[FieldTrip] seed based SOURCE connectivity analysis betweenGroups - GA, plotting and statistics

Schoffelen, J.M. (Jan Mathijs) jan.schoffelen at donders.ru.nl
Thu Oct 25 08:49:44 CEST 2018


Hi Conny,

Again, could you please spill more details?
-what is the connectivity metric you want to compute?
-what do you mean with ‘cfg.refindx seems not to do anything’?
-what have you done in terms of diagnostics yourself? have you looked into the code with breakpoints etc.?

Jan-Mathijs

On 24 Oct 2018, at 23:42, Conny Quaedflieg <cornelia.quaedflieg at uni-hamburg.de<mailto:cornelia.quaedflieg at uni-hamburg.de>> wrote:

Dear Jan-Mathijs,

Thank you for your quick reply.

@1R Indeed ft_connectivityanalysis on  individual dipole positions (PCC). Cfg.refindx’ seems not to do anything, are there other options to run a seed-based connectivity analysis?
@R2 We indeed performed source-reconstruction for each subject on a subject-specific grid, that maps onto a template grid in spatially normalized space.
    I constructed a GA of the individual data and would like to plot these on a standard cortical sheet / brain surface.

Best
Conny

Van: Schoffelen, J.M. (Jan Mathijs)<mailto:jan.schoffelen at donders.ru.nl>
Verzonden: woensdag 24 oktober 2018 10:16
Aan: FieldTrip discussion list<mailto:fieldtrip at science.ru.nl>
Onderwerp: Re: [FieldTrip] seed based SOURCE connectivity analysis betweenGroups - GA, plotting and statistics

Hi Conny,

You are a bit short on the details, so it is hard to give to-the-point feedback.

@1 this depends on the type of connectivity metric you have in mind. You mention the ‘cfg.refindx’ so I assume that you want to use ft_connectivityanalysis. Also, do you use ‘parcellated’ source data, or is the data defined on individual dipole positions?

@2 this works best if your individual subject source models can be easily compared, e.g. according to

http://www.fieldtriptoolbox.org/tutorial/sourcemodel#performing_group_analysis_on_3-dimensional_source-reconstructed_data

This allows for averaging/statistics at the low-number-of-sources (before interpolation) and saves a lot of memory.

Best wishes,

Jan-Mathijs




On 23 Oct 2018, at 00:18, Quaedflieg, Conny (PSYCHOLOGY) <conny.quaedflieg at maastrichtuniversity.nl<mailto:conny.quaedflieg at maastrichtuniversity.nl>> wrote:


Dear Fieldtripers,

I’m trying to compare 2 groups (n=40 per group) on SOURCE connectivity data using a seed (based on an atlas).
Based on the help function this should be possible using cfg.refindx.

Though, the analysis looks exactly the same with and without the refindx specified.

I would be really grateful with help on the following

  1.  Ideas how to run a seed based source analysis
  2.  How can I combine source data of several pp’s and plot the grand averages and run statistics over it?

I tried this with ft_sourcegandaverage though when interpolating the data to the MRI I get error messages that the data is too large and that it wil take too long.

Best

Conny Quaedflieg, PhD
Assistant Professor
Department of Clinical Psychological Science
Faculty of Psychology and Neuroscience
UNS 40, Room A3731a
043-883164




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