1. Neuroscience
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Classical conditioning drives learned reward prediction signals in climbing fibers across the lateral cerebellum

  1. William Heffley
  2. Court Hull  Is a corresponding author
  1. Duke University School of Medicine, United States
Research Article
  • Cited 18
  • Views 2,856
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Cite this article as: eLife 2019;8:e46764 doi: 10.7554/eLife.46764

Abstract

Classical models of cerebellar learning posit that climbing fibers operate according to a supervised learning rule to instruct changes in motor output by signaling the occurrence of movement errors. However, cerebellar output is also associated with non-motor behaviors, and recently with modulating reward association pathways in the VTA. To test how the cerebellum processes reward related signals in the same type of classical conditioning behavior typically studied to evaluate reward processing in the VTA and striatum, we have used calcium imaging to visualize instructional signals carried by climbing fibers across the lateral cerebellum in mice before and after learning. We find distinct climbing fiber responses in three lateral cerebellar regions that can each signal reward prediction. These instructional signals are well suited to guide cerebellar learning based on reward expectation and enable a cerebellar contribution to reward driven behaviors, suggesting a broad role for the lateral cerebellum in reward-based learning.

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Author details

  1. William Heffley

    Department of Neurobiology, Duke University School of Medicine, Durham, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7733-7398

  2. Court Hull

    Department of Neurobiology, Duke University School of Medicine, Durham, United States
    For correspondence
    hull@neuro.duke.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0360-8367

Funding

National Institute of Neurological Disorders and Stroke (5R01NS096289)

  • Court Hull

National Institute of Neurological Disorders and Stroke (F31NS103425)

  • William Heffley

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

Ethics

Animal experimentation: All experimental procedures using animals were carried out with the approval of the Duke University Animal Care and Use Committee (protocol #A010-19-01).

Reviewing Editor

  1. Jennifer L Raymond, Stanford School of Medicine, United States

Publication history

  1. Received: March 12, 2019
  2. Accepted: July 30, 2019
  3. Accepted Manuscript published: September 11, 2019 (version 1)
  4. Version of Record published: November 11, 2019 (version 2)

Copyright

© 2019, Heffley & Hull

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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Further reading

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    Cerebellar climbing fibers encode expected reward size

    Noga Larry et al.
    Research Article Updated

    Climbing fiber inputs to the cerebellum encode error signals that instruct learning. Recently, evidence has accumulated to suggest that the cerebellum is also involved in the processing of reward. To study how rewarding events are encoded, we recorded the activity of climbing fibers when monkeys were engaged in an eye movement task. At the beginning of each trial, the monkeys were cued to the size of the reward that would be delivered upon successful completion of the trial. Climbing fiber activity increased when the monkeys were presented with a cue indicating a large reward, but not a small reward. Reward size did not modulate activity at reward delivery or during eye movements. Comparison between climbing fiber and simple spike activity indicated different interactions for coding of movement and reward. These results indicate that climbing fibers encode the expected reward size and suggest a general role of the cerebellum in associative learning beyond error correction.

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