I’m using the following nuisance regressors to denoise my data: 6 parameter motion and motion outliers. I will be using fsl_glm to do this. From my understanding, the motion outliers column will regress out volumes that are subject to large amounts of movement. Does this mean I will have to edit my timing files to take into account the volumes that were regressed out?
I also need to regress out dummy scans, which I will do using
non_steady_state_XX columns. At what stage should this be introduced? Should this be included in my denoising stage above, if so, does this mean I will have to edit my timing files further to take this into account? If I include it in my deonoising stage, would I still need to include the dummy scan regressor in my first and second-level analyses so that parameter estimates are not generated for these scans? Or do I not include them in my denoising step and just include them as regressors in my analyses?
Finally, If I have some participants where non-steady states were correctly identified for some runs but not in others, is it worth rerunning this but including the flag
--dummy-scans N on these participants or is the effect on confound regressors only slight?
Apologies for all the questions, but many thanks in advance for your time!