AFNI Class Notes 8/23/19:

afni_proc.py

To see all examples:

afni_proc.py | grep "      Example "

To review an example:

afni_proc.py | grep -A20 "Example 6"

tcat: combine runs (first) [see 3dTcat]

despike: truncate spikes in each voxel's time series (after tcat before tshift)

-despike_mask: allow Automasking in 3dDespike (default none)

-despike_opts_3dDes OPTS... : specify additional options for 3dDespike

-despike_opts_3dDes -nomask -ignore 2

ricor: RETROICOR - removal of cardiac/respiratory regressors [skipping]

tshift: slice time alignment (before align/tlrc/volreg)[see 3dTshift] data is collected asyncronously   and then aligned

-tshift_interp [-quintic(default),-Fourier,-cubic]

-tshift_opts_ts -tpattern alt+z

align: alignment between anat and EPI (before tlrc/volreg)

Uses: align_epi_anat.py can provide details such as

-align_opts_aea -cost lpa -giant_move -resample off

Default: use the EPI base from the EPI alignment choice unless

-align_epi_ext_dset : you provide a external dataset for alignment

-volreg_base_dset : you provide a external dataset for volreg

-align_epi_strip_method 3dAutomask

tlrc: figure out alignment between anat and template(after align, before volreg)

-tlrc_base TT_N27+tlrc (using @auto_tlrc)

-tlrc_NL_warp (using auto_warp.py)

volreg: align anat and EPI together, and to standard template(before blur, regress)

-volreg_align_to MIN_OUTLIER

-volreg_base_ind RUN SUB : i.e. run 1 slice 128 = 1 128

-volreg_align_to [third/first/last]

-volreg_interp -cubic

-volreg_align_e2a : aligning epi to anat [see align_epi_anat.py]

-volreg_tlrc_warp : warp to standard space

blur: apply desired FWHM blur to EPI data(before regress)

-blur_filter -1blur_fwhm (using 3dmerge: Note this blur “by” not blur “to”)

-blur_size 4 (using 3dBlurToFWHM: Note this blur “to”)

-blur_in_automask /-blur_in_mask no (uses 3dBlurInMask: Blur “to” in mask – default “auto”)

regress: polort, motion, mot deriv, bandpass, censor(), anticor

other notes: -anat_uniform_method unifize (using 3dUnifize)