Hi, I am using EEG 128 channels data for EEG connectivity analysis. I have computed sensor level connectivity (coherence) using Matlab. Now I want to compute EEG source connectivity to compare with the computed sensor level connectivity results of coherence. My data is long and continues, having 128 channels and sampling rate 250 per second. I do not have fMRI scan for any subject. I studied the brainstorm tutorials but still need help.
How I can load my EEG data into brainstorm?
What are the steps I should take to compute source connectivity?
How I can export the estimated sources into Matlab to apply coherence?
I appreciate if anyone can brief me about how to do it. Thanks
How I can load my EEG data into brainstorm?
Start by following all the introduction tutorials using the example dataset, at least until #23.
Then follow the EEG and Epilepsy tutorial (also using the example dataset, not your own data).
Please get back to us if you have more specific questions about data import.
What are the steps I should take to compute source connectivity?
Estimate the sources, then use one the connectivity processes either between multiple ROIs (NxN) or between one seed and the rest of the brain (1xN).
The connectivity tutorial is under construction, but already contains a lot of useful information:
https://neuroimage.usc.edu/brainstorm/Tutorials/Connectivity
How I can export the estimated sources into Matlab to apply coherence?
The files generated by Brainstorm are already Matlab .mat files, readily available from your personal Matlab scripts. There are some graphical and scripting tools to make it faster to load the Brainstorm structures into Matlab:
https://neuroimage.usc.edu/brainstorm/Tutorials/Scripting#Custom_processing