An important component of healthy human brain function is inhibitory control, the ability to stop the currently adopted behavioral strategies in response to changing task demands. Traditionally, it has been thought that the capacity for inhibitory control is fairly stable in an individual; however, recent experimental data have revealed that human subjects readily alter their measured inhibitory control capacity in response to environmental changes. In this proposal, Dr. Angela Yu of the University of California, San Diego and Dr. Chiang-Shan Li of Yale University will use a new computational framework to account for such flexibility in terms of the underlying component processes in the brain. They will record brain activity from the volunteers when they must interrupt a habitual response and utilize a Bayesian ideal observer framework to model subjects, internal representation of the task demands, and dynamic adjustment of that representation and consequent changes in behavioral strategy based on experienced outcomes. This project is expected to facilitate an integrated theoretical and neurobiological understanding of human cognitive control as a more dynamic and adaptive phenomenon than traditionally envisioned.
Deficits in inhibitory control afflict a number of psychiatric conditions, such as attention deficit hyperactivity disorder, depression, drug abuse, and obsessive-compulsive disorder. Understanding the brain's computational and organizational principles underlying inhibitory control would help to unravel how malfunctions of the underlying components may lead to different types of pathology, a focus of Dr. Li's current research. This proposal will allow Dr. Yu to continue to train graduate and undergraduate students in cognitive neuroscience research and, in particular, to support women scientists, who are under-represented in this field. This effort will also allow Dr. Li to broaden his participation in the Perspectives in Science and Engineering, a research program at Yale University dedicated to training undergraduates with advanced knowledge in science and engineering. Finally, Dr. Yu and Dr. Li will participate in the big data sharing effort by making the data available to support other efforts that aim to make use of real data in the teaching of STEM-related courses and to enable participation in discovery science by those who would otherwise have no access to such data.
