And, the attached is the output files from this script. I am not sure if I can find the pre-processed but non-statistically analyzed data among these outputs or should run another script. Please let me know.
afni_proc.py creates a commented (!) processing script automatically, so you can look through that for the exact outputs of things you want.
as part of its processing, afni_proc.py commands including running an AFNI program called gen_ss_review_scripts.py to go through and look for certain outputs, and then make a dictionary of them. You can see a description of all important dsets/info that it currently looks for with:
gen_ss_review_scripts.py -show_uvar_dict
That will allow you to find what “keys” in the dictionary you would be interested in, and you can then look in the file created by that program for your specific processing, which will be called: out.ss_review_uvars.json.
You can then see what specific file was created for that “key”.
you can look at the files in time reversed order:
ls -ltr RESULTS_DIRECTORY
and the largest files near the end are probably the processed time series you want: probably either errts* or fitts* files are what you are looking for (depends on whether you are performing resting state or task data, respectively).
Just to add on to Paul’s comment, note that the pb0* datasets are the EPI going through the stages of preprocessing. So the last one, pb04scale is the input to the regression (as you can see in the 3dDeconvolve command in the proc script). It should match the later created all_runs dataset, since there seems to be just one run. If you want to see tissue contrast, it might be worth looking at the volreg dataset.
As Paul noted, it is worth looking through the proc script a bit.
rick
The
National Institute of Mental Health (NIMH) is part of the National Institutes of
Health (NIH), a component of the U.S. Department of Health and Human
Services.
