[Eeglablist] IC connectivity analysis in between-subject domain

[Makoto Miyakoshi]

Dear Tim, Knyzev, Robert, and the list,

I would also be very interested in giving a pressure to Tim on this issue.

Makoto


2013/3/28 robert coben <drcoben at gmail.com>

> I would also be very interested in hearing a discussion about ways of
> assessing coherence via eeglab. Specifically, related to multivariate forms
> of surface coherence and types of source coherence. Thank you,
>
> Rob Coben, PhD
>
>
> On Mar 27, 2013, at 9:45 PM, Knyzev GG <knyazev at physiol.ru> wrote:
>
> Dear list members,****
>
> I would really appreciate a help in applying a connectivity analysis to IC
> time courses in multi-subject  samples. So far SIFT is only applicable to
> single subject data. So I have three questions to (principally) Tim Mullen
> and all interested or knowledgeable members:****
> 1.       Are there some extensions or developments of SIFT that allow
> multi-subject analysis but are not yet included in the current eeglab. If
> the answer is yes, is it possible to obtain them in the near future?****
> 2.       Please refer me to publications that applied connectivity
> measures in a multi-subject design to ICs derived individually in each
> subject. My google scholar search yielded only publications that used
> either a single-subject design (e.g., Mullen et al., 2011) or group ICA.**
> **
> 3.       If there are no positive answers to the two above questions,
> could you please explain how such analysis could be implemented in
> principle. After applying either clustering procedure or some other
> approach, like measure projection, in a multi-subject sample we have a
> number of IC clusters. One cluster may include several components from one
> subject and no one from another. There have been recently a discussion on
> the least how to perform and interpret statistical tests on such clusters.
> My understanding of this discussion is that there are no so far a simple
> answer. But here I have another concern. How to obtain cluster-related time
> course which would allow to extract cluster-related phase information which
> is needed for connectivity analysis. Suppose one wants to do a network
> graph analysis on connectivity measures treating each cluster as a node. Of
> course one may just average the time courses of all cluster’s ICs, but I
> wonder what such averaged across several ICs belonging to different
> subjects time course would represent and how meaningful would be its phase
> information?****
>
> Thank you for your time.****
>
> Best regards,****
> Gennady Knyazev****
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-- 
Makoto Miyakoshi
Swartz Center for Computational Neuroscience
Institute for Neural Computation, University of California San Diego
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