A decentralised neural model explaining optimal integration of navigational strategies in insects

Sun, Xuelong, Yue, Shigang and Mangan, Michael (2020) A decentralised neural model explaining optimal integration of navigational strategies in insects. eLife, 9 . ISSN 2050-084X

Full content URL: https://doi.org/10.7554/eLife.54026

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A decentralised neural model explaining optimal integration of navigational strategies in insects
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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.

Keywords:Insect navigation, Central complex, Desert ants, Optimal integration, Ring attractor, Mushroom body
Subjects:G Mathematical and Computer Sciences > G730 Neural Computing
Divisions:College of Science > School of Computer Science
ID Code:41703
Deposited On:04 Aug 2020 09:37

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