I am cleaning old rest data that the lab has not gotten around to using (preferably via Python). For each scan, I have raw timeseries from both a respiration belt and a pulse-ox, already trimmed and resampled to the TR frequency.
My question is, what are the next steps to use this data to clean the rest data? Is it as simple as fitting a linear model predicting each voxel’s timeseries from the noise timeseries, then saving out the residuals? Knowing fMRI, this feels too straightforward.