The role of the ventromedial prefrontal cortex in abstract state-based inference during decision making in humans
Many real-life decision-making problems incorporate higher-order structure, involving interdependencies between different stimuli, actions, and subsequent rewards. It is not known whether brain regions implicated in decision making, such as the ventromedial prefrontal cortex (vmPFC), use a stored model of the task structure to guide choice (model-based decision making) or merely learn action or state values without assuming higher-order structure as in standard reinforcement learning. To discriminate between these possibilities, we scanned human subjects with functional magnetic resonance imaging while they performed a simple decision-making task with higher-order structure, probabilistic reversal learning. We found that neural activity in a key decision-making region, the vmPFC, was more consistent with a computational model that exploits higher-order structure than with simple reinforcement learning. These results suggest that brain regions, such as the vmPFC, use an abstract model of task structure to guide behavioral choice, computations that may underlie the human capacity for complex social interactions and abstract strategizing. Copyright © 2006 Society for Neuroscience.
Computation and Neural Systems Program, California Institute of Technology, Pasadena, CA 91125, United States Division of Humanities and Social Sciences, California Institute of Technology, Pasadena, CA 91125, United States Division of Humanities and Social Sciences, California Institute of Technology, M/C 228-77, 1200 East California Boulevard, Pasadena, CA 91125, United States
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Cited By (since 1996): 17
Export Date: 10 March 2008
Record created on 2008-03-12, modified on 2016-08-08