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Predictive decision making driven by multiple time-linked reward representations in the anterior cingulate cortex

Author

Listed:
  • Marco K. Wittmann

    (University of Oxford)

  • Nils Kolling

    (University of Oxford)

  • Rei Akaishi

    (University of Oxford
    Center for Visual Science, University of Rochester)

  • Bolton K. H. Chau

    (University of Oxford
    The Hong Kong Polytechnic University)

  • Joshua W. Brown

    (Indiana University)

  • Natalie Nelissen

    (University of Oxford)

  • Matthew F. S. Rushworth

    (University of Oxford
    Centre for Functional MRI of the Brain, University of Oxford)

Abstract

In many natural environments the value of a choice gradually gets better or worse as circumstances change. Discerning such trends makes predicting future choice values possible. We show that humans track such trends by comparing estimates of recent and past reward rates, which they are able to hold simultaneously in the dorsal anterior cingulate cortex (dACC). Comparison of recent and past reward rates with positive and negative decision weights is reflected by opposing dACC signals indexing these quantities. The relative strengths of time-linked reward representations in dACC predict whether subjects persist in their current behaviour or switch to an alternative. Computationally, trend-guided choice can be modelled by using a reinforcement-learning mechanism that computes a longer-term estimate (or expectation) of prediction errors. Using such a model, we find a relative predominance of expected prediction errors in dACC, instantaneous prediction errors in the ventral striatum and choice signals in the ventromedial prefrontal cortex.

Suggested Citation

  • Marco K. Wittmann & Nils Kolling & Rei Akaishi & Bolton K. H. Chau & Joshua W. Brown & Natalie Nelissen & Matthew F. S. Rushworth, 2016. "Predictive decision making driven by multiple time-linked reward representations in the anterior cingulate cortex," Nature Communications, Nature, vol. 7(1), pages 1-13, November.
  • Handle: RePEc:nat:natcom:v:7:y:2016:i:1:d:10.1038_ncomms12327
    DOI: 10.1038/ncomms12327
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    Cited by:

    1. Alexander Nitsch & Mona M. Garvert & Jacob L. S. Bellmund & Nicolas W. Schuck & Christian F. Doeller, 2024. "Grid-like entorhinal representation of an abstract value space during prospective decision making," Nature Communications, Nature, vol. 15(1), pages 1-20, December.
    2. Ethan Trepka & Mehran Spitmaan & Bilal A. Bari & Vincent D. Costa & Jeremiah Y. Cohen & Alireza Soltani, 2021. "Entropy-based metrics for predicting choice behavior based on local response to reward," Nature Communications, Nature, vol. 12(1), pages 1-16, December.
    3. Wei-Hsiang Lin & Justin L Gardner & Shih-Wei Wu, 2020. "Context effects on probability estimation," PLOS Biology, Public Library of Science, vol. 18(3), pages 1-45, March.

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