Hello dear AFNI gurus,

Following along this question and it's answers: Create ventricle mask in MNI space

I intend to do a resting state analysis without Freesurfer (that takes waaaay tooooo muuuuch time) and want to use MNI152 template. So I'm going through example 11b method (that ventricle extraction method seems okay to me, who am I to judge).

First, I will be running @SSwarper:

@SSwarper -input Session_1_t2_tse_tra_192_0_2.nii.gz \
-subid duodenumreyiz \
-odir  anat_warped \
-base  MNI152_2009_template_SSW.nii.gz \
-giant_move

Then, I'm resampling the ventricle mask in the suma_MNI152_2009 folder that I downloaded a while back. Now the question is: what should be the master dataset as above thread shows that using -dxyz method might give unintended results. I used preprocessed resting state of another subject, who was preprocessed using a different afni_proc.py script but aligned to MNI152 via @SSwarper and sampled to 3x3x3 mm^3. So the bulk of this question is this: does that make sense?

3dresample -master sub-10159.rest.nii -prefix ventricle_mask.nii -inset aparc+aseg_REN_vent.nii.gz

Then, do the preprocessing (slightly modified version of 11b):

afni_proc.py \
-blocks despike tshift align tlrc volreg blur mask scale regress \
-script proc.duodenumreyiz \
-subj_id duodenumreyiz \
-out_dir duodenumreyiz.preprocessed \
-scr_overwrite \
-copy_anat $subjpath/anat/anat_warped/anatSS.duodenumreyiz.nii \
-dsets $subjpath/func/Session_2_RSTpre_V01_R01_0_12.nii \
-tcat_remove_first_trs 2 \
-align_opts_aea -cost lpc+ZZ \
-tlrc_base $tpath/$btemplate \
-tlrc_NL_warp \
-tlrc_NL_warped_dsets \
$subjpath/anat/anat_warped/anatQQ.duodenumreyiz.nii \
$subjpath/anat/anat_warped/anatQQ.duodenumreyiz.aff12.1D \
$subjpath/anat/anat_warped/anatQQ.duodenumreyiz_WARP.nii \
-volreg_align_to MIN_OUTLIER \
-volreg_align_e2a \
-volreg_tlrc_warp \
-volreg_warp_dxyz 3 \
-mask_segment_anat yes \
-mask_segment_erode yes \
-mask_import Tvent ventricle_mask.nii \
-mask_intersect Svent CSFe Tvent \
-mask_epi_anat yes \
-regress_motion_per_run \
-regress_ROI_PC Svent 3 \
-regress_ROI_PC_per_run Svent \
-regress_make_corr_vols WMe Svent \
-regress_anaticor_fast \
-regress_censor_motion 0.2 \
-regress_censor_outliers 0.05 \
-regress_apply_mot_types demean deriv \
-regress_est_blur_epits \
-regress_est_blur_errts \
-regress_run_clustsim yes
-html_review_style pythonic

Is this a legitimate method as preprocessing?

Thanks and best regards,
Yasir