Arish Alreja

The paper introduces a reinforcement learning model for face perception that incorporates environmental feedback, showing it matches supervised and unsupervised models in capturing neural responses to faces.

The paper describes an immersive paradigm for studying natural social behavior and its neural correlates in epilepsy patients using synchronized behavioral and neurophysiological data.

This paper uses an efficient coding model to show that optimal E:I ratios in sensory cortices arise from trade-offs between computational accuracy and representation capacity under brain volume constraints.

This study uses intracranial recordings to show that individual face and word representations in human ventral temporal cortex start in domain-selective areas and later involve distributed regions.