How the insect central complex could coordinate multimodal navigation

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Abstract

The central complex of the insect midbrain is thought to coordinate insect guidance strategies. Computational models can account for specific behaviours but their applicability across sensory and task domains remains untested. Here we assess the capacity of our previous model (Sun et al., 2020) of visual navigation to generalise to olfactory navigation and its coordination with other guidance in flies and ants. We show that fundamental to this capacity is the use of a biologically-plausible neural copy-and-shift mechanism that ensures sensory information is presented in a format compatible with the insect steering circuit regardless of its source. Moreover, the same mechanism is shown to allow the transfer cues from unstable/egocentric to stable/geocentric frames of reference providing a first account of the mechanism by which foraging insects robustly recover from environmental disturbances. We propose that these circuits can be flexibly repurposed by different insect navigators to address their unique ecological needs.

Data availability

The current manuscript is a computational study, so no data have been generated for this manuscript. Modelling code is uploaded as Source Code File and is also available via Github (https://github.com/XuelongSun/insectNavigationCX).

The following data sets were generated

1. Sun X
(2021) How the insect central complex could coordinate multimodal navigation
Publicly available at Github (https://github.com).

https://github.com/XuelongSun/insectNavigationCX

Article and author information

Author details

Xuelong Sun

Machine Life and Intelligence Research Centre, School of Mathematics and Information Science, Guangzhou University, Guangzhou, China

For correspondence
xsun@lincoln.ac.uk

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0001-9035-5523
Shigang Yue

Computational Intelligence Lab and L-CAS, 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.
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

EU Horizon 2020 Framework Program (ULTRACEPT 778062)

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.

Copyright

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.