I’ve seen a couple of threads about how to incorporate ICA-AROMA outputs and nuisance regressor outputs from fmriprep, but I wanted to revisit the issue a bit.
As jdkent mentions in the fmriprep github thread, here:
the authors of ICA-AROMA suggest doing participant-level processing as follows:
- Motion-correct, intensity-normalize, smooth at 6mm
- run ICA-AROMA and remove ICs from data using fsl_regfilt
- regress out WM, CSF and linear trend nuisance regressors, then do high-pass filtering.
It’s not clear to me how I would implement this approach using fmriprep outputs. In the AROMA paper’s approach, are the WM and CSF regressors at step 3 calculated after ICA-AROMA noise ICs have been removed? Or are they recalculated on the denoised outputs? Or am I reading Tom Nichols comments from the github thread correctly, and it doesn’t matter if you use WM/CSF regressors calculated before or after denoising?