The killer fly hunger games : target size and speed predict decision to pursuit

© The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Brain, Behavior and Evolution 86 (2015): 28-27, doi:10.1159/000435944.Predatory animals have evolved to optimally detect their prey using exquisite sensory systems such as vision, olfaction and hearing. It may not be so surprising that vertebrates, with large central nervous systems, excel at predatory behaviors. More striking is the fact that many tiny insects, with their miniscule brains and scaled down nerve cords, are also ferocious, highly successful predators. For predation, it is important to determine whether a prey is suitable before initiating pursuit. This is paramount since pursuing a prey that is too large to capture, subdue or dispatch will generate a substantial metabolic cost (in the form of muscle output) without any chance of metabolic gain (in the form of food). In addition, during all pursuits, the predator breaks its potential camouflage and thus runs the risk of becoming prey itself. Many insects use their eyes to initially detect and subsequently pursue prey. Dragonflies, which are extremely efficient predators, therefore have huge eyes with relatively high spatial resolution that allow efficient prey size estimation before initiating pursuit. However, much smaller insects, such as killer flies, also visualize and successfully pursue prey. This is an impressive behavior since the small size of the killer fly naturally limits the neural capacity and also the spatial resolution provided by the compound eye. Despite this, we here show that killer flies efficiently pursue natural (Drosophila melanogaster) and artificial (beads) prey. The natural pursuits are initiated at a distance of 7.9 ± 2.9 cm, which we show is too far away to allow for distance estimation using binocular disparities. Moreover, we show that rather than estimating absolute prey size prior to launching the attack, as dragonflies do, killer flies attack with high probability when the ratio of the prey's subtended retinal velocity and retinal size is 0.37. We also show that killer flies will respond to a stimulus of an angular size that is smaller than that of the photoreceptor acceptance angle, and that the predatory response is strongly modulated by the metabolic state. Our data thus provide an exciting example of a loosely designed matched filter to Drosophila, but one which will still generate successful pursuits of other suitable prey.This work was funded by the Air Force Office of Scientific Research (FA9550-10-0472 to R.M. Olberg and FA9550-15-1-0188 to P.T. Gonzalez-Bellido and K. Nordström), an Isaac Newton Trust/Wellcome Trust ISSF/University of Cambridge Joint Research Grant to Paloma T. Gonzalez-Bellido, a Biotechnology and Biological Sciences Research Council David Phillips Fellowship (BBSRC, BB/L024667/1) to Trevor J. Wardill, the Swedish Research Council (2012-4740) to Karin Nordström and a Shared Equipment Grant from the School of Biological Sciences (University of Cambridge)

The Killer Fly Hunger Games: Target Size and Speed Predict Decision to Pursuit.

Predatory animals have evolved to optimally detect their prey using exquisite sensory systems such as vision, olfaction and hearing. It may not be so surprising that vertebrates, with large central nervous systems, excel at predatory behaviors. More striking is the fact that many tiny insects, with their miniscule brains and scaled down nerve cords, are also ferocious, highly successful predators. For predation, it is important to determine whether a prey is suitable before initiating pursuit. This is paramount since pursuing a prey that is too large to capture, subdue or dispatch will generate a substantial metabolic cost (in the form of muscle output) without any chance of metabolic gain (in the form of food). In addition, during all pursuits, the predator breaks its potential camouflage and thus runs the risk of becoming prey itself. Many insects use their eyes to initially detect and subsequently pursue prey. Dragonflies, which are extremely efficient predators, therefore have huge eyes with relatively high spatial resolution that allow efficient prey size estimation before initiating pursuit. However, much smaller insects, such as killer flies, also visualize and successfully pursue prey. This is an impressive behavior since the small size of the killer fly naturally limits the neural capacity and also the spatial resolution provided by the compound eye. Despite this, we here show that killer flies efficiently pursue natural (Drosophila melanogaster) and artificial (beads) prey. The natural pursuits are initiated at a distance of 7.9 ± 2.9 cm, which we show is too far away to allow for distance estimation using binocular disparities. Moreover, we show that rather than estimating absolute prey size prior to launching the attack, as dragonflies do, killer flies attack with high probability when the ratio of the prey's subtended retinal velocity and retinal size is 0.37. We also show that killer flies will respond to a stimulus of an angular size that is smaller than that of the photoreceptor acceptance angle, and that the predatory response is strongly modulated by the metabolic state. Our data thus provide an exciting example of a loosely designed matched filter to Drosophila, but one which will still generate successful pursuits of other suitable prey.This work was funded the Air force Office of Scientific Research (FA9550-10-0472 to Prof. Robert Olberg). An Isaac Newton Trust / Wellcome Trust ISSF / University of Cambridge Joint Research Grant to Gonzalez-Bellido. BBSRC TO TREVOR WARDILL The Swedish Research Council (2012-4740) to Nordström and a Shared Equipment Grant from the School of Biological Sciences (U. of Cambridge).This is the final version of the article. It first appeared from Karger via http://dx.doi.org/10.1159/00043594

Active Vision Strategies in Predation

Visual predation requires precise and accurate behaviour, for which many predators have evolved excellent visual skills. However, an animal's visual abilities are greatly affected by how it moves its eyes, known as active vision. Insects have immobile eyes but can direct their gaze by moving their heads and bodies. This thesis examines three predatory insects with different predatory strategies, to understand the extent to which active vision can be used in predation. The first experimental chapter considers the African praying mantid, Sphodromantis lineola. Praying mantids are stationary terrestrial predators, which use their extremely mobile necks to visually track prey until it is within reach. By using statistical models, we identified what factors elicited strikes and, importantly, their success rate. The timing of head movements greatly increased the chances of strike success, with earlier movements increasing the success rate. The second experimental chapter addresses how darting robber flies, Psilonyx annulatus, aerially attack static prey. Prior to attacking, darting robber flies translate their body around a central point, assessing their prey. After assessment, they attack from a position correlated with the target's absolute size, not its angular size. Prey is beyond the robber fly's stereopsis range during the period of assessment. Assessments of differently sized targets have similarities with the behaviour exhibited by jumping insects, which use motion parallax, a form of active vision, to assess jump distance, suggesting darting robber flies also use motion parallax to predate. The final experimental chapter considers killer flies, Coenosia attenuata, which chase moving targets aerially. Killer flies use a combination of gravity and wing acceleration to increase their speed when chasing prey from above. This increased speed restricts the flies' ability to steer. However, killer flies create strong looming stimuli which may trigger their prey to produce evasive manoeuvres, thereby slowing down. Moreover, by travelling faster towards their prey, killer flies may avoid losing track of it, a real danger when chasing moving prey with low- resolution eyes potentially avoided thanks to active vision. By employing active vision, each of the predators considered can achieve impressive performances, despite relying on very different strategies to capture prey. The use of active vision can increase the success of already excellent visual predators and improve the performance of predator with limited vision. However, active vision can also substantially alter predatory behaviour, leading to a trade- off between the advantages in visual perception active vision can bring and the disadvantage in behavioural efficiency of active vision strategies

Descending premotor target tracking systems in flying insects

The control of behaviour in all animals requires efficient transformation of sensory signals into the task-specific activation of muscles. Predation offers an advantageous model behaviour to study the computational organisation underlying sensorimotor control. Predators are optimised through diverse evolutionary arms races to outperform their prey in terms of sensorimotor coordination, leading to highly specialised anatomical adaptations and hunting behaviours, which are often innate and highly stereotyped. Predatory flying insects present an extreme example, performing complex visually-guided pursuits of small, often fast flying prey over extremely small timescales. Furthermore, this behaviour is controlled by a tiny nervous system, leading to pressure on neuronal organisation to be optimised for coding efficiency. In dragonflies, a population of eight pairs of bilaterally symmetric Target Selective Descending Neurons (TSDNs) relay visual information about small moving objects from the brain to the thoracic motor centres. These neurons encode the movement of small moving objects across the dorsal fovea region of the eye which is fixated on prey during predatory pursuit, and are thought to constitute the commands necessary for actuating an interception flight path. TSDNs are characterised by their receptive fields, with responses of each TSDN type spatially confined to a specific portion of the dorsal fovea visual field and tuned to a specific direction of object motion. To date, little is known about the descending representations mediating target tracking in other insects. This dissertation presents a comparative report of descending neurons in a variety of flying insects. The results are organised into three chapters: Chapter 3 identifies TSDNs in demoiselle damselflies and compares their response properties to those previously described in dragonflies. Demoiselle TSDNs are also found to integrate binocular information, which is further elaborated with prism and eyepatch experiments. Chapter 4 describes TSDNs in two dipteran species, the robberfly Holcocephala fusca and the killerfly Coenosia attenuata. Chapter 5 describes an interaction between small- and wide-field visual features in TSDNs of both predatory and nonpredatory dipterans, finding functional similarity of these neurons for prey capture and conspecific pursuit. Dipteran TSDN responses are repressed by background motion in a direction dependent manner, suggesting a control architecture in which target tracking and optomotor stabilization pathways operate in parallel during pursuit.echnology and Biological Sciences ResearchCouncil (BB/M011194/1

Modeling visual-based pitch, lift and speed control strategies in hoverflies

<div><p>To avoid crashing onto the floor, a free falling fly needs to trigger its wingbeats quickly and control the orientation of its thrust accurately and swiftly to stabilize its pitch and hence its speed. Behavioural data have suggested that the vertical optic flow produced by the fall and crossing the visual field plays a key role in this anti-crash response. Free fall behavior analyses have also suggested that flying insect may not rely on graviception to stabilize their flight. Based on these two assumptions, we have developed a model which accounts for hoverflies´ position and pitch orientation recorded in 3D with a fast stereo camera during experimental free falls. Our dynamic model shows that optic flow-based control combined with closed-loop control of the pitch suffice to stabilize the flight properly. In addition, our model sheds a new light on the visual-based feedback control of fly´s pitch, lift and thrust. Since graviceptive cues are possibly not used by flying insects, the use of a vertical reference to control the pitch is discussed, based on the results obtained on a complete dynamic model of a virtual fly falling in a textured corridor. This model would provide a useful tool for understanding more clearly how insects may or not estimate their absolute attitude.</p></div

Can the Youth Materialism Scale be used across different countries and cultures?

As global material wealth rises and young people are heavily exposed to advertising across a range of channels, including rapidly developing social media where material goods are flaunted as symbols of a happy and successful lifestyle, materialism levels across the world seem likely to rise. Given consistent research showing the correlation between materialism and low well-being, this gives cause for concern. However, no studies have so far tested whether current measures of youth materialism are generalizable across different countries and cultures. Our article fills this gap by exploring through a range of internal and external validity tests whether the popular Youth Materialism Scale (YMS) can be used with confidence across China, France, Belgium, Poland, the United Kingdom, and the United States. We show that a 5-item version of YMS is invariant across the countries (internal validity) and that it broadly correlates in expected ways with six different theoretically related constructs: Self-Esteem, Life Satisfaction, Attitude to Advertising, Parental Support, TV Use, and Internet Use (external validity). We believe that researchers and policy makers can confidently use this 5-item version of the scale in international contexts

Visual Adaptations and Behavioural Strategies to Detect and Catch Small Targets

Predatory behaviours are ideal for studying the limits of performance and control within animals. Predation naturally creates a competition between the sensors and physiology of predator and prey. Aerial predation demonstrates the greatest feats of physical performance, demanding the highest speeds and accelerations whilst both predator and prey are free to pitch, yaw, and roll. These high speeds and degrees of rotational freedom make control a complex problem. However, from the perspective of the researcher attempting to decipher the control laws that underpin predator guidance, the question is made more soluble by the predator’s fixation on its target. The goal of the pursuer is clear, to contact the target, and thus their systems are focused on the optimization of that action. This is as opposed to more mundane activities, where conflicting interests compete for the attention and behavioural response of the animal. In order to study the necessary trade-offs that underpin aerial predation, this thesis will focus on the hunting behaviour of two fly species. The first is a robber fly, Holcocephala fusca, on which the majority of the first two chapters focus. Secondarily, work with the killer fly Coenosia attenuata will be included in the latter two chapters as a direct contrast to results from Holcocephala. Both are miniature dipteran predators, but not closely related. The structure of this thesis is broken into six chapters, summarised in the following list: 1. Thecompoundeyeofinsectsgenerallyhasmuchpoorerresolutionthanthatofcameratype eyes. Poor resolution is exacerbated in smaller insects that cannot commit the resources required for eyes with large lenses that facilitate high spatial resolution. Holcocephala has developed a small number of facets into a forward-facing acute zone where the spatial acuity is reduced to ~0.28°, rivalling the very best resolution of any compound eye. The only compound eyes with a comparable spatial resolution belong to dragonflies, in excess of an order of magnitude larger than Holcocephala. 2. Numerous potential targets may be airborne within the visual range of a predator. Not all of these may be suitable. Chasing unsuitable targets may waste energy or result in direct harm should they turn out to be larger than the predator can overcome. It is thus a strong imperative for a predator to filter the targets it takes after. Targets silhouetted against the sky display a paucity of cues that a predator could use to determine their size. Holcocephala displays acute size selectivity towards smaller targets. This selectivity goes beyond heuristic rules and size/speed ratios. Instead, Holcocephala appears able to determine absolute size and distance of targets. 3. Both Holcocephala and Coenosia intercept targets, heading for where the target is going to be in the future rather than its current location. Both species plot trajectories in keeping with the guidance law of proportional navigation, an algorithm derived for modern guided missiles. There are key differences evident in the internal physiological constants applied to the control system between the species. These differences are likely linked to the specific environmental conditions and visual physiologies of the flies, especially the range at which targets are attacked. 4. Stemming from the use of the proportional navigational framework, this chapter dives into the intricacies of gain and the weighting of the navigational constant, and the geometric factors that underpin the control effort and eventual success of the control system. 5. “Falcon-diving” can be found in killer flies dropping from their enclosure ceiling, in which they miss targets after diving towards them. Through proportional navigation, it can be demonstrated that the navigational system combined with excessive speed results in acceleration demands the body cannot match. 6. Holcocephala is capable of evading static obstacle whilst intercepting targets. Application of proportional navigation and a secondary obstacle-evasive controller can demonstrate where the fly is combining multiple inputs to guide its heading.This work was funded by the United States Airforce Office of Scientific Research

Neurons against Noise : Neural adaptations for dim light vision in hawkmoths

All animals perceive the world through their senses, which form the basis for their decisions and motor actions. However, when these all-important senses reach their limit and cease to provide reliable information, the animal’s survival is threatened. Among the senses, vision is brought to its limits on a daily basis, because its signal strength is diminished as night falls, and increases again as the sun rises. In this thesis, I investigated adaptations that enable the visual system of hawkmoths, a group of insects, to cope with the low light intensities they face at night. I have focused on neural adaptations, manifested in the processing of visual neurons, in contrast to anatomical adaptations, such as modifications of the eye. I showed that neural adaptations exist in the motion vision system of hawkmoths, in the form of integration of visual information in space and time. Furthermore, I demonstrated that a combination of such spatial and temporal summation increased sensitivity and information content in dim light (Paper I). The amount of spatial and temporal summation matched the ecological needs of different hawkmoth species, as well as their anatomical adaptations for visual sensitivity: night active species, and species with less sensitive eyes had more extensive spatial and temporal summation than day-active species and species with very sensitive optics (Paper II). Furthermore, I identified and characterised candidate neurons that carry out spatial and temporal summation in the brain of hawkmoths (Paper III). Finally, I quantified the effects of temporal summation on the ability of hawkmoths to track flowers in hovering flight at different light levels, and showed that a subset of the observed behavioural phenomena could be explained by temporal processing in the nervous system (Paper IV). Taken together, this work has provided detailed insight into how neural processing can increase visual reliability in dim light. The results presented are not only relevant to hawkmoths, since neural summation is also expected to increase visual sensitivity in other species of nocturnal insects, and can be compared to similar mechanisms in vertebrates. Furthermore, this work is instructive for the development of artificial visual systems, for which insect brains have proven to be a successful biomimetic model