Interhemispheric Connectivity

[tourette95]

Hi there!
I'm wondering if it is possible in BS to compute just the interhemispheric connectivity (like coherence or iCoh) or to specify the electrode pairs to be computed.

I mean, is there an option to compute just O1-O2, T3-T4, and P3-P4 in a single process?

Thanks in advance

[Francois]

Yes, you can use the Process2 tab and select the same files on both sides.
The processes "AxB" would let you select any number of channels independently on each side.

[tourette95]

Hi!
I tried it but it did not work:

I selected the same file (imported raw) on both sides, then I click run --> Processes --> Connectivity --> Amplitude Envelope Correlation (AEC) AxB but then I had just one electrode to compute AEC 1x19. What I want to compute is interhemispheric AEC (I mean between electrode pairs: O1 with O2, T4 with T3, etc).

I know that if I compute NxN AEC I will get these values too, but I don't want a big connectivity matrix cause many variables can affect results and give no significant results, I would like to get a connectivity matrix with just interhemispheric electrode pairs, is that possible?

Thanks!

[Francois]

Ah indeed, AxB lets you do only 1xN across separate files, so not a solution for you.

Then I don't think there is any solution other than computing the full NxN matrix and keeping only the values that are interesting for you.
If you really don't want to see the other values, you can explicitly set them to zero in the matrix. You'd need to edit the TF field in the connectivity file manually:
https://neuroimage.usc.edu/brainstorm/Tutorials/Scripting#Custom_processing

How the Corr matix is saved?

Hi Junpeng, In the processes “Correlation 1xN”, “Correlation NxN” and “Correlation AxB”, the measure that is used is the same. In the NxN case, it just repeats it for all the pairs of signals, there is no covariance of the other signals involved. The results are the same as the non-diagonal values returned by the corrcoef function with only two signals in input. The full code of the function and some additional explanations are available here: Cheers, Francois

PTE: How is the connectivity matrix stored?

Hi Sebastian, To get the connectivity matrix correctly formatted, you can do the following: Read the file timefreq_connect…mat into the variable TfMat, or right-click > File > Export to Matlab > “TfMat” R = bst_memory(‘GetConnectMatrix’, TfMat); The matrix R is the connectivity matrix [signalsA x signalsB x Frequencies] The frequency bins are described in the TfMat.Freqs: R(:,:,1) is frequency TfMat.Freqs(1) For details on the algorithm, see directly the process function process_compress_sym…