1. Neuroscience
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Structural and functional properties of a probabilistic model of neuronal connectivity in a simple locomotor network

  1. Andrea Ferrario  Is a corresponding author
  2. Robert Merrison-Hort
  3. Stephen R Soffe
  4. Roman Borisyuk
  1. University of Plymouth, United Kingdom
  2. University of Bristol, United Kingdom
Research Article
  • Cited 6
  • Views 1,365
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Cite this article as: eLife 2018;7:e33281 doi: 10.7554/eLife.33281

Abstract

Although, in most animals, brain connectivity varies between individuals, behaviour is often similar across a species. What fundamental structural properties are shared across individual networks that define this behaviour? We describe a probabilistic model of connectivity in the hatchling Xenopus tadpole spinal cord which, when combined with a spiking model, reliably produces rhythmic activity corresponding to swimming. The probabilistic model allows calculation of structural characteristics that reflect common network properties, independent of individual network realisations. We use the structural characteristics to study examples of neuronal dynamics, in the complete network and various sub-networks, and this allows us to explain the basis for key experimental findings, and make predictions for experiments. We also study how structural and functional features differ between detailed anatomical connectomes and those generated by our new, simpler, model.

Article and author information

Author details

  1. Andrea Ferrario

    School of Computing, Electronics and Mathematics, University of Plymouth, Plymouth, United Kingdom
    For correspondence
    andrea.ferrario@plymouth.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9082-1555
  2. Robert Merrison-Hort

    School of Computing, Electronics and Mathematics, University of Plymouth, Plymouth, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  3. Stephen R Soffe

    School of Biological Sciences, University of Bristol, Bristol, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  4. Roman Borisyuk

    School of Computing, Electronics and Mathematics, University of Plymouth, Plymouth, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.

Funding

Biotechnology and Biological Sciences Research Council (BB/L000814/1)

  • Andrea Ferrario
  • Roman Borisyuk

Plymouth University (BB/L002353/1)

  • Stephen R Soffe

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: November 2, 2017
  2. Accepted: March 25, 2018
  3. Accepted Manuscript published: March 28, 2018 (version 1)
  4. Version of Record published: April 20, 2018 (version 2)

Copyright

© 2018, Ferrario 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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