hello AFNI,
after I attended your bootcamp this january, I am trying to align some epi using afni_proc.py. The standard version for resting state does not align them properly, so I have tried different modifications with a bit of preprocessing before inserting the data in afni_proc. This is the script I have used:
3dUnifize -prefix 3danat+orig -input anat.nii.gz -GM
3dcopy rest.nii.gz 3drest+orig
3dWarp -deoblique -prefix rest_warp 3drest+orig
3dSkullStrip -input 3danat+orig -prefix 3danat.ns
@Align_Centers -prefix rest_warpAC -dset rest_warp+orig \
-base 3danat.ns+orig. -cm

# run afni_proc.py
afni_proc.py -subj_id $subj \
-script proc.$subj \
-scr_overwrite \
-blocks despike tshift align tlrc volreg \
-copy_anat 3danat.ns+orig \
-tcat_remove_first_trs 13 \
-dsets rest_warpAC+orig \
-align_opts_aea -cost lpc+ZZ -giant_move \
-anat_has_skull no \
-tlrc_opts_at -OK_maxite \
-volreg_align_to MIN_OUTLIER \
-volreg_align_e2a \
-volreg_tlrc_warp \
-volreg_interp -Fourier

The best results until now appear to be with giant_move and lpc+ZZ options, but it looks like the original image is shifted and its shape it is changed a lot when compared to the original. The dorsal cortex is great, but the inferior temporal lobes seem to be sort of compressed. Actually, for the inferior brain, the tshifted epi seems to better match the anat... this happens for more than one subject, and is a tendency I have seen in other samples too (that's why I prefer to use cost such as crU, when it works). With these results, is it ok to go on with the analysis or should I change something in the script?
Until now I have played with options like blur_fwhm 2 in skullstrip, and different costs (crU, lpa, nmi), -big_move or nothing, cmass, -rigid_body, -check_flip in aea

Thanks for any suggestion!
stefano