My interests are wide-ranging but focus on the frontal lobes. How do people and animals learn, optimize, and control goal-directed behavior in complex and changing environments? These abilities entail reinforcement learning, planning, prediction, expectation, evaluation, and sequential ordering of movements, in addition to complex sensory processing. Currently I have three main research thrusts:
- Develop computational models of brain circuitry involved in cognitive control. My recent model of the Anterior Cingulate Cortex, or ACC (Brown & Braver, 2005, Science), suggests that ACC is critically involved in predicting the likelihood of making a mistake. Current simulations further predict that ACC activity also depends on the predicted severity of the consequences of a mistake, should one occur.
- Test computational model predictions with fMRI. Computational modeling often provides counter-intuitive, non-trivial predictions that strongly guide empirical investigations. We are beginning to test whether ACC activity in healthy individuals reflects perceived behavioral risk, as predicted by the computational modeling work.
- Investigate the neural bases of cognitive impairment in clinical populations using fMRI and computational modeling. We are interested in how impairments in working memory interact with possible impairments in an individual’s ability to monitor their own behavior. Computational modeling provides a framework for understanding the nature of information processing in both normal and pathological human brains.
The College of Arts