Confidence-guided updating of choice bias during perceptual decisions is a widespread behavioral phenomenon

  1. Armin Lak  Is a corresponding author
  2. Emily Hueske
  3. Junya Hirokawa
  4. Paul Masset
  5. Torben Ott
  6. Anne E Urai
  7. Tobias H Donner
  8. Matteo Carandini
  9. Susumu Tonegawa
  10. Naoshige Uchida
  11. Adam Kepecs  Is a corresponding author
  1. University College London, United Kingdom
  2. MIT, United States
  3. Doshisha University, Japan
  4. Cold Spring Harbor Laboratory, United States
  5. University Medical Center Hamburg-Eppendorf, Germany
  6. The Picower Institute for Learning and Memory, RIKEN-MIT Center for Neural Circuit Genetics, Massachusetts Institute of Technology, United States
  7. Harvard University, United States

Abstract

Learning from past successes and failures improves decisions to produce appropriate actions in each perceived situation. However, reinforcement learning is not thought to be engaged during well-trained perceptual decision tasks, —after task acquisition is complete and performance is stable—, since choice accuracy is limited by perception. We report a novel form of reinforcement learning during perceptual decisions: past rewards bias future perceptual choices specifically when the previous stimulus was difficult to judge, and the confidence in obtaining the reward was low. We identified this phenomenon in six datasets from four laboratories, across mice, rats and humans, and sensory modalities from olfaction and audition to vision. We show that reinforcement learning models incorporating decision confidence into their teaching signal explain this choice updating. Thus, reinforcement learning mechanisms are continually engaged to produce systematic adjustments of choices even in well-learned perceptual decisions in order to optimize behavior in an uncertain world.

Data availability

The data used in this study is available at http://dx.doi.org/10.6084/m9.figshare.4300043

The following previously published data sets were used

Article and author information

Author details

  1. Armin Lak

    Institute of Ophthalmology, University College London, London, United Kingdom
    For correspondence
    armin.lak@dpag.ox.ac.uk
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1926-5458
  2. Emily Hueske

    Picower Institute, MIT, Cambridge, United States
    Competing interests
    No competing interests declared.
  3. Junya Hirokawa

    Graduate School of Brain Science, Doshisha University, Kyotanabe, Japan
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1238-5713
  4. Paul Masset

    Cold Spring Harbor Laboratory, Cold Spring Harbor, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2001-7515
  5. Torben Ott

    Cold Spring Harbor Laboratory, Cold Spring Harbor, United States
    Competing interests
    No competing interests declared.
  6. Anne E Urai

    Cold Spring Harbor Laboratory, Cold Spring Harbor, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5270-6513
  7. Tobias H Donner

    Department of Neurophysiology and Pathophysiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
    Competing interests
    Tobias H Donner, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7559-6019
  8. Matteo Carandini

    UCL Institute of Ophthalmology, University College London, London, United Kingdom
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4880-7682
  9. Susumu Tonegawa

    Department of Brain and Cognitive Sciences, Department of Biology, The Picower Institute for Learning and Memory, RIKEN-MIT Center for Neural Circuit Genetics, Massachusetts Institute of Technology, Cambridge, United States
    Competing interests
    No competing interests declared.
  10. Naoshige Uchida

    Center for Brain Science, Harvard University, Cambridge, United States
    Competing interests
    Naoshige Uchida, Reviewing editor, eLife.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5755-9409
  11. Adam Kepecs

    Cold Spring Harbor Laboratory, Cold Spring Harbor, United States
    For correspondence
    akepecs@wustl.edu
    Competing interests
    No competing interests declared.

Funding

Wellcome (106101)

  • Armin Lak

Wellcome (213465)

  • Armin Lak

National Institutes of Health (R01 MH110404)

  • Naoshige Uchida

National Institutes of Health (R01MH097061 and R01DA038209)

  • Naoshige Uchida

Wellcome (205093)

  • Matteo Carandini

Deutsche Forschungsgemeinschaft (DO 1240/2-1 and DO 1240/3-1)

  • Tobias H Donner

RIKEN-CBS

  • Emily Hueske
  • Susumu Tonegawa

JPB Foundation

  • Emily Hueske
  • Susumu Tonegawa

Howard Hughes Medical Institute

  • Emily Hueske
  • Susumu Tonegawa

German Academic Exchange Service

  • Anne E Urai

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

Ethics

Animal experimentation: The experimental procedures were approved by Institutional committees at Cold Spring Harbor Laboratory (for experiments on rats), MIT and Harvard University (for mice auditory experiments) and were in accordance with National Institute of Health standards (project ID: 18-14-11-08-1). Experiments on mice visual decisions were approved by the home Office of the United Kingdom (license 70/8021). Experiments in humans were approved by the ethics committee at the University of Amsterdam (project ID: 2014­-BC­-3376).

Human subjects: The ethics committee at the University of Amsterdam approved the study, and all observers gave their informed consent.project ID: 2014-BC-3376

Copyright

© 2020, Lak 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. Armin Lak
  2. Emily Hueske
  3. Junya Hirokawa
  4. Paul Masset
  5. Torben Ott
  6. Anne E Urai
  7. Tobias H Donner
  8. Matteo Carandini
  9. Susumu Tonegawa
  10. Naoshige Uchida
  11. Adam Kepecs
(2020)
Confidence-guided updating of choice bias during perceptual decisions is a widespread behavioral phenomenon
eLife 9:e49834.
https://doi.org/10.7554/eLife.49834

Share this article

https://doi.org/10.7554/eLife.49834

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