1. Computational and Systems Biology

Neural arbitration between social and individual learning systems

  1. Andreea Oliviana Diaconescu  Is a corresponding author
  2. Madeline Stecy
  3. Lars Kasper
  4. Christopher J Burke
  5. Zoltan Nagy
  6. Christoph Mathys
  7. Philippe N Tobler
  1. Centre for Addiction and Mental Health, University of Toronto, Canada
  2. Rutgers Robert Wood Johnson Medical School, United States
  3. Institute for Biomedical Engineering, Switzerland
  4. University of Zurich, Switzerland
  5. Scuola Internazionale Superiore di Studi Avanzati (SISSA), Italy
https://doi.org/10.7554/eLife.54051
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  1. Andreea Oliviana Diaconescu
  2. Madeline Stecy
  3. Lars Kasper
  4. Christopher J Burke
  5. Zoltan Nagy
  6. Christoph Mathys
  7. Philippe N Tobler
(2020)
Neural arbitration between social and individual learning systems
eLife 9:e54051.
https://doi.org/10.7554/eLife.54051
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Abstract

Decision making requires integrating self-gathered information with advice from others. However, the arbitration process by which one source of information is selected over the other has not been fully elucidated. In this study, we formalised arbitration as the relative precision of predictions, afforded by each learning system, using hierarchical Bayesian modelling. In a probabilistic learning task, participants predicted the outcome of a lottery using recommendations from a more informed advisor and/or self-sampled outcomes. Decision confidence, as measured by the number of points participants wagered on their predictions, varied with our relative precision definition of arbitration. Functional neuroimaging demonstrated arbitration signals that were independent of decision confidence and involved modality-specific brain regions. Arbitrating in favour of self-gathered information activated the dorsolateral prefrontal cortex and the midbrain, whereas arbitrating in favour of social information engaged the ventromedial prefrontal cortex and the amygdala. These findings indicate that relative precision captures arbitration between social and individual learning systems at both behavioural and neural levels.

Data availability

Data generated during this study are available in Dryad under the doi:10.5061/dryad.wwpzgmsgs. Source data files have been provided for the main tables and figures. The routines for all analyses are available as Matlab code: https://github.com/andreeadiaconescu/arbitration. The instructions for running the code in order to reproduce the results can be found in the ReadMe file.

The following data sets were generated

Article and author information

Author details

  1. Andreea Oliviana Diaconescu

    Department of Psychiatry, Centre for Addiction and Mental Health, University of Toronto, Toronto, Canada
    For correspondence
    andreea.diaconescu@utoronto.ca
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3633-9757

  2. Madeline Stecy

    Medicine, Rutgers Robert Wood Johnson Medical School, New Jersey, United States
    Competing interests
    The authors declare that no competing interests exist.

  3. Lars Kasper

    MR Technology Group & Translational Neuromodeling Unit, Institute for Biomedical Engineering, Zurich, Switzerland
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7667-603X

  4. Christopher J Burke

    Laboratory for Social and Neural Systems Research, University of Zurich, Zurich, Switzerland
    Competing interests
    The authors declare that no competing interests exist.

  5. Zoltan Nagy

    Laboratory for Social and Neural Systems Research, University of Zurich, Zurich, Switzerland
    Competing interests
    The authors declare that no competing interests exist.

  6. Christoph Mathys

    Neuroscience, Scuola Internazionale Superiore di Studi Avanzati (SISSA), Trieste, Italy
    Competing interests
    The authors declare that no competing interests exist.

  7. Philippe N Tobler

    Department of Economics, Laboratory for Social and Neural Systems Research, University of Zurich, Zürich, Switzerland
    Competing interests
    The authors declare that no competing interests exist.

Funding

Swiss National Foundation (PZ00P3_167952)

  • Andreea Oliviana Diaconescu

Swiss National Foundation (PP00P1_150739)

  • Philippe N Tobler

Swiss National Foundation (100014_165884)

  • Philippe N Tobler

Swiss National Foundation (100019_176016)

  • Philippe N Tobler

Krembil Foundation

  • Andreea Oliviana Diaconescu

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: Informed consent, and consent to publish, was obtained from all participants. The study was approved by the Ethics Committee of the Canton of Zürich (KEK-ZH 2010-0327). All participants gave written informed consent before taking part in the study.

Copyright

© 2020, Diaconescu et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Andreea Oliviana Diaconescu
  2. Madeline Stecy
  3. Lars Kasper
  4. Christopher J Burke
  5. Zoltan Nagy
  6. Christoph Mathys
  7. Philippe N Tobler
(2020)
Neural arbitration between social and individual learning systems
eLife 9:e54051.
https://doi.org/10.7554/eLife.54051

Share this article

https://doi.org/10.7554/eLife.54051

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