A Computational model of the integration of landmarks and motion in the insect central complex

Alex J. Cope*, Chelsea Sabo, Eleni Vasilaki, Andrew Barron, James A R Marshall

*Corresponding author for this work

Research output: Contribution to journalArticle

15 Citations (Scopus)
22 Downloads (Pure)

Abstract

The insect central complex (CX) is an enigmatic structure whose computational function has evaded inquiry, but has been implicated in a wide range of behaviours. Recent experimental evidence from the fruit fly (Drosophila melanogaster) and the cockroach (Blaberus discoidalis) has demonstrated the existence of neural activity corresponding to the animal's orientation within a virtual arena (a neural 'compass'), and this provides an insight into one component of the CX structure. There are two key features of the compass activity: an offset between the angle represented by the compass and the true angular position of visual features in the arena, and the remapping of the 270° visual arena onto an entire circle of neurons in the compass. Here we present a computational model which can reproduce this experimental evidence in detail, and predicts the computational mechanisms that underlie the data. We predict that both the offset and remapping of the fly's orientation onto the neural compass can be explained by plasticity in the synaptic weights between segments of the visual field and the neurons representing orientation. Furthermore, we predict that this learning is reliant on the existence of neural pathways that detect rotational motion across the whole visual field and uses this rotation signal to drive the rotation of activity in a neural ring attractor. Our model also reproduces the 'transitioning' between visual landmarks seen when rotationally symmetric landmarks are presented. This model can provide the basis for further investigation into the role of the central complex, which promises to be a key structure for understanding insect behaviour, as well as suggesting approaches towards creating fully autonomous robotic agents.
Original languageEnglish
Article numbere0172325
Pages (from-to)1-19
Number of pages19
JournalPLoS ONE
Volume12
Issue number2
DOIs
Publication statusPublished - 27 Feb 2017

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Copyright the Author(s) 2017. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

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