Shared representations in brains and models reveal a two-route cortical organization during scene perception

The brain transforms visual inputs into cortical representations that support diverse cognitive and behavioral goals. Characterizing how this information is organized and routed across the human brain is essential for understanding how we process complex visual scenes. Here, we applied representational similarity analysis to 7T fMRI data collected during natural scene viewing. We quantified representational geometry shared across individuals and compared it to hierarchical features from vision and language neural networks across model layers. By integrating these comparisons with representational connectivity between cortical regions, we identified two distinct processing routes: a ventromedial pathway specialized for scene layout and environmental context, and a lateral occipitotemporal pathway selective for animate content. Vision models aligned with shared structure in both routes, whereas language models corresponded primarily with the lateral pathway and showed negative alignment in early visual and ventral cortex. These findings refine classical visual-stream models by revealing a distributed cortical network with separable representational routes for context and animate content during scene perception.