[Eeglablist] Question about the use of ICA and GC

[Salim Al-wasity]

Dears
Have a nice day. Kindly I have a question regarding ICA:
I have EEG data of (44 channels X 294000 samples)

1- I applied the ICA to separate the noise and
find the ICs which are belong to brain activities.
2- I used the Granger Causality (GC) in SIFT to
find the connectivity between these ICs and discover which component influence
which. However I am not sure about the results that I have got.

My question is that If I used ICA to decompose the
EEG signal into their sources (hint: the decomposed ICs is much less than the
actual brain sources), theoretically these ICs would be independent, and the
use of GC would be useless since the latter algorithm search for the dependence
across ICs?
Or the ICA will minimize the mutual information, and the separated components will not be ~100% independent, therefore each component has more that one source,
and GC  can find some influence across these components for the remaining not separated sources. 
 
Your cooperation is highly appreciated
 
Yours
Salim Al-Wasity
PhD student
Rehabilitation Centre
Biomedical Engineering Department-School of Engineering
University of Glasgow
Glasgow-United Kingdom
+44 742 371 4444
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