The spatial frequency tuning of optic-flow-dependent behaviors in the bumblebee Bombus impatiens

Brightness cues affect gap negotiation behaviours in zebra finches flying between perches

Flying animals have had to evolve robust and effective guidance strategies for dealing with habitat clutter. Birds and insects use optic flow expansion cues to sense and avoid obstacles, but orchid bees have also been shown to use brightness cues during gap negotiation. Such brightness cues might therefore be of general importance in structuring visually guided flight behaviours. To test the hypothesis that brightness cues also affect gap negotiation behaviours in birds, we presented captive zebra finches Taeniopygia guttata with a symmetric or asymmetric background brightness distribution on the other side of a tunnel. The background brightness conditions influenced both the birds' decision to enter the tunnel aperture, and their flight direction upon exit. Zebra finches were more likely to initiate flight through the tunnel if they could see a bright background through it; they were also more likely to fly to the bright side upon exiting. We found no evidence of the centring response that would be expected if optic flow cues were balanced bilaterally during gap negotiation. Instead, the birds entered the tunnel by targeting a clearance of approximately one wing length from its near edge. Brightness cues therefore affect how zebra finches structure their flight when negotiating gaps in enclosed environments.

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.

Neuroscience and architecture: Modulating behavior through sensorimotor responses to the built environment

As we move through the world, natural and built environments implicitly guide behavior by appealing to certain sensory and motor dynamics. This process can be motivated by automatic attention to environmental features that resonate with specific sensorimotor responses. This review aims at providing a psychobiological framework describing how environmental features can lead to automated sensorimotor responses through defined neurophysiological mechanisms underlying attention. Through the use of automated processes in subsets of cortical structures, the goal of this framework is to describe on a neuronal level the functional link between the designed environment and sensorimotor responses. By distinguishing between environmental features and sensorimotor responses we elaborate on how automatic behavior employs the environment for sensorimotor adaptation. This is realized through a thalamo-cortical network integrating environmental features with motor aspects of behavior. We highlight the underlying transthalamic transmission from an Enactive and predictive perspective and review recent studies that effectively modulated behavior by systematically manipulating environmental features. We end by suggesting a promising combination of neuroimaging and computational analysis for future studies.

Numerosity tuning in human association cortices and local image contrast representations in early visual cortex

Human early visual cortex response amplitudes monotonically increase with numerosity (object number), regardless of object size and spacing. However, numerosity is typically considered a high-level visual or cognitive feature, while early visual responses follow image contrast in the spatial frequency domain. We find that, at fixed contrast, aggregate Fourier power (at all orientations and spatial frequencies) follows numerosity closely but nonlinearly with little effect of object size, spacing or shape. This would allow straightforward numerosity estimation from spatial frequency domain image representations. Using 7T fMRI, we show monotonic responses originate in primary visual cortex (V1) at the stimulus’s retinotopic location. Responses here and in neural network models follow aggregate Fourier power more closely than numerosity. Truly numerosity tuned responses emerge after lateral occipital cortex and are independent of retinotopic location. We propose numerosity’s straightforward perception and neural responses may result from the pervasive spatial frequency analyses of early visual processing.

The authors show that spatial frequency domain Fourier power closely but nonlinearly follows numerosity, simplifying computing numerosity from early visual responses. Monotonic early visual cortex and neural network responses follow Fourier power, while later tuned responses follow numerosity.

Spatial tuning of translational optic flow responses in hawkmoths of varying body size

To safely navigate their environment, flying insects rely on visual cues, such as optic flow. Which cues insects can extract from their environment depends closely on the spatial and temporal response properties of their visual system. These in turn can vary between individuals that differ in body size. How optic flow-based flight control depends on the spatial structure of visual cues, and how this relationship scales with body size, has previously been investigated in insects with apposition compound eyes. Here, we characterised the visual flight control response limits and their relationship to body size in an insect with superposition compound eyes: the hummingbird hawkmoth Macroglossum stellatarum. We used the hawkmoths’ centring response in a flight tunnel as a readout for their reception of translational optic flow stimuli of different spatial frequencies. We show that their responses cut off at different spatial frequencies when translational optic flow was presented on either one, or both tunnel walls. Combined with differences in flight speed, this suggests that their flight control was primarily limited by their temporal rather than spatial resolution. We also observed strong individual differences in flight performance, but no correlation between the spatial response cutoffs and body or eye size.

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.

Multisensory-motor integration in olfactory navigation of silkmoth, Bombyx mori, using virtual reality system

Most animals survive and thrive due to navigational behavior to reach their destinations. In order to navigate, it is important for animals to integrate information obtained from multisensory inputs and use that information to modulate their behavior. In this study, by using a virtual reality (VR) system for an insect, we investigated how the adult silkmoth integrates visual and wind direction information during female search behavior (olfactory behavior). According to the behavioral experiments using a VR system, the silkmoth had the highest navigational success rate when odor, vision, and wind information were correctly provided. However, the success rate of the search was reduced if the wind direction information provided was different from the direction actually detected. This indicates that it is important to acquire not only odor information but also wind direction information correctly. When the wind is received from the same direction as the odor, the silkmoth takes positive behavior; if the odor is detected but the wind direction is not in the same direction as the odor, the silkmoth behaves more carefully. This corresponds to a modulation of behavior according to the degree of complexity (turbulence) of the environment. We mathematically modeled the modulation of behavior using multisensory information and evaluated it using simulations. The mathematical model not only succeeded in reproducing the actual silkmoth search behavior but also improved the search success relative to the conventional odor-source search algorithm.

A micro-CT-based standard brain atlas of the bumblebee

In recent years, bumblebees have become a prominent insect model organism for a variety of biological disciplines, particularly to investigate learning behaviors as well as visual performance. Understanding these behaviors and their underlying neurobiological principles requires a clear understanding of brain anatomy. Furthermore, to be able to compare neuronal branching patterns across individuals, a common framework is required, which has led to the development of 3D standard brain atlases in most of the neurobiological insect model species. Yet, no bumblebee 3D standard brain atlas has been generated. Here we present a brain atlas for the buff-tailed bumblebee Bombus terrestris using micro-computed tomography (micro-CT) scans as a source for the raw data sets, rather than traditional confocal microscopy, to produce the first ever micro-CT-based insect brain atlas. We illustrate the advantages of the micro-CT technique, namely, identical native resolution in the three cardinal planes and 3D structure being better preserved. Our Bombus terrestris brain atlas consists of 30 neuropils reconstructed from ten individual worker bees, with micro-CT allowing us to segment neuropils completely intact, including the lamina, which is a tissue structure often damaged when dissecting for immunolabeling. Our brain atlas can serve as a platform to facilitate future neuroscience studies in bumblebees and illustrates the advantages of micro-CT for specific applications in insect neuroanatomy.

The neuroecology of bee flight behaviours

By combining functional, ecological and evolutionary perspectives, neuroecology can provide key insights into understanding how behaviour and the underlying sensory and neural processes are shaped by ecology and evolutionary history. Bees are an ideal system for neuroecological studies because they represent a numerous and diverse insect group that inhabit a broad range of environments. Flight is central to the evolutionary success of bees and is the key to their survival and fitness but this review of recent work on fundamental flight behaviours in different species - landing, collision avoidance and speed control - reveals striking differences. We discuss the potential ecological and evolutionary drivers behind this variation but argue that to understand their adaptive value future work should include multidisciplinary approaches that integrate neuroscience, ecology, phylogeny and behaviour.

Spatial Vision and Visually Guided Behavior in Apidae

The family Apidae, which is amongst the largest bee families, are important pollinators globally and have been well studied for their visual adaptations and visually guided behaviors. This review is a synthesis of what is known about their eyes and visual capabilities. There are many species-specific differences, however, the relationship between body size, eye size, resolution, and sensitivity shows common patterns. Salient differences between castes and sexes are evident in important visually guided behaviors such as nest defense and mate search. We highlight that Apis mellifera and Bombus terrestris are popular bee models employed in the majority of studies that have contributed immensely to our understanding vision in bees. However, other species, specifically the tropical and many non-social Apidae, merit further investigation for a better understanding of the influence of ecological conditions on the evolution of bee vision.

Eye and wing structure closely reflects the visual ecology of dung beetles

An important resource partitioning strategy allowing dung beetles to coexist in the same habitat, while utilising the same food, is species' separation of activity times. After establishing the diel activity period of three closely related, co-occurring dung beetles, we examined their eye and wing morphology. Absolute and relative eye size, and facet size were greater in the nocturnal Escarabaeus satyrus, followed by the crepuscular Scarabaeus zambesianus and then the diurnal Kheper lamarcki. The diurnal K. lamarcki had the highest wing aspect ratio (long, narrow wings), followed by the crepuscular S. zambesianus and the nocturnal E. satyrus (short, broad wings), suggesting that dim-light active species fly slower than diurnal species. In addition, the two species active in dim light had a lower wing loading than the diurnal species, indicating the need for greater manoeuvrability in the dark. Analyses of wing shape revealed that the diurnal K. lamarcki wing had a proportionally larger jugal and anal region than both dim light species. Our results show that different species of dung beetles have a combination of optical and morphological wing adaptations to support their foraging activities in diverse light conditions.

Gap perception in bumblebees

A number of insects fly over long distances below the natural canopy, where the physical environment is highly cluttered consisting of obstacles of varying shape, size and texture. While navigating within such environments, animals need to perceive and disambiguate environmental features that might obstruct their flight. The most elemental aspect of aerial navigation through such environments is gap identification and 'passability' evaluation. We used bumblebees to seek insights into the mechanisms used for gap identification when confronted with an obstacle in their flight path and behavioral compensations employed to assess gap properties. Initially, bumblebee foragers were trained to fly though an unobstructed flight tunnel that led to a foraging chamber. After the bees were familiar with this situation, we placed a wall containing a gap that unexpectedly obstructed the flight path on a return trip to the hive. The flight trajectories of the bees as they approached the obstacle wall and traversed the gap were analyzed in order to evaluate their behavior as a function of the distance between the gap and a background wall that was placed behind the gap. Bumblebees initially decelerated when confronted with an unexpected obstacle. Deceleration was first noticed when the obstacle subtended around 35 deg on the retina but also depended on the properties of the gap. Subsequently, the bees gradually traded off their longitudinal velocity to lateral velocity and approached the gap with increasing lateral displacement and lateral velocity. Bumblebees shaped their flight trajectory depending on the salience of the gap, indicated in our case by the optic flow contrast between the region within the gap and on the obstacle, which decreased with decreasing distance between the gap and the background wall. As the optic flow contrast decreased, the bees spent an increasing amount of time moving laterally across the obstacles. During these repeated lateral maneuvers, the bees are probably assessing gap geometry and passability.

The role of lateral optic flow cues in hawkmoth flight control

Flying animals require sensory feedback on changes of their body position, as well as on their distance to nearby objects. The apparent image motion, or optic flow, which is generated as animals move through the air, can provide this information. Flight tunnel experiments have been crucial for our understanding of how insects use this optic flow for flight control in confined spaces. However, previous work mainly focused on species from two insect orders: Hymenoptera and Diptera. We therefore set out to investigate if the previously described control strategies to navigate enclosed environments are also used by insects with a different optical system, flight kinematics and phylogenetic background. We tested the role of lateral visual cues for forward flight control in the hummingbird hawkmoth Macroglossum stellatarum (Sphingidae, Lepidoptera), which possess superposition compound eyes, and have the ability to hover in addition to their fast forward flight capacities. Our results show that hawkmoths use a similar strategy for lateral position control as bees and flies in balancing the magnitude of translational optic flow perceived in both eyes. However, the control of lateral optic flow on flight speed in hawkmoths differed from that in bees and flies. Moreover, hawkmoths showed individually attributable differences in position and speed control when the presented optic flow was unbalanced.

Visual Control of Walking Speed in Drosophila

An animal's self-motion generates optic flow across its retina, and it can use this visual signal to regulate its orientation and speed through the world. While orientation control has been studied extensively in Drosophila and other insects, much less is known about the visual cues and circuits that regulate translational speed. Here, we show that flies regulate walking speed with an algorithm that is tuned to the speed of visual motion, causing them to slow when visual objects are nearby. This regulation does not depend strongly on the spatial structure or the direction of visual stimuli, making it algorithmically distinct from the classic computation that controls orientation. Despite the different algorithms, the visual circuits that regulate walking speed overlap with those that regulate orientation. Taken together, our findings suggest that walking speed is controlled by a hierarchical computation that combines multiple motion detectors with distinct tunings. VIDEO ABSTRACT.

Echo interval and not echo intensity drives bat flight behavior in structured corridors

To navigate in the natural environment, animals must adapt their locomotion in response to environmental stimuli. The echolocating bat relies on auditory processing of echo returns to represent its surroundings. Recent studies have shown that echo flow patterns influence bat navigation, but the acoustic basis for flight path selection remains unknown. To investigate this problem, we released bats in a flight corridor with walls constructed of adjacent individual wooden poles, which returned cascades of echoes to the flying bat. We manipulated the spacing and echo strength of the poles comprising each corridor side, and predicted that bats would adapt their flight paths to deviate toward the corridor side returning weaker echo cascades. Our results show that the bat's trajectory through the corridor was not affected by the intensity of echo cascades. Instead, bats deviated toward the corridor wall with more sparsely spaced, highly reflective poles, suggesting that pole spacing, rather than echo intensity, influenced bat flight path selection. This result motivated investigation of the neural processing of echo cascades. We measured local evoked auditory responses in the bat inferior colliculus to echo playback recordings from corridor walls constructed of sparsely and densely spaced poles. We predicted that evoked neural responses would be discretely modulated by temporally distinct echoes recorded from the sparsely spaced pole corridor wall, but not by echoes from the more densely spaced corridor wall. The data confirm this prediction and suggest that the bat's temporal resolution of echo cascades may drive its flight behavior in the corridor.

Spatial Encoding of Translational Optic Flow in Planar Scenes by Elementary Motion Detector Arrays

Elementary Motion Detectors (EMD) are well-established models of visual motion estimation in insects. The response of EMDs are tuned to specific temporal and spatial frequencies of the input stimuli, which matches the behavioural response of insects to wide-field image rotation, called the optomotor response. However, other behaviours, such as speed and position control, cannot be fully accounted for by EMDs because these behaviours are largely unaffected by image properties and appear to be controlled by the ratio between the flight speed and the distance to an object, defined here as relative nearness. We present a method that resolves this inconsistency by extracting an unambiguous estimate of relative nearness from the output of an EMD array. Our method is suitable for estimation of relative nearness in planar scenes such as when flying above the ground or beside large flat objects. We demonstrate closed loop control of the lateral position and forward velocity of a simulated agent flying in a corridor. This finding may explain how insects can measure relative nearness and control their flight despite the frequency tuning of EMDs. Our method also provides engineers with a relative nearness estimation technique that benefits from the low computational cost of EMDs.

Comparison of Visually Guided Flight in Insects and Birds

Over the last half century, work with flies, bees, and moths have revealed a number of visual guidance strategies for controlling different aspects of flight. Some algorithms, such as the use of pattern velocity in forward flight, are employed by all insects studied so far, and are used to control multiple flight tasks such as regulation of speed, measurement of distance, and positioning through narrow passages. Although much attention has been devoted to long-range navigation and homing in birds, until recently, very little was known about how birds control flight in a moment-to-moment fashion. A bird that flies rapidly through dense foliage to land on a branch—as birds often do—engages in a veritable three-dimensional slalom, in which it has to continually dodge branches and leaves, and find, and possibly even plan a collision-free path to the goal in real time. Each mode of flight from take-off to goal could potentially involve a different visual guidance algorithm. Here, we briefly review strategies for visual guidance of flight in insects, synthesize recent work from short-range visual guidance in birds, and offer a general comparison between the two groups of organisms.

Parameters of motion vision in low-light in the hawkmoth, Manduca sexta

The hawkmoth Manduca sexta, is nocturnally active, beginning its flight activity at sunset, and executing rapid controlled maneuvers to search for food and mates in dim light conditions. This moth's visual system has been shown to trade off spatial and temporal resolution for increased sensitivity in these conditions. The study presented here uses tethered flying moths to characterize the flight performance envelope of M. sexta's wide-field-motion-triggered steering response in low light conditions by measuring attempted turning in response to wide-field visual motion. Moths were challenged with a horizontally oscillating sinusoidal grating at a range of luminance, from daylight to starlight conditions. The impact of luminance on response to a range of temporal frequencies and spatial wavelengths was assessed across a range of pattern contrasts. The optomotor response decreased as a function of decreasing luminance, and the lower limit of the moth's contrast sensitivity was found to be between 1% to 5%. The preferred spatial frequency for M. sexta increased from 0.06 to 0.3 cycles/degree as the luminance decreased, but the preferred temporal frequency remained stable at 4.5 Hz across all conditions. The relationship between the optomotor response time to the temporal frequency of the pattern movement did not vary significantly with luminance levels. Taken together, these results suggest that the behavioral response to wide-field visual input in M. sexta is adapted to operate during crepuscular to nocturnal luminance levels, and the decreasing light levels experienced during that period changes visual acuity and does not affect their response time significantly.

Differences in spatial resolution and contrast sensitivity of flight control in the honeybees Apis cerana and Apis mellifera

Visually-guided behaviour is constrained by the capacity of the visual system to resolve detail. This is, in turn, limited by the spatial resolution and contrast sensitivity of the underlying visual system. Because these properties are interdependent and vary non-uniformly, it is only possible to fully understand the limits of a specific visually guided behaviour when they are investigated in combination. To understand the visual limits of flight control in bees, which rely heavily on vision to control flight, and to explore whether they vary between species, we tested how changes in spatial resolution and contrast sensitivity affect the speed and position control of the Asian and European honeybees (Apis cerana and A. mellifera). Despite their apparent similarity, we found some interesting and surprising differences between the visual limits of these species. While the effect of spatial frequency and contrast on position control is similar between the species, ground speed is differently affected by these variables. A comparison with published data from the bumblebee Bombus terrestris reveals further differences. The visual resolution that limits the detection and use of optic flow for flight control in both species of honeybees is lower than previously anatomically determined resolution and differs from object detection limits of A. mellifera, providing evidence that the limits of spatial resolution and contrast sensitivity are highly tuned to the particular behavioural task of a species.

High contrast sensitivity for visually guided flight control in bumblebees

Many insects rely on vision to find food, to return to their nest and to carefully control their flight between these two locations. The amount of information available to support these tasks is, in part, dictated by the spatial resolution and contrast sensitivity of their visual systems. Here, we investigate the absolute limits of these visual properties for visually guided position and speed control in Bombus terrestris. Our results indicate that the limit of spatial vision in the translational motion detection system of B. terrestris lies at 0.21 cycles deg⁻¹ with a peak contrast sensitivity of at least 33. In the perspective of earlier findings, these results indicate that bumblebees have higher contrast sensitivity in the motion detection system underlying position control than in their object discrimination system. This suggests that bumblebees, and most likely also other insects, have different visual thresholds depending on the behavioral context.

Optic flow-based collision-free strategies: From insects to robots

Flying insects are able to fly smartly in an unpredictable environment. It has been found that flying insects have smart neurons inside their tiny brains that are sensitive to visual motion also called optic flow. Consequently, flying insects rely mainly on visual motion during their flight maneuvers such as: takeoff or landing, terrain following, tunnel crossing, lateral and frontal obstacle avoidance, and adjusting flight speed in a cluttered environment. Optic flow can be defined as the vector field of the apparent motion of objects, surfaces, and edges in a visual scene generated by the relative motion between an observer (an eye or a camera) and the scene. Translational optic flow is particularly interesting for short-range navigation because it depends on the ratio between (i) the relative linear speed of the visual scene with respect to the observer and (ii) the distance of the observer from obstacles in the surrounding environment without any direct measurement of either speed or distance. In flying insects, roll stabilization reflex and yaw saccades attenuate any rotation at the eye level in roll and yaw respectively (i.e. to cancel any rotational optic flow) in order to ensure pure translational optic flow between two successive saccades. Our survey focuses on feedback-loops which use the translational optic flow that insects employ for collision-free navigation. Optic flow is likely, over the next decade to be one of the most important visual cues that can explain flying insects' behaviors for short-range navigation maneuvers in complex tunnels. Conversely, the biorobotic approach can therefore help to develop innovative flight control systems for flying robots with the aim of mimicking flying insects' abilities and better understanding their flight.

How bumblebees use lateral and ventral optic flow cues for position control in environments of different proximity

Flying insects frequently navigate through environments of different complexity. In this study, buff-tailed bumblebees (Bombus terrestris L.) were trained to fly along tunnels of different widths, from 60 to 240 cm. In tunnel widths of 60 and 120 cm, bumblebees control their lateral position by balancing the magnitude of translational optic flow experienced in the lateral visual field of each eye. In wider tunnels, bumblebees use translational optic flow cues in the ventral visual field to control their lateral position and to steer along straight tracks. Our results also suggest that bumblebees prefer to fly over surfaces that provide strong ventral optic flow cues, rather than over featureless ones. Together, these strategies allow bumblebees to minimize the risk of collision and to maintain relatively straight flight paths in a broad range of environments.

Finding the gap: a brightness-based strategy for guidance in cluttered environments

The ability to move safely between obstacles is critical for animals that fly rapidly through cluttered environments but surprisingly little is known about how they achieve this. Do they reactively avoid obstacles or do they instead fly towards the gaps between them? If they aim towards gaps, what information do they use to detect and fly through them? Here, we aim to answer these questions by presenting orchid bees with different apertures. When negotiating gaps, orchid bees locate and fly close to the point that gives them greatest clearance from the edges. The cue that they use to pinpoint this spot is the brightness gradient formed across the aperture. Furthermore, we find that orchid bees also rely on brightness cues to locate gaps that are sufficiently large to negotiate safely. The advantage of using brightness for locating and negotiating gaps in a cluttered environment is that it provides information about the safest path through obstacles, at least in a forest environment. This brightness-based guidance strategy for gap detection and negotiation represents a fast, computationally simple and efficient mechanism to identify the clearest path through a forest and is, therefore, likely to represent a more general mechanism used by other animals.

Visual guidance of forward flight in hummingbirds reveals control based on image features instead of pattern velocity

Information about self-motion and obstacles in the environment is encoded by optic flow, the movement of images on the eye. Decades of research have revealed that flying insects control speed, altitude, and trajectory by a simple strategy of maintaining or balancing the translational velocity of images on the eyes, known as pattern velocity. It has been proposed that birds may use a similar algorithm but this hypothesis has not been tested directly. We examined the influence of pattern velocity on avian flight by manipulating the motion of patterns on the walls of a tunnel traversed by Anna's hummingbirds. Contrary to prediction, we found that lateral course control is not based on regulating nasal-to-temporal pattern velocity. Instead, birds closely monitored feature height in the vertical axis, and steered away from taller features even in the absence of nasal-to-temporal pattern velocity cues. For vertical course control, we observed that birds adjusted their flight altitude in response to upward motion of the horizontal plane, which simulates vertical descent. Collectively, our results suggest that birds avoid collisions using visual cues in the vertical axis. Specifically, we propose that birds monitor the vertical extent of features in the lateral visual field to assess distances to the side, and vertical pattern velocity to avoid collisions with the ground. These distinct strategies may derive from greater need to avoid collisions in birds, compared with small insects.

A Model for an Angular Velocity-Tuned Motion Detector Accounting for Deviations in the Corridor-Centering Response of the Bee

We present a novel neurally based model for estimating angular velocity (AV) in the bee brain, capable of quantitatively reproducing experimental observations of visual odometry and corridor-centering in free-flying honeybees, including previously unaccounted for manipulations of behaviour. The model is fitted using electrophysiological data, and tested using behavioural data. Based on our model we suggest that the AV response can be considered as an evolutionary extension to the optomotor response. The detector is tested behaviourally in silico with the corridor-centering paradigm, where bees navigate down a corridor with gratings (square wave or sinusoidal) on the walls. When combined with an existing flight control algorithm the detector reproduces the invariance of the average flight path to the spatial frequency and contrast of the gratings, including deviations from perfect centering behaviour as found in the real bee's behaviour. In addition, the summed response of the detector to a unit distance movement along the corridor is constant for a large range of grating spatial frequencies, demonstrating that the detector can be used as a visual odometer.

Dynamic Echo Information Guides Flight in the Big Brown Bat

Animals rely on sensory feedback from their environment to guide locomotion. For instance, visually guided animals use patterns of optic flow to control their velocity and to estimate their distance to objects (e.g., Srinivasan et al., 1991, 1996). In this study, we investigated how acoustic information guides locomotion of animals that use hearing as a primary sensory modality to orient and navigate in the dark, where visual information is unavailable. We studied flight and echolocation behaviors of big brown bats as they flew under infrared illumination through a corridor with walls constructed from a series of individual vertical wooden poles. The spacing between poles on opposite walls of the corridor was experimentally manipulated to create dense/sparse and balanced/imbalanced spatial structure. The bats' flight trajectories and echolocation signals were recorded with high-speed infrared motion-capture cameras and ultrasound microphones, respectively. As bats flew through the corridor, successive biosonar emissions returned cascades of echoes from the walls of the corridor. The bats flew through the center of the corridor when the pole spacing on opposite walls was balanced and closer to the side with wider pole spacing when opposite walls had an imbalanced density. Moreover, bats produced shorter duration echolocation calls when they flew through corridors with smaller spacing between poles, suggesting that clutter density influences features of the bat's sonar signals. Flight speed and echolocation call rate did not, however, vary with dense and sparse spacing between the poles forming the corridor walls. Overall, these data demonstrate that bats adapt their flight and echolocation behavior dynamically when flying through acoustically complex environments.

Airflow and optic flow mediate antennal positioning in flying honeybees

To maintain their speeds during navigation, insects rely on feedback from their visual and mechanosensory modalities. Although optic flow plays an essential role in speed determination, it is less reliable under conditions of low light or sparse landmarks. Under such conditions, insects rely on feedback from antennal mechanosensors but it is not clear how these inputs combine to elicit flight-related antennal behaviours. We here show that antennal movements of the honeybee, Apis mellifera, are governed by combined visual and antennal mechanosensory inputs. Frontal airflow, as experienced during forward flight, causes antennae to actively move forward as a sigmoidal function of absolute airspeed values. However, corresponding front-to-back optic flow causes antennae to move backward, as a linear function of relative optic flow, opposite the airspeed response. When combined, these inputs maintain antennal position in a state of dynamic equilibrium.

DOI:http://dx.doi.org/10.7554/eLife.14449.001

Insects combine information from different senses to help them navigate during flight. Flying insects see moving images, which the brain can use to measure their speeds. Insect antennae also help to judge speed, as they signal to the brain about the physical forces that result from the insect moving through the air. To accurately detect these forces, and also to detect odors from the surrounding environment, insects must precisely position their antennae as they fly.

To investigate how honeybees use different types of sensory information to position their antennae during flight, Roy Khurana and Sane first placed freely-flying and tethered bees in a wind tunnel. Flying forward causes air to flow from the front to the back of the bee. The experiments revealed that a bee brings its antennae forward and holds them in a specific position that depends on the rate of airflow. As the bee flies forward more quickly (or airflow increases), the antennae are positioned further forward.

Roy Khurana and Sane then investigated how the movement of images across the insect’s eyes causes their antennae to change position. This unexpectedly revealed that moving images across the eye from front to back, which simulates what bees see when flying forward, causes the bees to move their antennae backward. However, exposing the bees to both the frontal airflow and front-to-back image motion as normally experienced during forward flight caused the bees to maintain their antennae in a fixed position. This behaviour results from the opposing responses of the antennae to the two stimuli.

Future challenges will be to determine how the brain of a honeybee combines the information from different senses to position the antennae, and to discover what this behaviour implies for insect flight in general.

DOI:http://dx.doi.org/10.7554/eLife.14449.002

Echo-acoustic flow affects flight in bats

Flying animals need to react fast to rapid changes in their environment. Visually guided animals use optic flow, generated by their movement through structured environments. Nocturnal bats cannot make use of optic flow, but rely mostly on echolocation. Here, we show that bats exploit echo-acoustic flow to negotiate flight through narrow passages. Specifically, bats' flight between lateral structures is significantly affected by the echo-acoustic salience of those structures, independent of their physical distance. This is true even though echolocation, unlike vision, provides explicit distance cues. Moreover, the bats reduced the echolocation sound levels in stronger flow, probably to compensate for the increased summary target strength of the lateral reflectors. However, bats did not reduce flight velocity under stronger echo-acoustic flow. Our results demonstrate that sensory flow is a ubiquitous principle for flight guidance, independent of the fundamentally different peripheral representation of flow across the senses of vision and echolocation.

Spatial Vision in Bombus terrestris

Bombus terrestris is one of the most commonly used insect models to investigate visually guided behavior and spatial vision in particular. Two fundamental measures of spatial vision are spatial resolution and contrast sensitivity. In this study, we report the threshold of spatial resolution in B. terrestris and characterize the contrast sensitivity function of the bumblebee visual system for a dual choice discrimination task. We trained bumblebees in a Y-maze experimental set-up to associate a vertical sinusoidal grating with a sucrose reward, and a horizontal grating with absence of a reward. Using a logistic psychometric function, we estimated a resolution threshold of 0.21 cycles deg⁻¹ of visual angle. This resolution is in the same range but slightly lower than that found in honeybees (Apis mellifera and A. cerana) and another bumblebee species (B. impatiens). We also found that the contrast sensitivity of B. terrestris was 1.57 for the spatial frequency 0.090 cycles deg⁻¹ and 1.26 for 0.18 cycles deg⁻¹.

Aerodynamics, sensing and control of insect-scale flapping-wing flight

There are nearly a million known species of flying insects and 13 000 species of flying warm-blooded vertebrates, including mammals, birds and bats. While in flight, their wings not only move forward relative to the air, they also flap up and down, plunge and sweep, so that both lift and thrust can be generated and balanced, accommodate uncertain surrounding environment, with superior flight stability and dynamics with highly varied speeds and missions. As the size of a flyer is reduced, the wing-to-body mass ratio tends to decrease as well. Furthermore, these flyers use integrated system consisting of wings to generate aerodynamic forces, muscles to move the wings, and sensing and control systems to guide and manoeuvre. In this article, recent advances in insect-scale flapping-wing aerodynamics, flexible wing structures, unsteady flight environment, sensing, stability and control are reviewed with perspective offered. In particular, the special features of the low Reynolds number flyers associated with small sizes, thin and light structures, slow flight with comparable wind gust speeds, bioinspired fabrication of wing structures, neuron-based sensing and adaptive control are highlighted.

Bumblebee flight performance in environments of different proximity

Flying animals are capable of navigating through environments of different complexity with high precision. To control their flight when negotiating narrow tunnels, bees and birds use the magnitude of apparent image motion (known as optic flow) generated by the walls. In their natural habitat, however, these animals would encounter both cluttered and open environments. Here, we investigate how large changes in the proximity of nearby surfaces affect optic flow-based flight control strategies. We trained bumblebees to fly along a flight and recorded how the distance between the walls--from 60 cm to 240 cm--affected their flight control. Our results reveal that, as tunnel width increases, both lateral position and ground speed become increasingly variable. We also find that optic flow information from the ground has an increasing influence on flight control, suggesting that bumblebees measure optic flow flexibly over a large lateral and ventral field of view, depending on where the highest magnitude of optic flow occurs. A consequence of this strategy is that, when flying in narrow spaces, bumblebees use optic flow information from the nearby obstacles to control flight, while in more open spaces they rely primarily on optic flow cues from the ground.

Bumblebees measure optic flow for position and speed control flexibly within the frontal visual field

When flying through narrow spaces, insects control their position by balancing the magnitude of apparent image motion (optic flow) experienced in each eye and their speed by holding this value about a desired set point. Previously, it has been shown that when bumblebees encounter sudden changes in the proximity to nearby surfaces – as indicated by a change in the magnitude of optic flow on each side of the visual field – they adjust their flight speed well before the change, suggesting that they measure optic flow for speed control at low visual angles in the frontal visual field. Here, we investigated the effect that sudden changes in the magnitude of translational optic flow have on both position and speed control in bumblebees if these changes are asymmetrical; that is, if they occur only on one side of the visual field. Our results reveal that the visual region over which bumblebees respond to optic flow cues for flight control is not dictated by a set viewing angle. Instead, bumblebees appear to use the maximum magnitude of translational optic flow experienced in the frontal visual field. This strategy ensures that bumblebees use the translational optic flow generated by the nearest obstacles – that is, those with which they have the highest risk of colliding – to control flight.

Effect of light intensity on flight control and temporal properties of photoreceptors in bumblebees

To control flight, insects rely on the pattern of visual motion generated on the retina as they move through the environment. When light levels fall, vision becomes less reliable and flight control thus becomes more challenging. Here, we investigated the effect of light intensity on flight control by filming the trajectories of free-flying bumblebees (Bombus terrestris, Linnaeus 1758) in an experimental tunnel at different light levels. As light levels fell, flight speed decreased and the flight trajectories became more tortuous but the bees were still remarkably good at centring their flight about the tunnel's midline. To investigate whether this robust flight performance can be explained by visual adaptations in the bumblebee retina, we also examined the response speed of the green-sensitive photoreceptors at the same light intensities. We found that the response speed of the photoreceptors significantly decreased as light levels fell. This indicates that bumblebees have both behavioural (reduction in flight speed) and retinal (reduction in response speed of the photoreceptors) adaptations to allow them to fly in dim light. However, the more tortuous flight paths recorded in dim light suggest that these adaptations do not support flight with the same precision during the twilight hours of the day.

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.

A biomimetic vision-based hovercraft accounts for bees' complex behaviour in various corridors

Here we present the first systematic comparison between the visual guidance behaviour of a biomimetic robot and those of honeybees flying in similar environments. We built a miniature hovercraft which can travel safely along corridors with various configurations. For the first time, we implemented on a real physical robot the 'lateral optic flow regulation autopilot', which we previously studied computer simulations. This autopilot inspired by the results of experiments on various species of hymenoptera consists of two intertwined feedback loops, the speed and lateral control loops, each of which has its own optic flow (OF) set-point. A heading-lock system makes the robot move straight ahead as fast as 69 cm s(-1) with a clearance from one wall as small as 31 cm, giving an unusually high translational OF value (125° s(-1)). Our biomimetic robot was found to navigate safely along straight, tapered and bent corridors, and to react appropriately to perturbations such as the lack of texture on one wall, the presence of a tapering or non-stationary section of the corridor and even a sloping terrain equivalent to a wind disturbance. The front end of the visual system consists of only two local motion sensors (LMS), one on each side. This minimalistic visual system measuring the lateral OF suffices to control both the robot's forward speed and its clearance from the walls without ever measuring any speeds or distances. We added two additional LMSs oriented at +/-45° to improve the robot's performances in stiffly tapered corridors. The simple control system accounts for worker bees' ability to navigate safely in six challenging environments: straight corridors, single walls, tapered corridors, straight corridors with part of one wall moving or missing, as well as in the presence of wind.

Spatial vision in insects is facilitated by shaping the dynamics of visual input through behavioral action

Insects such as flies or bees, with their miniature brains, are able to control highly aerobatic flight maneuvres and to solve spatial vision tasks, such as avoiding collisions with obstacles, landing on objects, or even localizing a previously learnt inconspicuous goal on the basis of environmental cues. With regard to solving such spatial tasks, these insects still outperform man-made autonomous flying systems. To accomplish their extraordinary performance, flies and bees have been shown by their characteristic behavioral actions to actively shape the dynamics of the image flow on their eyes ("optic flow"). The neural processing of information about the spatial layout of the environment is greatly facilitated by segregating the rotational from the translational optic flow component through a saccadic flight and gaze strategy. This active vision strategy thus enables the nervous system to solve apparently complex spatial vision tasks in a particularly efficient and parsimonious way. The key idea of this review is that biological agents, such as flies or bees, acquire at least part of their strength as autonomous systems through active interactions with their environment and not by simply processing passively gained information about the world. These agent-environment interactions lead to adaptive behavior in surroundings of a wide range of complexity. Animals with even tiny brains, such as insects, are capable of performing extraordinarily well in their behavioral contexts by making optimal use of the closed action-perception loop. Model simulations and robotic implementations show that the smart biological mechanisms of motion computation and visually-guided flight control might be helpful to find technical solutions, for example, when designing micro air vehicles carrying a miniaturized, low-weight on-board processor.

Blowfly flight characteristics are shaped by environmental features and controlled by optic flow information

Blowfly flight consists of two main components, saccadic turns and intervals of mostly straight gaze direction, although, as a consequence of inertia, flight trajectories usually change direction smoothly. We investigated how flight behavior changes depending on the surroundings and how saccadic turns and intersaccadic translational movements might be controlled in arenas of different width with and without obstacles. Blowflies do not fly in straight trajectories, even when traversing straight flight arenas; rather, they fly in meandering trajectories. Flight speed and the amplitude of meanders increase with arena width. Although saccade duration is largely constant, peak angular velocity and succession into either direction are variable and depend on the visual surroundings. Saccade rate and amplitude also vary with arena layout and are correlated with the 'time-to-contact' to the arena wall. We provide evidence that both saccade and velocity control rely to a large extent on the intersaccadic optic flow generated in eye regions looking well in front of the fly, rather than in the lateral visual field, where the optic flow at least during forward flight tends to be strongest.

Visual flight control in naturalistic and artificial environments

Although the visual flight control strategies of flying insects have evolved to cope with the complexity of the natural world, studies investigating this behaviour have typically been performed indoors using simplified two-dimensional artificial visual stimuli. How well do the results from these studies reflect the natural behaviour of flying insects considering the radical differences in contrast, spatial composition, colour and dimensionality between these visual environments? Here, we aim to answer this question by investigating the effect of three- and two-dimensional naturalistic and artificial scenes on bumblebee flight control in an outdoor setting and compare the results with those of similar experiments performed in an indoor setting. In particular, we focus on investigating the effect of axial (front-to-back) visual motion cues on ground speed and centring behaviour. Our results suggest that, in general, ground speed control and centring behaviour in bumblebees is not affected by whether the visual scene is two- or three dimensional, naturalistic or artificial, or whether the experiment is conducted indoors or outdoors. The only effect that we observe between naturalistic and artificial scenes on flight control is that when the visual scene is three-dimensional and the visual information on the floor is minimised, bumblebees fly further from the midline of the tunnel. The findings presented here have implications not only for understanding the mechanisms of visual flight control in bumblebees, but also for the results of past and future investigations into visually guided flight control in other insects.

Visual control of navigation in insects and its relevance for robotics

Flying insects display remarkable agility, despite their diminutive eyes and brains. This review describes our growing understanding of how these creatures use visual information to stabilize flight, avoid collisions with objects, regulate flight speed, detect and intercept other flying insects such as mates or prey, navigate to a distant food source, and orchestrate flawless landings. It also outlines the ways in which these insights are now being used to develop novel, biologically inspired strategies for the guidance of autonomous, airborne vehicles.

Nocturnal insects use optic flow for flight control

To avoid collisions when navigating through cluttered environments, flying insects must control their flight so that their sensory systems have time to detect obstacles and avoid them. To do this, day-active insects rely primarily on the pattern of apparent motion generated on the retina during flight (optic flow). However, many flying insects are active at night, when obtaining reliable visual information for flight control presents much more of a challenge. To assess whether nocturnal flying insects also rely on optic flow cues to control flight in dim light, we recorded flights of the nocturnal neotropical sweat bee, Megalopta genalis, flying along an experimental tunnel when: (i) the visual texture on each wall generated strong horizontal (front-to-back) optic flow cues, (ii) the texture on only one wall generated these cues, and (iii) horizontal optic flow cues were removed from both walls. We find that Megalopta increase their groundspeed when horizontal motion cues in the tunnel are reduced (conditions (ii) and (iii)). However, differences in the amount of horizontal optic flow on each wall of the tunnel (condition (ii)) do not affect the centred position of the bee within the flight tunnel. To better understand the behavioural response of Megalopta, we repeated the experiments on day-active bumble-bees (Bombus terrestris). Overall, our findings demonstrate that despite the limitations imposed by dim light, Megalopta-like their day-active relatives-rely heavily on vision to control flight, but that they use visual cues in a different manner from diurnal insects.

Non-directional motion detectors can be used to mimic optic flow dependent behaviors

Insect navigational behaviors including obstacle avoidance, grazing landings, and visual odometry are dependent on the ability to estimate flight speed based only on visual cues. In honeybees, this visual estimate of speed is largely independent of both the direction of motion and the spatial frequency content of the image. Electrophysiological recordings from the motion-sensitive cells believed to underlie these behaviors have long supported spatio-temporally tuned correlation-type models of visual motion detection whose speed tuning changes as the spatial frequency of a stimulus is varied. The result is an apparent conflict between behavioral experiments and the electrophysiological and modeling data. In this article, we demonstrate that conventional correlation-type models are sufficient to reproduce some of the speed-dependent behaviors observed in honeybees when square wave gratings are used, contrary to the theoretical predictions. However, these models fail to match the behavioral observations for sinusoidal stimuli. Instead, we show that non-directional motion detectors, which underlie the correlation-based computation of directional motion, can be used to mimic these same behaviors even when narrowband gratings are used. The existence of such non-directional motion detectors is supported both anatomically and electrophysiologically, and they have been hypothesized to be critical in the Dipteran elementary motion detector (EMD) circuit.