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

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.

Data availability

Datasets supporting the findings of this study are ~50 GB per experiment, and are therefore available through a request to the corresponding author. Processed data have been provided for each figure, and analysis code has been place in GitHub (https://github.com/Glickfeld-And-Hull-Laboratories/Heffley_Hull_2019_eLife).

Article and author information

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.

Metrics

  • 3,942
    Page views
  • 689
    Downloads
  • 45
    Citations

Article citation count generated by polling the highest count across the following sources: Scopus, Crossref, PubMed Central.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. William Heffley
  2. Court Hull
(2019)
Classical conditioning drives learned reward prediction signals in climbing fibers across the lateral cerebellum
eLife 8:e46764.
https://doi.org/10.7554/eLife.46764
  1. Further reading

Further reading

    1. Neuroscience
    Ashley L Holloway, Talia N Lerner
    Insight

    New studies examine how the different sub-structures in the cerebellum are organized to receive information during complex behavioral tasks

    1. Neuroscience
    Marina E Wosniack, Dylan Festa ... Jimena Berni
    Research Article

    All animals face the challenge of finding nutritious resources in a changing environment. To maximize life-time fitness, the exploratory behavior has to be flexible, but which behavioral elements adapt and what triggers those changes remain elusive. Using experiments and modeling, we characterized extensively how Drosophila larvae foraging adapts to different food quality and distribution and how the foraging genetic background influences this adaptation. Our work shows that different food properties modulated specific motor programs. Food quality controls the travelled distance by modulating crawling speed and frequency of pauses and turns. Food distribution, and in particular the food-no food interphase, controls turning behavior, stimulating turns towards the food when reaching the patch border and increasing the proportion of time spent within patches of food. Finally, the polymorphism in the foraging gene (rover-sitter) of the larvae adjusts the magnitude of the behavioral response to different food conditions. This study defines several levels of control of foraging and provides the basis for the systematic identification of the neuronal circuits and mechanisms controlling each behavioral response.