AFNI Class Notes 08/30/19:

Example:
set subj = CAJe_110
set top_dir = /mnt/nfs2/users/alans/CAJe/${subj}BRIKS
afni_proc.py -subj_id $subj \

-script proc.$subj -scr_overwrite \

-blocks despike tshift align tlrc volreg blur mask scale \

-despike_opts_3dDes -ignore 2 \

-copy_anat $top_dir/${subj}+orig \

-dsets $top_dir/${subj}MS+orig.HEAD \

-tcat_remove_first_trs 2 \

-tlrc_base MNI_avg152T1+tlrc \

-volreg_align_to MIN_OUTLIER \

-volreg_align_e2a \

-volreg_tlrc_warp \

-blur_in_automask \

-blur_to_fwhm -blur_size 6.0

Running afni_proc.py produces: proc.CAJe_110 (txt)

This can be run to create the needed files. Primarily:

File	Description	Blocks	Notes
pb00.CAJe_110.r01.tcat+orig	combined or cut original functional scan	tcat	auto: controlled above by -tcat_remove_first_trs 2
pb01.CAJe_110.r01.despike+orig	3dDespiked file	despike	option: helps bad data muchly
pb02.CAJe_110.r01.tshift+orig	3dTshift	tshift	option: suggested for event based
pb03.CAJe_110.r01.volreg+tlrc	Fulling aligned file	align, tlrc, volreg	required: This is a key step using align_epi_anat.py
pb04.CAJe_110.r01.blur+tlrc	blurred file	blur	option: since we used -blur_in_automask -blur_size 4.0 this is blur "to"
pb05.CAJe_110.r01.scale+tlrc	scaled	scale	option: preps for 3dREMLfit
CAJe_110_ns+tlrc	anatomical underlay	tlrc	option: we are in tlrc not mni due to : -tlrc_base TT_N27+tlrc
outcount_rall.1D	3dToutcount file	outcount	auto: data quality signal. vital to observe to assess signal
dfile_rall.1D	volreg residuals	volreg	This is the useful in regression later and data quality now.
out.mask_ae_overlap.txt	outcome of alignments	align	Gives info of anat v. epi: %(A \ B) gives the epi outside or anat and if this is really high that is bad news.
out.mask_ae_dice.txt	outcome of alignments	align	quick measure of overlap less detailed but can be of use.

plot your timeseries quality files with 1dplot outcount_rall.1D, etc.

You can also get an estimate of movement with SumMove