Let me revive this!
We want to use ANATICOR in our task based data analysis but I don't see how it helps me? I realized that the ANATICOR part is run after 3dDeconvole (I guess that is what Rick mean with 3dREML.fit). So how is this helping me, the ANATICOR info is not in the big regression? I want my stats output to be cleaned from the noise that ANATICOR takes care of (spatially varying WM noise). But only the residuals are "cleaned" with ANATICOR? How do I use this?
Or do I misunderstand what 3dREML.fit does?
afni_proc.py -subj_id $sub_id \
-dsets $fmri_data \
-copy_anat $T1_data \
-blocks despike tshift align volreg mask regress \
-mask_segment_anat yes \
-mask_segment_erode yes \
-align_opts_aea \
-giant_move \
-tcat_remove_first_trs 0 \
-volreg_align_to MIN_OUTLIER \
-volreg_align_e2a \
-regress_censor_motion 0.3 \
-regress_censor_outliers 0.1 \
-regress_anaticor \
-regress_reml_exec \
-regress_apply_mot_types demean deriv \
-regress_stim_types AM1 \
-regress_basis 'dmBLOCK' \
-regress_stim_times $stim/* \
-regress_stim_labels Q_other Q_self C_other C_self O_other_dwn O_other_up O_self_dwn O_self_up motor \
-regress_local_times \
-regress_opts_3dD \
-allzero_OK \
-GOFORIT 6 \
Thanks!
Edited 3 time(s). Last edit at 10/25/2016 10:58AM by Robin.