censor threshold for specific patients

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 :frowning: ***
** 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?