A Computational Model of Stereoscopic Prey Capture inPraying Mantises

Abstract

We present a simple model which can account for the stereoscopic sensitivity of praying mantis predatory strikes. The model consists of a single "disparity sensor": a binocular neuron sensitive to stereoscopic disparity and thus to distance from the animal. The model is based closely on the known behavioural and neurophysiological properties of mantis stereopsis. The monocular inputs to the neuron reflect temporal change and are insensitive to contrast sign, making the sensor insensitive to interocular correlation. The monocular receptive fields have a excitatory centre and inhibitory surround, making them tuned to size. The disparity sensor combines inputs from the two eyes linearly, applies a threshold and then an exponent output nonlinearity. The activity of the sensor represents the model mantiss instantaneous probability of striking. We integrate this over the stimulus duration to obtain the expected number of strikes in response to moving targets with different stereoscopic distance, size and vertical disparity. We optimised the parameters of the model so as to bring its predictions into agreement with our empirical data on mean strike rate as a function of stimulus size and distance. The model proves capable of reproducing the relatively broad tuning to size and narrow tuning to stereoscopic distance seen in mantis striking behaviour. The model also displays realistic responses to vertical disparity. Most surprisingly, although the model has only a single centre-surround receptive field in each eye, it displays qualitatively the same interaction between size and distance as we observed in real mantids: the preferred size increases as prey distance increases beyond the preferred distance. We show that this occurs because of a stereoscopic "false match" between the leading edge of the stimulus in one eye and its trailing edge in the other; further work will be required to find whether such false matches occur in real mantises. This is the first image-computable model of insect stereopsis, and reproduces key features of both neurophysiology and striking behaviour.