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Dopamine-dependent prediction errors underpin reward-seeking behaviour in humans

Author

Listed:
  • Mathias Pessiglione

    (Wellcome Department of Imaging Neuroscience)

  • Ben Seymour

    (Wellcome Department of Imaging Neuroscience)

  • Guillaume Flandin

    (Wellcome Department of Imaging Neuroscience)

  • Raymond J. Dolan

    (Wellcome Department of Imaging Neuroscience)

  • Chris D. Frith

    (Wellcome Department of Imaging Neuroscience)

Abstract

Dopamine by Choice The brain messenger dopamine is traditionally known as the 'pleasure molecule', linked with our desire for food and sex, as well as drug and gambling addictions. The precise function of dopamine in humans has remained elusive, and theories have relied almost exclusively on animal experiments. Using brain imaging technology, Pessiglione et al. scanned healthy human volunteers as they gambled for money after taking drugs that interfere with dopamine signals. Volunteers with boosted dopamine became better gamblers than their dopamine-suppressed counterparts. When dopamine levels were either enhanced or reduced by drugs, the scans showed that both reward-related learning and associated striatal activity are modulated, confirming the critical role of dopamine in integrating reward information for generation future decisions.

Suggested Citation

  • 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.
    • Handle: RePEc:nat:nature:v:442:y:2006:i:7106:d:10.1038_nature05051
    DOI: 10.1038/nature05051
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    Cited by:

    1. Necker, Sarah & Ziegelmeyer, Michael, 2016. "Household risk taking after the financial crisis," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 141-160.
    2. Kuhnen, Camelia M. & Miu, Andrei C., 2017. "Socioeconomic status and learning from financial information," Journal of Financial Economics, Elsevier, vol. 124(2), pages 349-372.
    3. Tal Neiman & Yonatan Loewenstein, 2011. "Reinforcement learning in professional basketball players," Discussion Paper Series dp593, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
    4. Filip Grill & Marc Guitart-Masip & Jarkko Johansson & Lars Stiernman & Jan Axelsson & Lars Nyberg & Anna Rieckmann, 2024. "Dopamine release in human associative striatum during reversal learning," Nature Communications, Nature, vol. 15(1), pages 1-9, December.
    5. Antoine Collomb-Clerc & Maëlle C. M. Gueguen & Lorella Minotti & Philippe Kahane & Vincent Navarro & Fabrice Bartolomei & Romain Carron & Jean Regis & Stephan Chabardès & Stefano Palminteri & Julien B, 2023. "Human thalamic low-frequency oscillations correlate with expected value and outcomes during reinforcement learning," Nature Communications, Nature, vol. 14(1), pages 1-10, December.
    6. George I. Christopoulos & Xiao-Xiao Liu & Ying-yi Hong, 2017. "Toward an Understanding of Dynamic Moral Decision Making: Model-Free and Model-Based Learning," Journal of Business Ethics, Springer, vol. 144(4), pages 699-715, September.
    7. Sophie Massin, 2011. "La notion d'addiction en économie : La théorie du choix rationnel à l'épreuve," Revue d'économie politique, Dalloz, vol. 121(5), pages 713-750.
    8. Gifford Jr., Adam, 2009. "Cultural, cognition and human action," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 38(1), pages 13-24, January.
    9. Kuhnen, Camelia M. & Knutson, Brian, 2011. "The Influence of Affect on Beliefs, Preferences, and Financial Decisions," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 46(3), pages 605-626, June.
    10. Davide Cenci & Manuel Glauco Carbone & Camilla Callegari & Icro Maremmani, 2022. "Psychomotor Symptoms in Chronic Cocaine Users: An Interpretative Model," IJERPH, MDPI, vol. 19(3), pages 1-10, February.
    11. David Vaquero-Puyuelo & Concepción De-la-Cámara & Beatriz Olaya & Patricia Gracia-García & Antonio Lobo & Raúl López-Antón & Javier Santabárbara, 2021. "Anhedonia as a Potential Risk Factor of Alzheimer’s Disease in a Community-Dwelling Elderly Sample: Results from the ZARADEMP Project," IJERPH, MDPI, vol. 18(4), pages 1-12, February.
    12. Hachi E. Manzur & Ksenia Vlasov & You-Jhe Jhong & Hung-Yen Chen & Shih-Chieh Lin, 2023. "The behavioral signature of stepwise learning strategy in male rats and its neural correlate in the basal forebrain," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    13. repec:mea:meawpa:14279 is not listed on IDEAS
    14. Bruno B Averbeck, 2015. "Theory of Choice in Bandit, Information Sampling and Foraging Tasks," PLOS Computational Biology, Public Library of Science, vol. 11(3), pages 1-28, March.
    15. Daniel Serra, 2021. "Decision-making: from neuroscience to neuroeconomics—an overview," Theory and Decision, Springer, vol. 91(1), pages 1-80, July.
    16. 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.
    17. Maël Lebreton & Karin Bacily & Stefano Palminteri & Jan B Engelmann, 2019. "Contextual influence on confidence judgments in human reinforcement learning," PLOS Computational Biology, Public Library of Science, vol. 15(4), pages 1-27, April.
    18. Paul M Bays & Ben A Dowding, 2017. "Fidelity of the representation of value in decision-making," PLOS Computational Biology, Public Library of Science, vol. 13(3), pages 1-16, March.
    19. Daniel Serra, 2019. "Neuroeconomics and modern neuroscience," CEE-M Working Papers halshs-02160907, CEE-M, Universtiy of Montpellier, CNRS, INRA, Montpellier SupAgro.
    20. He A Xu & Alireza Modirshanechi & Marco P Lehmann & Wulfram Gerstner & Michael H Herzog, 2021. "Novelty is not surprise: Human exploratory and adaptive behavior in sequential decision-making," PLOS Computational Biology, Public Library of Science, vol. 17(6), pages 1-32, June.
    21. Hanan Shteingart & Tal Neiman & Yonatan Loewenstein, 2012. "The Role of First Impression in Operant Learning," Discussion Paper Series dp626, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
    22. Reimann, Martin & Bechara, Antoine, 2010. "The somatic marker framework as a neurological theory of decision-making: Review, conceptual comparisons, and future neuroeconomics research," Journal of Economic Psychology, Elsevier, vol. 31(5), pages 767-776, October.
    23. Agnieszka Boroń & Małgorzata Śmiarowska & Anna Grzywacz & Krzysztof Chmielowiec & Jolanta Chmielowiec & Jolanta Masiak & Tomasz Pawłowski & Dariusz Larysz & Andrzej Ciechanowicz, 2022. "Association of Polymorphism within the Putative miRNA Target Site in the 3′UTR Region of the DRD2 Gene with Neuroticism in Patients with Substance Use Disorder," IJERPH, MDPI, vol. 19(16), pages 1-21, August.
    24. Stefano Palminteri & Emma J Kilford & Giorgio Coricelli & Sarah-Jayne Blakemore, 2016. "The Computational Development of Reinforcement Learning during Adolescence," PLOS Computational Biology, Public Library of Science, vol. 12(6), pages 1-25, June.

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