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Published on: October 4, 2021
L-DOPA reduces model-free control of behavior by attenuating the transfer of value to action
Nils B Kroemer1, Ying Lee2, Shakoor Pooseh3
1Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany; Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany.
Abstract:
Dopamine is a key neurotransmitter in action control. However, influential theories of dopamine function make conflicting predictions about the effect of boosting dopamine neurotransmission. Here, we tested if increases in dopamine tone by administration of L-DOPA upregulate reward learning as predicted by reinforcement learning theories, and if increases are specific for deliberative "model-based" control or reflexive "model-free" control. Alternatively, L-DOPA may impair learning as suggested by "value" or "thrift" theories of dopamine. To this end, we employed a two-stage Markov decision-task to investigate the effect of L-DOPA (randomized cross-over) on behavioral control while brain activation was measured using fMRI. L-DOPA led to attenuated model-free control of behavior as indicated by the reduced impact of reward on choice. Increased model-based control was only observed in participants with high working memory capacity. Furthermore, L-DOPA facilitated exploratory behavior, particularly after a stream of wins in the task. Correspondingly, in the brain, L-DOPA decreased the effect of reward at the outcome stage and when the next decision had to be made. Critically, reward-learning rates and prediction error signals were unaffected by L-DOPA, indicating that differences in behavior and brain response to reward were not driven by differences in learning. Taken together, our results suggest that L-DOPA reduces model-free control of behavior by attenuating the transfer of value to action. These findings provide support for the value and thrift accounts of dopamine and call for a refined integration of valuation and action signals in reinforcement learning models.
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