Our goal is to understand fundamental principles for the function and organization of neuronal circuits in the mammalian cortex. We investigate how circuits perform computations involved in working memory and decision-making, especially in the context of spatial navigation.

Our approach is based on connecting properties of neuronal circuit function with behavior in the mouse. We utilize a variety of experimental methods to study activity dynamics in circuits and the relationship between circuit dynamics and architecture. Recently, we have initiated efforts to combine our experimental program with a program for computational and theoretical modeling. Together our approach emphasizes the dynamics and the mechanisms by which circuits perform computations (how does a circuit compute?) and, to a lesser extent, also aims to identify the computations performed in specific circuits (what does a circuit compute?).

Current work in the lab focuses in large part on the posterior parietal cortex (PPC), which is thought to be a key interface between sensory and motor information, including during working memory, decision-making, and navigation. Current projects emphasize a variety of questions. First, we aim to identify the fundamental activity patterns in the PPC during complex behaviors and the mechanisms by which these activity patterns are generated. We investigate PPC activity dynamics using measurements of activity in large neuronal populations during behavior, controlled manipulations of PPC activity to reveal key features of dynamics in PPC populations, and studies of how activity patterns develop during learning of new behavioral tasks. Second, we aim to understand how dynamics in the PPC arise from the underlying microcircuit architecture. We are developing approaches to map features of microcircuit architecture in neuronal populations that have been functionally characterized to aid understanding of circuit-level structure-function relationships. Third, we are studying how the PPC interacts with other brain areas in a larger network for complex computations. We utilize experiments to manipulate and monitor specific input and output pathways of the PPC.

Experiments in the lab are centered around behavioral, optical, and electrophysiological approaches. We train mice to perform perceptual decision-making and working memory tasks based on navigation through virtual reality environments. As mice perform tasks, we measure neuronal activity using sub-cellular resolution two-photon calcium imaging, large scale extracellular electrophysiology, and whole-cell patch-clamp recordings. We also probe circuit properties using simultaneous activity manipulations and activity measurements. In addition, we have a long-standing interest in developing novel approaches to study principles of neuronal circuit function and in establishing methods to expand the range of behaviors and computations that can be studied in the mouse model system. Currently, the lab is pursuing ways to combine data collected through experiments with the development of computational models, with the goal of establishing a tight experiment-theory loop.

The lab is composed of researchers with wide ranging and complementary skills and training. We aim to assemble a team that through intra-lab collaborative efforts will utilize interdisciplinary approaches and thinking to establish new ideas on the function of cortical circuits. Therefore, lab members with diverse backgrounds, including in experiment and computation, are highly valued.