A wealth of evidence for the automaticity of perceptual organization processes points toward the existence of a global-to-local processing bias in early perceptual stages. Global features are encoded and spontaneously reported during early conscious vision, resulting in the perception of coherent objects prior to identifying detailed information. Yet, results from experiments that presented illusory figure presentation below the perceptual threshold to study the reliance of perceptual organization on visual awareness have shown conflicting findings, leaving open the question of how global features interact during figure perception. The present study will examine the interaction between symmetry and perceptual completion under conditions of restricted awareness.

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Decoding behavioral signifiers for the brain state of vigilance can have far reaching implications for understanding actions and identifying disease. We are using high resolution video recordings of mice as they navigate a maze, but have access to very few pre-determined behavioral signifiers. Several recent publications implemented computer vision to extract a variety of previously unreachable aspects of behavioral analysis, including animal pose estimation and distinguishable internal states. These descriptions allowed for the identification and characterization of dynamics, which then revealed an unprecedented richness to the behaviors that determine decision making. Applying such computational approaches in our maze in the context of behaviors that have been validated to measure choice and memory can reveal dimensions of behavior that predict or even determine psychological constructs like vigilance. DSI scholars would use pose estimation analysis to evaluate behavioral signifiers for choice and memory and relate it to our real time concurrent measures of neural activity and transmitter release. The students would also have opportunity to examine the effect of disease models known to impair performance on our maze task on any identified signifier.

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Columbia Data Science Institute (DSI) Scholars Program

The DSI Scholars Program is to engage and support undergraduate and master students in participating data science related research with Columbia faculty. The program’s unique enrichment activities will foster a learning and collaborative community in data science at Columbia.

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