Assistant Professor, Department of Neurology
UCSF Weill Institute for Neurosciences
San Francisco, California
I develop and use computational, cutting-edge engineering, and experimental approaches to basic and applied neuroscience and build theories of brain function.
The production of flexible but controlled behavioral sequences in simpler animals may be an evolutionary foundation for higher cognitive abilities in humans. I study how real-time function emerges from the nervous system of C. elegans, a 1 millimeter long roundworm. Despite having only 302 neurons, this animal has a rich behavioral repertoire including probabilistic and directed taxis, associative learning, cooperation, and coordinated body movement. I combine dynamical systems analysis with the development and application of high-throughput, high-resolution neural activity imaging technologies to understand how this "low-n" neural network processes sensory stimuli and integrates them with an evolving internal state in order to produce competent, continuous behavior.
On an entirely different evolutionary branch, organisms acquired the ability to harness large pools of largely undifferentiated neurons and shape them through development and learning in order to flexibly solve problems and drive complex tasks, thereby getting around the limited information capacity of the genome. I am also interested in understanding how these "high-n" neural systems achieve what they do, and determining what ingredients, or rules of assembly and operation, are required in order for such sophisticated problem-solving functions to emerge.