We study neural coding and computation from a theoretical perspective with particular emphasis on probabilistic reasoning and decision making under uncertainty, complex behavioral modeling, computational models of cortical circuits and circuit function, dynamics of spiking neural networks, and statistical analysis of neural and behavioral data. Previous work has been largely concerned with sensory-motor transformations and neural representations of complex stimuli such as odors. More recently, we have been focusing on developing non-linear latent state space models of neural networks as standard linear models are incapable of generating even very simple behaviors.
Education and Training
- Northwestern University, Ph.D. 2003
Associated Faculty Labs
Selected Grants and Awards
- Department of Neurobiology