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How instructed knowledge modulates the neural systems of reward learning.

ABSTRACT: Recent research in neuroeconomics has demonstrated that the reinforcement learning model of reward learning captures the patterns of both behavioral performance and neural responses during a range of economic decision-making tasks. However, this powerful theoretical model has its limits. Trial-and-error is only one of the means by which individuals can learn the value associated with different decision options. Humans have also developed efficient, symbolic means of communication for learning without the necessity for committing multiple errors across trials. In the present study, we observed that instructed knowledge of cue-reward probabilities improves behavioral performance and diminishes reinforcement learning-related blood-oxygen level-dependent (BOLD) responses to feedback in the nucleus accumbens, ventromedial prefrontal cortex, and hippocampal complex. The decrease in BOLD responses in these brain regions to reward-feedback signals was functionally correlated with activation of the dorsolateral prefrontal cortex (DLPFC). These results suggest that when learning action values, participants use the DLPFC to dynamically adjust outcome responses in valuation regions depending on the usefulness of action-outcome information.

SUBMITTER: Li J

PROVIDER: S-EPMC3017128 | biostudies-other | 2011 Jan

REPOSITORIES: biostudies-other

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How instructed knowledge modulates the neural systems of reward learning.

Li Jian J Delgado Mauricio R MR Phelps Elizabeth A EA

Proceedings of the National Academy of Sciences of the United States of America 20101220 1

Recent research in neuroeconomics has demonstrated that the reinforcement learning model of reward learning captures the patterns of both behavioral performance and neural responses during a range of economic decision-making tasks. However, this powerful theoretical model has its limits. Trial-and-error is only one of the means by which individuals can learn the value associated with different decision options. Humans have also developed efficient, symbolic means of communication for learning wi ...[more]

PMID: 21173266

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Project description:Instructions have a powerful effect on learning and decision-making, biasing choice even in the face of disconfirming feedback. Detrimental biasing effects have been reported in a number of studies in which instruction was given prior to trial-and-error learning. Previous work has attributed individual differences in instructional bias to variations in prefrontal and striatal dopaminergic genes, suggesting a role for prefrontally-mediated cognitive control processes in biasing learning. The current study replicates and extends these findings. Human subjects performed a probabilistic reinforcement learning task after receiving inaccurate instructions about the quality of one of the options. In order to establish a causal relationship between prefrontal cortical mechanisms and instructional bias, we applied transcranial direct current stimulation over dorsolateral prefrontal cortex (anodal, cathodal, or sham) while subjects performed the task. We additionally genotyped subjects for the COMT Val158Met genetic polymorphism, which influences the breakdown of prefrontal dopamine, and for the DAT1/SLC6A3 variable number tandem repeat, which affects expression of striatal dopamine transporter. We replicated the finding that the COMT Met allele is associated with increased instructional bias and further demonstrated that variation in DAT1 has similar effects to variation in COMT, with 9-repeat carriers demonstrating increased bias relative to 10-repeat homozygotes. Consistent with increased top-down regulation of reinforcement learning, anodal subjects demonstrated greater bias relative to sham, though this effect was present only early in training. In contrast, there was no effect of cathodal stimulation. Finally, we fit computational models to subjects' data to better characterize the mechanisms underlying instruction bias. A novel choice bias model, in which instructions influence decision-making rather than learning, was found to best account for subjects' behavior. Overall, these data provide further evidence for the role of frontostriatal interactions in biasing instructed reinforcement learning, which adds to the growing literature documenting both costs and benefits of cognitive control.

Dataset Information

How instructed knowledge modulates the neural systems of reward learning.

Publications

How instructed knowledge modulates the neural systems of reward learning.

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