High-pass filtering with fmriprep and FSL

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Hi all,

I’m using fmriprep outputs in a first-level GLM implemented with FSL (fast event-related design). I am including aCompCor regressors and the cosine regressors as confound variables. I understand that aCompCor is conducted on high-pass-filtered data, but the func data output from fmriprep is NOT yet high-pass-filtered. I read elsewhere that the cosine regressors should be added to your first-level GLM to perform this high-pass filtering.

But things get complicated when I try to implement this in my FSL first-level analysis. I could choose to apply high-pass filtering with FSL. Additionally, when I set up my task GLM, there is an option to apply temporal filtering to each regressor. The help menu indicates that if one has applied high-pass filtering to the data, then one should also apply temporal filtering to the task regressor. I assume that if I disable high-pass filtering in FSL, I will not be able to apply temporal filtering to task regressors. If I add the aCompCor + cosine regressors from fmriprep in a separate file for additional confound EVs, FSL will not apply temporal filtering to these confound regressors (to my knowledge).

So, I have a few questions about this situation.

  1. If I disable high-pass filtering and temporal filtering of regressors in FSL, will adding the cosine regressors to my GLM essentially do both of these steps? I’m not sure why FSL applies this in two steps. I’m worried that if I don’t apply temporal filtering there may be an issue with my task regressors.

  2. Alternatively, would it be reasonable to enable high-pass filtering (cutoff of 128 seconds, the same as used in the CompCor pipeline) and temporal filtering of regressors in FSL, but not include the cosine regressors?

I did find this related thread here, but it looks like there was no conclusion.

Thanks in advance!