Graduate Training in Neuroscience
University of Washington
Assistant Professor, Department of Applied Mathematics
My interests are in computational and theoretical neuroscience. Current and recent projects model neural systems on two different scales. First, at the level of large-scale statistical descriptions of neural populations, we focus on idealized network models for sensory discrimination and interval timing tasks. A key issue here is the development and impact of correlated neural activity across different cells in the networks. Second, at the finer-scale level of individual spike times, we are studying circuit-based mechanisms that determine the repeatability of spike trains across multiple stimulus presentations. Throughout, we use tools from dynamical systems, stochastic processes, and scientific computing, and work closely with colleagues performing physiological and psychophysical experiments.