Bruno Olshausen

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Reveal Contact Info

Professor

Helen Wills Neuroscience Institute and School of Optometry

Olshausen Lab

Current Research

How does the brain build representations of 3D surfaces, material properties, objects, and motion from the voltage fluctuations of photoreceptors in the retina? Somehow, nature has figured out a solution to this daunting problem. The desire to solve this puzzle—reverse engineering nature’s solution—is what drives my research. While neurophysiological and neuroanatomical studies over the past four decades have revealed much about the structure and function of the visual system, this approach alone will not solve the puzzle. The problem we currently face in neuroscience is not a lack of data, but rather the inability to ask the right questions. The reason for this is that we do not have a proper theoretical framework for guiding our thinking. If we knew what were the basic principles that allow a system to ‘see’, then we would know what components to look for. But currently we do not have such principles. For this reason, I am focusing my efforts on developing new theoretical frameworks and models of vision that could help guide our thinking in experimental neuroscience.

Background

I started out as an engineer wanting to build robots inspired by how brains work, and I ended up as a neuroscientist attempting to understand how nervous systems process information, inspired and guided by engineering principles. I first learned about neural networks as a student at Stanford, through Bernie Widrow’s course on Adaptive Filters and Misha Pavel and Ilan Vardi’s Connectionist Models seminar (1986/87). I then found my way to Pentti Kanerva’s Sparse Distributed Memory (SDM) research group at NASA/Ames, where I worked for two years as a research assistant to develop vision applications of SDM. During this time I learned about Charlie Anderson and David Van Essen’s work on ‘shifter circuits,’ which eventually led to my doing a Ph.D. under their joint supervision as a student in the CNS program at Caltech (1989-1994). My thesis was on dynamic routing circuits, essentially a generalization of shifter circuits which could serve as a neural mechanism for forming position and size (and rotation) invariant representations in the visual cortex. Toward the end of my thesis work I learned about David Field’s work on models of sensory coding based on natural image statistics, which seemed like a promising way to learn feature representations at various stages of the cortical hierarchy. One of my goals ever since has been to bring these two ideas together – dynamic routing and feature learning – to build a hierarchical model of the visual cortex. My first faculty job was at UC Davis, initially in Psychology and then Neurobiology, Physiology and Behavior, along with the Center for Neuroscience, from 1996-2005. Along with Pentti Kanerva and Fritz Sommer, I helped Jeff Hawkins to launch the Redwood Neuroscience Institute in 2002. This was incorporated into UC Berkeley’s program in 2005, where I have remained since. I am currently Professor in the Helen Wills Neuroscience Institute and the School of Optometry, and I direct the Redwood Center for Theoretical Neuroscience.