Optimal searching behaviour generated intrinsically by the central pattern generator for locomotion

  1. David W Sims
  2. Nicolas E Humphries
  3. Nan Hu
  4. Violeta Medan
  5. Jimena Berni  Is a corresponding author
  1. Marine Biological Association of the United Kingdom, United Kingdom
  2. University of Cambridge, United Kingdom
  3. Universidad de Buenos Aires, Argentina

Abstract

Efficient searching for resources such as food by animals is key to their survival. It has been proposed that diverse animals from insects to sharks and humans adopt searching patterns that resemble a simple Lévy random walk, which is theoretically optimal for 'blind foragers' to locate sparse, patchy resources. To test if such patterns are generated intrinsically, or arise via environmental interactions, we tracked free-moving Drosophila larvae with (and without) blocked synaptic activity in the brain, suboesophageal ganglion (SOG) and sensory neurons. In brain-blocked larvae we found that extended substrate exploration emerges as multi-scale movement paths similar to truncated Lévy walks. Strikingly, power-law exponents of brain/SOG/sensory-blocked larvae averaged 1.96, close to a theoretical optimum (µ ≅ 2.0) for locating sparse resources. Thus, efficient spatial exploration can emerge from autonomous patterns in neural activity. Our results provide the strongest evidence so far for the intrinsic generation of Lévy-like movement patterns.

Data availability

All data generated and analysed in this study are available in Dryad (doi: 10.5061/dryad.7m0cfxpq0). Results from analysis are also included in the manuscript and supporting files.

The following data sets were generated

Article and author information

Author details

  1. David W Sims

    Marine Biological Association of the United Kingdom, Plymouth, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  2. Nicolas E Humphries

    Marine Biological Association of the United Kingdom, Plymouth, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  3. Nan Hu

    Department of Zoology, University of Cambridge, Cambridge, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. Violeta Medan

    Departamento de Fisiología, Biología Molecular y Celular, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires, Argentina
    Competing interests
    The authors declare that no competing interests exist.
  5. Jimena Berni

    Department of Zoology, University of Cambridge, Cambridge, United Kingdom
    For correspondence
    jb672@cam.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5068-1372

Funding

Wellcome (105568/Z/14/Z)

  • Jimena Berni

Royal Society (105568/Z/14/Z)

  • Jimena Berni

Consejo Nacional de Investigaciones Científicas y Técnicas (PICT 20121578)

  • Violeta Medan

Natural Environment Research Council (Oceans 2025 Strategic Research Programme)

  • David W Sims

Marine Biological Association (Senior Research Fellowship)

  • David W Sims

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

Reviewing Editor

  1. Ronald L Calabrese, Emory University, United States

Publication history

  1. Received: July 18, 2019
  2. Accepted: October 24, 2019
  3. Accepted Manuscript published: November 1, 2019 (version 1)
  4. Version of Record published: November 26, 2019 (version 2)
  5. Version of Record updated: December 3, 2019 (version 3)

Copyright

© 2019, Sims 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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  1. David W Sims
  2. Nicolas E Humphries
  3. Nan Hu
  4. Violeta Medan
  5. Jimena Berni
(2019)
Optimal searching behaviour generated intrinsically by the central pattern generator for locomotion
eLife 8:e50316.
https://doi.org/10.7554/eLife.50316

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