Eric Shea-Brown

Applications in Life Sciences
Statistical Methodology

I am an associate professor at the University of Washington Applied Mathematics Department, adjunct in the Department of Physiology and Biophysics, and a member of the Program in Neurobiology and Behavior.

Our work is on the nonlinear dynamics of neurons, neural networks, and neural populations. These dynamics are beautiful, and are richly varied from setting to setting – at times governed by mechanisms we can distill and explain and at times eluding our best analytical tools. Beyond explaining the emergent dynamics of neural circuits, we want to understand how they encode and make decisions about the sensory world. Making progress on these twin problems requires a range of perspectives and methods. We delight in collaboration with fellow theorists of many different backgrounds, and with cognitive neuroscientists, clinicians, and electrophysiologists. Our methods blend data analysis, dynamical systems, stochastic processes, and information theory – and treat neural dynamics occurring on a number of spatial and temporal scales.

Our group is supported by the Burroughs-Wellcome Fund (BWF) Scientific Interfaces Program, the NSF, the NIH, and the Pacific Northwest Center for Neural Engineering.

Before coming to UW, I was a postdoctoral fellow in mathematical neuroscience in the group of Prof. John Rinzel, at NYU’s Courant Institute and Center for Neural Science. In 2004, I completed my Ph.D in Princeton’s Program in Applied and Computational Mathematics, advised by Prof. Phil Holmes and co-advised by Prof. Jonathan Cohen. At Princeton I also worked closely with Prof. Hersch Rabitz, and other wonderful faculty. My graduate work was supported by the National Science Foundation, the Burroughs-Wellcome Fund, and Princeton’s Graduate School. Before I moved to Princeton, I worked at the Lawrence Livermore National Laboratory and studied Engineering Physics at UC-Berkeley.