Rice University

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Electrical and Computer Engineering
Digital Signal Processing
IEEE Signal Processing Society

Speaker: Bruno Olshausen
Professor, Helen Wills Neuroscience Institute and School of Optometry
Director, Redwood Center for Theoretical Neuroscience

University of California - Berkeley

Do V1 neurons have receptive fields?

Thursday, March 13, 2014
4:00 PM  to 5:00 PM

1064  George R. Brown Hall
Rice University
6100 Main St
Houston, Texas, USA

The idea that the response properties of visual neurons may be characterized in terms of ‘receptive fields’ is widely accepted by much of the vision science community, and it has inspired the computational architecture of state of the art computer vision systems (so-called ‘deep nets’). Yet a closer examination of how neurons actually respond to time-varying natural scenes, the complex neural architecture of visual cortex, and the biophysical properties of dendritic trees, leads us to question this conventional wisdom. Here I will present neurophysiological evidence that V1 response properties require a different way of thinking about what these neurons are doing that goes beyond the traditional receptive field concept. I shall describe one possible framework based on inferential computations. Neural models of perceptual inference rely heavily upon recurrent computation in which information propagates both within and between levels of representation in a bi-directional manner. The inferential framework shifts us away from thinking of ‘receptive fields’ and ‘tuning’ of individual neurons, and instead toward how populations of neurons interact via horizontal and top-down feedback connections to perform collective computations.

Host: Richard Baraniuk

Biography of Bruno Olshausen:
Bruno Olshausen received B.S. and M.S. degrees in Electrical Engineering from Stanford University, and a Ph.D. in Computation and Neural Systems from the California Institute of Technology. He did his postdoctoral work in the Department of Psychology at Cornell University, and at the Center for Biological and Computational Learning at the Massachusetts Institute of Technology. He joined the faculty at the University of California at Davis in 1996, and in 2005 moved to UC Berkeley, where he is currently Professor of Neuroscience and Optometry. He also directs the Redwood Center for Theoretical Neuroscience, a multidisciplinary group focusing on building mathematical and computational models of brain function.

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