Flights of Learning

Cognitive abilities related to foraging behavior in Vespula vulgaris (Hymenoptera: Vespidae)

Vespula vulgaris is an invasive social wasp that has become established in many parts of the world. Plastic cognitive systems are expected to be advantageous for invasive species, given that they continuously face dynamic and unpredictable environments. We analyzed foraging behavior associated with undepleted and depleted resources. The wasps were trained to associate a certain location with food and we recorded their behavior after successive displacement of it. We also studied how long wasps continued to search for food that was no longer available and whether it was dependent on experience. We found that when wasps associated a certain location with food, they returned to the same site even though food was no longer available or had been displaced. Handling time remained constant, while relocation time and learning flights decreased with experience. With a food position change, learning flights increased and searching time varied with experience. When food was removed, hovering and landings were greatest in wasps that had the most experience with the resource, although extinction of the searching response was not dependent on experience. Our results illustrate the plasticity of wasp behavior in uncertain foraging contexts, which could have allowed the species to establish successfully in new habitats.

Colour and motion affect a dune wasp's ability to detect its cryptic spider predators

Ambush predators depend on cryptic body colouration, stillness and a suitable hunting location to optimise the probability of prey capture. Detection of cryptic predators, such as crab spiders, by flower seeking wasps may also be hindered by wind induced movement of the flowers themselves. In a beach dune habitat, Microbembex nigrifrons wasps approaching flowerheads of the Palafoxia lindenii plant need to evaluate the flowers to avoid spider attack. Wasps may detect spiders through colour and movement cues. We tracked the flight trajectories of dune wasps as they approached occupied and unoccupied flowers under two movement conditions; when the flowers were still or moving. We simulated the appearance of the spider and the flower using psychophysical visual modelling techniques and related it to the decisions made by the wasp to land or avoid the flower. Wasps could discriminate spiders only at a very close range, and this was reflected in the shape of their trajectories. Wasps were more prone to making errors in threat assessment when the flowers are moving. Our results suggest that dune wasp predation risk is augmented by abiotic conditions such as wind and compromises their early detection capabilities.

Many paths, one destination: mapping the movements of a kleptoparasitic spider on the host's web

Kleptoparasitic spiders live and forage in the webs of other spiders. Using vibratory cues generated by the host spider during prey capture, they leave their resting positions in the upper peripheries of the host web and move towards the centre of the web where they feed along with the host spider or steal small pieces of prey. While the triggers for initiating the foraging raids are known, there is little information about the fine-scale trajectory dynamics in this model system. We mapped the movement of the kleptoparasite Argyrodes elevatus in the web of the host Trichonephila clavipes. We filmed the movement of the kleptoparasite spiders and quantified the trajectory shape, speed, heading directions and path revisitation. Our results show that kleptoparasitic spider movement is spatially structured, with higher levels of speed at the peripheries and slower in the centre of the web. We found a high level of variation in trajectory shapes between individuals. We found that the majority of heading orientations were away from the hub suggesting that detouring or repeated approaches are an essential component of kleptoparasite movement strategies. Our results of the revisitation rate also confirm this pattern, where locations close to the hub were revisited more often than in the periphery. The kleptoparasite-host spider system is a promising model to study fine-scale movement patterns in small bounded spaces.

The Critical Role of Head Movements for Spatial Representation During Bumblebees Learning Flight

Bumblebees perform complex flight maneuvers around the barely visible entrance of their nest upon their first departures. During these flights bees learn visual information about the surroundings, possibly including its spatial layout. They rely on this information to return home. Depth information can be derived from the apparent motion of the scenery on the bees' retina. This motion is shaped by the animal's flight and orientation: Bees employ a saccadic flight and gaze strategy, where rapid turns of the head (saccades) alternate with flight segments of apparently constant gaze direction (intersaccades). When during intersaccades the gaze direction is kept relatively constant, the apparent motion contains information about the distance of the animal to environmental objects, and thus, in an egocentric reference frame. Alternatively, when the gaze direction rotates around a fixed point in space, the animal perceives the depth structure relative to this pivot point, i.e., in an allocentric reference frame. If the pivot point is at the nest-hole, the information is nest-centric. Here, we investigate in which reference frames bumblebees perceive depth information during their learning flights. By precisely tracking the head orientation, we found that half of the time, the head appears to pivot actively. However, only few of the corresponding pivot points are close to the nest entrance. Our results indicate that bumblebees perceive visual information in several reference frames when they learn about the surroundings of a behaviorally relevant location.

Taking a goal-centred dynamic snapshot as a possibility for local homing in initially naïve bumblebees

It is essential for central place foragers, such as bumblebees, to return reliably to their nest. Bumblebees, leaving their inconspicuous nest hole for the first time need to gather and learn sufficient information about their surroundings to allow them to return to their nest at the end of their trip, instead of just flying away to forage. Therefore, we assume an intrinsic learning programme that manifests itself in the flight structure immediately after leaving the nest for the first time. In this study, we recorded and analysed the first outbound flight of individually marked naïve bumblebees in an indoor environment. We found characteristic loop-like features in the flight pattern that appear to be necessary for the bees to acquire environmental information and might be relevant for finding the nest hole after a foraging trip. Despite common features in their spatio-temporal organisation, first departure flights from the nest are characterised by a high level of variability in their loop-like flight structure across animals. Changes in turn direction of body orientation, for example, are distributed evenly across the entire area used for the flights without any systematic relationship to the nest location. By considering the common flight motifs and this variability, we came to the hypothesis that a kind of dynamic snapshot is taken during the early phase of departure flights centred at the nest location. The quality of this snapshot is hypothesised to be 'tested' during the later phases of the departure flights concerning its usefulness for local homing.

A tiger beetle's pursuit of prey depends on distance

Tiger beetles pursue prey by adjusting their heading according to a time-delayed proportional control law that minimizes the error angle (Haselsteiner et al 2014 J. R. Soc. Interface 11 20140216). This control law can be further interpreted in terms of mechanical actuation: to catch prey, tiger beetles exert a sideways force by biasing their tripod gait in proportion to the error angle measured half a stride earlier. The proportional gain was found to be nearly optimal in the sense that it minimizes the time to point directly toward the prey. For a time-delayed linear proportional controller, the optimal gain, k, is inversely proportional to the time delay, τ, and satisfies [Formula: see text]. Here we present evidence that tiger beetles adjust their control gain during their pursuit of prey. Our analysis shows two critical distances: one corresponding to the beetle's final approach to the prey, and the second, less expected, occurring at a distance around 10 cm for a prey size of 4.5 mm. The beetle initiates its chase using a sub-critical gain and increases the gain to the optimal value once the prey is within this critical distance. Insects use a variety of methods to detect distance, often involving different visual cues. Here we examine two such methods: one based on motion parallax and the other based on the prey's elevation angle. We show that, in order for the motion parallax method to explain the observed data, the beetle needs to correct for the ratio of the prey's sideways velocity relative to its own. On the other hand, the simpler method based on the elevation angle can detect both the distance and the prey's size. Moreover we find that the transition distance corresponds to the accuracy required to distinguish small prey from large predators.

Object Recognition in Flight: How Do Bees Distinguish between 3D Shapes?

Honeybees (Apis mellifera) discriminate multiple object features such as colour, pattern and 2D shape, but it remains unknown whether and how bees recover three-dimensional shape. Here we show that bees can recognize objects by their three-dimensional form, whereby they employ an active strategy to uncover the depth profiles. We trained individual, free flying honeybees to collect sugar water from small three-dimensional objects made of styrofoam (sphere, cylinder, cuboids) or folded paper (convex, concave, planar) and found that bees can easily discriminate between these stimuli. We also tested possible strategies employed by the bees to uncover the depth profiles. For the card stimuli, we excluded overall shape and pictorial features (shading, texture gradients) as cues for discrimination. Lacking sufficient stereo vision, bees are known to use speed gradients in optic flow to detect edges; could the bees apply this strategy also to recover the fine details of a surface depth profile? Analysing the bees' flight tracks in front of the stimuli revealed specific combinations of flight maneuvers (lateral translations in combination with yaw rotations), which are particularly suitable to extract depth cues from motion parallax. We modelled the generated optic flow and found characteristic patterns of angular displacement corresponding to the depth profiles of our stimuli: optic flow patterns from pure translations successfully recovered depth relations from the magnitude of angular displacements, additional rotation provided robust depth information based on the direction of the displacements; thus, the bees flight maneuvers may reflect an optimized visuo-motor strategy to extract depth structure from motion signals. The robustness and simplicity of this strategy offers an efficient solution for 3D-object-recognition without stereo vision, and could be employed by other flying insects, or mobile robots.

Bumblebee Homing: The Fine Structure of Head Turning Movements

Changes in flight direction in flying insects are largely due to roll, yaw and pitch rotations of their body. Head orientation is stabilized for most of the time by counter rotation. Here, we use high-speed video to analyse head- and body-movements of the bumblebee Bombus terrestris while approaching and departing from a food source located between three landmarks in an indoor flight-arena. The flight paths consist of almost straight flight segments that are interspersed with rapid turns. These short and fast yaw turns ("saccades") are usually accompanied by even faster head yaw turns that change gaze direction. Since a large part of image rotation is thereby reduced to brief instants of time, this behavioural pattern facilitates depth perception from visual motion parallax during the intersaccadic intervals. The detailed analysis of the fine structure of the bees' head turning movements shows that the time course of single head saccades is very stereotypical. We find a consistent relationship between the duration, peak velocity and amplitude of saccadic head movements, which in its main characteristics resembles the so-called "saccadic main sequence" in humans. The fact that bumblebee head saccades are highly stereotyped as in humans, may hint at a common principle, where fast and precise motor control is used to reliably reduce the time during which the retinal images moves.

Motion as a source of environmental information: a fresh view on biological motion computation by insect brains

Despite their miniature brains insects, such as flies, bees and wasps, are able to navigate by highly erobatic flight maneuvers in cluttered environments. They rely on spatial information that is contained in the retinal motion patterns induced on the eyes while moving around ("optic flow") to accomplish their extraordinary performance. Thereby, they employ an active flight and gaze strategy that separates rapid saccade-like turns from translatory flight phases where the gaze direction is kept largely constant. This behavioral strategy facilitates the processing of environmental information, because information about the distance of the animal to objects in the environment is only contained in the optic flow generated by translatory motion. However, motion detectors as are widespread in biological systems do not represent veridically the velocity of the optic flow vectors, but also reflect textural information about the environment. This characteristic has often been regarded as a limitation of a biological motion detection mechanism. In contrast, we conclude from analyses challenging insect movement detectors with image flow as generated during translatory locomotion through cluttered natural environments that this mechanism represents the contours of nearby objects. Contrast borders are a main carrier of functionally relevant object information in artificial and natural sceneries. The motion detection system thus segregates in a computationally parsimonious way the environment into behaviorally relevant nearby objects and-in many behavioral contexts-less relevant distant structures. Hence, by making use of an active flight and gaze strategy, insects are capable of performing extraordinarily well even with a computationally simple motion detection mechanism.

Visual motion-sensitive neurons in the bumblebee brain convey information about landmarks during a navigational task

Bees use visual memories to find the spatial location of previously learnt food sites. Characteristic learning flights help acquiring these memories at newly discovered foraging locations where landmarks—salient objects in the vicinity of the goal location—can play an important role in guiding the animal's homing behavior. Although behavioral experiments have shown that bees can use a variety of visual cues to distinguish objects as landmarks, the question of how landmark features are encoded by the visual system is still open. Recently, it could be shown that motion cues are sufficient to allow bees localizing their goal using landmarks that can hardly be discriminated from the background texture. Here, we tested the hypothesis that motion sensitive neurons in the bee's visual pathway provide information about such landmarks during a learning flight and might, thus, play a role for goal localization. We tracked learning flights of free-flying bumblebees (Bombus terrestris) in an arena with distinct visual landmarks, reconstructed the visual input during these flights, and replayed ego-perspective movies to tethered bumblebees while recording the activity of direction-selective wide-field neurons in their optic lobe. By comparing neuronal responses during a typical learning flight and targeted modifications of landmark properties in this movie we demonstrate that these objects are indeed represented in the bee's visual motion pathway. We find that object-induced responses vary little with object texture, which is in agreement with behavioral evidence. These neurons thus convey information about landmark properties that are useful for view-based homing.

Gaze characteristics of freely walking blowflies Calliphora vicina in a goal-directed task

In contrast to flying flies, walking flies experience relatively strong rotational gaze shifts, even during overall straight phases of locomotion. These gaze shifts are caused by the walking apparatus and modulated by the stride frequency. Accordingly, even during straight walking phases, the retinal image flow is composed of both translational and rotational optic flow, which might affect spatial vision, as well as fixation behavior. We addressed this issue for an orientation task where walking blowflies approached a black vertical bar. The visual stimulus was stationary, or either the bar or the background moved horizontally. The stride-coupled gaze shifts of flies walking toward the bar had similar amplitudes under all visual conditions tested. This finding indicates that these shifts are an inherent feature of walking, which are not even compensated during a visual goal fixation task. By contrast, approaching flies showed a frequent stop-and-go behavior that was affected by the stimulus conditions. As sustained image rotations may impair distance estimation during walking, we propose a hypothesis that explains how rotation-independent translatory image flow containing distance information can be determined. The algorithm proposed works without requiring differentiation at the behavioral level of the rotational and translational flow components. By contrast, disentangling both has been proposed to be necessary during flight. By comparing the retinal velocities of the edges of the goal, its rotational image motion component can be removed. Consequently, the expansion velocity of the goal and, thus, its proximity can be extracted, irrespective of distance-independent stride-coupled rotational image shifts.

Can Bees See at a Glance?

Primates can analyse visual scenes extremely rapidly, making accurate decisions for presentation times of only 20ms. We asked if bumblebees, despite having potentially more limited processing power, could similarly detect and discriminate visual patterns presented for durations of 100ms or less. Bumblebees detected stimuli and discriminated between differently oriented and coloured stimuli even when presented as briefly as 20ms but failed to identify ecologically relevant shapes (predatory spiders on flowers) even when presented for 100ms. This suggests a profound difference between primate and insect visual processing, so that while primates can capture entire visual scenes 'at a glance', insects might have to rely on continuous online sampling of the world around them, using a process of active vision which requires longer integration times.

The ontogeny of bumblebee flight trajectories: from naïve explorers to experienced foragers

Understanding strategies used by animals to explore their landscape is essential to predict how they exploit patchy resources, and consequently how they are likely to respond to changes in resource distribution. Social bees provide a good model for this and, whilst there are published descriptions of their behaviour on initial learning flights close to the colony, it is still unclear how bees find floral resources over hundreds of metres and how these flights become directed foraging trips. We investigated the spatial ecology of exploration by radar tracking bumblebees, and comparing the flight trajectories of bees with differing experience. The bees left the colony within a day or two of eclosion and flew in complex loops of ever-increasing size around the colony, exhibiting Lévy-flight characteristics constituting an optimal searching strategy. This mathematical pattern can be used to predict how animals exploring individually might exploit a patchy landscape. The bees' groundspeed, maximum displacement from the nest and total distance travelled on a trip increased significantly with experience. More experienced bees flew direct paths, predominantly flying upwind on their outward trips although forage was available in all directions. The flights differed from those of naïve honeybees: they occurred at an earlier age, showed more complex looping, and resulted in earlier returns of pollen to the colony. In summary bumblebees learn to find home and food rapidly, though phases of orientation, learning and searching were not easily separable, suggesting some multi-tasking.

Odometry and insect navigation

Animals have needed to find their way about almost since a free-living life style evolved. Particularly, if an animal has a home – shelter or nesting site – true navigation becomes necessary to shuttle between this home and areas of other activities, such as feeding. As old as navigation is in the animal kingdom, as diverse are its mechanisms and implementations, depending on an organism's ecology and its endowment with sensors and actuators. The use of landmarks for piloting or the use of trail pheromones for route following have been examined in great detail and in a variety of animal species. The same is true for senses of direction – the compasses for navigation – and the construction of vectors for navigation from compass and distance cues. The measurement of distance itself – odometry – has received much less attention. The present review addresses some recent progress in the understanding of odometers in invertebrates, after outlining general principles of navigation to put odometry in its proper context. Finally, a number of refinements that increase navigation accuracy and safety are addressed.

Two odometers in honeybees?

Although several studies have examined how honeybees gauge and report the distance and direction of a food source to their nestmates, relatively little is known about how this information is combined to obtain a representation of the position of the food source. In this study we manipulate the amount of celestial compass information available to the bee during flight, and analyse the encoding of spatial information in the waggle dance as well as in the navigation of the foraging bee. We find that the waggle dance encodes information about the total distance flown to the food source, even when celestial compass cues are available only for a part of the journey. This stands in contrast to how a bee gauges distance flown when it navigates back to a food source that it already knows. When bees were trained to find a feeder placed at a fixed distance in a tunnel in which celestial cues were partially occluded and then tested in a tunnel that was fully open to the sky,they searched for the feeder at a distance that corresponds closely to the distance that was flown under the open sky during the training. Thus, when navigating back to a food source, information about distance travelled is disregarded when there is no concurrent input from the celestial compass. We suggest that bees may possess two different odometers – a `community'odometer that is used to provide information to nestmates via the dance, and a `personal' odometer that is used by an experienced individual to return to a previously visited source.

Depth, contrast and view-based homing in outdoor scenes

Panoramic image differences can be used for view-based homing under natural outdoor conditions, because they increase smoothly with distance from a reference location (Zeil et al., J Opt Soc Am A 20(3):450-469, 2003). The particular shape, slope and depth of such image difference functions (IDFs) recorded at any one place, however, depend on a number of factors that so far have only been qualitatively identified. Here we show how the shape of difference functions depends on the depth structure and the contrast of natural scenes, by quantifying the depth- distribution of different outdoor scenes and by comparing it to the difference functions calculated with differently processed panoramic images, which were recorded at the same locations. We find (1) that IDFs and catchment areas become systematically wider as the average distance of objects increases, (2) that simple image processing operations -- like subtracting the local mean, difference-of-Gaussian filtering and local contrast normalization -- make difference functions robust against changes in illumination and the spurious effects of shadows, and (3) by comparing depth-dependent translational and depth-independent rotational difference functions, we show that IDFs of contrast-normalized snapshots are predominantly determined by the depth-structure and possibly also by occluding contours in a scene. We propose a model for the shape of IDFs as a tool for quantitative comparisons between the shapes of these functions in different scenes.

Catchment areas of panoramic snapshots in outdoor scenes

We took panoramic snapshots in outdoor scenes at regular intervals in two- or three-dimensional grids covering 1 m2 or 1 m3 and determined how the root mean square pixel differences between each of the images and a reference image acquired at one of the locations in the grid develop over distance from the reference position. We then asked whether the reference position can be pinpointed from a random starting position by moving the panoramic imaging device in such a way that the image differences relative to the reference image are minimized. We find that on time scales of minutes to hours, outdoor locations are accurately defined by a clear, sharp minimum in a smooth three-dimensional (3D) volume of image differences (the 3D difference function). 3D difference functions depend on the spatial-frequency content of natural scenes and on the spatial layout of objects therein. They become steeper in the vicinity of dominant objects. Their shape and smoothness, however, are affected by changes in illumination and shadows. The difference functions generated by rotation are similar in shape to those generated by translation, but their plateau values are higher. Rotational difference functions change little with distance from the reference location. Simple gradient descent methods are surprisingly successful in recovering a goal location, even if faced with transient changes in illumination. Our results show that view-based homing with panoramic images is in principle feasible in natural environments and does not require the identification of individual landmarks. We discuss the relevance of our findings to the study of robot and insect homing.

Vision in flying insects

Vision guides flight behaviour in numerous insects. Despite their small brain, insects easily outperform current man-made autonomous vehicles in many respects. Examples are the virtuosic chasing manoeuvres male flies perform as part of their mating behaviour and the ability of bees to assess, on the basis of visual motion cues, the distance travelled in a novel environment. Analyses at both the behavioural and neuronal levels are beginning to unveil reasons for such extraordinary capabilities of insects. One recipe for their success is the adaptation of visual information processing to the specific requirements of the behavioural tasks and to the specific spatiotemporal properties of the natural input.

A comparative study of geometric rule learning by nutcrackers (Nucifraga columbiana), pigeons (Columba livia), and jackdaws (Corvus monedula)

Three avian species, a seed-caching corvid (Clark's nutcrackers; Nucifraga columbiana), a non-seed-caching corvid (jackdaws; Corvus monedula), and a non-seed-caching columbid (pigeons; Columba livia), were tested for ability to learn to find a goal halfway between 2 landmarks when distance between the landmarks varied during training. All 3 species learned, but jackdaws took much longer than either pigeons or nutcrackers. The nutcrackers searched more accurately than either pigeons or jackdaws. Both nutcrackers and pigeons showed good transfer to novel landmark arrays in which interlandmark distances were novel, but inconclusive results were obtained from jackdaws. Species differences in this spatial task appear quantitative rather than qualitative and are associated with differences in natural history rather than phylogeny.