Dr. White heads the Section on Neural Function at the National Institute of Mental Health. He received a Ph.D. in the Neural Sciences from Washington University in St. Louis and conducted postdoctoral research at Yale University. Since coming to NIMH in 2002, his laboratory has developed numerous genetic tools for refined circuit-mapping in the brain of the fruit fly, Drosophila melanogaster. Following Niko Tinbergen, his laboratory is interested in applying these tools to understanding the function, development, and evolution of the neural circuitry governing molting behaviors in the fly. The laboratory combines state-of-the-art methods for monitoring and manipulating brain activity with computational tools for analyzing and modeling behavior and circuit function. Dr. White was promoted to Senior Investigator at NIMH in 2010 and was appointed Chief of the Laboratory of Molecular Biology in 2011.
My laboratory is interested in understanding how nervous systems generate behavior. Using genetically encoded tools to monitor and functionally manipulate targeted neurons in the brain of the fruit fly, Drosophila melanogaster, we seek to understand how neural networks integrate information from the environment and the body to orchestrate ordered motor sequences. Our efforts focus primarily on the stereotyped behavioral sequences used by fruit flies to molt, a process that involves first loosening, and then shedding, an old exoskeleton, and finally expanding and hardening a new one. Studying the neural basis of these behaviors allows us to answer basic questions about how motor sequences are initiated, sustained, and terminated and how their component programs are assembled and temporally organized by the nervous system. Because molting is under both hormonal and environmental control, we are also able to analyze the mechanisms by which intrinsic and extrinsic influences are weighed by the nervous system to generate behavioral decisions, and to determine how behavioral priorities can be altered by hormone-induced transitions in brain state. We seek answers at the level of circuit architecture and dynamics, but are also interested in developing testable models that expose the underlying neural computations.