Thank you so much for the simple explanation!
For now, I have edited my afni_proc.py based on example 9b: resting state analysis with ANATICOR, as follows:
afni_proc.py -subj_id $subj \
-script proc.$subj -scr_overwrite \
-blocks despike tshift align tlrc volreg blur mask regress \
-copy_anat $top_dir/anat_shft.nii \
-dsets $top_dir/run1_shft+orig.HEAD \
-tcat_remove_first_trs 3 \
-align_opts_aea -giant_move \
-tlrc_base MNI_avg152T1+tlrc \
-tlrc_opts_at -OK_maxite \
-volreg_align_to MIN_OUTLIER \
-volreg_align_e2a \
-volreg_tlrc_warp \
-blur_size 4.0 \
-mask_epi_anat yes \
-regress_anaticor \
-regress_censor_motion 0.2 \
-regress_bandpass 0.01 0.1 \
-regress_apply_mot_types demean deriv \
-regress_motion_per_run \
-regress_est_blur_errts \
-regress_run_clustsim no
However, I face another problem.. now I am encountering an error with 3dDeconvolve.
++ 3dDeconvolve extending num_stimts from 0 to 118 due to -ortvec
++ 3dDeconvolve: AFNI version=AFNI_19.1.23 (Jun 24 2019) [64-bit]
++ Authored by: B. Douglas Ward, et al.
++ STAT automask has 74515 voxels (out of 271633 = 27.4%)
++ Skipping check for initial transients
++ Input polort=4; Longest run=492.5 s; Recommended minimum polort=4 ++ OK ++
++ Number of time points: 197 (before censor) ; 42 (after)
+ Number of parameters: 123 [123 baseline ; 0 signal]
** ERROR: *** Censoring has made regression impossible :( ***
** FATAL ERROR: 3dDeconvolve dies: Insufficient data (42) for estimating 123 parameters
It appears that there are too many time points being censored (looking at the motion_censor.1D file, there does seem to be quite a bit of motion in fMRI, so I suppose that makes sense), but I am not sure why there are so many parameters for resting fMRI. Where would I go from here?