Mask for Global Signal Regression

Dear all,

I want to perform  Global Signal Regression on files which I have already preprocessed (swau) using another toolbox. For GSR, one can choose between "SPM apriori" and "Automask". This confuses me; What is the difference between the Option "Segment" for WM/CSF-regression and the option "Automask" for GSR? Also, can't I use the already existing brainmasks which I stored in the folder WorkingDirectory/Masks/WarpedMasks?






1. For WM and CSF, you can use segmentation results. But there are no segmentation results for brain mask.

2. Yan, C.G., Wang, X.D., Zuo, X.N., Zang, Y.F., 2016. DPABI: Data Processing & Analysis for (Resting-State) Brain Imaging. Neuroinformatics 14, 339-351.

"DPABI generates a coverage mask with a program equivalent to AFNI’s 3dAutomask (https://afni.nimh.nih. gov/pub/dist/doc/program_help/3dAutomask.html). Specifically, the program estimates gradual clip values to set the background regions of the mean EPI volume to zero based on histogram gazing. Then the largest connected component of voxels above the clip values were selected to generate the coverage mask for a given subject, with erosion and filling the holes."

This is a mask based on functional data, which should work well.

3. You can use WarpedMasks. If you use SPM apriori, the apriori brain mask is warped to original space and used in nuisance regression.