Jason M Samonds
Visual perception is an interactive process involving prediction, identification, classification, and decision or reaction. My interest is in understanding how the visual cortex takes local information and forms a global percept. Specifically, how does the cortex integrate distributed signals in order to identify correlations and patterns among those local cues? The problem is compounded by the fact that patterns and objects are typically embedded within an environment that also contains structure and correlation. We use knowledge from natural scene statistics, psychophysical data, and computer vision algorithms to formulate hypotheses, and we employ rigorous statistical analyses on simultaneous recordings and imaging from multiple neurons distributed across the cortical network. Our results provide us with clues on how the brain is able to segment and identify objects, as well as reveal properties of the underlying cortical mechanisms.