Hi Giovanni,
- Yes, this sounds correct. Some comments:
- Instead of using the “downsample to atlas” process, which is more designed for full cortical segmentations, you could use the process “Extract > Scouts time series”, and then use the signals as the input of the connectivity process.
- In the Desikan-Killiany atlas, the regions are too large to be functionally homogeneous: averaging the source activity over large regions causes most of the interesting signal to be lost…
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All those methods are bivariance. All the pairs of signals are processed independently, the number of regions does not influence the results you get. We know that this is not the correct way to do this type of analysis, multivariate approaches are in development as well.
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All the functions related with the functional connectivity analysis in Brainstorm are still undocumented: incomplete theory, in development, not tested, subject to future changes.
The Granger causality estimation particularly needs some more work to identify what is really significant in the results we obtain. Correlation and coherence are simpler metrics that can lead to less random results.
If you still want to use this method, yes, use the current default value. -
For this: I don’t know… Coherence and correlation are working well, some people are probably using them now, but I have no reference to give you.
Cheers,
Francois