AFNI does not give logical result

I use AFNI and uber_subject.py and when ı look my afni_proc.py script it’s look ok and also it performs all the processing without any error. At our project we are trying to compare non-stationary data NOTMOCO and stationary data MOCO . (MOCO has motion at 0.1mm-0.3mm band and NOTMOCO has motion at 1mm-2mm band and MOCO is the motion corrected NOTMOCO data created by MR own software). I use motion censor limit 3mm and at the result script it says there is no censored TR. But MOCO gave more meaningful clusters and more activated voxels than NOTMOCO and this result is just opposite at GIFT,CONN and REST. How can it be possible ? What should I do ?

afni_proc.py -subj_id $subj
-script proc.$subj -scr_overwrite
-blocks despike tshift align tlrc volreg blur mask regress
-copy_anat $anat_dir/anat+orig
-dsets $epi_dir/r01+orig.HEAD
-tcat_remove_first_trs 5
-volreg_align_to third
-volreg_align_e2a
-volreg_tlrc_warp
-blur_size 6.0
-regress_censor_motion 3.0
-regress_bandpass 0.01 0.1
-regress_apply_mot_types demean deriv
-regress_est_blur_errts