Hi Michael,

The basic aspect that might not be clear is that the censor fractions are not based on stimulus timing, but on stimulus response timing. 3dDeconvolve writes a regression matrix of idealized BOLD response curves (or whatever one asks for), and it is the censored fractions of these curves that are reported with "num TRs censored per stim". Note that "per stim" is really space-saving shorthand for either per regressor or per stimulus response, say. The fraction is with respect to the number of time points that a single regressor is non-zero, not the number of time points that are simply part of the stimulation time.

Even if the stimuli do not overlap, even per TR, the response curves typically do, and quite a bit. Add up the number of time points with non-zero regressor values, and it is often 5 to 20 times the number of time points.

Consider this, though the descriptions are short:

gen_ss_review_scripts.py -help_fields

Regarding censoring singly or in pairs, the default for afni_proc.py is for outlier censoring to be only for those specific time points, however motion censoring comes in pairs. If nothing else, that is because motion censoring is based on the difference in position between 2 adjacent time points, and the program cannot tell during which the motion actually happened (possibly during one, possibly during both, almost impossibly between them).

Does this seem reasonable?

- rick