I've done a volume-based task functional connectivity analysis involving a 3dTCorrMap step. Now I want to do replicate it in surface space. AFNI/SUMA seem to require that each hemisphere is analyzed separately -- is that correct? I'd rather have a merged dataset so I can use operations like 3dTCorrMap across the whole brain (both hemispheres) at once.
Below is my afniproc code that results in a dataset for each hemisphere. Any suggestions on how it can be modified to produce one dataset covering both hemispheres? (I tried changing _?h.spec to _both.spec and that didn't work....) Thanks.
# afni_proc.py -subj_id ${name}.surf.v${version} \
# -blocks align volreg surf blur scale regress \
# -copy_anat ${name}/SUMA/brainmask.nii \
# -dsets ${name}/${name}_run?.tcat+orig.HEAD \
# -surf_anat ${name}/SUMA/${name}_SurfVol.nii \
# -anat_has_skull no \
# -surf_spec ${name}/SUMA/std.141.${name}_?h.spec \
# -surf_anat_aligned yes \
# #-tcat_remove_first_trs 3 \
# -align_opts_aea -giant_move \
# -volreg_align_to third \
# -volreg_align_e2a \
# -blur_size 8 \
# -regress_stim_files pitchstims.txt timestims.txt bothstims.txt \
# -regress_stim_labels pitch time both \
# -regress_basis 'NONE' \
# -regress_stim_types file \
# -regress_use_stim_files \
# #-regress_motion_per_run \
# -regress_censor_motion 0.5 \
# -regress_opts_3dD \
# -jobs 2 \
# -gltsym 'SYM: pitch time both' -glt_label 1 'all_gt_rest'
#
# tcsh proc.${name}.surf.v${version}
