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Praying mantids are the only insects proven to have stereoscopic vision (stereopsis): the ability to perceive depth from the slightly shifted images seen by the two eyes. Recently, the first neurons likely to be involved in mantis stereopsis were described and a speculative neuronal circuit suggested. Here we further investigate classes of neurons in the lobula complex of the praying mantis brain and their tuning to stereoscopically-defined depth. We used sharp electrode recordings with tracer injections to identify visual projection neurons with input in the optic lobe and output in the central brain. In order to measure binocular response fields of the cells the animals watched a vertical bar stimulus in a 3D insect cinema during recordings. We describe the binocular tuning of 19 neurons projecting from the lobula complex and the medulla to central brain areas. The majority of neurons (12/19) were binocular and had receptive fields for both eyes that overlapped in the frontal region. Thus, these neurons could be involved in mantis stereopsis. We also find that neurons preferring different contrast polarity (bright vs dark) tend to be segregated in the mantis lobula complex, reminiscent of the segregation for small targets and widefield motion in mantids and other insects. [ABSTRACT FROM AUTHOR]

The optomotor response has been widely used to investigate insect sensitivity to contrast and motion. Several studies have revealed the sensitivity of this response to frequency and contrast, but we know less about the spatial integration underlying this response. Specifically, few studies have investigated how the horizontal angular extent of stimuli influences the optomotor response. We presented mantises with moving gratings of varying horizontal extents at three different contrasts in the central or peripheral regions of their visual fields. We assessed the relative effectivity of different regions to elicit the optomotor response and modelled the dependency of the response on the angular extent subtended by stimuli at these different regions. Our results show that the optomotor response is governed by stimuli in the central visual field and not in the periphery. The model also shows that in the central region, the probability of response increases linearly with increase in horizontal extent up to a saturation point. Furthermore, the dependency of the optomotor response on the angular extent of the stimulus is modulated by contrast. We discuss the implications of our results for different modes of stimulus presentation and for models of the underlying mechanisms of motion detection in the mantis. [ABSTRACT FROM AUTHOR]

The detection of visual motion and its direction is a fundamental task faced by several visual systems. The motion detection system of insects has been widely studied with the majority of studies focussing on flies and bees. Here we characterize the contrast sensitivity of motion detection in the praying mantis Sphodromantis lineola, an ambush predator that stays stationary for long periods of time while preying on fast-moving prey. In this, its visual behaviour differs from previously studied insects and we might therefore expect its motion detection system to differ from theirs. To investigate the sensitivity of the mantis we analyzed its optomotor response in response to drifting gratings with different contrasts and spatio-temporal frequencies. We find that the contrast sensitivity of the mantis depends on the spatial and temporal frequencies present in the stimulus and is separably tuned to spatial and temporal frequency rather than specifically to object velocity. Our results also suggest that mantises are sensitive to a broad range of velocities, in which they differ from bees and are more similar to hoverflies. We discuss our results in relation to the contrast sensitivities of other insects and the visual ecology of the mantis. [ABSTRACT FROM AUTHOR]

One of the key problems in designing and implementing graph analysis algorithms for distributed platforms is to find an optimal way of managing communication flows in the massively parallel processing network. Message‐passing and global synchronization are powerful abstractions in this regard, especially when used in combination. This paper studies the use of a hardware‐implemented refutable global barrier as a design optimization technique aimed at unifying these abstractions at the API level. The paper explores the trade‐offs between the related overheads and performance factors on a message‐passing prototype machine with 49,152 RISC‐V threads distributed over 48 FPGAs (called the Partially Ordered Event‐Triggered Systems platform). Our experiments show that some graph applications favour synchronized communication, but the effect is hard to predict in general because of the interplay between multiple hardware and software factors. A classifier model is therefore proposed and implemented to perform such a prediction based on the application graph topology parameters: graph diameter, degree of connectivity, and reconvergence metric. The presented experimental results demonstrate that the correct choice of communication mode, granted by the new model‐driven approach, helps to achieve 3.22 times faster computation time on average compared to the baseline platform operation. [ABSTRACT FROM AUTHOR]

One of the key problems in designing and implementing graph analysis algorithms for distributed platforms is to find an optimal way of managing communication flows in the massively parallel processing network. Message‐passing and global synchronization are powerful abstractions in this regard, especially when used in combination. This paper studies the use of a hardware‐implemented refutable global barrier as a design optimization technique aimed at unifying these abstractions at the API level. The paper explores the trade‐offs between the related overheads and performance factors on a message‐passing prototype machine with 49,152 RISC‐V threads distributed over 48 FPGAs (called the Partially Ordered Event‐Triggered Systems platform). Our experiments show that some graph applications favour synchronized communication, but the effect is hard to predict in general because of the interplay between multiple hardware and software factors. A classifier model is therefore proposed and implemented to perform such a prediction based on the application graph topology parameters: graph diameter, degree of connectivity, and reconvergence metric. The presented experimental results demonstrate that the correct choice of communication mode, granted by the new model‐driven approach, helps to achieve 3.22 times faster computation time on average compared to the baseline platform operation. [ABSTRACT FROM AUTHOR]

Evolutionary biologists have long been fascinated by camouflage patterns that help animals reduce their chances of being detected by predators [ 1–4 ]. However, patterns that hide prey when they remain stationary, such as those that match their backgrounds [ 5, 6 ], are rendered ineffective once prey are moving [ 7–10 ]. The question remains: can a moving animal ever be patterned in a way that helps reduce detection by predators? One long-standing idea is that high-contrast patterns with repeated elements, such as stripes, which are highly visible when prey are stationary, can actually conceal prey when they move fast enough [ 11–14 ]. This is predicted by the "flicker fusion effect," which occurs when prey move with sufficient speed that their pattern appears to blur, making them appear more featureless and become less conspicuous against the background [ 2, 8 ]. However, although this idea suggests a way to camouflage moving prey, it has not been empirically tested, and it is not clear that it would work at speeds that are biologically relevant to a predator [ 13 ]. Combining psychophysics and behavioral approaches, we show that speed and pattern interact to determine the detectability of prey to the praying mantis (Sphodromantis lineola) and, crucially, that prey with high-contrast stripes become less visible than prey with background-matching patterns when moving with sufficient speed. We show that stripes can reduce the detection of moving prey by exploiting the spatiotemporal limitations of predator perception, and that the camouflaging effect of a pattern depends upon the speed of prey movement. • The effectiveness of a pattern to camouflage moving animals is speed dependent • High-contrast stripes are effective at hiding prey moving with sufficient speed • Stripes make prey less visible than background-matching patterns as speed increases • Combined with the appropriate pattern, movement can make, not break, camouflage By presenting praying mantids with artificial moving prey, Umeton et al. show that the camouflage efficacy of a pattern depends on the speed at which an animal moves. Surprisingly, with increasing speed, high-contrast striped prey become better camouflaged than prey with a background-matching pattern. [ABSTRACT FROM AUTHOR]

Summary Stereopsis is the ability to estimate distance based on the different views seen in the two eyes [ 1–5 ]. It is an important model perceptual system in neuroscience and a major area of machine vision. Mammalian, avian, and almost all machine stereo algorithms look for similarities between the luminance-defined images in the two eyes, using a series of computations to produce a map showing how depth varies across the scene [ 3, 4, 6–14 ]. Stereopsis has also evolved in at least one invertebrate, the praying mantis [ 15–17 ]. Mantis stereopsis is presumed to be simpler than vertebrates’ [ 15, 18 ], but little is currently known about the underlying computations. Here, we show that mantis stereopsis uses a fundamentally different computational algorithm from vertebrate stereopsis—rather than comparing luminance in the two eyes’ images directly, mantis stereopsis looks for regions of the images where luminance is changing . Thus, while there is no evidence that mantis stereopsis works at all with static images, it successfully reveals the distance to a moving target even in complex visual scenes with targets that are perfectly camouflaged against the background in terms of texture. Strikingly, these insects outperform human observers at judging stereoscopic distance when the pattern of luminance in the two eyes does not match. Insect stereopsis has thus evolved to be computationally efficient while being robust to poor image resolution and to discrepancies in the pattern of luminance between the two eyes. Video Abstract [ABSTRACT FROM AUTHOR]

Stereo or '3D' vision is an important but costly process seen in several evolutionarily distinct lineages including primates, birds and insects. Many selective advantages could have led to the evolution of stereo vision, including range finding, camouflage breaking and estimation of object size. In this paper, we investigate the possibility that stereo vision enables praying mantises to estimate the size of prey by using a combination of disparity cues and angular size cues. We used a recently developed insect 3D cinema paradigm to present mantises with virtual prey having differing disparity and angular size cues. We predicted that if they were able to use these cues to gauge the absolute size of objects, we should see evidence for size constancy where they would strike preferentially at prey of a particular physical size, across a range of simulated distances. We found that mantises struck most often when disparity cues implied a prey distance of 2.5 cm; increasing the implied distance caused a significant reduction in the number of strikes. We, however, found no evidence for size constancy. There was a significant interaction effect of the simulated distance and angular size on the number of strikes made by the mantis but this was not in the direction predicted by size constancy. This indicates that mantises do not use their stereo vision to estimate object size. We conclude that other selective advantages, not size constancy, have driven the evolution of stereo vision in the praying mantis. [ABSTRACT FROM AUTHOR]

Perceiving motion-in-depth is essential to detecting approaching or receding objects, predators and prey. This can be achieved using several cues, including binocular stereoscopic cues such as changing disparity and interocular velocity differences, and monocular cues such as looming. Although these have been studied in detail in humans, only looming responses have been well characterized in insects and we know nothing about the role of stereoscopic cues and how they might interact with looming cues. We used our 3D insect cinema in a series of experiments to investigate the role of the stereoscopic cues mentioned above, as well as looming, in the perception of motion-in-depth during predatory strikes by the praying mantis Sphodromantis lineola. Our results show that motion-in-depth does increase the probability of mantis strikes but only for the classic looming stimulus, an expanding luminance edge. Approach indicated by radial motion of a texture or expansion of a motion-defined edge, or by stereoscopic cues, all failed to elicit increased striking. We conclude that mantises use stereopsis to detect depth but not motion-in-depth, which is detected via looming. [ABSTRACT FROM AUTHOR]