Neural pathway for visual object coding in the human temporal lobe

Understanding how the human brain encodes visual objects involves deciphering the neural mechanisms along the ventral visual pathway. Here, we recorded intracranial EEG in the human ventral temporal cortex (VTC) and medial temporal lobe (MTL), along with single neurons in the MTL, to investigate how complex visual features are translated into semantic representations. The VTC exhibited axis-based feature coding, and by constructing a neural feature space using VTC neural axes, we observed that MTL neurons encode a receptive field within the VTC neural feature space. This computational framework explains how dense feature-based representations in the VTC are translated into sparse semantic-based representations in the MTL. We further validated our findings using an additional dataset with different stimuli. Lastly, we uncovered the physiological basis of this computational framework by demonstrating VTC-MTL interactions at multiple levels. Together, our neural computational framework provides a mechanistic understanding of the neural processes underlying object recognition.