Hello,
There are a couple of issues you need to consider before this comparison.
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First of all, try to compare the PSD of raw EEG, scouts’ time series for the surface, and scouts’ time series for the volume. If you apply the same approach for surface and volume source reconstructions, you should at least see a similar pattern for surface and volume.
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Here, you have computed 1 x N connectivity, in which you need to specify one scout as the source. Since you wanna compare surface with volume, your source is not the same in two cases, besides the thing that all sinks are also different. So, if you want to perform a comparison in this way, select the scouts as the source, in which they have a high overlap between surface and volume.
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At this time, I recommend using magnitude-squared coherence instead of imaginary coherence to you.
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Please note that coherence is a measure of pairwise correlation in the frequency domain. This measure is divided by the power of each variable. I do agree that if you see an alpha peak in all channels, you expect a high coherence between all pairwise channels, but don’t forget the correlation and normalization.
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My observation on resting-state MEG (comapring networks computed by the signal on sensors and surface scouts) is that you should see a somehow similar pattern (especially in alpha band).
Hope it works for you,
Hossein
(Brainstorm Software Collaborator)