1. Computational and Systems Biology
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A decentralised neural model explaining optimal integration of navigational strategies in insects

  1. Xuelong Sun  Is a corresponding author
  2. Shigang Yue  Is a corresponding author
  3. Michael Mangan  Is a corresponding author
  1. University of Lincoln, United Kingdom
  2. University of Sheffield, United Kingdom
Research Article
  • Cited 6
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Cite this article as: eLife 2020;9:e54026 doi: 10.7554/eLife.54026

Abstract

Insect navigation arises from the coordinated action of concurrent guidance systems but the neural mechanisms through which each functions, and are then coordinated, remains unknown. We propose that insects require distinct strategies to retrace familiar routes (route-following) and directly return from novel to familiar terrain (homing) using different aspects of frequency encoded views that are processed in different neural pathways. We also demonstrate how the Central Complex and Mushroom Bodies regions of the insect brain may work in tandem to coordinate the directional output of different guidance cues through a contextually switched ring-attractor inspired by neural recordings. The resultant unified model of insect navigation reproduces behavioural data from a series of cue conflict experiments in realistic animal environments and offers testable hypotheses of where and how insects process visual cues, utilise the different information that they provide and coordinate their outputs to achieve the adaptive behaviours observed in the wild.

Data availability

All the source code of the implementation and part of the data are uploaded to Github and are available via https://github.com/XuelongSun/InsectNavigationToolkitModelling

Article and author information

Author details

  1. Xuelong Sun

    Computational Intelligent Lab, School of Computer Science, University of Lincoln, Lincoln, United Kingdom
    For correspondence
    xsun@lincoln.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9035-5523
  2. Shigang Yue

    Computational Intelligent Lab, School of Computer Science, University of Lincoln, Lincoln, United Kingdom
    For correspondence
    syue@lincoln.ac.uk
    Competing interests
    The authors declare that no competing interests exist.
  3. Michael Mangan

    Sheffield Robotics, Department of Computer Science, University of Sheffield, Sheffield, United Kingdom
    For correspondence
    m.mangan@sheffield.ac.uk
    Competing interests
    The authors declare that no competing interests exist.

Funding

Horizon 2020 Framework Programme (ULTRACEPT 778062)

  • Xuelong Sun
  • Shigang Yue

Horizon 2020 Framework Programme (STEP2DYNA 691154)

  • Xuelong Sun
  • Shigang Yue

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

Reviewing Editor

  1. Mani Ramaswami, Trinity College Dublin, Ireland

Publication history

  1. Received: November 28, 2019
  2. Accepted: June 26, 2020
  3. Accepted Manuscript published: June 26, 2020 (version 1)
  4. Version of Record published: July 16, 2020 (version 2)

Copyright

© 2020, Sun 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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