Hi Rick,

Thank you very much for your reply!

> My guess is that you want srms, as it must be in [0,1]. But maybe there is a different scalar that you want, which would also
> scale into the 0.5 threshold. There is currently no method to apply this in afni_proc.py, as those curves seemed to noisy to
> be robust. But if it is something you feel is important, I could consider adding something.

Our initial idea was to do a censoring based on Power et al., 2012 and, particularly, based on intensity instead of the 6 motion parameters, and it would be interesting if AFNI had a way to do it (for example, censoring with dvars or srms), but using enorm is fine! I have also read here the explanations why it's more appropriate to use enorm than fd (it is a calculation more proportional to the real movement), and for now, we will apply enorm to censoring because it seems very reasonable.

> Regarding enorm (this time of the motion parameters), note that it is not generally used in the linear regression. The (de-meaned)
> motion parameters are used, and/or their derivatives. But enorm itself is generally just used for censoring and QC. Note that
> enorm would capture little that the motion derivatives would not.

It make sense!

> The dvars regressor could be used in the regression (though not currently via afni_proc.py). In that case, scaling would not matter much.
> Does that seem reasonable?

A doubt emerged related to this: Is it correct to use as a regressor a file that contains a value for each volume except for the first volume?
(Because the first value in the dvars file is always 0.)

Thanks again!

Best wishes,
Marina.