Hello,

I am having difficulty getting the same volume and intensity of activation on the surface analyses as I do on the standard volume analyses.

1. I created the surfaces painstakingly in Freesurfer. I aligned the surface to the experimental data set. I created standard meshes. I created a syntax to run the analyses on the surface. See script below.


#!/usr/bin/env tcsh

# created by uber_subject.py: version 0.29 (November 22, 2011)
# creation date: Thu Feb 23 14:42:42 2012


# set subject and group identifiers
set subj = sub7
set group = control

# run afni_proc.py to create a single subject processing script
afni_proc.py -subj_id $subj \
-script proc.$subj -scr_overwrite \
-blocks tshift align volreg surf blur scale regress \
-copy_anat anatomy+orig \
-tcat_remove_first_trs 2 \
-dsets \
left_grasp_sub7+orig.HEAD \
left_index_sub7+orig.HEAD \
left_spread_sub7+orig.HEAD \
-volreg_align_to third \
-volreg_align_e2a \
-surf_anat SurVol_Alnd+orig \
-surf_spec std.sub7.rh.spec std.sub7.lh.spec \
-blur_size 6.0 \
-regress_stim_times \
left_grasp_sub7_onset_truncated_RM.txt \
left_index_sub7_onset_truncated_RM.txt \
left_spread_sub7_onset_truncated_RM.txt \
-regress_stim_labels \
grasp index spread \
-regress_basis 'BLOCK(2,1)' \
-regress_censor_motion 0.3 \
-regress_opts_3dD \
-num_glt 13 \
-gltsym 'SYM: grasp' -glt_label 1 LG \
-gltsym 'SYM: index' -glt_label 2 LI \
-gltsym 'SYM: spread' -glt_label 3 LS \
-gltsym 'SYM: grasp +index +spread' -glt_label 4 L_all \
-gltsym 'SYM: grasp -index' -glt_label 5 LG-LI \
-gltsym 'SYM: grasp -spread' -glt_label 6 LG-LS \
-gltsym 'SYM: index -grasp' -glt_label 7 LI-LG \
-gltsym 'SYM: index -spread' -glt_label 8 LI-LS \
-gltsym 'SYM: spread -grasp' -glt_label 9 LS-LG \
-gltsym 'SYM: spread -index' -glt_label 10 LS-LI \
-gltsym 'SYM: grasp -0.5*index -0.5*spread' -glt_label 11 LG_U \
-gltsym 'SYM: index -0.5*grasp -0.5*spread' -glt_label 12 LI_U \
-gltsym 'SYM: spread -0.5*index -0.5*grasp' -glt_label 13 LS_U

3. When I run Afni and Suma together the surface aligns with the structural data. When I load the dset from the analyses it is weaker than the normal analyses by more than double the t-value.

4. You suggested increasing the smoothing kernnel from 4 to 6 which I did. Our data was acquired at 2.25 X1X1 so I am not sure that a much larger kernel would make sense.

Do you have any thoughts as to what I should have done differently? The only difference from the standard analyses are that I mapped the analyses onto the surface.

Becky