Just for the sake of an example, let's say that I have a two subject hyperscanning EEG data file that contains 64 channels (32 from each subject). To process source estimation, one would process this file in duplicate, and block out the channels of the opposite subject. Epoching on an event of interest would be performed and any bad trials would be marked accordingly.
Once source kernals are calculated for each subject, let's say I extract scouts time series for the whole recording for all areas in the Mindboggle atlas. I think it makes 62 areas? That would mean 124 areas for both subjects combined.
Then, one could 'import into the database' a triplicate (or "dummy") of the original hyperscanning file, and manually modify the channel file to have 124 channels (one has to be careful to modify all relevant portions of the channel file, but it is not that difficult). One could then manually copy the scouts time series obtained from processing the first two files, and paste this into the 124ch modified triplicate file.
From Brainstorm's perspective, we would now have a 124 ch file full of sensor/electrode-level time series data. But in fact, it would be scouts time series data from two subjects. This data could then be epoched as appropriate, with bad trials marked based on our initial processing of subjects-separate data. Then, we could run Brainstorm's sensor level coherence analysis. But the results returned would actually be intra and inter-brain coherence for our extracted scouts.
Obviously, creation of the dummy file invites opportunity for human error, and thus would require extreme caution. But I think it is very interesting and worth doing, albeit a little cumbersome. Of course if there was a built in way to achieve what I described above, that would be highly desirable. However, I don't think anyone has developed it on the Brainstorm platform yet, right?
I have not yet actually attempted the above yet. It is still very conceptual and experimental. I'm very keen to hear your and anyone else's thoughts on this topic.