Cerebellar implementation of movement sequences through feedback

  1. Andrei Khilkevich  Is a corresponding author
  2. Juan Zambrano
  3. Molly-Marie Richards
  4. Michael Dean Mauk
  1. University of Texas at Austin, United States

Abstract

Most movements are not unitary, but are comprised of sequences. Although patients with cerebellar pathology display severe deficits in the execution and learning of sequences1,2, most of our understanding of cerebellar mechanisms has come from analyses of single component movements. Eyelid conditioning is a cerebellar-mediated behavior that provides the ability to control and restrict inputs to the cerebellum through stimulation of mossy fibers. We utilized this advantage to test directly how the cerebellum can learn a sequence of inter-connected movement components in rabbits. We show that the feedback signals from one component are sufficient to serve as a cue for the next component in the sequence. In vivo recordings from Purkinje cells demonstrated that all components of the sequence were encoded similarly by cerebellar cortex. These results provide a simple yet general framework for how the cerebellum can use simple associate learning processes to chain together a sequence of appropriately timed responses.

Data availability

All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Figures. Source data is provided for Figures 2-8.

Article and author information

Author details

  1. Andrei Khilkevich

    Center for Learning and Memory, University of Texas at Austin, Austin, United States
    For correspondence
    khilkevich@utexas.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1876-4928
  2. Juan Zambrano

    Center for Learning and Memory, University of Texas at Austin, Austin, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Molly-Marie Richards

    Center for Learning and Memory, University of Texas at Austin, Austin, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Michael Dean Mauk

    Center for Learning and Memory, University of Texas at Austin, Austin, United States
    Competing interests
    The authors declare that no competing interests exist.

Funding

National Institute of Mental Health (MH 46904)

  • Michael Dean Mauk

National Institute of Neurological Disorders and Stroke (NS 98308)

  • Michael Dean Mauk

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

Ethics

Animal experimentation: Treatment of animals and surgical procedures were in accordance with National Institutes of Health guidelines and an institutional animal care and use committee (IACUC) protocol (#AUP-2015-00137) of the University of Texas at Austin. Every effort was made to minimize suffering.

Copyright

© 2018, Khilkevich 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.

Metrics

  • 3,004
    views
  • 447
    downloads
  • 37
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Citations by DOI

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. Andrei Khilkevich
  2. Juan Zambrano
  3. Molly-Marie Richards
  4. Michael Dean Mauk
(2018)
Cerebellar implementation of movement sequences through feedback
eLife 7:e37443.
https://doi.org/10.7554/eLife.37443

Share this article

https://doi.org/10.7554/eLife.37443