Dear Rick,

Thanks a lot for your response! Regarding the use of 3dinfo, I was looking at single bricks using the square brackets, but it is indeed more convenient to use the -verb flag to see all of the information together. Thanks for the suggestion! Regarding GLT, I deleted the 4 lines:

-regress_opts_3dD \
-jobs 1 \
-gltsym 'SYM: activation_stimulus' \
-glt_label 1 activity \

And the file 'stats.${subject_name}_REML' consists now of 5 bricks rather than 8. These 5 bricks are the same as previously the first 5 ones. However, I am not sure if I understand the difference between AM1 and AM2. Now in '3dDeconvolve' help I see that " 'AM1' is for special cases, and normally should not be used for FMRI task activation analyses!! " However, when I change AM1 to AM2, I run into errors I can not understand:

*+ WARNING: -------------------------------------------------
*+ WARNING: Problems with the X matrix columns, listed below:
*+ WARNING: !! * Column 4 [activation_stimulus#2] is all zeros
*+ WARNING: !! * Column 5 [activation_stimulus#3] is all zeros
*+ WARNING: -------------------------------------------------
*+ WARNING: !! in Signal+Baseline matrix:
* Largest singular value=2.05851
* 2 singular values are less than cutoff=2.05851e-07
* Implies strong collinearity in the matrix columns!
*+ WARNING: !! in Signal-only matrix:
* Largest singular value=1.00013
* 2 singular values are less than cutoff=1.00013e-07
* Implies strong collinearity in the matrix columns!
*+ WARNING: +++++ !! Matrix inverse average error = 0.0138889 ** BEWARE **
** ERROR: !! 3dDeconvolve: Can't run past 5 matrix warnings without '-GOFORIT 5'
** 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 !!

My afni_proc.py command is now:

afni_proc.py \
-subj_id $subject \
-script proc.$subject -scr_overwrite \
-tcat_remove_first_trs 0 \
-dsets ${subject}_${task}_bold.nii \
-volreg_align_to third \
-blur_size 8.0 \
-regress_stim_types AM2 \
-regress_stim_times \
AFNI_${study}_${exper_design}.txt \
-regress_stim_labels activation_stimulus \
-regress_basis 'SPMG2(20)' \
-regress_make_ideal_sum sum_ideal.1D \
-regress_run_clustsim no \
-regress_est_blur_epits \
-regress_est_blur_errts \
-regress_reml_exec \
-regress_opts_reml -Rwherr whitened_errts.${subject}_REML

Do you know to what extent can the results differ/be biased if I leave AM1 (no errors)?

Best wishes,

Wiktor Olszowy