Probing the mysterious underpinnings of multi-voxel fMRI analyses

Various arguments have been proposed for or against sub-voxel sensitivity or hyperacuity in functional magnetic resonance imaging (fMRI) at standard resolution. Sub-voxel sensitivity might exist, but nevertheless the performance of multi-voxel fMRI analyses is very likely to be dominated by a larger-scale organization, even if this organization is very weak. Up to now, most arguments are indirect in nature: they do not in themselves proof or contradict sub-voxel sensitivity, but they are suggestive, seem consistent or not with sub-voxel sensitivity, or show that the principle might or might not work. Here the previously proposed smoothing argument against hyperacuity is extended with simulations that include more realistic signal, noise, and analysis properties than any of the simulations presented before. These simulations confirm the relevance of the smoothing approach to find out the scale of the functional maps that underlie the outcome of multi-voxel analyses, at least in relative terms (differences in the scale of different maps). However, image smoothing, like most other arguments in the literature, is an indirect argument, and at the end of the day such arguments are not sufficient to decide the issue on whether and how much sub-voxel maps contribute. A few suggestions are made about the type of evidence that is needed to help us understand the as yet mysterious underpinnings of multi-voxel fMRI analyses.