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Dopamine regulates decision thresholds in human reinforcement learning in males

Author

Listed:
  • Karima Chakroun

    (University Medical Center Hamburg-Eppendorf)

  • Antonius Wiehler

    (Motivation, Brain and Behavior Lab, Paris Brain Institute (ICM), Pitié-Salpêtrière Hospital)

  • Ben Wagner

    (Technical University Dresden)

  • David Mathar

    (University of Cologne)

  • Florian Ganzer

    (Integrated Psychiatry Winterthur)

  • Thilo Eimeren

    (University Medical Center Cologne)

  • Tobias Sommer

    (University Medical Center Hamburg-Eppendorf)

  • Jan Peters

    (University Medical Center Hamburg-Eppendorf
    University of Cologne)

Abstract

Dopamine fundamentally contributes to reinforcement learning, but recent accounts also suggest a contribution to specific action selection mechanisms and the regulation of response vigour. Here, we examine dopaminergic mechanisms underlying human reinforcement learning and action selection via a combined pharmacological neuroimaging approach in male human volunteers (n = 31, within-subjects; Placebo, 150 mg of the dopamine precursor L-dopa, 2 mg of the D2 receptor antagonist Haloperidol). We found little credible evidence for previously reported beneficial effects of L-dopa vs. Haloperidol on learning from gains and altered neural prediction error signals, which may be partly due to differences experimental design and/or drug dosages. Reinforcement learning drift diffusion models account for learning-related changes in accuracy and response times, and reveal consistent decision threshold reductions under both drugs, in line with the idea that lower dosages of D2 receptor antagonists increase striatal DA release via an autoreceptor-mediated feedback mechanism. These results are in line with the idea that dopamine regulates decision thresholds during reinforcement learning, and may help to bridge action selection and response vigor accounts of dopamine.

Suggested Citation

  • Karima Chakroun & Antonius Wiehler & Ben Wagner & David Mathar & Florian Ganzer & Thilo Eimeren & Tobias Sommer & Jan Peters, 2023. "Dopamine regulates decision thresholds in human reinforcement learning in males," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-41130-y
    DOI: 10.1038/s41467-023-41130-y
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    References listed on IDEAS

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    1. Nitzan Shahar & Tobias U Hauser & Michael Moutoussis & Rani Moran & Mehdi Keramati & NSPN consortium & Raymond J Dolan, 2019. "Improving the reliability of model-based decision-making estimates in the two-stage decision task with reaction-times and drift-diffusion modeling," PLOS Computational Biology, Public Library of Science, vol. 15(2), pages 1-25, February.
    2. Jan Peters & Mark D’Esposito, 2020. "The drift diffusion model as the choice rule in inter-temporal and risky choice: A case study in medial orbitofrontal cortex lesion patients and controls," PLOS Computational Biology, Public Library of Science, vol. 16(4), pages 1-25, April.
    3. Mathias Pessiglione & Ben Seymour & Guillaume Flandin & Raymond J. Dolan & Chris D. Frith, 2006. "Dopamine-dependent prediction errors underpin reward-seeking behaviour in humans," Nature, Nature, vol. 442(7106), pages 1042-1045, August.
    4. Maël Lebreton & Sophie Bavard & Jean Daunizeau & Stefano Palminteri, 2019. "Assessing inter-individual differences with task-related functional neuroimaging," Nature Human Behaviour, Nature, vol. 3(9), pages 897-905, September.
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