Hello AFNI experts,
I am analyzing a dataset of children with large unilateral strokes, and I am struggling to find a procedure for structural to functional alignment that works well. I have been using the lpc+ZZ cost function, to match the dark CSF in the anatomicals to the bright CSF in the functionals. It seems like the mask generated for the epi base (min outlier volume) in the align_epi_anat.py procedure cuts out a lot of the brain, and then it has a hard time aligning - I attached an image of the automask overalyed onto the Outbrick…_ns+tlrc anatomical output from the alignment, and also the jpeg produced by @snapshot_volreg on the alignment outputs. I saw in one of the tutorial videos that there are specific scripts that have been generated to help with aligning stroke brains, and was wondering where I can find them, or if you have suggestions for what I should try next? Here is also a copy of the preprocessing steps that I passed to afni_proc.py:
afni_proc.py -subj_id SP_Ch008 -copy_anat
-blocks tshift align tlrc volreg blur mask scale regress
-tcat_remove_first_trs 2 -align_opts_aea -cost lpc+ZZ -tlrc_base
MNI152_T1_2009c+tlrc -volreg_align_to MIN_OUTLIER -volreg_align_e2a
-regress_stim_labels CTRL EMOT INSTR REST -regress_censor_motion 0.3
-regress_basis_multi ‘BLOCK(24,1)’ ‘BLOCK(24,1)’ ‘BLOCK(3,1)’
‘BLOCK(9,1)’ -regress_reml_exec -regress_est_blur_errts
-regress_opts_3dD -gltsym ‘SYM: CTRL -REST’ -glt_label 1 CTRL-REST
-gltsym ‘SYM: EMOT -REST’ -glt_label 2 EMOT-REST -gltsym 'SYM: EMOT
-CTRL’ -glt_label 3 EMOT-CTRL -gltsym ‘SYM: CTRL -EMOT’ -glt_label 4
Would you be able to upload one subject’s EPI and anatomical? I can probably take a look at it more easily then.
I can PM you instructions for uploading.
For large stroke lesions, we have a couple methods we have used in the past. Once we see some data, Paul and I can take a look and offer some suggestions.
While you’re waiting on an evaluation of your data, try adding either: