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Hi, I am currently using Featquery to extract the number of voxels/mean z values within a number of functionally defined binarised masks specified in MNI (1x1x1mm) space. I notice that when Featquery registers the masks back to native (4x4x4mm) space they seem to lose a degree of their (proportional) spatial extent. I discovered this by manually registering the binarised masks to native space (using reg/standard2example_func.mat) and finding a large discrepancy when comparing the number of voxels within the manually registered masks to that calculated within the corresponding mask by Featquery. I see now that, despite being originally binarised, the edges of the masks have values ranging from 0-1 when I manually register them to native space. Although I can change the interpolation value in Featquery to preserve the size of the original masks, would you be kind enough to explain to me where this alteration in mask values comes from so that I don't overcompensate. Any assistance would be greatly appreciated. Many thanks in advance, Dan.