A unified neural model explaining optimal multi-guidance coordination in insect navigation

Sun, Xuelong (2021) A unified neural model explaining optimal multi-guidance coordination in insect navigation. PhD thesis, University of Lincoln.

A unified neural model explaining optimal multi-guidance coordination in insect navigation
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Item Type:Thesis (PhD)
Item Status:Live Archive


The robust navigation of insects arises from the coordinated action of concurrently functioning and interacting guidance systems. Computational models of specific brain regions can account for isolated behaviours such as path integration or route following, but the neural mechanisms by which their outputs are coordinated remains unknown. In this work, a functional modelling approach was taken to identify and model the elemental guidance subsystems required by homing insects. Then we produced realistic adaptive behaviours by integrating different guidance's outputs in a biologically constrained unified model mapped onto identified neural circuits. Homing paths are quantitatively and qualitatively compared with real ant data in a series of simulation studies replicating key infield experiments.

Our analysis reveals that insects require independent visual homing and route following capabilities which we show can be realised by encoding panoramic skylines in the frequency domain, using image processing circuits in the optic lobe and learning pathways through the Mushroom Bodies (MB) and Anterior Optic Tubercle (AOTU) to Bulb (BU) respectively before converging in the Central Complex (CX) steering circuit.

Further, we demonstrate that a ring attractor network inspired by firing patterns recorded in the CX can optimally integrate the outputs of path integration and visual homing systems guiding simulated ants back to their familiar route, and a simple non-linear weighting function driven by the output of the MB provides a context-dependent switch allowing route following strategies to dominate and the learned route retraced back to the nest when familiar terrain is encountered.

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. These results forward the case for a distributed architecture of the insect navigational toolkit.
This unified model then be further validated by modelling the olfactory navigation of flies and ants. With simple adaptions of the sensory inputs, this model reproduces the main characteristics of the observed behavioural data, further demonstrating the useful role played by sensory-processing to CX to motor pathway in generating context-dependent coordination behaviours. In addition, this model help to complete the unified model of insect navigation by adding the olfactory cues that is one of the most crucial cues for insects.

Keywords:insect navigation, central complex, mushroom bodies, optimal integration, orientation guidance, steering circuits, ring attractors
Subjects:C Biological Sciences > C990 Biological Sciences not elsewhere classified
G Mathematical and Computer Sciences > G730 Neural Computing
G Mathematical and Computer Sciences > G790 Artificial Intelligence not elsewhere classified
Divisions:College of Science > School of Computer Science
ID Code:46104
Deposited On:25 Aug 2021 11:04

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