Hi AFNI experts,
I got a question here, after i finished preprocessing step by using afni_proc.py, i found some of the data get an error message like:
** ERROR: *** Censoring has made regression impossible 
***
** FATAL ERROR: 3dDeconvolve dies: Insufficient data (112) for estimating 142 parameters
and my afni_proc.py script as follows:
afni_proc.py -subj_id ${line} \
-script proc_${line} \
-dsets \
${input_dir}/${line}/rest+orig \
-copy_anat ${input_dir}/${line}/anat_ns_shft_al+orig \
-out_dir ${line}.results \
-blocks despike tshift tlrc volreg blur mask \
regress \
-tcat_remove_first_trs 2 \
-tlrc_base MNI152_T1_2009c+tlrc \
-volreg_align_to MIN_OUTLIER \
-volreg_tlrc_warp \
-volreg_warp_dxyz 3 \
-mask_segment_anat yes \
-mask_segment_erode yes \
-regress_censor_motion 0.4 \
-regress_censor_outliers 0.1 \
-regress_bandpass 0.01 0.1 \
-regress_apply_mot_types demean deriv \
-regress_ROI WMe \
-regress_est_blur_epits \
-regress_est_blur_errts \
-execute
I wondering that if it is influenced by the threshold of censor value? The dataset here is scanned from UWS(unresponsive wakefulness syndrome) patients, could you provide a suggestion about how to determine the threshold value here?