[Eeglablist] IC connectivity analysis in between-subject domain

[Knyzev GG]

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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