At the moment, this information is input via a command-line interface, or with an optional question/answer session (afni_proc.py -ask_me). Eventually, a GUI will become available (but not yet).

• • • At the moment, this information is input via a command-line interface, or with an optional question/answer session (afni_proc.py -ask_me). Eventually, a GUI will become available (but not yet).
  • Once afni_proc.py has all the necessary information, it produces a tcsh (T-shell) script that contains all the data processing steps. This script can be easily executed and the end result will be a functional/statistical dataset, as well as numerous datasets produced from the intermediary steps.

• Before we go any further, start the processing script :

• • we will discuss it more, soon
  • under AFNI_data4, execute the script containing the afni_proc.py command
  • • this will create the processing script, proc.sb23.blk
  • execute the proc.sb23.blk script, as recommended by afni_proc.py
  • • takes ~4 minutes on my laptop
    • • cd AFNI_data4
      • tcsh s1.afni_proc.block
      • tcsh -x proc.sb23.blk |& tee output.proc.sb23.blk
  • note that one could subsequently run s10.surface.analysis to analyze the data in the surface domain (which takes ~37 minutes on my laptop)