A Model-Driven Functional Atlas of Human Visual Cortex under Naturalistic Vision

Visual preferences overlap in cortex and recur across objects and scenes. Describing their combinations is a central challenge for a functional atlas of natural vision. We construct a fine-grained atlas by relating sparse, interpretable Transformer features to human fMRI responses. Individual functional modes link image properties to cortical coefficient patterns, resolving distinctions within familiar category-associated regions. Continuous coordinates reveal regional mixtures in which a locally enriched mode contributes only part of the overall profile. Response-matched families show corresponding cortical patterns across the observed participants and independently learned model dictionaries, providing recurrent atlas elements. Condition subatlases organize these elements by both relative preference and common participation: features shared across image categories are retained alongside those that distinguish them. Model responses to individual images select smaller subsets of these repertoires. Together, the results describe visual cortex through overlapping functional patterns whose combinations connect a recurrent atlas to the diversity of natural images.