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