EEG resting state - connectivity

I am phd student in cognitive science (cognitive modeling).

I have some questions:

  1. My research is about finding some features on resting state EEG of two groups .

2)I have 200 Seconds resting state EEG for each case.after pre-processing I want to choose 5 segment(block) of EEG data with 10 second duration for each.

3)then I want to measure ROI(Scouts) activity by source localization using brainstorm.

  1. then I want to find effective connectivity between ROI(sources) for each segment.

what do you suggest ? GC or transfer entropy or something else ? can I do that in brainstorm?

I tested PTE & GC N*N in brainstorm

5)after that I want to compare all case/segments in two groups

which statistic method do you suggest ? Can i do that in brainstorm?

6)Do you suggest another method? Is there any research paper that used brainstorm for measuring connectivity ?

@hossein27en @Sylvain ?

Dear sir

Anything new about this post?

I would use Amplitude Envelope Correlation: it has a correction for volume conduction (the ortogonalize signals option) and it has probed to be robust and better than many functional connectivity measures.

for statistical analysis I suggest you the two groups permutation test,
sure you can do in BS everything you wrote in last post


thank you for your respond.
What about Effective connectivity ?
Is it suitable for resting state EEG?

Yes, in that case you can use Granger's Causality, but I think it dependes what you want to know, there is another measures that give the information flow direction like Imaginary Coherence, but I'm not sure about how useful or valid is to get the causality in resting state...

Maybe another BS members can help..

@hossein27en @Sylvain ?

1 Like

Hi Omid, @omidsefat

As another member said, Amplitude Envelope Correlation is a pretty good method to compute the Resting-State connectivity when you have recordings that are not short (like 500ms). For your case, it looks great.

To compute the Effective connectivity there are other approaches. Imaginary and Lagged coherence are suitable algorithms plus Granger Causality. All of those measures are already in Brainstorm.

Granger usually works well when you don't have too many channels.

In case you want to construct sources, please don't compute them by absolute values of dipoles since it damages the frequency characterization of signals. A simple average should work well.

Hi Hossein,

just curious, but when you say "recordings that are not short (like 500 ms)", are you saying that 500 ms is okay for AEC, or that it's considered to be too short for AEC?

Thank you! : )