There are much more expert people to reply to this than me, but in the interest of time zonal considerations, I'll mention that "afni_proc.py" is about to become your new best friend.

In short, you can use afni_proc.py to enter a compact set of options and build a whole script that calls lots of AFNI commands and populates thems with all the necessary command options/procotols/etc. Then, you can run the resulting script to process your data in one fell swoop. The benefit is that you have: an efficient way to enter what you want, and a written record of *exactly* what was run (as the script itself). At the end, Rick has also put in a number of wrappers to help with automatic viewing of helpful things like subject motion and regressors.

Please type:
$ afni_proc.py
or
$ afni_proc.py -h_view
into a terminal and see the wonderful possibilities that exist for building a RSFC pipeline. I believe that examples 9, 9b, 10 and 10b are all modern examples, depending on what you want to use as regressors, RSFC parameter output, and final space (template vs native).

--pt

--pt