1. Neuroscience
  2. Physics of Living Systems
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Variability in locomotor dynamics reveals the critical role of feedback in task control

  1. Ismail Uyanik  Is a corresponding author
  2. Shahin Sefati
  3. Sarah A Stamper
  4. Kyoung-A Cho
  5. M Mert Ankarali
  6. Eric S Fortune
  7. Noah J Cowan  Is a corresponding author
  1. Johns Hopkins University, United States
  2. Middle East Technical University, Turkey
  3. New Jersey Institute of Technology, United States
Research Article
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Cite this article as: eLife 2020;9:e51219 doi: 10.7554/eLife.51219

Abstract

Animals vary considerably in size, shape, and physiological features across individuals, but yet achieve remarkably similar behavioral performances. We examined how animals compensate for morphophysiological variation by measuring the system dynamics of individual knifefish (Eigenmannia virescens) in a refuge tracking task. Kinematic measurements of Eigenmannia were used to generate individualized estimates of each fish's locomotor plant and controller, revealing substantial variability between fish. To test the impact of this variability on behavioral performance, these models were used to perform simulated 'brain transplants'-computationally swapping controllers and plants between individuals. We found that simulated closed-loop performance was robust to mismatch between plant and controller. This suggests that animals rely on feedback rather than precisely tuned neural controllers to compensate for morphophysiological variability.

Article and author information

Author details

  1. Ismail Uyanik

    Laboratory of Computational Sensing and Robotics, Johns Hopkins University, Baltimore, United States
    For correspondence
    uyanikismail@gmail.com
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-3535-5616
  2. Shahin Sefati

    Department of Mechanical Engineering, Johns Hopkins University, Baltimore, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Sarah A Stamper

    Department of Mechanical Engineering, Johns Hopkins University, Baltimore, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Kyoung-A Cho

    Department of Mechanical Engineering, Johns Hopkins University, Baltimore, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. M Mert Ankarali

    Department of Electrical and Electronics Engineering, Middle East Technical University, Ankara, Turkey
    Competing interests
    The authors declare that no competing interests exist.
  6. Eric S Fortune

    Department of Biological Sciences, New Jersey Institute of Technology, Newark, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Noah J Cowan

    Laboratory of Computational Sensing and Robotics, Johns Hopkins University, Baltimore, United States
    For correspondence
    ncowan@jhu.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-2502-3770

Funding

National Science Foundation (1557895)

  • Noah J Cowan

National Science Foundation (1557858)

  • Eric S Fortune

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 used for this study were reviewed and approved by Johns Hopkins (protocol: FI19A178) and Rutgers (protocol: 999900774) Animal Care and Use committees and followed the guidelines given by the National Research Council and the Society for Neuroscience.

Reviewing Editor

  1. Ronald L Calabrese, Emory University, United States

Publication history

  1. Received: August 20, 2019
  2. Accepted: January 21, 2020
  3. Accepted Manuscript published: January 23, 2020 (version 1)

Copyright

© 2020, Uyanik 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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