Broad Area Colloquium For AI-Geometry-Graphics-Robotics-Vision

Does the Visual System Predict the Future or the Past?

Terrence J. Sejnowski
Salk Institute for Biological Studies
Howard Hughes Medical Institute

Monday, May 7, 2001, 4:15PM


In the flash-lag illusion, a flash and a moving object in the same location appear to be offset. I will present a series of psychophysical experiments that yield data inconsistent with two previously proposed explanations, motion extrapolation (a predictive model), and latency difference (an on-line model). The evidence points toward an alternative model, consistent with other experiments such as backward masking: visual awareness is neither predictive nor on-line, but is instead postdictive, such that the percept attributed to the time of the flash is a function of events that happen in the ~80 ms following the flash. An explanation for this conclusion can be found in the way that the visual system is organized to handle temporal order.

About the Speaker

Terrence Sejnowski is an Investigator with the Howard Hughes Medical Institute and a Professor at The Salk Institute for Biological Studies where he directs the Computational Neurobiology Laboratory. He is also Professor of Biology and Adjunct Professor in the Departments of Physics, Neurosciences, Psychology, Cognitive Science, and Computer Science and Engineering at the University of California, San Diego, where he is Director of the Institute for Neural Computation.

Dr. Sejnowski received B.S. in physics from the Case-Western Reserve University, M.A. in physics from Princeton University, and a Ph.D. in physics from Princeton University in 1978.

From 1978-1979 Dr. Sejnowski was a postdoctoral fellow in the Department of Biology at Princeton University and from 1979-1982 he was a postdoctoral fellow in the Department of Neurobiology at Harvard Medical School. In 1982 he joined the faculty of the Department of Biophysics at the Johns Hopkins University, where he achieved the rank of Professor before moving to San Diego in 1988. He has had a long-standing affiliation with the California Institute of Technology, as a Wiersma Visiting Professor of Neurobiology in 1987, as a Sherman Fairchild Distinguished Scholar in 1993 and as a part-time Visiting Professor 1995-1998.

Dr. Sejnowski received a Presidential Young Investigator Award in 1984. He received the Wright Prize from the Harvey Mudd College for excellence in interdisciplinary research in 1996 and the Hebb Prize for his contributions to learning algorithms by the International Neural Network Society in 1999. He was elected Fellow of the Institute of Electrical and Electronics Engineers in 2000.

In 1989, Dr. Sejnowski founded Neural Computation, published by the MIT Press, the leading journal in the area of neural networks and computational neuroscience. He is also the President of the Neural Information Processing Systems Foundation, a non-profit organization that oversees the annual NIPS Conference. This interdisciplinary meeting brings together researchers from many disciplines, including biology, physics, mathematics and engineering.

The long-range goal Dr. Sejnowski's research is to build linking principles from brain to behavior using computational models. This goal is being pursued with a combination of theoretical and experimental approaches at several levels of investigation ranging from the biophysical level to the systems level. Hippocampal and cortical slice preparations are being used to explore the properties of single neurons and synapses. Biophysical models of electrical and chemical signal processing within neurons are used as an adjunct to physiological experiments. The dynamics of network models are studied to explore how populations of neurons interact during states of alertness and sleep. In particular, his research has focused on how sensory information is represented in the visual cortex, primarily of form, motion, and binocular vision, and how sensorimotor transformations are performed. His laboratory has developed new methods for analyzing the sources for electrical and magnetic signals recorded from the scalp and hemodynamic signals from functional brain imaging.


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