Cortical Mechanisms of Visual Category Recognition and Learning

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Summary and Relevance of Proposed Research Humans have an impressive capacity to recognize the category membership of sensory stimuli. This ability, which is disrupted by a brain-based diseases and conditions such as Alzheimer’s disease, schizophrenia, stroke, and attention deficit disorder, is critical because it allows us to respond appropriately to the stimuli and events that we encounter in the environment. We are not born with an innate library of categories, such as “tables” and “chairs”, which we are preprogrammed to recognize. Instead, we learn to recognize familiar categories through experience. Our recent work has shown that both the posterior parietal cortex (PPC) and prefrontal cortex (PFC) are involved in categorical decisions. We recorded from neurons in PPC and PFC during performance of visual motion categorization tasks. These recordings revealed that neurons in both areas robustly encoded stimuli according to their learned category membership, suggesting that both regions are involved in computing and representing abstract categorical information about visual stimuli. We also showed that activity in PPC is causally related to categorical decisions, using reversible inactivation. This project uses novel brain recording techniques to monitor the activity of large neuronal populations of neurons in the lateral intraparietal area, frontal eye field, and superior colliculus during visual categorical decisions. This will allow us to gain a mechanistic understanding of how interactions between neurons in these three regions enable computations which transform visual feature encoding into categorical decisions. This work will also determine how multiple behavioral functions are mediated by this brain network, including eye movements and spatial attention, as well assess the causal significance of each brain area to categorical decisions. While much is known about how the brain processes visual features (such as color, orientation, and direction of motion), less is known about how the brain learns and represents the meaning, or category, of stimuli. A greater understanding of visual categorization is critical for addressing a number of brain diseases and conditions (e.g. stroke, Alzheimer’s disease, attention deficit disorder, schizophrenia, and stroke) that leave patients impaired in everyday tasks that require visual learning, recognition and/or evaluating and responding appropriately to sensory information. The long-term goal of this project is to guide the next generation of treatments for these brain-based diseases and disorders by helping to develop a detailed understanding of the brain mechanisms that underlie learning, memory and recognition. These studies also have relevance for understanding and addressing learning disabilities, such as attention deficit disorder and dyslexia, which affect a substantial fraction of school age children and young adults. Thus, a detailed understanding of the basic brain mechanisms of categorical decisions and attention will likely give important insights into the causes and potential treatments for disorders involving these cognitive and perceptual abilities.