Hello AFNI experts!
I have two basic and quick questions,
I am not used to working with human datasets and I am surprised with the processing time with afni_proc.py
I have human BOLD images at a resolution of 2.8 and afni_proc.py takes more than 5h per subject and my computer has good characteristics.
Is that normal?
afni_proc.py -subj_id imapt1s080 -script Imapt1s080/proc.imapt1s080 -scr_overwrite -out_dir imapt1s080.results -blocks despike tshift align tlrc volreg blur mask regress -dsets Rest_BOLD.nii.gz -copy_anat anatSS.imapt1s080.nii -anat_has_skull no -tcat_remove_first_trs 5 -regress_RSFC -volreg_align_to first -volreg_align_e2a -volreg_tlrc_warp -align_opts_aea -epi_strip 3dAutomask -cost lpc+zz -giant_move -check_flip -tlrc_base MNI152_2009_template_SSW.nii.gz -tlrc_NL_warp -tlrc_NL_warped_dsets anatQQ.imapt1s080.nii anatQQ.imapt1s080.aff12.1D anatQQ.imapt1s080_WARP.nii -regress_motion_per_run -regress_bandpass 0.01 0.1 -blur_size 4 -regress_est_blur_detrend yes -regress_run_clustsim no -execute
Should I decrease the resolution of the BOLD prior to afni_proc to speed up the process? Losing spatial resolution is not a big deal in my study.
Also, to calculate mALFF, the result is strongly dependent on the mask used. Is there a way with afni_proc to add this mask in -regress_RSFC?
Thank you!
Clément
