Bayesian Decoding Reveals Retinotopic Selectivity for Body Positions in Body-Selective Regions

The Extrastriate Body Area (EBA) represents information about human bodies. Though EBA is not usually considered a retinotopic area, past work has demonstrated visual field biases in different parts of EBA. Here, we probe the retinotopic position-specificity of EBA. Past research has used relatively coarse tests of position sensitivity, including contrasts between body parts presented in isolation in a few fixed retinotopic locations. To address this limitation, we modeled BOLD fMRI responses to stimuli consisting of rendered bodies performing actions in different retinotopic positions. To minimize naturalistic confounds of visual field location and motion, we varied the camera trajectory and added moving textures to bodies and backgrounds. We then extracted features describing the presence and retinotopic location of body parts, and applied linear regression to map these features onto fMRI responses and predict responses to withheld stimuli. This model yielded accurate predictions across cortical regions in and around EBA. Variance partitioning against a motion energy model revealed unique variance explained in these voxels by body features. To explore retinotopic position sensitivity in body selective regions, we computed contrasts between weights for body features reflecting different locations of bodies. As expected, these revealed left versus right visual field contralateral selectivity. We used two multivariate analyses to further quantify position selectivity.. Principal component analysis on the model weights revealed a dominant dimension of horizontal selectivity, alongside a less pronounced dimension that subtly suggests vertical selectivity. Consistent with this result, Bayesian decoding of body locations was more reliable than chance in the horizontal direction and in some cases more reliable than chance in the vertical direction as well. Overall, our findings suggest that EBA has more position sensitivity than has previously been appreciated. Even coarse coding of retinotopic body location could reveal socially relevant information about the position of bodies relative to gaze.