Multisensory Part-based Representations of Objects in Human Lateral Occipital Cortex

The format of high-level object representations in temporal-occipital cortex is a fundamental and as yet unresolved issue. Here we use fMRI to show that human lateral occipital cortex (LOC) encodes novel 3-D objects in a multisensory and part-based format. We show that visual and haptic exploration of objects leads to similar patterns of neural activity in human LOC and that the shared variance between visually and haptically induced patterns of BOLD contrast in LOC reflects the part structure of the objects. We also show that linear classifiers trained on neural data from LOC on a subset of the objects successfully predict a novel object based on its component part structure. These data demonstrate a multisensory code for object representations in LOC that specifies the part structure of objects.