Abstract
We exploited co-occurrences between color and other properties of natural scenes to identify and visualize functionally distinct brain regions. For each voxel in the Natural Scenes Dataset (NSD), we computed a scaled response-weighted average of the stimulus images. The colors of "voxel-preferred images" (VPIs) reflect stimulus properties that covary with color in natural scenes: Color serves as a tag for functional distinctions in voxel responses. Mapping VPIs onto cortical surfaces revealed reliable and structured color patterns that segment voxel clusters. Boundaries between clusters of similarly colored VPIs tend to coincide with boundaries defined using other methods, and heterogeneity within regions suggests functional subdivisions. VPIs provide a simple data-driven method for analyzing fMRI responses to natural scenes and visualizing cortical organization.