Using aCompCor for nuissance regression


I’ve sorted through discussions on here re: high numbers of aCompCor regressors output from fmriprep but still find myself a bit confused. My functional runs are 197 volumes (TR: 1.5s). I was originally planning to use the top 10 components from the combined mask and the cosine regressors in my GLMs, but then noticed how little variance is accounted for (~ 10%). If I were to use the 50% rule, I’d have upwards of 70 nuissance regressors which seems excessive.

I tried to use the Broken Stick logic for each participant and run, and again find that I’d need between ~30 and 70 nuissance regressors per run. I can see there’s not a great consensus on this, so I may just go with the top 5 CSF and top 5 WM …but wanted to check and see if anyone encountered the same issue.