1d_tool.py censor motion question

Dear AFNI experts,

I am wonder what is the difference between these two examples of censor motion using 1d_too.py.
What is different when you use ‘-censor_motion’ or ‘-moderate_mask’?

       a. general example ~3~

          1d_tool.py -infile motion.1D -set_nruns 9     \
                     -derivative -censor_prev_TR        \
                     -collapse_cols euclidean_norm      \
                     -moderate_mask -1.2 1.2            \
                     -show_censor_count                 \
                     -write_censor subjA_censor.1D      \
                     -write_CENSORTR subjA_CENSORTR.txt

       b. using -censor_motion ~3~

          The -censor_motion option is available, which implies '-derivative',
          '-collapse_cols euclidean_norm', 'moderate_mask -LIMIT LIMIT', and the
          prefix for '-write_censor' and '-write_CENSORTR' output files.  This
          option will also result in subjA_enorm.1D being written, which is the
          euclidean norm of the derivative, before the extreme mask is applied.

          1d_tool.py -infile motion.1D -set_nruns 9     \
                     -show_censor_count                 \
                     -censor_motion 1.2 subjA           \

Best regards,

Hi Karel,

Those examples should have the same effect. The purpose of -moderate_mask is to allow one to censor based on some external time series. In the case of the Euclidean norm, there is no need to worry about large negative values in the -moderate_mask option, for example, since the values will be non-negative. For those starting with a 6 column motion parameter file, or even an enorm input, there is little reason to use that option.

  • rick