ok. Thanks.

I ran my 3ddecon script and got the following message:

*+ WARNING: -------------------------------------------------
*+ WARNING: Problems with the X matrix columns, listed below:
*+ WARNING: * Column 6 [Easy#1] is all zeros
*+ WARNING: * Column 8 [Difficult#1] is all zeros
*+ WARNING: -------------------------------------------------
*+ WARNING: !! in Signal+Baseline matrix:
* Largest singular value=2.06565
* 2 singular values are less than cutoff=2.06565e-07
* Implies strong collinearity in the matrix columns!
*+ WARNING: !! in Signal-only matrix:
* Largest singular value=1.00123
* 2 singular values are less than cutoff=1.00123e-07
* Implies strong collinearity in the matrix columns!
*+ WARNING: +++++ !! Matrix inverse average error = 0.00888889 ** BEWARE **
*+ WARNING: GLT setup: inversion of C[1/(X'X)]C' fails; trying SVD.
[This happens when some regressor columns are all ]
[zero, or when the GLT has linearly-dependent rows]
[********* EXAMINE YOUR RESULTS WITH CARE ********]
*+ WARNING: GLT setup: inversion of C[1/(X'X)]C' fails; trying SVD.
[This happens when some regressor columns are all ]
[zero, or when the GLT has linearly-dependent rows]
[********* EXAMINE YOUR RESULTS WITH CARE ********]
*+ WARNING: !! 3dDeconvolve -GOFORIT is set to 3: running despite 3 matrix warnings
*+ WARNING: !! See file 3dDeconvolve.err for all WARNING and ERROR messages !!
*+ WARNING: !! Please be sure you understand what you are doing !!
*+ WARNING: !! If in doubt, consult with someone or with the AFNI message board !!

This is my 3ddecon script below:

3dDeconvolve -input ${subj}_vis_moco_LPI_MNI_b6.nii.gz \
-mask ../binary_brainmask.nii.gz \
-polort 4 -float -jobs 4 \
-allzero_OK -nfirst 0 \
-GOFORIT 3 -local_times \
-basis_normall 1 -full_first \
-num_stimts 8 \
-stim_times_AM2 1 ../Easy_PM.1D 'BLOCK(21,1)' -stim_label 1 'Easy' \
-stim_times_AM2 2 ../Difficult_PM.1D 'BLOCK(21,1)' -stim_label 2 'Difficult' \
-stim_file 3 motion/${subj}_vr_motion_demean.1D'[0]' -stim_label 3 'roll' -stim_base 3 \
-stim_file 4 motion/${subj}_vr_motion_demean.1D'[1]' -stim_label 4 'pitch' -stim_base 4 \
-stim_file 5 motion/${subj}_vr_motion_demean.1D'[2]' -stim_label 5 'yaw' -stim_base 5 \
-stim_file 6 motion/${subj}_vr_motion_demean.1D'[3]' -stim_label 6 'dS' -stim_base 6 \
-stim_file 7 motion/${subj}_vr_motion_demean.1D'[4]' -stim_label 7 'dL' -stim_base 7 \
-stim_file 8 motion/${subj}_vr_motion_demean.1D'[5]' -stim_label 8 'dP' -stim_base 8 \
-num_glt 4 \
-gltsym 'SYM: +Easy[0] +Difficult[0]' -glt_label 1 'Easy+Difficult_avrg' \
-gltsym 'SYM: +Easy[1] +Difficult[1]' -glt_label 2 'Easy+Difficult_slope' \
-gltsym 'SYM: +Easy[0] -Difficult[0]' -glt_label 3 'Easy-Difficult_avrg' \
-gltsym 'SYM: +Easy[1] -Difficult[1]' -glt_label 4 'Easy-Difficult_slope' \
-tout \
-x1D X.mat.1D \
-xjpeg X.jpg \
-bucket ${subj}_stats_PM.nii.gz

This is not creating that 2nd regressor for each stimulus if I'm correct, and for the glt's, its only doing the ones for the average value of the modulation variable, not for the slope of the modulation variable.

This is how my stim files look like, where the first number is the onset and the second is the number of distractors:
For easy
67*15 121*15 220*15 265*15 319*15 418*15 463*15

For difficult
94*25 166*25 193*25 292*25 364*25 391*25 490*25

Any suggestions?

Thanks a lot