Hi all
I have an EEG signal that recorded during eyes open and eyes closed state. (sampling rate 256, 64 Channels)
I would like to do an analysis to find which regions of the brain have connectivity during this task in frequency 4-8.
that’s why first of all I removed EOG artifacts then used a bandpass filter for extracting the frequencies 4-8 Hz from EEG.
I did computing head model, computing noise covariance and computing sources [2016].
But I have a problem when I want to do connectivity analysis. I get some errors when I want to use coherence analysis.
I’ve read the tutorial about connectivity but this part is not explained enough.
Would you please tell me what should I do step by step for observing which regions of the brain have connectivity in frequencies 4-8 Hz during my task.
I will so appreciate if you could help me
Hello
Please copy-paste here the full error message you get.
Thanks
Francois
I’m sorry, there are still no proper tutorials for the connectivity analysis.
With the options you selected, you are trying to compute a connectivity measure for 15171x15171 pairs of signals (all the source signals). For the coherence frequency resolution you selected, this requires the creation in memory of a few matrices of about 200Gb. This is not something you can do on any computer.
If you want to compute a full connectivity network for the whole brain, you need to decrease the size of the data you generate by using regions of interest instead of all the source signals. Ideally, you should base all your computation based on your hypothesis, which should be something relatively specific (for instance “the connectivity between region A and region B is higher in condition 1 than in condition 2”), and compute only the measures you really need.
Then you can compute this one single measure for all the subjects and all the conditions, and test for significance with non-parametric tests.
Thanks a lot, dear Francois
So I should read ROI selection tutorial now.