Hi Maya,
You could run afni_proc.py on the EPI datasets, just telling it to do the scale and regress blocks:
afni_proc.py -subj_id phant.SR \
-dsets phantom*.nii \
-blocks scale regress \
-tcat_remove_first_trs 2
To get more QC out, include the volreg block, even if it should not do much.
Also, here I request running @radial_correlate on the tcat and regress data (that could be added above).
afni_proc.py -subj_id phant.QC \
-dsets phantom*.nii \
-blocks volreg scale regress \
-tcat_remove_first_trs 2 \
-volreg_compute_tsnr yes \
-radial_correlate_blocks tcat regress
Or, just let it pretend to analyze as simple resting state. This would also include tshift and blur blocks, along with censoring. Hopefully your phantom isn't too prone to motion...
ap_run_simple_rest.tcsh -epi phantom*.nii -run_proc
Does that seem reasonable?
- rick