Cognition is a primary function of the human brain. If cognition can be concisely described with a mathematically-specific description, then these equations provide large-scale constraints on the collective activity of large numbers of neurons. Similarly, the observed behavior of ensembles of neurons places constraints on mathematical models of cognition.

The goal is to develop physically-constrained models of cognition, with special attention to learning and memory. Our theoretical work makes use of mathematical analysis and computational tools. We do collaborative empirical work with cognitive and systems neuroscientists to constrain theories. We have recently begun collaborative work applying ideas from cognitive science and neuroscience to machine learning. See the research page for more details.

Because of the interdisciplinary nature of the work we do, successful students need to have a variety of skills. Students in Psychological and Brain Sciences need to have some technical competency (math beyond calculus and/or programming experience). Students with a technical background (physics, computer science, engineering) need to have at least a strong interest in cognitive science. See the people page for current and past lab members.