Suspicious Coincidences in the Brain
Terrence J. Sejnowski
Howard Hughes Medical Institute
Salk Institute for Biological Studies
University of California, San Diego
February 24, 2012
2:00 - 3:00 pm
Davis Auditorium, Fletcher Allen
Brains need to make quick sense of massive amounts of ambiguous information with minimal energy costs and have evolved an intriguing mixture of analog and digital mechanisms to allow this efficiency. Analog electrical and biochemical signals inside neurons are used for integrating synaptic inputs from other neurons. The digital part is the all-or-none action potential, or spike, that lasts for a millisecond or less and is used to send messages over a long distance. Spike coincidences occur when neurons fire together at nearly the same time. In this lecture I will show how rare spike coincidences can be used efficiently to represent important visual events and how this architecture can be implemented with analog VLSI technology to simplify the early stages of visual processing.
Terrence Sejnowski is the Francis Crick Professor at The Salk Institute for Biological Studies where he directs the Computational Neurobiology Laboratory, an Investigator with the Howard Hughes Medical Institute, and a Professor of Biology and Computer Science and Engineering at the University of California, San Diego, where he is Co-Director of the Institute for Neural Computation. The long-range goal of Dr. Sejnowski's laboratory is to understand the computational resources of brains and 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. 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 by blind separation using independent components analysis (ICA). Dr. Sejnowski has published over 300 scientific papers and 12 books, including The Computational Brain, with Patricia Churchland. He received the Wright Prize for Interdisciplinary research in 1996, the Hebb Prize from the International Neural Network Society in 1999, and the IEEE Neural Network Pioneer Award in 2002. He was elected an IEEE Fellow in 2000, an AAAS Fellow in 2006, to the Institute of Medicine in 2008, the National Academy of Sciences in 2010 and the National Academy of Engineering in 2011.