Neural Mechanisms of Categorical Decisions and Learning During Saccade-Based Visual Foraging - Summary and Relevance of Proposed Research Humans have a remarkable capacity to learn to recognize the significance of visual 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 learn about the meaning of the stimuli that we encounter, and it enables us to make appropriate decisions. Our recent work examined the roles of a network of cortical and subcortical areas to visual category decisions, including posterior parietal cortex (PPC), frontal eye field (FEF), and superior colliculus (SC). However, those previous studies only examined these regions after weeks or months of training required to learn the categorization tasks. The long training required to learn those tasks precluded studying mechanisms by which neural category encoding developed during the learning process itself. This project develops a novel paradigm for studying rapid within-session category learning using a saccade-based foraging paradigm which takes advantage of subjects’ innate ability to search among arrays of visual stimuli with saccades. In this paradigm, subjects are presented with arrays of stimuli belonging to two or three categories, with each category associated with a different reward amount. Subjects must search or “forage” among stimuli by making self-guided saccades to obtain the reward associated with each target image. During foraging-based learning, population recordings will monitor PPC, SC, FEF, and orbitofrontal cortex (OFC). We will also assess the causal contributions of these regions using reversible inactivation during task performance. This will determine how interactions between neurons in these regions enable rapid category learning and transforming category recognition into stimulus selection and saccadic motor plans. 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.
