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Stephanie Palmer is an Associate Professor at the University of Chicago, specializing in how populations of neurons collectively encode information from sensory inputs and perform computational tasks related to signals. Her research encompasses the examination of various systems, including predictive coding in the retina and visual cortex of rodents, as well as motion coding in the area MT and temporal coding in the zebra finch song system. Through her collaborations with experimentalists, Palmer investigates general principles of neural population coding, particularly how neurons are optimized to predict future inputs, and how information is represented in a combinatorial manner across neural populations. She has a background in Chemical Physics (BS from Michigan State University) and Theoretical Physics (DPhil from the University of Oxford), along with a Postdoctoral experience in Neuroscience from the University of California, San Francisco. Palmer's work emphasizes the relationship between dynamics in coding and behavior, aiming to test and refine theories in the field with precise experimental measurements.
Department of Philosophy