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I apologize if this has already been posted to the list, but I did not see it come through successfully. Thanks! Dear FSLers, We have a question regarding correction for multiple comparisons in a diffusion tensor imaging study: We have conducted a DTI study in which we have a priori areas of interest in our voxel-based analysis. We've pulled out the areas of interest and are only evaluating them initially, so the correction for multiple comparisons should be based on the number of voxels considered, with smoothing/clustering criteria taken into account. So far, this is all fine. However, the problem arises when I realize that the registrations that FSL uses to put DTI data into standardized space (using an MNI template), takes 2x2x2 data and registers it into a 1x1x1 volume. The voxel-based contrast is done on the registered 1x1x1 images, and thus, eight times the number of comparisons are made than would have been made on the original data. So the question is: How do we correct for multiple comparisons? It doesn't make sense to me to "increase" resolution and the number of comparisons without actually adding real information. Does anyone have any suggestions how to deal with this situation? Thank you!