1. Neuroscience
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Modelling spinal locomotor circuits for movements in developing zebrafish

  1. Yann Roussel
  2. Stephanie F Gaudreau
  3. Emily R Kacer
  4. Mohini Sengupta
  5. Tuan V Bui  Is a corresponding author
  1. École Polytechnique Fédérale de Lausanne, Switzerland
  2. University of Ottawa, Canada
  3. Washington University School of Medicine, United States
Research Article
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Cite this article as: eLife 2021;10:e67453 doi: 10.7554/eLife.67453

Abstract

Many spinal circuits dedicated to locomotor control have been identified in the developing zebrafish. How these circuits operate together to generate the various swimming movements during development remains to be clarified. In this study, we iteratively built models of developing zebrafish spinal circuits coupled to simplified musculoskeletal models that reproduce coiling and swimming movements. The neurons of the models were based upon morphologically or genetically identified populations in the developing zebrafish spinal cord. We simulated intact spinal circuits as well as circuits with silenced neurons or altered synaptic transmission to better understand the role of specific spinal neurons. Analysis of firing patterns and phase relationships helped identify possible mechanisms underlying the locomotor movements of developing zebrafish. Notably, our simulations demonstrated how the site and the operation of rhythm generation could transition between coiling and swimming. The simulations also underlined the importance of contralateral excitation to multiple tail beats. They allowed us to estimate the sensitivity of spinal locomotor networks to motor command amplitude, synaptic weights, length of ascending and descending axons, and firing behaviour. These models will serve as valuable tools to test and further understand the operation of spinal circuits for locomotion.

Data availability

The code for the models and for the figures, as well as the data used to make the figures, can be accessed at https://github.com/bui-lab/code. Updates and revisions to the models will also be made available at this site.

Article and author information

Author details

  1. Yann Roussel

    Blue Brain Project, École Polytechnique Fédérale de Lausanne, Geneva, Switzerland
    Competing interests
    The authors declare that no competing interests exist.
  2. Stephanie F Gaudreau

    Biology, University of Ottawa, Ottawa, Canada
    Competing interests
    The authors declare that no competing interests exist.
  3. Emily R Kacer

    Biology, University of Ottawa, Ottawa, Canada
    Competing interests
    The authors declare that no competing interests exist.
  4. Mohini Sengupta

    Department of Neuroscience, Washington University School of Medicine, St Louis, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5234-8258
  5. Tuan V Bui

    Biology, Brain and Mind Research Institute, Centre for Neural Dynamics, University of Ottawa, Ottawa, Canada
    For correspondence
    tuan.bui@uottawa.ca
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0024-1544

Funding

Natural Sciences and Engineering Research Council of Canada (RGPIN-2015-06403)

  • Tuan V Bui

McDonnell Center for Cellular and Molecular Neurobiology Postdoc Fellowship (FY21)

  • Mohini Sengupta

Natural Sciences and Engineering Research Council of Canada (NSERC 712210101627)

  • Stephanie F Gaudreau

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

Reviewing Editor

  1. Vatsala Thirumalai, National Centre for Biological Sciences, India

Publication history

  1. Received: February 11, 2021
  2. Accepted: September 1, 2021
  3. Accepted Manuscript published: September 2, 2021 (version 1)

Copyright

© 2021, Roussel 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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