Hello,
I am attempting to execute afni_proc with linear warp, and am getting an error I've never seen before:
*+ WARNING: Problems with the X matrix columns, listed below:
*+ WARNING: !! * Columns 0 [Run#1Pol#0] and 18 [mot_demean_r01[0]#0] are (nearly?) collinear!
*+ WARNING: !! * Columns 0 [Run#1Pol#0] and 19 [mot_demean_r01[1]#0] are (nearly?) collinear!
*+ WARNING: !! * Columns 0 [Run#1Pol#0] and 20 [mot_demean_r01[2]#0] are (nearly?) collinear!
*+ WARNING: !! * Columns 0 [Run#1Pol#0] and 21 [mot_demean_r01[3]#0] are (nearly?) collinear!
*+ WARNING: !! * Columns 0 [Run#1Pol#0] and 22 [mot_demean_r01[4]#0] are (nearly?) collinear!
*+ WARNING: !! * Columns 18 [mot_demean_r01[0]#0] and 19 [mot_demean_r01[1]#0] are (nearly?) collinear!
*+ WARNING: !! * Columns 18 [mot_demean_r01[0]#0] and 20 [mot_demean_r01[2]#0] are (nearly?) collinear!
*+ WARNING: !! * Columns 18 [mot_demean_r01[0]#0] and 21 [mot_demean_r01[3]#0] are (nearly?) collinear!
*+ WARNING: !! * Columns 18 [mot_demean_r01[0]#0] and 22 [mot_demean_r01[4]#0] are (nearly?) collinear!
*+ WARNING: !! * Columns 19 [mot_demean_r01[1]#0] and 20 [mot_demean_r01[2]#0] are (nearly?) collinear!
*+ WARNING: !! * Columns 19 [mot_demean_r01[1]#0] and 21 [mot_demean_r01[3]#0] are (nearly?) collinear!
*+ WARNING: !! * Columns 19 [mot_demean_r01[1]#0] and 22 [mot_demean_r01[4]#0] are (nearly?) collinear!
*+ WARNING: !! * Columns 20 [mot_demean_r01[2]#0] and 21 [mot_demean_r01[3]#0] are (nearly?) collinear!
*+ WARNING: !! * Columns 20 [mot_demean_r01[2]#0] and 22 [mot_demean_r01[4]#0] are (nearly?) collinear!
*+ WARNING: !! * Columns 21 [mot_demean_r01[3]#0] and 22 [mot_demean_r01[4]#0] are (nearly?) collinear!
*+ WARNING: -------------------------------------------------
++ ----- Signal+Baseline matrix condition [X] (728x30): 377.694 ++ GOOD ++
++ ----- Signal-only matrix condition [X] (728x5): 2.08372 ++ VERY GOOD ++
++ ----- Baseline-only matrix condition [X] (728x25): 372.092 ++ GOOD ++
++ ----- stim_base-only matrix condition [X] (728x12): 227.472 ++ GOOD ++
++ ----- polort-only matrix condition [X] (728x13): 9.91029 ++ VERY GOOD ++
++ +++++ Matrix inverse average error = 9.61458e-08 ++ VERY GOOD ++
++ Matrix setup time = 2.21 s
** ERROR: !! 3dDeconvolve: Can't run past 15 matrix warnings without '-GOFORIT 15'
** 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 !!
Here is my afni_proc command:
#!/usr/bin/env tcsh
# created by uber_subject.py: version 0.37 (April 14, 2015)
# creation date: Thu Dec 31 14:20:32 2015
# set data directories
set top_dir = /project2/jschnei1/MRI/MJE/MJ_041
set anat_dir = $top_dir/Nifti
set epi_dir = $top_dir/ZShim
# set subject and group identifiers
set subj = MJ_041
set group_id = test
# run afni_proc.py to create a single subject processing script
afni_proc.py -subj_id MJ_041 \
-script proc.$subj.IGT -scr_overwrite \
-blocks despike tshift align tlrc volreg blur mask scale regress \
-copy_anat $anat_dir/brainmask.nii \
-anat_has_skull no \
-tcat_remove_first_trs 0 \
-tshift_opts_ts -tpattern altplus \
-dsets $epi_dir/MJ_041+orig. \
-volreg_align_to MIN_OUTLIER \
-tlrc_base $top_dir/MNI152_2009_template_SSW.nii.gz \
-volreg_align_to MIN_OUTLIER \
-volreg_align_e2a \
-volreg_tlrc_warp \
-blur_size 5.0 \
-mask_epi_anat yes \
-regress_stim_times \
$top_dir/control.txt \
$top_dir/losses.txt \
$top_dir/selAB.txt \
$top_dir/selCD.txt \
$top_dir/wins.txt \
-regress_stim_labels \
control losses selAB selCD wins \
-regress_basis 'GAM' \
-regress_censor_motion 0.3 \
-regress_apply_mot_types demean deriv \
-regress_motion_per_run \
-regress_opts_3dD \
-gltsym 'SYM: wins -losses' -glt_label 1 wins-losses \
-gltsym 'SYM: selAB -selCD' -glt_label 2 selAB-selCD \
-gltsym 'SYM: .5*selAB +.5*selCD -control' -glt_label 3 sel-control \
-regress_reml_exec \
-regress_polort 12 \
-regress_anaticor_fast \
-regress_make_ideal_sum sum_ideal.1D \
-regress_est_blur_epits \
-regress_est_blur_errts \
-regress_run_clustsim no
I tried setting my regress_polort from 2 to 12, that did not change anything. I also switched out the stimulus information for a subject whose processing executed successfully, to see if it has something to do with the stimulus information. This did not solve the problem. This subject did have a slightly odd skull-stripped T1 dataset, where 3dSkullStrip did not do a great job and cut out some parts of cortex, but that does not seem to be the root of the problem above.
Please let me know if you see anything glaringly wrong with the way things are set up.
Thank you!
Mikey
