Dear Zarrar,
> I was interested in doing something just like this and was glad to
> see that Klara asked this question. I have another clarification
> question regarding the use of fsl_motion_outliers. When you add the
> confound file produced by fsl_motion_outliers to your FEAT model,
> does this impact the inclusion of the motion parameters as
> covariates? So if you previously included the motion parameters as
> covariates, will they no longer be necessary with the inclusion of
> the confound matrix from fsl_motion_outliers?
No, they are pretty much complementary. Including the motion
parameters removes (as a first order approximation) effects that
depend ~linearly on subject position, such as e.g. distortion-by-
position and dropout-by-position interactions.
The covariates you get from motion_outliers on the other hand removes
effects related to "subject velocity" (again as a first order
approximation). For example if someone makes a sudden movement in the
middle of the acquisition of a volume the rigid-body transformation is
no longer valid, and such a volume would be picked up by
motion_outliers.
Good Luck Jesper
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