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Ageing is associated with disrupted reinforcement learning whilst learning to help others is preserved

Author

Listed:
  • Jo Cutler

    (School of Psychology, University of Birmingham
    University of Oxford
    University of Oxford)

  • Marco K. Wittmann

    (University of Oxford
    University of Oxford)

  • Ayat Abdurahman

    (University of Oxford
    University of Oxford
    University of Cambridge)

  • Luca D. Hargitai

    (University of Oxford)

  • Daniel Drew

    (University of Oxford
    University of Oxford
    University of Oxford)

  • Masud Husain

    (University of Oxford
    University of Oxford
    University of Oxford)

  • Patricia L. Lockwood

    (School of Psychology, University of Birmingham
    University of Oxford
    University of Oxford
    University of Oxford)

Abstract

Reinforcement learning is a fundamental mechanism displayed by many species. However, adaptive behaviour depends not only on learning about actions and outcomes that affect ourselves, but also those that affect others. Using computational reinforcement learning models, we tested whether young (age 18–36) and older (age 60–80, total n = 152) adults learn to gain rewards for themselves, another person (prosocial), or neither individual (control). Detailed model comparison showed that a model with separate learning rates for each recipient best explained behaviour. Young adults learned faster when their actions benefitted themselves, compared to others. Compared to young adults, older adults showed reduced self-relevant learning rates but preserved prosocial learning. Moreover, levels of subclinical self-reported psychopathic traits (including lack of concern for others) were lower in older adults and the core affective-interpersonal component of this measure negatively correlated with prosocial learning. These findings suggest learning to benefit others is preserved across the lifespan with implications for reinforcement learning and theories of healthy ageing.

Suggested Citation

  • Jo Cutler & Marco K. Wittmann & Ayat Abdurahman & Luca D. Hargitai & Daniel Drew & Masud Husain & Patricia L. Lockwood, 2021. "Ageing is associated with disrupted reinforcement learning whilst learning to help others is preserved," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-24576-w
    DOI: 10.1038/s41467-021-24576-w
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    Cited by:

    1. Ruth Pauli & Inti A. Brazil & Gregor Kohls & Miriam C. Klein-Flügge & Jack C. Rogers & Dimitris Dikeos & Roberta Dochnal & Graeme Fairchild & Aranzazu Fernández-Rivas & Beate Herpertz-Dahlmann & Amaia, 2023. "Action initiation and punishment learning differ from childhood to adolescence while reward learning remains stable," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    2. Penghui Wang & Rui Ding & Wenjiao Shi & Jun Li, 2024. "Potential Reductions in the Environmental Impacts of Agricultural Production in Hubei Province, China," Agriculture, MDPI, vol. 14(3), pages 1-17, March.
    3. Patricia L. Lockwood & Jo Cutler & Daniel Drew & Ayat Abdurahman & Deva Sanjeeva Jeyaretna & Matthew A. J. Apps & Masud Husain & Sanjay G. Manohar, 2024. "Human ventromedial prefrontal cortex is necessary for prosocial motivation," Nature Human Behaviour, Nature, vol. 8(7), pages 1403-1416, July.

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