Bumblebees perceive the spatial layout of their environment in relation to their body size and form to minimize inflight collisions

Bumblebees attend to both the properties of the string and the target in string-pulling tasks, but prioritize the features of the string

Previous studies have demonstrated that associative learning and experience play important roles in the string-pulling of bumblebees (Bombus terrestris). However, the features of the target (artificial flower with sugar reward) and the string that bees learn in such tasks remain unknown. This study aimed to explore the specific aspects of the string-flower arrangement that bumblebees learn and how they prioritize these features. We show that bumblebees trained with string-pulling are sensitive to the flower stimuli; they exhibit a preference for pulling strings connected to flowers over strings that are not attached to a target. Additionally, they chose to pull strings attached to flowers of the same color and shape as experienced during training. The string feature also plays a crucial role for bumblebees when the flower features are identical. Furthermore, bees prioritized the features of the strings rather than the flowers when both cues were in conflict. Our results show that bumblebees solve string-pulling tasks by acquiring knowledge about the characteristics of both targets and strings, and contribute to a deeper understanding of the cognitive processes employed by bees when tackling non-natural skills.

Evidence for socially influenced and potentially actively coordinated cooperation by bumblebees

Cooperation is common in animals, yet the specific mechanisms driving collaborative behaviour in different species remain unclear. We investigated the proximate mechanisms underlying the cooperative behaviour of bumblebees in two different tasks, where bees had to simultaneously push a block in an arena or a door at the end of a tunnel for access to reward. In both tasks, when their partner's entry into the arena/tunnel was delayed, bees took longer to first push the block/door compared with control bees that learned to push alone. In the tunnel task, just before gaining access to reward, bees were more likely to face towards their partner than expected by chance or compared with controls. These results show that bumblebees' cooperative behaviour is not simply a by-product of individual efforts but is socially influenced. We discuss how bees' turning behaviours, e.g. turning around before first reaching the door when their partner was delayed and turning back towards the door in response to seeing their partner heading towards the door, suggest the potential for active coordination. However, because these behaviours could also be interpreted as combined responses to social and secondary reinforcement cues, future studies are needed to help clarify whether bumblebees truly use active coordination.

Wind Gates Search States in Free Flight

For any organism tracking a chemical cue to its source, the motion of its surrounding fluid provides crucial information for success. For both swimming and flying animals engaged in olfaction driven search, turning into the direction of oncoming wind or water current is often a critical first step 1, 2 . However, in nature, wind and water currents may not always provide a reliable directional cue 3, 4, 5 . It is unclear how organisms adjust their search strategies accordingly due to the challenges of separately controlling flow and chemical encounters. Here, we use the genetic toolkit of Drosophila melanogaster , a model organism for olfaction 6 , to develop an optogenetic paradigm to deliver temporally precise "virtual" olfactory experiences in free-flying animals while independently manipulating the wind conditions. We show that in free flight, Drosophila melanogaster adopt distinct search routines that are gated by whether they are flying in laminar wind or in still air. We first confirm that in laminar wind flies turn upwind, and further, we show that they achieve this using a rapid turn. In still air, flies adopt remarkably stereotyped "sink and circle" search state characterized by ∼60°turns at 3-4 Hz, biased in a consistent direction. In both laminar wind and still air, immediately after odor onset, flies decelerate and often perform a rapid turn. Both maneuvers are consistent with predictions from recent control theoretic analyses for how insects may estimate properties of wind while in flight 7, 8 . We suggest that flies may use their deceleration and "anemometric" turn as active sensing maneuvers to rapidly gauge properties of their wind environment before initiating a proximal or upwind search routine.

Finding the gap: neuromorphic motion-vision in dense environments

Animals have evolved mechanisms to travel safely and efficiently within different habitats. On a journey in dense terrains animals avoid collisions and cross narrow passages while controlling an overall course. Multiple hypotheses target how animals solve challenges faced during such travel. Here we show that a single mechanism enables safe and efficient travel. We developed a robot inspired by insects. It has remarkable capabilities to travel in dense terrain, avoiding collisions, crossing gaps and selecting safe passages. These capabilities are accomplished by a neuromorphic network steering the robot toward regions of low apparent motion. Our system leverages knowledge about vision processing and obstacle avoidance in insects. Our results demonstrate how insects might safely travel through diverse habitats. We anticipate our system to be a working hypothesis to study insects' travels in dense terrains. Furthermore, it illustrates that we can design novel hardware systems by understanding the underlying mechanisms driving behaviour.

Ancient insect vision tuned for flight among rocks and plants underpins natural flower colour diversity

Understanding the origins of flower colour signalling to pollinators is fundamental to evolutionary biology and ecology. Flower colour evolves under pressure from visual systems of pollinators, like birds and insects, to establish global signatures among flowers with similar pollinators. However, an understanding of the ancient origins of this relationship remains elusive. Here, we employ computer simulations to generate artificial flower backgrounds assembled from real material sample spectra of rocks, leaves and dead plant materials, against which to test flowers' visibility to birds and bees. Our results indicate how flower colours differ from their backgrounds in strength, and the distributions of salient reflectance features when perceived by these key pollinators, to reveal the possible origins of their colours. Since Hymenopteran visual perception evolved before flowers, the terrestrial chromatic context for its evolution to facilitate flight and orientation consisted of rocks, leaves, sticks and bark. Flowers exploited these pre-evolved visual capacities of their visitors, in response evolving chromatic features to signal to bees, and differently to birds, against a backdrop of other natural materials. Consequently, it appears that today's flower colours may be an evolutionary response to the vision of diurnal pollinators navigating their world millennia prior to the first flowers.

Efficient visual learning by bumble bees in virtual-reality conditions: Size does not matter

Recent developments allowed establishing virtual-reality (VR) setups to study multiple aspects of visual learning in honey bees under controlled experimental conditions. Here, we adopted a VR environment to investigate the visual learning in the buff-tailed bumble bee Bombus terrestris. Based on responses to appetitive and aversive reinforcements used for conditioning, we show that bumble bees had the proper appetitive motivation to engage in the VR experiments and that they learned efficiently elemental color discriminations. In doing so, they reduced the latency to make a choice, increased the proportion of direct paths toward the virtual stimuli and walked faster toward them. Performance in a short-term retention test showed that bumble bees chose and fixated longer on the correct stimulus in the absence of reinforcement. Body size and weight, although variable across individuals, did not affect cognitive performances and had a mild impact on motor performances. Overall, we show that bumble bees are suitable experimental subjects for experiments on visual learning under VR conditions, which opens important perspectives for invasive studies on the neural and molecular bases of such learning given the robustness of these insects and the accessibility of their brain.

Body size awareness matters when dogs decide whether to detour an obstacle or opt for a shortcut

Body-awareness is one of the fundamental modules of self-representation. We investigated how body-awareness could contribute to dogs' decision making in a novel spatial problem where multiple solutions are possible. Family dogs (N = 68) had to obtain a treat from behind a transparent fence. They had two options: either detour around the fence (7 m), or take a shortcut through a doorway (2 m). We had three conditions: small door open, large door open, and doors closed. Our results indicated that dogs assess the size of the doorway, and if they find it too small, they decide to detour instead, while in the case of the open large door, they rather opted for the shortcut without hesitation. Shorter headed dogs tended to choose open doors more often, while longer headed dogs rather chose detours, probably because of their better peripheral vision. While body size awareness did not manifest differently in dogs with short or long heads, we showed for the first time a connection between head shape and physical cognition in dogs. We showed that dogs rely on their body-awareness in a naturalistic setting where multiple solutions exist simultaneously. Dogs make decisions without lengthy trial-and-error learning and choose between options based on their body-awareness.

Ants combine object affordance with latent learning to make efficient foraging decisions

The affordance of an object refers to its functional properties. For example, a bowl has the affordance of holding water, but a sieve does not. Here, we report that ants learn the affordance of a novel object without this attribute being rewarded, and use the memory of this affordance to avoid predicted, but never experienced, crowding. Ants were trained to feeders, which could support either only one ant or many. Two feeders were encountered, each of identical design but differently scented. After training, on the outward journey, half the ants encounter nestmates, which had fed on food matching one of the training feeders. Encountering returning nestmates reduced preference for the feeder matching the scent of the encountered nestmates, but only for ants trained on a limited-access feeder; ants trained on an unlimited feeder were unaffected. In other words, only if ants know that the food access is limited, and receive information that this feeder is heavily visited, do they reduce their preference for this feeder. To achieve this, the ants had to combine memories of the feeders' affordance with the presence of nestmates. Then they had to use semantic knowledge that restricted food access combined with nestmate presence predicts a likelihood of crowding, or a rule such as "if the food is restricted and there are nestmates on the path, go to another food source." Regardless of the mechanism, these results demonstrate that ants latently learn the affordance of their surroundings, an unexpected cognitive ability for an invertebrate.

FlyDetector-Automated Monitoring Platform for the Visual-Motor Coordination of Honeybees in a Dynamic Obstacle Scene Using Digital Paradigm

Vision plays a crucial role in the ability of compound-eyed insects to perceive the characteristics of their surroundings. Compound-eyed insects (such as the honeybee) can change the optical flow input of the visual system by autonomously controlling their behavior, and this is referred to as visual-motor coordination (VMC). To analyze an insect's VMC mechanism in dynamic scenes, we developed a platform for studying insects that actively shape the optic flow of visual stimuli by adapting their flight behavior. Image-processing technology was applied to detect the posture and direction of insects' movement, and automatic control technology provided dynamic scene stimulation and automatic acquisition of perceptual insect behavior. In addition, a virtual mapping technique was used to reconstruct the visual cues of insects for VMC analysis in a dynamic obstacle scene. A simulation experiment at different target speeds of 1-12 m/s was performed to verify the applicability and accuracy of the platform. Our findings showed that the maximum detection speed was 8 m/s, and triggers were 95% accurate. The outdoor experiments showed that flight speed in the longitudinal axis of honeybees was more stable when facing dynamic barriers than static barriers after analyzing the change in geometric optic flow. Finally, several experiments showed that the platform can automatically and efficiently monitor honeybees' perception behavior, and can be applied to study most insects and their VMC.

The potential underlying mechanisms during learning flights

Hymenopterans, such as bees and wasps, have long fascinated researchers with their sinuous movements at novel locations. These movements, such as loops, arcs, or zigzags, serve to help insects learn their surroundings at important locations. They also allow the insects to explore and orient themselves in their environment. After they gained experience with their environment, the insects fly along optimized paths guided by several guidance strategies, such as path integration, local homing, and route-following, forming a navigational toolkit. Whereas the experienced insects combine these strategies efficiently, the naive insects need to learn about their surroundings and tune the navigational toolkit. We will see that the structure of the movements performed during the learning flights leverages the robustness of certain strategies within a given scale to tune other strategies which are more efficient at a larger scale. Thus, an insect can explore its environment incrementally without risking not finding back essential locations.

Optic flow enrichment via Drosophila head and retina motions to support inflight position regulation

Developing a functional description of the neural control circuits and visual feedback paths underlying insect flight behaviors is an active research area. Feedback controllers incorporating engineering models of the insect visual system outputs have described some flight behaviors, yet they do not explain how insects are able to stabilize their body position relative to nearby targets such as neighbors or forage sources, especially in challenging environments in which optic flow is poor. The insect experimental community is simultaneously recording a growing library of in-flight head and eye motions that may be linked to increased perception. This study develops a quantitative model of the optic flow experienced by a flying insect or robot during head yawing rotations (distinct from lateral peering motions in previous work) with a single other target in view. This study then applies a model of insect visuomotor feedback to show via analysis and simulation of five species that these head motions sufficiently enrich the optic flow and that the output feedback can provide relative position regulation relative to the single target (asymptotic stability). In the simplifying case of pure rotation relative to the body, theoretical analysis provides a stronger stability guarantee. The results are shown to be robust to anatomical neck angle limits and body vibrations, persist with more detailed Drosophila lateral-directional flight dynamics simulations, and generalize to recent retinal motion studies. Together, these results suggest that the optic flow enrichment provided by head or pseudopupil rotation could be used in an insect's neural processing circuit to enable position regulation.

Ants combine systematic meandering and correlated random walks when searching for unknown resources

Animal search movements are typically assumed to be mostly random walks, although non-random elements may be widespread. We tracked ants (Temnothorax rugatulus) in a large empty arena, resulting in almost 5 km of trajectories. We tested for meandering by comparing the turn autocorrelations for empirical ant tracks and simulated, realistic Correlated Random Walks. We found that 78% of ants show significant negative autocorrelation around 10 mm (3 body lengths). This means that turns in one direction are likely followed by turns in the opposite direction after this distance. This meandering likely makes the search more efficient, as it allows ants to avoid crossing their own paths while staying close to the nest, avoiding return-travel time. Combining systematic search with stochastic elements may make the strategy less vulnerable to directional inaccuracies. This study is the first to find evidence for efficient search by regular meandering in a freely searching animal.

Optic flow based spatial vision in insects

The optic flow, i.e., the displacement of retinal images of objects in the environment induced by self-motion, is an important source of spatial information, especially for fast-flying insects. Spatial information over a wide range of distances, from the animal's immediate surroundings over several hundred metres to kilometres, is necessary for mediating behaviours, such as landing manoeuvres, collision avoidance in spatially complex environments, learning environmental object constellations and path integration in spatial navigation. To facilitate the processing of spatial information, the complexity of the optic flow is often reduced by active vision strategies. These result in translations and rotations being largely separated by a saccadic flight and gaze mode. Only the translational components of the optic flow contain spatial information. In the first step of optic flow processing, an array of local motion detectors provides a retinotopic spatial proximity map of the environment. This local motion information is then processed in parallel neural pathways in a task-specific manner and used to control the different components of spatial behaviour. A particular challenge here is that the distance information extracted from the optic flow does not represent the distances unambiguously, but these are scaled by the animal's speed of locomotion. Possible ways of coping with this ambiguity are discussed.

Discrimination of edge orientation by bumblebees

Simple feature detectors in the visual system, such as edge-detectors, are likely to underlie even the most complex visual processing, so understanding the limits of these systems is crucial for a fuller understanding of visual processing. We investigated the ability of bumblebees (Bombus terrestris) to discriminate between differently angled edges. In a multiple-choice, “meadow-like” scenario, bumblebees successfully discriminated between angled bars with 7° differences, significantly exceeding the previously reported performance of eastern honeybees (Apis cerana, limit: 15°). Neither the rate at which bees learned, nor their final discrimination performance were affected by the angular orientation of the training bars, indicating a uniform performance across the visual field. Previous work has found that, in dual-choice tests, eastern honeybees cannot reliably discriminate between angles with less than 25° difference, suggesting that performance in discrimination tasks is affected by the training regime, and doesn’t simply reflect the perceptual limitations of the visual system. We used high resolution LCD monitors to investigate bumblebees’ angular resolution in a dual-choice experiment. Bumblebees could still discriminate 7° angle differences under such conditions (exceeding the previously reported limit for Apis mellifera, of 10°, as well as that of A. cerana). Bees eventually reached similar levels of accuracy in the dual-choice experiment as they did under multiple-choice conditions but required longer learning periods. Bumblebees show impressive abilities to discriminate between angled edges, performing better than two previously tested species of honeybee. This high performance may, in turn, support complex visual processing in the bumblebee brain.

Wind and route choice affect performance of bees flying above versus within a cluttered obstacle field

Bees flying through natural landscapes frequently encounter physical challenges, such as wind and cluttered vegetation, but the influence of these factors on flight performance remains unknown. We analyzed 548 videos of wild-caught honeybees (Apis mellifera) flying through an enclosure containing a field of vertical obstacles that bees could choose to fly within (through open corridors, without maneuvering) or above. We varied obstacle field height and wind condition (still, headwinds or tailwinds), and examined how these factors affected bees’ flight altitude, ground speed, and side-to-side casting motions (lateral excursions). When obstacle fields were short, bees flew at altitudes near the midpoint between the tunnel floor and ceiling. When obstacle fields approached or exceeded this midpoint, bees tended to increase their altitude, but they did not always avoid flying through obstacles, despite having the freedom to do so. Bees that flew above the obstacles exhibited 40% faster ground speeds and 36% larger lateral excursions than bees that flew within the obstacle fields. Wind did not affect flight altitude, but bees flew 12–19% faster in tailwinds, and their lateral excursions were 19% larger when flying in headwinds or tailwinds, as compared to still air. Our results show that bees flying through complex environments display flexibility in their route choices (i.e., flying above obstacles in some trials and through them in others), which affects their overall flight performance. Similar choices in natural landscapes could have broad implications for foraging efficiency, pollination, and mortality in wild bees.

Bumblebees display characteristics of active vision during robust obstacle avoidance flight

Insects are remarkable flyers and capable of navigating through highly cluttered environments. We tracked the head and thorax of bumblebees freely flying in a tunnel containing vertically oriented obstacles to uncover the sensorimotor strategies used for obstacle detection and collision avoidance. Bumblebees presented all the characteristics of active vision during flight by stabilizing their head relative to the external environment and maintained close alignment between their gaze and flightpath. Head stabilization increased motion contrast of nearby features against the background to enable obstacle detection. As bees approached obstacles, they appeared to modulate avoidance responses based on the relative retinal expansion velocity (RREV) of obstacles and their maximum evasion acceleration was linearly related to RREVmax. Finally, bees prevented collisions through rapid roll manoeuvres implemented by their thorax. Overall, the combination of visuo-motor strategies of bumblebees highlights elegant solutions developed by insects for visually guided flight through cluttered environments.

Insights into insect cognition through mirror-induced behaviour in paper wasps

Mirror studies have uncovered evidence for self-awareness in several non-human animals; however, this approach has not been extended to invertebrates. Here, we examined mirror responses of Polistes paper wasps, insects with high social cognitive abilities. We used a highly replicated design, exposing wasps to mirror self-recognition (MSR) test stimuli (mirror, facial marking) and several control stimuli (non-reflective surfaces, invisible marks, and sham marks). We found that nest-founding queen wasps respond to mirrors with increases in antennation and touching over non-reflective surfaces. Visible marks also resulted in more exploratory behaviours (antennating and touching the mirror), but decreases in self-directed behaviours typically used as indicators of MSR. While this experiment does not support the notion that wasps possess self-awareness, it shows that wasps respond to subtle alterations in their visual environment and appearance with exploratory behaviour. This work thus increases our understanding of insects’ cognitive abilities, suggesting high levels of perceptual richness.

Ecological Entomology: How Is Gibson's Framework Useful?

To date, numerous studies have demonstrated the fundamental role played by optic flow in the control of goal-directed displacement tasks in insects. Optic flow was first introduced by Gibson as part of their ecological approach to perception and action. While this theoretical approach (as a whole) has been demonstrated to be particularly suitable for the study of goal-directed displacements in humans, its usefulness in carrying out entomological field studies remains to be established. In this review we would like to demonstrate that the ecological approach to perception and action could be relevant for the entomologist community in their future investigations. This approach could provide a conceptual and methodological framework for the community in order to: (i) take a critical look at the research carried out to date, (ii) develop rigorous and innovative experimental protocols, and (iii) define scientific issues that push the boundaries of the current scientific field. After a concise literature review about the perceptual control of displacement in insects, we will present the framework proposed by Gibson and suggest its added value for carrying out research in the field of behavioral ecology in insects.

Gap affordance judgments in bumblebees: Same as humans?

When flying through narrow gaps, bumblebees of different body sizes fly either straightforward or sideways, depending on the relation between their wingspan and the width of the gap (Ravi et al., 2020). They thus behave like humans when walking through narrow passages, which raises the question of the mechanisms underlying their own-body perception.

Insect inspired vision-based velocity estimation through spatial pooling of optic flow during linear motion

Insects rely on the perception of image motion, or optic flow, to estimate their velocity relative to nearby objects. This information provides important sensory input for avoiding obstacles. However, certain behaviors, such as estimating the absolute distance to a landing target, accurately measuring absolute distance traveled, and estimating the ambient wind speed require decoupling optic flow into its component parts: absolute ground velocity and distance to nearby objects. Behavioral experiments suggest that insects perform these calculations, but their mechanism for doing so remains unknown. Here we present a novel algorithm that combines the geometry of dynamic forward motion with known features of insect visual processing to provide a hypothesis for how insects mightdirectlyestimate absolute ground velocity from a combination of optic flow and acceleration information. Our robotics-inspired-biology approach reveals three critical requirements. First, absolute ground velocity can only be directly estimated from optic flow during times of active acceleration and deceleration. Second, spatial pooling of optic flow across a receptive field helps to alleviate the effects of noise and/or low resolution visual systems. Third, averaging velocity estimates from multiple receptive fields further helps to reject noise. Our algorithm provides a hypothesis for how insects might estimate absolute velocity from vision during active maneuvers, and also provides a theoretical framework for designing fast analog circuitry for efficient state estimation that can be applied to insect-sized robots.

Information Is Where You Find It: Perception as an Ecologically Well-Posed Problem

Texts on visual perception typically begin with the following premise: Vision is an ill-posed problem, and perception is underdetermined by the available information. If this were really the case, however, it is hard to see how vision could ever get off the ground. James Gibson's signal contribution was his hypothesis that for every perceivable property of the environment, however subtle, there must be a higher order variable of information, however complex, that specifies it-if only we are clever enough to find them. Such variables are informative about behaviorally relevant properties within the physical and ecological constraints of a species' niche. Sensory ecology is replete with instructive examples, including weakly electric fish, the narwal's tusk, and insect flight control. In particular, I elaborate the case of passing through gaps. Optic flow is sufficient to control locomotion around obstacles and through openings. The affordances of the environment, such as gap passability, are specified by action-scaled information. Logically ill-posed problems may thus, on closer inspection, be ecologically well-posed.

Animal Cognition: The Self-Image of a Bumblebee

Knowing one's body dimensions is a core aspect of individual experience and self-awareness. A recent study illustrates how bees take into account their own body size both in preparation for and while traversing small gaps.