Dear AFNI experts,

I am pre-processing data that is concatenated across 3 runs (RANTI.1, 2, 3) using the script below. Although I would like the data aggregated across runs for my subsequent GLTs, I would like to pre-process the data independent (ie apply motion correction and alignment separately for each run) as runs were sometimes separated by a few minutes/movement due to re-positioning of external equipment (eye movement system) between runs. Is this possible? If so, are there specifications I should indicate within a single pre-processing script, or should I develop separate scripts for each run and then concatenate after pre-processing has been completed?

Thanks very much,
Kathryn

afni_proc.py -subj_id $subj \
-script proc.$subj -scr_overwrite \
-blocks tshift align tlrc volreg blur mask scale regress \
-copy_anat $anat_dir/anatSS.$subj.nii \
-dsets \
$epi_dir/pb00.$subj.fMRI.RANTI.1.nii \
$epi_dir/pb00.$subj.fMRI.RANTI.2.nii \
$epi_dir/pb00.$subj.fMRI.RANTI.3.nii \
-tcat_remove_first_trs 0 \
-align_opts_aea -ginormous_move -deoblique on -cost lpc+ZZ \
-volreg_align_to MIN_OUTLIER \
-volreg_opts_vr -heptic \
-volreg_align_e2a \
-volreg_tlrc_warp -tlrc_base /usr/bin/abin/MNI152_2009_template_SSW.nii.gz \
-tlrc_NL_warp \
-tlrc_NL_warped_dsets \
$anat_dir/anatQQ.$subj.nii \
$anat_dir/anatQQ.$subj.aff12.1D \
$anat_dir/anatQQ.$subj_WARP.nii \
-blur_size 4.0 \
-regress_stim_times \
$stim_dir/Catch_Cue_N_Onset.1D \
$stim_dir/Catch_Cue_R_Onset.1D \
$stim_dir/Task_N.1D \
$stim_dir/Task_R.1D \
-regress_stim_labels \
Catch_Cue_N_Onset Catch_Cue_R_Onset Task_N Task_R \
-regress_basis 'GAM' \
-regress_censor_motion 0.5 \
-regress_apply_mot_types demean deriv \
-regress_motion_per_run \
-regress_opts_3dD \
-gltsym 'SYM: Catch_Cue_R_Onset -Catch_Cue_N_Onset' -glt_label 1 \
Cue_Reward-Cue_Neutral \
-gltsym 'SYM: Task_R - Task_N' -glt_label 2 \
Task_Reward-Task_Neutral \
-regress_make_ideal_sum sum_ideal.1D \
-regress_est_blur_epits \
-regress_est_blur_errts