Dear Michiko,
> I was wondering what is typically used to regress motion for diffusion analyses - would this be information in the eddy_movement_rms file or could one use motion estimates from say, resting state fMRI analyses? Are there any differences in doing so?
in general one doesn’t regress out motion for diffusion analysis. At least not for the “first level”, i.e. the estimation of diffusion tensors, FA, MD, ball-and-stick parameters etc.
If you refer to the "second level", i.e. a comparison of first level parameters between groups, against some independent variable etc, then it can be useful to include a motion confound. That motion confound should be one (or a small number of) summary statistic of movement. That summary statistic can for example be derived from the .eddy_movement_rms or the .eddy_restricted_movement_rms. I don’t think there is any consensus on what that statistic should be. One suggestion could be the sum of the first column (with absolute movement) and the sum of absolute values of the second column (with relative movement), resulting in two values per subject (and hence two columns in your design matrix).
You should definitely use the motion estimates from the diffusion data. You could easily imagine a situation where a subject got a little uncomfortable and moved in the rs-fMRI scan and not in the diffusion, or vice versa.
Jesper
>
> Thanks!
>
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