It is axiomatic to neuroscience that the brain’s information processing abilities result from the flow of information through networks of neurons interconnected by signaling junctions called synapses. Attempts to understand brain function have always been constrained, however, by the fact that these so-called “neural circuits” involve astronomically vast numbers of incredibly tiny elements packed in three dimensions at very high densities. These features of neural circuits have made the prospects for abstracting “wiring diagrams” seem very dim indeed, in spite of the obvious analytical benefits that such diagrams would confer.
Recent advances in molecular genetics and computer science are now opening up new avenues, however, and it may be time to reevaluate old conclusions about how completely brain circuitry can be known. Professor Smith will describe some of these new approaches to “reverse-engineering” neural circuitry and present some of the beautiful images that have been among the first fruits of these efforts.
Smith is Professor of Molecular and Cellular Physiology at the Stanford University School of Medicine. He earned a PhD in Physiology and Psychology at the University of Washington in 1977, was a Miller Postdoctoral Fellow at the University of California, Berkeley, 1977-1980, and then joined the Faculty of the Department of Physiology at the Yale University School of Medicine in 1980. Smith moved to Stanford in 1989. Smith’s research has focused on cellular signaling and structural dynamics in brain development and function. He has pioneered many optical measurement and imaging techniques and their applications to brain exploration.