Computational Modeling of Neurons

Kath 

Wednesdays@NICO Seminar, Noon, October 27 2010, Chambers Hall, Lower Level

Prof. William Kath, Northwestern University

Abstract

Experimental advances are rapidly revealing new insights about the workings of neurons and the networks in which they are connected. Simultaneously, computational models of neurons have grown swiftly in terms of both their capability and utility. When constrained by experimental data, such models greatly enhance the observations and provide tools to construct new experimentally testable predictions. In this talk I will describe how this two‐pronged approach has helped explain some of the function of hippocampal CA1 pyramidal neurons, a group of principal cells in a region of the brain that is important for the formation of new memories. The models and experiments indicate that these relatively large neurons integrate and process their inputs in a two‐stage manner, in that they first combine inputs in localized parts of the dendritic tree before making an ultimate determination whether or not to signal downstream neurons with an action potential. This work is joint with Professor Nelson Spruston (NBP).

Biography

Bill Kath is Professor of Engineering Sciences and Applied Mathematics in the McCormick School of Engineering at Northwestern, with additional appointments in the Department of Neurobiology and Physiology, the Northwestern Physical Sciences‐Oncology Center, and the Northwestern University Center for Photonic Communication and Computing. He is a Fellow of the Optical Society of America and the Society of Industrial and Applied Mathematics. His research interests include the mathematical and computational modeling of biological systems and rare events in optical fiber communications.