Human choice behavior often reflects a competition between inflexible computationally efficient control on the one hand and a slower more flexible system of control on the other. This distinction is well captured by model-free and model-based reinforcement learning algorithms. Here, studying human subjects, we show it is possible to shift the balance of control between these systems by disruption of right dorsolateral prefrontal cortex, such that participants manifest a dominance of the less optimal model-free control. In contrast, disruption of left dorsolateral prefrontal cortex impaired model-based performance only in those participants with low working memory capacity.
Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.