Detecting motion is essential for animals to perform a wide variety of functions. In order to do so, animals could exploit motion cues, including both first-order cues—such as luminance correlation over time—and second-order cues, by correlating higher-order visual statistics. Since first-order motion cues are typically sufficient for motion detection, it is unclear why sensitivity to second-order motion has evolved in animals, including insects. Here, we investigate the role of second-order motion in prey capture by praying mantises. We show that prey detection uses second-order motion cues to detect figure motion. We further present a model of prey detection based on second-order motion sensitivity, resulting from a layer of position detectors feeding into a second layer of elementary-motion detectors. Mantis stereopsis, in contrast, does not require figure motion and is explained by a simpler model that uses only the first layer in both eyes. Second-order motion cues thus enable prey motion to be detected, even when perfectly matching the average background luminance and independent of the elementary motion of any parts of the prey. Subsequent to prey detection, processes such as stereopsis could work to determine the distance to the prey. We thus demonstrate how second-order motion mechanisms enable ecologically relevant behavior such as detecting camouflaged targets for other visual functions including stereopsis and target tracking.

Attentional selectivity tends to follow events considered as interesting stimuli. Indeed, the motion of visual stimuli present in the environment attract our attention and allow us to react and interact with our surroundings. Extracting relevant motion information from the environment presents a challenge with regards to the high information content of the visual input. In this work we propose a novel integration between an eccentric down-sampling of the visual field, taking inspiration from the varying size of receptive fields (RFs) in the mammalian retina, and the Spiking Elementary Motion Detector (sEMD) model. We characterize the system functionality with simulated data and real world data collected with bio-inspired event driven cameras, successfully implementing motion detection along the four cardinal directions and diagonally.

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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 mantis’s 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.