I see. I guess I might have processed the 2 time series in a single afni_proc.py command, and then split them at the end. That way, they would share the same volreg volume, and should be essentially aligned and in the same space at the end. Even without that, the should be pretty similar (unless the sessions were very different, brightness patterns and coverage changed, etc.).

Note that in afn_proc.py masks are *generated* and used for a couple things, but typically not *applied* to the datasets themselves---so there is data everywhere, and most programs have a "-mask .." option when needed to provide one.

In terms of concatenating the runs during processing, that could be chosen either way. But typically I might not mask the time series themselves.

That being said, it is good to be aware of the practical coverage of the data---if you have data with extremely low SNR and effectively no real signal in it in a region, do you want to include it in your matrix? I am not sure. You could include it, and hopefully it would just be noisy/zero, or you could choose to exclude some of the Power atlas because of how it overlaps (or where it doesn't) with your mask.

--pt