Fig. 1.

Schematic features of afni_proc.py. (A) Primary data inputs and descriptors are highlighted in green. The processing is managed hierarchically: first the user selects and orders the desired blocks (or major stages), and then for each can specify zero, one, or more options. The array of hot colors highlights which options are associated with which block, by matching them: the “tshift” block label with the “-tshift_opts_ts” option, etc. Note that the start of the option name typically matches the block, as well. (B) The afni_proc.py command creates a fully commented processing pipeline (“proc script”), so that the user has detailed understanding and provenance of all the steps of the analysis. (C) An example workflow that uses afni_proc.py for a single-subject analysis, utilizing some preliminary programs beforehand and incorporating automatically generated data checks and quality control features at the end. This can simply be looped over all subjects in a data collection.