Linking cortical surface area to computational properties in human visual perception

Cortical structure and function are closely linked, shaping the neural basis of human behavior. This study explores how cortical surface area (SA), a structural feature, influences computational properties in human visual perception. Using a combination of psychophysical, neuroimaging, and computational modeling approaches, we find that variations in SA across the parietal and frontal cortices are linked to distinct behavioral patterns in a motion perception task. These differences in behavior correspond to specific parameters within a divisive normalization model, indicating a unique contribution of SA to the spatial organization of cortical circuitry. This work highlights the importance of cortical architecture in modifying computational processes that underlie perception, enhancing our understanding of how structural differences can influence neural function and behavior.