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Name, Field, Position, Department, and Keyword |
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Faculty associated with: Mark V. Albert,   Sherry X. Xian Keywords: Computational Neuroscience (13), Systems Neuroscience (25), Vision (11) What is the goal of sensory coding? What are the statistical regularities in natural scenes, and how do they relate to the response properties of cortical cells? We investigate these and other questions from a combination of psychophysical and computational approaches |
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Graduate Student associated with: David J. Field Keywords: Computational Neuroscience (13), Mathematical Modeling (14), Vision (11) By evolution and experience, animal visual processing has adapted to the statistics of our natural environment to maximize both speed and metabolic efficiency. This has lead to complex visual systems with striking regularities among many animal species in terms of early cortical and pre-cortical coding. It is critical to our understanding that we establish the link between the guiding principles of computational efficiency and this resulting neural code. The primary approach I am taking involves studying the statistics of natural scenes to explain the response properties of neurons in early visual cortex. Currently, I am exploring ways of extending neurally-relevant efficient encoding techniques with linear spatial filters to various classes of nonlinear spatiotemporal filters. The intention is to explain cortical nonlinearities from an ecological efficiency perspective. Also visit my 5 Research/Photo Gallery entries |
Please report corrections, questions, comments, and problems to: Lori Miller (lmm8 AT cornell.edu)