Neural Coding of Complex 3D Shapes

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DESCRIPTION (provided by applicant): Our world is composed of 3D objects, and successful interaction with that world depends on neural processing of 3D object information. This is what makes vision so critical to our health, happiness and survival. Our long- term goal is to understand how complex 3D object information is processed in perception, memory, and cognition. Understanding these issues at a neural level will impact clinical approaches to visual agnosias, altered visual processing in neurological conditions like autism, and altered memory and decision functions in neurological conditions like Alzheimer's disease. We recently developed a novel adaptive sampling strategy for neural recording experiments, in which tests of object shape responses gradually adapt based on neural feedback. This highly efficient sampling strategy allows us to measure the specific object information signaled by neurons, which was not possible with previous experimental strategies. We now plan to leverage this approach to investigate the neural basis of 3D object perception, memory, and cognition, by measuring neural responses in inferotemporal visual cortex (IT), memory-related perirhinal and entorhinal cortex (PR and ER), and decision-related dorsolateral prefrontal cortex (PFC) of monkeys performing visual memory and discrimination tasks. These areas are the homologues of high-level object vision, memory, and decision areas in the human brain; only in monkeys can they be studied at the neural coding level. The unique aspect of our experiments is the use of adaptive sampling to identify the specific information signaled by individual neural responses, a critical element missing from previous research in this area. We will use this approach to address three specific questions: (1) Perception: Are 3D objects represented in terms of their medial axis shapes? This is a long-standing theory about object representation in the brain that has never been directly tested. (2) Memory: How are memory associations between 3D viewpoints formed in IT and PR/ER? Associating different views of the same object is the most computationally difficult aspect of vision. We will perform the first direct test of the prevailing theory that viewpoint association is learned through exposure to rotating objects during natural vision. (3) Cognition: How does 3D shape information in IT and PFC relate to behavioral decisions? The ultimate utility of 3D object perception is its use in guiding decision and behavior. Our experiment will be the first attempt to show how neural coding of complex 3D shape is related to object discrimination behavior.