Hi,

I am running through an analysis with afni_proc.py and keep getting a similar problem with all of the subjects that I run. The afni_proc.py command is the following:

afni_proc.py -subj_id subj -dsets verbs.nii -copy_anat T1_ss_orig_vol.nii \
-anat_has_skull no -blocks despike tshift align tlrc volreg blur mask \
scale regress -volreg_align_to MIN_OUTLIER -volreg_align_e2a \
-volreg_tlrc_warp -align_opts_aea -cost lpc+ZZ -tlrc_base \
MNI152_T1_2009c+tlrc -regress_stim_times ../noise_times.1D \
../verbs_times.1D -regress_stim_labels verbs noise -regress_basis \
'BLOCK(32,1)' -regress_apply_mot_types demean deriv -regress_reml_exec \
-regress_censor_motion 0.3 -regress_censor_outliers 0.1 \
-regress_anaticor_fast -regress_opts_3dD -gltsym 'SYM: +verbs -noise' \
-glt_label 1 verbs_minus_noise -regress_est_blur_epits \
-regress_est_blur_errts

And the text output is:

subject ID : subj
TRs removed (per run) : 0
num stim classes provided : 2
final anatomy dset : anat_final.subj+tlrc.HEAD
final stats dset : stats.subj_REML+tlrc.HEAD
final voxel resolution : 2.500000 2.500000 2.500000

motion limit : 0.3
num TRs above mot limit : 1
average motion (per TR) : 0.041809
average censored motion : 0.0391933
max motion displacement : 0.705158
max censored displacement : 0.465089
outlier limit : 0.1
average outlier frac (TR) : 0.00625512
num TRs above out limit : 2

num runs found : 1
num TRs per run : 211
num TRs per run (applied) : 208
num TRs per run (censored): 3
fraction censored per run : 0.014218
TRs total (uncensored) : 211
TRs total : 208
degrees of freedom used : 18
degrees of freedom left : 190

TRs censored : 3
censor fraction : 0.014218
num regs of interest : 2
num TRs per stim (orig) : 110 138
num TRs censored per stim : 0 3
fraction TRs censored : 0.000 0.022
ave mot per sresp (orig) : 0.034695 0.045865
ave mot per sresp (cens) : 0.034695 0.041945

TSNR average : 113.985
global correlation (GCOR) : 0.0921368
anat/EPI mask Dice coef : 0.916151
maximum F-stat (masked) : 18.4122
blur estimates (ACF) : 0.631012 3.635 10.2446
blur estimates (FWHM) : 0 0 0


All of my results more or less look like the attached image, with the most significant voxels from the decon falling outside of the brain. I have checked everything I can think of and cannot seem to find where this error is coming from. Any ideas as to why this might be happening? My colleagues have analyzed the same dataset with spm (with similar parameters as far as I can tell) and the results look as expected.

Thank you very much for any assistance,
Brady