Good morning AFNI experts - thanks in advance for some more help.

I have been running afni_proc.py for preprocessing of resting state analysis. Two of my subjects are coming back with this error, and I am not sure how to interpret it.

*+ WARNING: !! in Signal+Baseline matrix:
* Largest singular value=2.51095
* 9 singular values are less than cutoff=2.51095e-07
* Implies strong collinearity in the matrix columns!
*+ WARNING: !! in Baseline-only matrix:
* Largest singular value=2.51095
* 9 singular values are less than cutoff=2.51095e-07
* Implies strong collinearity in the matrix columns!
*+ WARNING: !! in stim_base-only matrix:
* Largest singular value=2.28363
* 5 singular values are less than cutoff=2.28363e-07
* Implies strong collinearity in the matrix columns!
*+ WARNING: +++++ !! Matrix inverse average error = 0.013769 ** BEWARE **
** ERROR: !! 3dDeconvolve: Can't run past 4 matrix warnings without '-GOFORIT 4'
** ERROR: !! Currently at -GOFORIT 0
** ERROR: !! See file 3dDeconvolve.err for all WARNING and ERROR messages !!
** ERROR: !! Be sure you understand what you are doing before using -GOFORIT !!
** ERROR: !! If in doubt, consult with someone or with the AFNI message board !!
** FATAL ERROR: !! 3dDeconvolve (regretfully) shuts itself down !!


the afni_proc settings (in case needed) are:
afni_proc.py -subj_id $name \
-dsets $name/rest1+orig.HEAD $name/rest2+orig.HEAD \
-copy_anat $name/anat+orig \
-blocks despike tshift align tlrc volreg mask regress \
-tcat_remove_first_trs 6 \
-volreg_align_e2a \
-volreg_tlrc_warp \
-mask_segment_anat yes \
-regress_censor_motion 0.2 \
-regress_censor_outliers 0.1 \
-regress_bandpass 0.0083 0.15 \
-regress_apply_mot_types demean deriv \
-regress_ROI brain WM CSF \
-regress_run_clustsim no \
-regress_est_blur_errts \
-out_dir $name/rest_results \

Thanks!