I have a questions concerning the use of dwidenoise when Prescan Normalize is turned on. dwidenoise requires that no preprocessing is performed on the data, but I am not sure if prescan norm would be a problem. To provide some background, it removes the brightness changes across the images that are due to the spatial positioning of the receive coils - and it appears to be a basic mathematical step - just a subtraction on a voxel by voxel basis, that doesn’t affect SNR (according to siemens).
I have tested dwidenoise on functional EPI data with and without prescan norm (what I had handy) and the noise maps are slightly different, though no structure is apparent. The resulting timeseries is nearly identical (vast majority of brain >0.95 correlation), thought there are slight changes in a voxel here and there.
Is there a clear theoretical reason that dwidenoise would fail or be incorrect on data that was scaled on a voxel by voxel basis in a way that doesn’t alter voxel SNR?