Hi, Ajay-

Well, scaling would be important, yes, because FMRI has no real unit-- but *how* scaling is actually done is equally important. I don't see how grand mean scaling would be a good way to go for FMRI data.

As discussed in the "Units and Scaling" section of Gang's paper here:
[www.ncbi.nlm.nih.gov]
[www.researchgate.net]
... a better method would be to use voxelwise scaling, to result in a voxelwise BOLD %-signal change interpretation in your data. That would be more comparable *both* across subjects *and* across the brain.

Re. resting vs task for scaling-- the reason scaling might not often be used in resting is that time series are often not compared directly across subjects, as people mainly just calculate correlation coefficients within each subject's brain; scaling doesn't affect correlation coefficient calculation. However, for looking at ALFF changes (i.e., voxelwise magnitude changes), it would likely be quite important to scale, having a %-signal change that would be meaningful (again, both across subjects and across the brain).

--pt