosur Road, P B 2900, Bengaluru 560 029,
Karnataka, India
Ph: +91-80-26995143
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From r.oostenveld at donders.ru.nl  Wed Jan 31 12:44:49 2018
From: r.oostenveld at donders.ru.nl (Robert Oostenveld)
Date: Wed, 31 Jan 2018 12:44:49 +0100
Subject: [FieldTrip] MEG/EEG FieldTrip toolkit course in Nijmegen:
	pre-registration now open
Message-ID: <24B65D6F-F33A-4981-BEE2-CB06C3DC8327@donders.ru.nl>

Dear all,

On 9-13 April 2018 we will host the yearly “Advanced MEG/EEG data analysis toolkit" at the Donders Institute in Nijmegen. The course is aimed at researchers that have already performed  MEG/EEG data acquisition and have a good understanding of their own experimental design. Furthermore, we expect that you know the basics of MATLAB and that you already have some experience with MEG/EEG preprocessing and analysis. 

This intense 5-day toolkit course will teach you advanced MEG and EEG data analysis methods. We will cover preprocessing, frequency analysis, source reconstruction, connectivity and various statistical methods. The toolkit will consist of a number of lectures, followed by hands-on sessions in which you will be tutored through the complete analysis of a MEG data set using the FieldTrip toolbox. There will be plenty of opportunity to interact and ask questions about your research and data. On the final day you will have the opportunity to work on your own dataset under supervision of skilled tutors.

We can only host a limited number of participants. From past experience we expect the course to be oversubscribed, hence we will start with pre-registration. The final selection of the participants will be based on the motivation, background experience and research interests that are provided in the registration form. The deadline for pre-registration is March 1, 2018.

More information, including the link to register and last years program can be found at http://www.ru.nl/donders/agenda/donders-tool-kits/vm-tool-kits/donders-meg-eeg-tool-kit/ <http://www.ru.nl/donders/agenda/donders-tool-kits/vm-tool-kits/donders-meg-eeg-tool-kit/>. Please note that this year we added an extra day to have more hands-on time and to better deal with EEG specific topics. 

best regards,
Robert

-----------------------------------------------------------
Robert Oostenveld, PhD

Senior Researcher & MEG Physicist
Donders Institute for Brain, Cognition and Behaviour
Radboud University, Nijmegen, The Netherlands

Visiting Professor
NatMEG - the Swedish National MEG facility
Karolinska Institute, Stockholm, Sweden

tel.: +31 (0)24 3619695
e-mail: r.oostenveld at donders.ru.nl
web: http://www.ru.nl/donders
skype: r.oostenveld
-----------------------------------------------------------

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From davide.tabarelli at unitn.it  Wed Jan 31 17:56:45 2018
From: davide.tabarelli at unitn.it (Davide Tabarelli)
Date: Wed, 31 Jan 2018 17:56:45 +0100
Subject: [FieldTrip] Subject level non parametric statistics for coherence
	with external stimulus
Message-ID: <FD9AA208-D908-4CA2-A3AD-CD9AE61E5EC7@unitn.it>

Dear Fieldtrip users,

I’m trying to calculate a statistical map for coherence differences between two conditions at a source level for a single subject, but I have some problems with channel combinations.

I have calculated common LCMV filters for my subject and computed source time series, that I have stored in a ft_timelock structure.
I have also successfully calculated coherence between the stimulus function and all dipoles for both conditions A and B using ft_freqanalysis and ft_connectivityanalysis.
Now I would like to compute a non parametric statistical map for the coherence difference between A and B using the approach of Maris & Schoffelen & Fries 2007.

I’m trying to use the “ft_statfun_indepsamplesZcoh” statistics as follow:

cfg=[]; 
cfg.parameter = 'fourierspctrm’; 
cfg.frequency = 5.5;
cfg.statistic = 'ft_statfun_indepsamplesZcoh’; 
cfg.method = 'montecarlo’; 
cfg.numrandomization = 1000;
cfg.design = design;
stat = ft_freqstatistics(icfg, fourier_conditionA, fourier_conditionA);

I realized this will compute the statistics for all the possible combination of channels, thus between stimulus and sources and between all pairs of sources … that is computationally non effordable (at least for me).

There is a way to tell ft_freqstatistics to use only some combination when computing the significance of coherence differences?

Or am I doing something wrong?

Thank you all !

D.

—
Davide Tabarelli, Ph.D.
Center for Mind Brain Sciences (CIMeC)
University of Trento,
Via delle Regole, 101
38123 Mattarello (TN)
Tel: +39 (0)461 283644
Italy