A neural computational framework for face processing in the human temporal lobe

A key question in cognitive neuroscience is how unified identity representations emerge from visual inputs. Here, we recorded intracranial electroencephalography (iEEG) from the human ventral temporal cortex (VTC) and medial temporal lobe (MTL), as well as single-neuron activity in the MTL, to demonstrate how dense feature-based representations in the VTC are translated into sparse identity-based representations in the MTL. First, we characterized the spatiotemporal neural dynamics of face coding in the VTC and MTL. The VTC, particularly the fusiform gyrus, exhibits robust axis-based feature coding. Remarkably, MTL neurons encode a receptive field within the VTC neural feature space, constructed using VTC neural axes, thereby bridging dense feature and sparse identity representations. We further validated our findings using recordings from a macaque. Lastly, inter-areal interactions between the VTC and MTL provide the physiological basis of this computational framework. Together, we reveal the neurophysiological underpinnings of a computational framework that explains how perceptual information is translated into face identities.