Multidimensional Feature Tuning in Category Selective Areas of Human Visual Cortex

Abstract

Two prominent accounts describe the functional organization of human high-level visual cortex. A categorical view emphasizes category-selective areas, while a dimensional view highlights continuous feature maps spanning these areas. Here, we asked whether these two views reflect complementary expressions of the same underlying organization. Using a data-driven decomposition of fMRI responses from human participants (female and male) in face-, body-, and scene-selective areas, we identified spatially overlapping activity patterns that were shared across individuals. Each area encoded multiple interpretable dimensions capturing both finer within-category and coarser between-category distinctions, even in the most category-selective voxels. These dimensions formed distinct clusters within category-selective areas but extended as distributed maps across visual cortex. Together, these findings reveal an underlying organization that links category-selective areas to continuous feature maps, thereby reconciling categorical and dimensional accounts of high-level visual cortex.