Hi @tsalo, I have a follow up question re using the SSS as a regressor, I figured it would be helpful to get your advice on this. I came across this thread where it’s mentioned that using the SSS may involve the risk of : "if you have vascular territories with large delays (due to pathology, or even, it seems, normal aging), then you can get multiple copies of the sLFO regressor showing up in the SSS. I refer to this as getting a "poison regressor".
Now, this problem might be relevant to my analysis as my dataset does include older adults (with potential vascular risk factors). Per my understanding I know that we have
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The —acfix flag that might help to disambiguate these repeated signals, but I’m not sure if it is THE recommended fix for this type of “poison regressor” problem.
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The thread also mentions that when supplying the SSS as the regressor, we should also make sure our brain mask does NOT include the SSS voxels - to avoid corrupting the subsequent regressor refinement steps. (maybe use a combination of GM+WM TPMs to create the brain mask instead of relying on FSL-BET/fmriprep default outputs)?
What do you think about using the SSS? Do you know of any repositories/papers that share an example of how to use such a regressor? (The only one I can currently find is this: Line 148-151 cvrisk-hemodynamics/BLV_func.sh at main · ahmedaak/cvrisk-hemodynamics · GitHub but there’s no inclusion of a brain mask etc)
Would greatly appreciate your thoughts on this! Thanks!