From skylight input to behavioural output: A computational model of the insect polarised light compass

Abstract

Many insects navigate by integrating the distances and directions travelled on an outward path, allowing direct return to the starting point. Fundamental to the reliability of this process is the use of a neural compass based on external celestial cues. Here we examine how such compass information could be reliably computed by the insect brain, given realistic constraints on the sky polarisation pattern and the insect eye sensor array. By processing the degree of polarisation in different directions for different parts of the sky, our model can directly estimate the solar azimuth and also infer the confidence of the estimate. We introduce a method to correct for tilting of the sensor array, as might be caused by travel over uneven terrain. We also show that the confidence can be used to approximate the change in sun position over time, allowing the compass to remain fixed with respect to ‘true north’ during long excursions. We demonstrate that the compass is robust to disturbances and can be effectively used as input to an existing neural model of insect path integration. We discuss the plausibility of our model to be mapped to known neural circuits, and to be implemented for robot navigation.

Multimodal interactions in insect navigation

“…2 a; ants: (Wehner 1984 ; Collett and Collett 2000 ); bees: (Hardie 1986 ); wasps: (Ugolini 1987 ); flies: (Weir and Dickinson 2012 ; Giraldo et al 2018 ); desert locusts: (Mappes and Homberg 2004 ); monarch butterflies (Merlin et al 2012 ); dung beetles: (el Jundi et al 2019 )) by which animals track their orientation with respect to the solar or lunar azimuth, through both direct visual detection of the light source (sun compass: (Wehner and Mueller 2006 ; Beetz and el Jundi 2018 ; Santschi 1911 ); moon compass (Dacke et al 2004 )), or by inference of its position through observation of correlated chromatic intensity gradients (diurnal: (Pfeiffer and Homberg 2007 ; el Jundi et al 2014 )), and polarised light patterns in the sky (diurnal: (Wehner 1976 ; Wehner and Labhart 2006 ; Wehner and Mueller 2006 ); nocturnal: (Wehner and Duelli 1971 ; Dacke et al 2003a , b )). Theoretically, the insect visual system could derive a celestial compass bearing accurate to less than one degree (Gkanias et al 2019 ) but as the cues constantly move with respect to their observer, due to the rotation of the earth, compensation mechanisms are required for long-term use (see e.g. (Wehner and Lanfranconi 1981 ; Dyer 1987 ; Towne and Moscrip 2008 )).…”

Two Compasses in the Central Complex of the Locust Brain

“…If the receptive fields of CX neurons are not zenith centered, then the internal E-vector compass based on the zenithal E-vector may substantially differ from a polarization compass based on a complete Rayleigh sky. Support for this hypothesis comes from a computational model of an insect-inspired polarization compass (Gkanias et al, 2018). Signals from a fan-shaped arrangement of E-vector analyzers as present in the dorsal rim area of the eye were fed into an array of compass neurons covering a 360°azimuth range.…”

Multi‐sensor fusion SLAM approach for the mobile robot with a bio‐inspired polarised skylight sensor

“…It has been proved that the Cataglyphis perceives the polarised skylight through an ommatidium of the dorsal rim area (DRA) in compound eyes (see Fig. 3 a ), and the polarised skylight is processed by eight photo‐receptor cells in ommatidia to calculate the orientation of the ant's nest [38, 39]. Two of eight photo‐receptor cells, denoted as 3 and 7 in Fig.…”

“… Processing stages of a desert ant (a) Desert ant's head in full‐face view, (b) Ommatidium with eight photoreceptor cells, (c) Simulated response and POL‐neuron response of the two photoreceptors given I = 1 and d = 0.9, (d) Model of a POL‐neuron unit. (a)–(d) Adapted and modified from [38, 39]…”