Dear Experts,
I have a question about resting-state data analysis.
I know that there are some debates on the usage of global signal regression on the seed-based resting-state data analysis since it might introduce false anti-correlated networks. I was told that global signal regression is same as global mean (not suggested now by SPM and replaced by grand mean). I am learning fmri-related statistics now. My understanding is the global signal regression is to remove the global signal effects ( regress out), but the global mean is to scale the mean and the difference of mean of every scan(time points) is still preserved. So they are not same. Is my understanding right? anybody could elaborate a little more if I am wrong?
Thanks for any opinions,
April
|