From skylight input to behavioural output: A computational model of the insect polarised light compass
Fig 1
Overview of the modelling pipeline.
Our simulation consists of four consecutive models (left to right). Given the position of the sun, a realistic skylight model [44] provides the predicted luminance, degree and angle of linear polarisation for every point in the sky-dome. This provides input to the eye model, based on biological data from insects [10, 38], which defines an array of polarisation sensitive photo-receptors facing different parts of the sky, and uses opponent processing to produce luminance-independent POL-neuron responses. The compass model provides a hypothesis for the unknown neural process that converts the POL-neuron response to a true compass signal in the TB1 neurons; this also utilises information about tilt of the sensor array, and allows for the movement of the sun with passing time. Finally, the compass neurons’ output is used along with speed as input to an anatomically grounded model of the central complex [35] which performs path integration and produces an output signal that can steer the insect back home. Blue boxes represent known systems in the pathway of the skylight; the red box represents a fuzzy/unknown system, which is the main focus of modelling in this paper.