Our team is interested in using Bayesian inference in SPM to model our data at the first- and second-level. SPM recommends that data not be smoothed before Bayesian estimation while ICA-AROMA (which we have used for motion correction) recommends smoothing. How reliable is ICA-AROMA for unsmoothed data? Any suggestions on best practices here?
I operate under the assumption that as long as the AROMA components are calculated from the smoothed data, you can either use fsl_regfilt to “nonaggressively” denoise the unsmoothed data, or enter the noise components into your first level model with the unsmoothed data. I’m looking up when I believe Martin Mennes said this in another conversation chain.
In short, derive the components from smoothed data, but you can apply the components to unsmoothed data.