Research

The brain’s fine-scale structure is naturally described in the language of physics, biochemistry, and cellular biology, whereas its large-scale structure is more easily framed by concepts from psychology, machine learning, and artificial intelligence. This is a very exciting time for neuroscience because experimenters are increasingly able to measure circuit-level phenomena that are poised to bridge the gap between low-level and high-level descriptions of the brain. Coordinated theoretical progress is needed to transform these data into hypotheses, theories, and principles of brain function.

Our research combines first-principles theory, phenomenological modeling, data analysis, and experimental design to build theoretical frameworks and data-driven models that advance the frontiers of neuroscience. We seek a multiscale understanding of the brain and ask questions that link across scales. We also seek general principles, which should illuminate the details of specific systems and direct broad thinking about the brain. Our integrative goals lead us to work on a wide variety of neuroscience problems, brain systems, and animal models. These efforts are closely coordinated with experimental work from collaborators around the world.