Neural arbitration between social and individual learning systems
- Centre for Addiction and Mental Health, University of Toronto, Canada
- Rutgers Robert Wood Johnson Medical School, United States
- Institute for Biomedical Engineering, Switzerland
- University of Zurich, Switzerland
- Scuola Internazionale Superiore di Studi Avanzati (SISSA), Italy
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.
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Neural Arbitration between Social and Individual Learning SystemsDryad Digital Repository, 10.5061/dryad.wwpzgmsgs.
Article and author information
Author details
Andreea Oliviana Diaconescu
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.
Reviewing Editor
- Woo-Young Ahn, Seoul National University, Korea (South), Republic of
Version history
- Received: November 28, 2019
- Accepted: August 10, 2020
- Accepted Manuscript published: August 11, 2020 (version 1)
- Version of Record published: September 7, 2020 (version 2)
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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Neural arbitration between social and individual learning systems
eLife 9:e54051.
https://doi.org/10.7554/eLife.54051
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