Dear brainstorm community, I’m using imaginary coherence NxN with EEG data, 32 electrodes. The output is fantastic, so first of all thanks for your gigantic work, but I’m finding some problems in the interpretation.
Chance are is more usful if I describe first my purpose in the research and then the problem I’m finding. I want to compare the changes in the coherence, between 2 conditions, in the frequency bands(delta, theta, alpha, beta). I excluded purposely gamma frequency.
Whe I run the function, I must put a maximun frequency resolution, so if I put 2Hz, and I want to study coherence until 30Hz, I will have 15 different output. Is there a way to group the data in the classic frequency bands( delta, theta, alpha, beta), or should I check manually basing on the maximun frequency band resolution?
When I export data, it is possible to export only the coherence matrix, but this is a matrix NxN channels, without the information about which frequency coherence is being reported. Is there a way to export the information about coherence each maximum frequency resolution step?
Moreover, it is possible to see how coherence changes on the scalps, each step of the maximun frequency band resolution, only when 1xN coherence is plotted, but there is not the possibility to do with NxN. Given that I cannot report in a paper the coherence of 1xN plot for each channel, how could I get an image of the global changes in the coherence for each frequency bands?
I know that this question are not very precise, and that in general the metrics of the connectivity data are very complex, but I hope you could give me some suggestions so that I could work on it.