I ran fMRIprep version 20.2.3 on BIDS data that passed the validation.
I used the aroma flag.
From what I could find in the documentation and discussions on this site, the AROMA pipeline should apply a 6mm smoothing kernel to the participants data .
Is that smoothing comparable to the smoothing you would expect in a traditional spm pipeline, to make group comparisons more robust?
Results look ok but not necessarily as smooth as the same data if preprocessed with SPM (but not denoised with AROMA).
Thanks a lot in advance!!
I’m pretty sure AROMA uses SUSAN (SUSAN - FslWiki), which is not a Gaussian smoothing kernel.
Hi @tsalo, thanks a lot for the quick response.
In your link it states under the mask SD option:
Mask SD : this determines the spatial extent of the smoothing. The mask is basically Gaussian with standard deviation (in image units - e.g. mm) set by the user.
So I am still unsure if I should run smoothing/blurring as I would for group/GLM analasys or if this has already been done.
desc-smoothAROMAnonaggr output is already smoothed and the AROMA workflow in fMRIPrep uses a FWHM of 6 mm for SUSAN. However, the level of smoothing you want depends on your research question, target regions, data resolution, etc., so I can’t say whether or not the data are smooth enough, too smooth, or just right for your group-level analysis.
Hi @tsalo, thank you.
Yes, right, the level of smoothing depends on such things and I don’t expect any help in that domain.
I was wondering if the kind of smoothing that is done within aroma/susan is equivalent to the smoothing that would be applied by the spm smoothing function.