Hi all!

I have a decision-making experiment where I present a stimulus (for 500 ms) and then subjects make a binary decision by pressing a button (1 or 2) within 2 s. Afterwards there are other irrelevant (for my analysis) stimuli, accounting for ~13 s, and then the next trial starts. I acquire data all over the experiment (TR = 2.2s).

I am trying to analyze the fMRI data associated to two different conditions: whether the decision is correct or whether it is wrong. My design should be model-based, as the order of trials (correct vs. incorrect) depends on the subjects' responses. However, I couldn't find tutorials on how to perform this analysis in AFNI. The afni_proc.py script I put together (below) gives very random results (significant areas mostly outside the brain). Stim files are text files with one rows per TR, and 1 if it is the TR with onset at the stimulus that leads to correct/incorrect decision, or 0 otherwise.

Do you have any suggestions on how to model this analysis in AFNI? I have been bouncing my head on this problem for months!

Thanks!
Davide

afni_proc.py -subj_id $SUBJ                                                  \
        -script proc.$SUBJ -scr_overwrite                                    \
        -blocks despike tshift align tlrc volreg blur mask scale regress     \
        -copy_anat $top_dir/$SUBJ/T1w_deobliqued.nii                         \
        -tcat_remove_first_trs 2                                             \
        -dsets $top_dir/$SUBJ/ep_*_deobliqued.nii.gz                         \
        -volreg_align_to MIN_OUTLIER                                         \
        -volreg_align_e2a                                                    \
        -volreg_tlrc_warp                                                    \
        -tshift_opts_ts -tpattern alt+z                                      \
        -blur_size 4.0                                                       \
        -regress_use_stim_files                                              \
        -regress_stim_files                                                  \
            $top_dir/$SUBJ/"$SUBJ"_correct_stim_file.1D                      \
            $top_dir/$SUBJ/"$SUBJ"_incorrect_stim_file.1D                    \
        -regress_stim_types file                                             \
        -regress_stim_labels                                                 \
            correct incorrect                                 \
        -regress_basis SPMG3                                                 \
        -regress_motion_per_run                                              \
        -regress_censor_motion 1.0                                           \
        -regress_censor_outliers 0.03                                        \
        -regress_opts_3dD                                                    \
            -gltsym 'SYM: correct -incorrect' -glt_label 1 correct-incorrect \
            -jobs 8                                                          \
        -regress_make_ideal_sum sum_ideal.1D                                 \
        -regress_est_blur_epits                                              \
        -regress_est_blur_errts                                              \
        -regress_run_clustsim no                                             \
end