Hi, Marina-

There examples for these cases in the afni_proc.py help file.

For example, for surface analysis with task-based FMRI:
https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/programs/afni_proc.py_sphx.html#s03-ap-surface-class-demo-basic-surface-analysis

Resting state surface analysis could be done similarly. A modern example of resting state analysis with surface projection is provided as part of the afni_proc.py multi-echo resting state FMRI demo, which can be downloaded and unpacked with:

@Install_APMULTI_Demo1_rest

The full AP command looks like this (see the script for what the variables are and how they can be populated:

afni_proc.py                                                            \
     -subj_id                  ${subj}                                  \
     -blocks despike tshift align volreg mask combine surf blur scale   \
         regress                                                        \
     -radial_correlate_blocks  tcat volreg                              \
     -copy_anat                ${anat_cp}                               \
     -anat_has_skull           no                                       \
     -anat_follower            anat_w_skull anat ${anat_skull}          \
     -anat_follower_ROI        aaseg        anat ${roi_all_2009}        \
     -anat_follower_ROI        aeseg        epi  ${roi_all_2009}        \
     -anat_follower_ROI        FSvent       epi  ${roi_FSvent}          \
     -anat_follower_ROI        FSWe         epi  ${roi_FSWe}            \
     -anat_follower_erode      FSvent FSWe                              \
     -surf_anat                ${surf_anat}                             \
     -surf_spec                ${surf_specs}                            \
     -blip_forward_dset        "${epi_forward}"                         \
     -blip_reverse_dset        "${epi_reverse}"                         \
     -dsets_me_run             ${dsets_epi_me}                          \
     -echo_times               ${me_times}                              \
     -combine_method           OC_tedort                                \
     -combine_tedort_reject_midk  no                                    \
     -tcat_remove_first_trs    ${nt_rm}                                 \
     -tshift_interp            -wsinc9                                  \
     -align_opts_aea           -cost lpc+ZZ -giant_move -check_flip     \
     -volreg_align_to          MIN_OUTLIER                              \
     -volreg_align_e2a                                                  \
     -volreg_warp_final_interp  wsinc5                                  \
     -volreg_compute_tsnr      yes                                      \
     -blur_size                ${blur_size}                             \
     -mask_epi_anat            yes                                      \
     -regress_motion_per_run                                            \
     -regress_make_corr_vols   aeseg FSvent                             \
     -regress_censor_motion    ${cen_motion}                            \
     -regress_censor_outliers  ${cen_outliers}                          \
     -regress_apply_mot_types  demean deriv                             \
     -html_review_style        pythonic

This assumes you ran FreeSurfer previously to get the mesh. You could use FreeSurfer ROIs for your surface analysis. If you don't have multi-echo FMRI data, you could remove those parts---namely, the combine block, and the "-echo_times .." and "-combine_* .." options. The "-blip_* .." options are because the demo also has reveres phase encoded EPIs, for B0 distortion correction. If you don't have that kind of data, you could also leave out those options.


--pt



Edited 1 time(s). Last edit at 03/16/2022 10:56PM by Daniel Glen.