Search

When an animal moves through the world, its brain receives a stream of information about the body’s translational velocity from motor commands and sensory feedback signals. These incoming signals are referenced to the body, but ultimately, they must be transformed into world-centric coordinates for navigation. Here we show that this computation occurs in the fan-shaped body in the brain of Drosophila melanogaster. We identify two cell types, PFNd and PFNv, that conjunctively encode translational velocity and heading as a fly walks. In these cells, velocity signals are acquired from locomotor brain regions and are multiplied with heading signals from the compass system. PFNd neurons prefer forward–ipsilateral movement, whereas PFNv neurons prefer backward–contralateral movement, and perturbing PFNd neurons disrupts idiothetic path integration in walking flies. Downstream, PFNd and PFNv neurons converge onto hΔB neurons, with a connectivity pattern that pools together heading and translation direction combinations corresponding to the same movement in world-centric space. This network motif effectively performs a rotation of the brain’s representation of body-centric translational velocity according to the current heading direction. Consistent with our predictions, we observe that hΔB neurons form a representation of translational velocity in world-centric coordinates. By integrating this representation over time, it should be possible for the brain to form a working memory of the path travelled through the environment.

While insects such as Drosophila are flying, aerodynamic instabilities require that they make millisecond time scale adjustments to their wing motion to stay aloft and on course. These stabilization reflexes can be modeled as a proportional-integral (PI) controller; however, it is unclear how such control might be instantiated in insects at the level of muscles and neurons. Here, we show that the b1 and b2 motor units—prominent components of the fly’s steering muscle system—modulate specific elements of the PI controller: the angular displacement (integral) and angular velocity (proportional), respectively. Moreover, these effects are observed only during the stabilization of pitch. Our results provide evidence for an organizational principle in which each muscle contributes to a specific functional role in flight control, a finding that highlights the power of using top-down behavioral modeling to guide bottom-up cellular manipulation studies.

SUMMARYTo maintain stable flight, animals continuously perform trimming adjustments to compensate for internal and external perturbations. Whereas animals use many different sensory modalities to detect such perturbations, insects rely extensively on optic flow to modify their motor output and remain on course. We studied this behavior in the fruit fly,Drosophila melanogaster, by exploiting the optomotor response, a robust reflex in which an animal steers so as to minimize the magnitude of rotatory optic flow it perceives. Whereas the behavioral and algorithmic structure of the optomotor response has been studied in great detail, its neural implementation is not well-understood. In this paper, we present findings implicating a group of nearly homomorphic descending neurons, the DNg02s, as a core component for the optomotor response in flyingDrosophila. Prior work on these cells suggested that they regulate the mechanical power to the flight system, presumably via connections to asynchronous flight motor neurons in the ventral nerve cord. When we chronically inactivated these cells, we observed that the magnitude of the optomotor response was diminished in proportion to the number of cells silenced, suggesting that the cells also regulate bilaterally asymmetric steering responses via population coding. During an optomotor response, flies coordinate changes in wing motion with movements of their head, abdomen, and hind legs, which are also diminished when the DNg02 cells are silenced. Using two-photon functional imaging, we show that the DNg02 cells respond most strongly to patterns of horizontal motion and that neuronal activity is closely correlated to motor output. However, unilateral optogenetic activation of DNg02 neurons does not elicit the asymmetric changes in wing motion characteristic of the optomotor response to a visual stimulus, but rather generates bilaterally symmetric increases in wingbeat amplitude. We interpret our experiments to suggest that flight maneuvers in flies require a more nuanced coordination of power muscles and steering muscles than previously appreciated, and that the physical flight apparatus of a fly might permit mechanical power to be distributed differentially between the two wings. Thus, whereas our experiments identify the DNg02 cells as a critical component of the optomotor reflex, our results suggest that other classes of descending cells targeting the steering muscle motor neurons are also required for the behavior.

SummaryLike many insect species, Drosophila melanogaster are capable of maintaining a stable flight trajectory for periods lasting up to several hours(1, 2). Because aerodynamic torque is roughly proportional to the fifth power of wing length(3), even small asymmetries in wing size require the maintenance of subtle bilateral differences in flapping motion to maintain a stable path. Flies can even fly straight after losing half of a wing, a feat they accomplish via very large, sustained kinematic changes to the both damaged and intact wings(4). Thus, the neural network responsible for stable flight must be capable of sustaining fine-scaled control over wing motion across a large dynamic range. In this paper, we describe an unusual type of descending neurons (DNg02) that project directly from visual output regions of the brain to the dorsal flight neuropil of the ventral nerve cord. Unlike most descending neurons, which exist as single bilateral pairs with unique morphology, there is a population of at least 15 DNg02 cell pairs with nearly identical shape. By optogenetically activating different numbers of DNg02 cells, we demonstrate that these neurons regulate wingbeat amplitude over a wide dynamic range via a population code. Using 2-photon functional imaging, we show that DNg02 cells are responsive to visual motion during flight in a manner that would make them well suited to continuously regulate bilateral changes in wing kinematics. Collectively, we have identified a critical set of DNs that provide the sensitivity and dynamic range required for flight control.

Despite the ecological importance of long-distance dispersal in insects, its mechanistic basis is poorly understood in genetic model species, in which advanced molecular tools are readily available. One critical question is how insects interact with the wind to detect attractive odor plumes and increase their travel distance as they disperse. To gain insight into dispersal, we conducted release-and-recapture experiments in the Mojave Desert using the fruit fly, Drosophila melanogaster. We deployed chemically baited traps in a 1 km radius ring around the release site, equipped with cameras that captured the arrival times of flies as they landed. In each experiment, we released between 30,000 and 200,000 flies. By repeating the experiments under a variety of conditions, we were able to quantify the influence of wind on flies’ dispersal behavior. Our results confirm that even tiny fruit flies could disperse ∼12 km in a single flight in still air and might travel many times that distance in a moderate wind. The dispersal behavior of the flies is well explained by an agent-based model in which animals maintain a fixed body orientation relative to celestial cues, actively regulate groundspeed along their body axis, and allow the wind to advect them sideways. The model accounts for the observation that flies actively fan out in all directions in still air but are increasingly advected downwind as winds intensify. Our results suggest that dispersing insects may strike a balance between the need to cover large distances while still maintaining the chance of intercepting odor plumes from upwind sources.

SUMMARYThe ability to keep track of one’s location in space is a critical behavior for animals navigating to and from a salient location, and its computational basis is now beginning to be unraveled. Here, we tracked flies in a ring-shaped channel as they executed bouts of search triggered by optogenetic activation of sugar receptors. Unlike experiments in open field arenas, which produce highly tortuous search trajectories, our geometrically constrained paradigm enabled us to monitor flies’ decisions to move toward or away from the fictive food. Our results suggest that flies use path integration to remember the location of a food site even after it has disappeared, and that flies can remember the location of a former food site even after walking around the arena one or more times. To determine the behavioral algorithms underlying Drosophila search, we developed multiple state transition models and found that flies likely accomplish path integration by combining odometry and compass navigation to keep track of their position relative to the fictive food. Our results indicate that whereas flies re-zero their path integrator at food when only one feeding site is present, they adjust their path integrator to a central location between sites when experiencing food at two or more locations. Together, this work provides a simple experimental paradigm and theoretical framework to advance investigations of the neural basis of path integration.

Despite the ecological importance of long-distance dispersal in insects, its underlying mechanistic basis is poorly understood. One critical question is how insects interact with the wind to increase their travel distance as they disperse. To gain insight into dispersal using a species amenable to further investigation using genetic tools, we conducted release-and-recapture experiments in the Mojave Desert using the fruit fly,Drosophila melanogaster. We deployed chemically-baited traps in a 1 km-radius ring around the release site, equipped with machine vision systems that captured the arrival times of flies as they landed. In each experiment, we released between 30,000 and 200,000 flies. By repeating the experiments under a variety of conditions, we were able to quantify the influence of wind on flies’ dispersal behavior. Our results confirm that even tiny fruit flies could disperse ∼15 km in a single flight in still air, and might travel many times that distance in a moderate wind. The dispersal behavior of the flies is well explained by a model in which animals maintain a fixed body orientation relative to celestial cues, actively regulate groundspeed along their body axis, and allow the wind to advect them sideways. The model accounts for the observation that flies actively fan out in all directions in still air, but are increasingly advected downwind as winds intensify. In contrast, our field data do not support a Lévy flight model of dispersal, despite the fact that our experimental conditions almost perfectly match the core assumptions of that theory.Significance StatementFlying insects play a vital role in terrestrial ecosystems, and their decline over the past few decades has been implicated in a collapse of many species that depend upon them for food. By dispersing over large distances, insects transport biomass from one region to another and thus their flight behavior influences ecology on a global scale. Our experiments provide key insight into the dispersal behavior of insects, and suggest that these animals employ a single algorithm that is functionally robust in both still air and under windy conditions. Our results will make it easier to study the ecologically important phenomenon of long-distance dispersal in a genetic model organism, facilitating the identification of cellular and genetic mechanisms.

Drosophila melanogaster is an established model for neuroscience research with relevance in biology and medicine. Until recently, research on the Drosophila brain was hindered by the lack of a complete and uniform nomenclature. Recognizing this, Ito et al. (2014) produced an authoritative nomenclature for the adult insect brain, using Drosophila as the reference. Here, we extend this nomenclature to the adult thoracic and abdominal neuromeres, the ventral nerve cord (VNC), to provide an anatomical description of this major component of the Drosophila nervous system. The VNC is the locus for the reception and integration of sensory information and involved in generating most of the locomotor actions that underlie fly behaviors. The aim is to create a nomenclature, definitions, and spatial boundaries for the Drosophila VNC that are consistent with other insects. The work establishes an anatomical framework that provides a powerful tool for analyzing the functional organization of the VNC.

For almost 100 years, biologists have made fundamental discoveries using a handful of model organisms that are not representative of the rich diversity found in nature. The advent of CRISPR genome editing now opens up a wide range of new organisms to mechanistic investigation. This increases not only the taxonomic breadth of current research but also the scope of biological problems that are now amenable to study, such as population control of invasive species, management of disease vectors such as mosquitoes, the creation of chimeric animal hosts to grow human organs and even the possibility of resurrecting extinct species such as passenger pigeons and mammoths. Beyond these practical applications, work on non-model organisms enriches our basic understanding of the natural world. This special issue addresses a broad spectrum of biological problems in non-model organisms and highlights the utility of genome editing across levels of complexity from development and physiology to behaviour and evolution.

The fruit fly, Drosophila melanogaster, is an established and powerful model system for neuroscience research with wide relevance in biology and medicine. Until recently, research on the Drosophila brain was hindered by the lack of a complete and uniform nomenclature. Recognising this problem, the Insect Brain Name Working Group produced an authoritative hierarchical nomenclature system for the adult insect brain, using Drosophila melanogaster as the reference framework, with other taxa considered to ensure greater consistency and expandability (Ito et al., 2014). Here, we extend this nomenclature system to the sub-gnathal regions of the adult Drosophila nervous system, thus providing a systematic anatomical description of the ventral nervous system (VNS). This portion of the nervous system includes the thoracic and abdominal neuromeres that were not included in the original work and contains the motor circuits that play essential roles in most fly behaviours.

Carbon dioxide is produced by many organic processes and is a convenient volatile cue for insects1 that are searching for blood hosts2, flowers3, communal nests4, fruit5 and wildfires6. Although Drosophila melanogaster feed on yeast that produce CO2 and ethanol during fermentation, laboratory experiments7-12 suggest that walking flies avoid CO2. Here we resolve this paradox by showing that both flying and walking Drosophila find CO2 attractive, but only when they are in an active state associated with foraging. Their aversion to CO2 at low-activity levels may be an adaptation to avoid parasites that seek CO2, or to avoid succumbing to respiratory acidosis in the presence of high concentrations of CO2 that exist in nature13,14. In contrast to CO2, flies are attracted to ethanol in all behavioural states, and invest twice the time searching near ethanol compared to CO2. These behavioural differences reflect the fact that ethanol is a unique signature of yeast fermentation, whereas CO2 is generated by many natural processes. Using genetic tools, we determined that the evolutionarily conserved ionotropic co-receptor IR25a is required for CO2 attraction, and that the receptors necessary for CO2 avoidance are not involved in this attraction. Our study lays the foundation for future research to determine the neural circuits that underlie both state- and odorant-dependent decision-making in Drosophila.

To navigate through the world, animals must stabilize their path against disturbances and change direction to avoid obstacles and to search for resources [1 ; 2]. Locomotion is thus guided by sensory cues but also depends on intrinsic processes, such as motivation and physiological state. Flies, for example, turn with the direction of large-field rotatory motion, an optomotor reflex that is thought to help them fly straight [3; 4 ; 5]. Occasionally, however, they execute fast turns, called body saccades, either spontaneously or in response to patterns of visual motion such as expansion [6; 7 ; 8]. These turns can be measured in tethered flying Drosophila [ 3; 4 ; 9], which facilitates the study of underlying neural mechanisms. Whereas there is evidence for an efference copy input to visual interneurons during saccades [10], the circuits that control spontaneous and visually elicited saccades are not well known. Using two-photon calcium imaging and electrophysiological recordings in tethered flying Drosophila, we have identified a descending neuron whose activity is correlated with both spontaneous and visually elicited turns during tethered flight. The cell’s activity in open- and closed-loop experiments suggests that it does not underlie slower compensatory responses to horizontal motion but rather controls rapid changes in flight path. The activity of this neuron can explain some of the behavioral variability observed in response to visual motion and appears sufficient for eliciting turns when artificially activated. This work provides an entry point into studying the circuits underlying the control of rapid steering maneuvers in the fly brain.

SummaryMosquitoes rely on the integration of multiple sensory cues, including olfactory, visual, and thermal stimuli, to detect, identify and locate their hosts [1–4]. Although we increasingly know more about the role of chemosensory behaviours in mediating mosquito-host interactions [1], the role of visual cues remains comparatively less studied [3], and how the combination of olfactory and visual information is integrated in the mosquito brain remains unknown. In the present study, we used a tethered-flight LED arena, which allowed for quantitative control over the stimuli, to show that CO2exposure affects target-tracking responses, but not responses to large-field visual stimuli. In addition, we show that CO2modulates behavioural responses to visual objects in a time-dependent manner. To gain insight into the neural basis of this olfactory and visual coupling, we conducted two-photon microscopy experiments in a new GCaMP6s-expressing mosquito line. Imaging revealed that the majority of ROIs in the lobula region of the optic lobe exhibited strong responses to small-field stimuli, but showed little response to a large-field stimulus. Approximately 20% of the neurons we imaged were modulated when an attractive odour preceded the visual stimulus; these same neurons also elicited a small response when the odour was presented alone. By contrast, imaging in the antennal lobe revealed no modulation when visual stimuli were presented before or after the olfactory stimulus. Together, our results are the first to reveal the dynamics of olfactory modulation in visually evoked behaviours of mosquitoes, and suggest that coupling between these sensory systems is asymmetrical and time-dependent.

Many animals use visual cues such as object shape, color and motion to detect and pursue conspecific mates. Contrast is another possibly informative visual cue, but has not been studied in great detail. In this study, we presented male

Many casual observers typecast Drosophila melanogaster as a stationary pest that lurks around fruit and wine. However, the omnipresent fruit fly, which thrives even in desert habitats, likely established and maintained its cosmopolitan status via migration over large spatial scales. To perform long-distance dispersal, flies must actively maintain a straight compass heading through the use of external orientation cues, such as those derived from the sky. In this Review, we address how D. melanogaster accomplishes long-distance navigation using celestial cues. We focus on behavioral and physiological studies indicating that fruit flies can navigate both to a pattern of linearly polarized light and to the position of the sun – the same cues utilized by more heralded insect navigators such as monarch butterflies and desert ants. In both cases, fruit flies perform menotaxis, selecting seemingly arbitrary headings that they then maintain over time. We discuss how the fly's nervous system detects and processes this sensory information to direct the steering maneuvers that underlie navigation. In particular, we highlight recent findings that compass neurons in the central complex, a set of midline neuropils, are essential for navigation. Taken together, these results suggest that fruit flies share an ancient, latent capacity for celestial navigation with other insects. Furthermore, they illustrate the potential of D. melanogaster to help us to elucidate both the cellular basis of navigation and mechanisms of directed dispersal on a landscape scale.

Insects exhibit impressive navigational abilities, from long distance migrations of monarch butterflies to path integration of desert ants in the genus Cataglyphis. Celestial cues — including polarized light and solar position — provide valuable information to navigating insects, and the brain regions that process this information appear largely conserved. Although not generally considered migratory, mark-recapture experiments indicate that Drosophila can cover 10 km of open desert in perhaps as little as a few hours without stopping to refuel. This impressive feat required flies to adopt a fairly straight path, likely accomplished by visually-guided navigation using celestial cues. Like many insects Drosophila possess the ability to navigate using the polarization pattern of skylight but sun-compass navigation in this genus has not been examined. Using a flight simulator with machine-vision wing tracking, we found that tethered D. melanogaster can use the position of a simulated sun to fly straight, and individuals vary in their heading preference. This preferred heading is maintained over short intervals, but fidelity decays as the time between flights is increased. By training flies with a stimulus restricted to one half of the arena, we could bias subsequent headings towards the side of the training stimulus. These findings suggest that flight and/or visual experience can influence heading, although the neural basis remains unknown. Drosophila sun compass navigation has the potential for future behavioral, ecological and neurobiological studies that could shed light on the deep evolutionary roots of visually-guided locomotion.

Many insects exploit skylight polarization as a compass cue for orientation and navigation. In the fruit fly,Drosophila melanogaster, photoreceptors R7 and R8 in the dorsal rim area (DRA) of the compound eye are specialized to detect the electric vector (e-vector) of linearly polarized light. These photoreceptors are arranged in stacked pairs with identical fields of view and spectral sensitivities, but mutually orthogonal microvillar orientations. As in larger flies, we found that the microvillar orientation of the distal photoreceptor R7 changes in a fan-like fashion along the DRA. This anatomical arrangement suggests that the DRA constitutes a detector for skylight polarization, in which different e-vectors maximally excite different positions in the array. To test our hypothesis, we measured responses to polarized light of varying e-vector angles in the terminals of R7/8 cells using genetically encoded calcium indicators. Our data confirm a progression of preferred e-vector angles from anterior to posterior in the DRA, and a strict orthogonality between the e-vector preferences of paired R7/8 cells. We observed decreased activity in photoreceptors in response to flashes of light polarized orthogonally to their preferred e-vector angle, suggesting reciprocal inhibition between photoreceptors in the same medullar column, which may serve to increase polarization contrast. Together, our results indicate that the polarization-vision system relies on a spatial map of preferred e-vector angles at the earliest stage of sensory processing.SIGNIFICANCE STATEMENTThe fly's visual system is an influential model system for studying neural computation, and much is known about its anatomy, physiology, and development. The circuits underlying motion processing have received the most attention, but researchers are increasingly investigating other functions, such as color perception and object recognition. In this work, we investigate the early neural processing of a somewhat exotic sense, called polarization vision. Because skylight is polarized in an orientation that is rigidly determined by the position of the sun, this cue provides compass information. Behavioral experiments have shown that many species use the polarization pattern in the sky to direct locomotion. Here we describe the input stage of the fly's polarization-vision system.

Resources are often sparsely clustered in nature. Thus, foraging animals may benefit from remembering the location of a newly discovered food patch while continuing to explore nearby [1, 2]. For example, after encountering a drop of yeast or sugar, hungry flies often perform a local search consisting of frequent departures and returns to the food site [3, 4]. Fruit flies, Drosophila melanogaster, can perform this food-centered search behavior in the absence of external stimuli or landmarks, instead relying solely on internal (idiothetic) cues to keep track of their location [5]. This path integration behavior may represent a deeply conserved navigational capacity in insects [6, 7], but the neural pathways underlying food-triggered searches remain unknown. Here, we used optogenetic activation to screen candidate cell classes and found that local searches can be initiated by diverse sensory neurons including sugar-sensors, water-sensors, olfactory-receptor neurons, as well as hunger-signaling neurons of the central nervous system. Optogenetically-induced searches resemble those triggered by actual food and are modulated by starvation state. Furthermore, search trajectories exhibit key features of path integration: searches remain tightly centered around the fictive-food site, even during long periods without reinforcement, and flies re-center their searches when they encounter a new fictive-food site. Flies can even perform elaborate local searches within a constrained maze. Together, these results suggest that flies enact local searches in response to a wide variety of food-associated cues, and that these sensory pathways may converge upon a common neural system for path integration. Optogenetically induced local searches in Drosophila can now serve as a tractable system for the study of spatial memory and navigation in insects.

SUMMARYIn most animals, the brain controls the body via a set of descending neurons (DNs) that traverse the neck and terminate in post-cranial regions of the nervous system. This critical neural population is thought to activate, maintain and modulate locomotion and other behaviors. Although individual members of this cell class have been well-studied across species ranging from insects to primates, little is known about the overall connectivity pattern of DNs as a population. We undertook a systematic anatomical investigation of descending neurons in the fruit fly,Drosophila melanogaster, and created a collection of over 100 transgenic lines targeting individual cell types. Our methods allowed us to describe the morphology of roughly half of an estimated 400 DNs and create a comprehensive map of connectivity between the sensory neuropils in the brain and the motor neuropils in the ventral nerve cord. Like the vertebrate spinal cord, our results show that the fly nerve cord is a highly organized, layered system of neuropils, an organization that reflects the fact that insects are capable of two largely independent means of locomotion – walking and fight – using distinct sets of appendages. Our results reveal the basic functional map of descending pathways in flies and provide tools for systematic interrogation of sensory-motor circuits.

Animals must use external cues to maintain a straight course over long distances. In this study, we investigated how the fruit fly

Animals must use external cues to maintain a straight course over long distances. In this study, we investigated how the fruit fly, Drosophila melanogaster, selects and maintains a flight heading relative to the axis of linearly polarized light, a visual cue produced by the atmospheric scattering of sunlight. To track flies’ headings over extended periods, we used a flight simulator that coupled the angular velocity of dorsally presented polarized light to the stroke amplitude difference of the animal's wings. In the simulator, most flies actively maintained a stable heading relative to the axis of polarized light for the duration of 15 minute flights. We found that individuals selected arbitrary, unpredictable headings relative to the polarization axis, which demonstrates that Drosophila can perform proportional navigation using a polarized light pattern. When flies flew in two consecutive bouts separated by a 5 minute gap, the two flight headings were correlated, suggesting individuals retain a memory of their chosen heading. We found that adding a polarized light pattern to a light intensity gradient enhanced flies’ orientation ability, suggesting Drosophila use a combination of cues to navigate. For both polarized light and intensity cues, flies’ capacity to maintain a stable heading gradually increased over several minutes from the onset of flight. Our findings are consistent with a model in which each individual initially orients haphazardly but then settles on a heading which is maintained via a self-reinforcing process. This may be a general dispersal strategy for animals with no target destination.

Although many behavioral studies have shown the importance of antennal mechanosensation in various aspects of insect flight control, the identities of the mechanosensory neurons responsible for these functions are still unknown. One candidate is the Johnston's organ (JO) neurons that are located in the second antennal segment and detect phasic and tonic rotations of the third antennal segment relative to the second segment. To investigate how different classes of JO neurons respond to different types of antennal movement during flight, we combined 2-photon calcium imaging with a machine vision system to simultaneously record JO neuron activity and the antennal movement from tethered flying fruit flies (Drosophila melanogaster). We found that most classes of JO neurons respond strongly to antennal oscillation at the wing beat frequency, but not to the tonic deflections of the antennae. To study how flies use input from the JO neurons during flight, we genetically ablated specific classes of JO neurons and examined their effect on the wing motion. Tethered flies flying in the dark require JO neurons to generate slow antiphasic oscillation of the left and right wing stroke amplitudes. However, JO neurons are not necessary for this antiphasic oscillation when visual feedback is available, indicating that there are multiple pathways for generating antiphasic movement of the wings. Collectively, our results are consistent with a model in which flying flies use JO neurons to detect increases in the wing-induced airflow and that JO neurons are involved in a response that decreases contralateral wing stoke amplitude.

Carbon dioxide is produced by many organic processes, and is a convenient volatile cue for insects1 searching for blood hosts2, flowers3, communal nests4, fruit5, and wildfires6. Curiously, although Drosophila melanogaster feed on yeast that produce CO2 and ethanol during fermentation, laboratory experiments suggest that walking flies avoid CO27–12. Here, we resolve this paradox by showing that both flying and walking Drosophila find CO2 attractive, but only when in an active state associated with foraging. Aversion at low activity levels may be an adaptation to avoid CO2-seeking-parasites, or succumbing to respiratory acidosis in the presence of high concentrations of CO2 that exist in nature13,14. In contrast to CO2, flies are attracted to ethanol in all behavioral states, and invest twice the time searching near ethanol compared to CO2. These behavioral differences reflect the fact that whereas CO2 is generated by many natural processes, ethanol is a unique signature of yeast fermentation. Using genetic tools, we determined that the evolutionarily ancient ionotropic co-receptor IR25a is required for CO2 attraction, and that the receptors necessary for CO2 avoidance are not involved. Our study lays the foundation for future research to determine the neural circuits underlying both state- and odorant- dependent decision making in Drosophila.

Superhydrophobic surfaces have been of key academic and commercial interest since the discovery of the so-called lotus effect in 1977. The effect of different ions on complex superhydrophobic biological systems, however, has received little attention. By bringing together ecology, biomechanics, physics, and chemistry our study provides insight into the ion-specific effects of wetting in the presence of sodium carbonate and its large-scale consequences. By comparing the surface structure and chemistry of the alkali fly—an important food source for migrating birds—to other species we show that their uniquely hydrophobic properties arise from very small physical and chemical changes, thereby connecting picoscale physics with globally important ecological impacts.

How mosquitoes determine which individuals to bite has important epidemiological consequences. This choice is not random; most mosquitoes specialize in one or a few vertebrate host species, and some individuals in a host population are preferred over others. Mosquitoes will also blood feed from other hosts when their preferred is no longer abundant, but the mechanisms mediating these shifts between hosts, and preferences for certain individuals within a host species, remain unclear. Here, we show that olfactory learning may contribute to Aedes aegypti mosquito biting preferences and host shifts. Training and testing to scents of humans and other host species showed that mosquitoes can aversively learn the scent of specific humans and single odorants and learn to avoid the scent of rats (but not chickens). Using pharmacological interventions, RNAi, and CRISPR gene editing, we found that modification of the dopamine-1 receptor suppressed their learning abilities. We further show through combined electrophysiological and behavioral recordings from tethered flying mosquitoes that these odors evoke changes in both behavior and antennal lobe (AL) neuronal responses and that dopamine strongly modulates odor-evoked responses in AL neurons. Not only do these results provide direct experimental evidence that olfactory learning in mosquitoes canplay an epidemiological role, but collectively, they also provide neuroanatomical and functional demonstration of the role of dopamine in mediating this learning-induced plasticity, for the first time in a disease vector insect.

The fruit fly,Drosophila melanogaster, is an established and powerful model system for neuroscience research with wide relevance in biology and medicine. Until recently, research on theDrosophilabrain was hindered by the lack of a complete and uniform nomenclature. Recognising this problem, the Insect Brain Name Working Group produced an authoritative hierarchical nomenclature system for the adult insect brain, usingDrosophila melanogasteras the reference framework, with other taxa considered to ensure greater consistency and expandability (Ito et al., 2014). Here, we extend this nomenclature system to the sub-gnathal regions of the adultDrosophilanervous system, thus providing a systematic anatomical description of the ventral nervous system (VNS). This portion of the nervous system includes the thoracic and abdominal neuromeres that were not included in the original work and contains the motor circuits that play essential roles in most fly behaviours.

During hovering flight, animals can increase the wing velocity and therefore the net aerodynamic force per stroke by increasing wingbeat frequency, wing stroke amplitude, or both. The magnitude and orientation of aerodynamic forces are also influenced by the geometric angle of attack, timing of wing rotation, wing contact, and pattern of deviation from the primary stroke plane. Most of the kinematic data available for flying animals are average values for wing stroke amplitude and wingbeat frequency because these features are relatively easy to measure, but it is frequently suggested that the more subtle and difficult-to-measure features of wing kinematics can explain variation in force production for different flight behaviors. Here, we test this hypothesis with multicamera high-speed recording and digitization of wing kinematics of honeybees (Apis mellifera) hovering and ascending in air and hovering in a hypodense gas (heliox: 21% O2, 79% He). Bees employed low stroke amplitudes (86.7° ± 7.9°) and high wingbeat frequencies (226.8 ± 12.8 Hz) when hovering in air. When ascending in air or hovering in heliox, bees increased stroke amplitude by 30%-45%, which yielded a much higher wing tip velocity relative to that during simple hovering in air. Across the three flight conditions, there were no statistical differences in the amplitude of wing stroke deviation, minimum and stroke-averaged geometric angle of attack, maximum wing rotation velocity, or even wingbeat frequency. We employed a quasi-steady aerodynamic model to estimate the effects of wing tip velocity and geometric angle of attack on lift and drag. Lift forces were sensitive to variation in wing tip velocity, whereas drag was sensitive to both variation in wing tip velocity and angle of attack. Bees utilized kinematic patterns that did not maximize lift production but rather maintained lift-to-drag ratio. Thus, our data indicate that, at least for honeybees, the overall time course of wing angles is generally preserved and modulation of wing tip velocity is sufficient to perform a diverse set of vertical flight behaviors.

Neuroscientists are using virtual reality systems, combined with other advances such as new molecular genetic tools and brain-recording technologies, to reveal how neuronal circuits process and act on visual information. The Web extra at http://youtu.be/e_BxdbNidyQ is an overview video showing the FlyVR system in operation, including four example experiments.

Most experiments on the flight behavior of Drosophila melanogaster have been performed within confined laboratory chambers, yet the natural history of these animals involves dispersal that takes place on a much larger spatial scale. Thirty years ago, a group of population geneticists performed a series of mark-and-recapture experiments on Drosophila flies, which demonstrated that even cosmopolitan species are capable of covering 10 km of open desert, probably in just a few hours and without the possibility of feeding along the way. In this review I revisit these fascinating and informative experiments and attempt to explain how—from takeoff to landing—the flies might have made these journeys based on our current knowledge of flight behavior. This exercise provides insight into how animals generate long behavioral sequences using sensory-motor modules that may have an ancient evolutionary origin.

Sensory systems provide abundant information about the environment surrounding an animal, but only a small fraction of that information is relevant for any given task. One example of this requirement for context-dependent filtering of a sensory stream is the role that optic flow plays in guiding locomotion. Flying animals, which do not have access to a direct measure of ground speed, rely on optic flow to regulate their forward velocity. This observation suggests that progressive optic flow, the pattern of front-to-back motion on the retina created by forward motion, should be especially salient to an animal while it is in flight, but less important while it is standing still. We recorded the activity of cells in the central complex of Drosophila melanogaster during quiescence and tethered flight using both calcium imaging and whole cell patch-clamp techniques. We observed a genetically identified set of neurons in the fan-shaped body that are unresponsive to visual motion while the animal is quiescent. During flight their baseline activity increases, and they respond to front-to-back motion with changes relative to this baseline. The results provide an example of how nervous systems selectively respond to complex sensory stimuli depending on the current behavioral state of the animal.

Flies execute their remarkable aerial maneuvers using a set of wing steering muscles, which are activated at specific phases of the stroke cycle [1, 2, 3]. The activation phase of these muscles—which determines their biomechanical output [4, 5, 6]—arises via feedback from mechanoreceptors at the base of the wings and structures unique to flies called halteres [7, 8, 9]. Evolved from the hindwings, the tiny halteres oscillate at the same frequency as the wings, although they serve no aerodynamic function [10] and are thought to act as gyroscopes [10, 11, 12, 13, 14, 15]. Like the wings, halteres possess minute control muscles whose activity is modified by descending visual input [16], raising the possibility that flies control wing motion by adjusting the motor output of their halteres, although this hypothesis has never been directly tested. Here, using genetic techniques possible in Drosophila melanogaster, we tested the hypothesis that visual input during flight modulates haltere muscle activity and that this, in turn, alters the mechanosensory feedback that regulates the wing steering muscles. Our results suggest that rather than acting solely as a gyroscope to detect body rotation, halteres also function as an adjustable clock to set the spike timing of wing motor neurons, a specialized capability that evolved from the generic flight circuitry of their four-winged ancestors. In addition to demonstrating how the efferent control loop of a sensory structure regulates wing motion, our results provide insight into the selective scenario that gave rise to the evolution of halteres.

Animals face the daunting task of controlling their limbs using a small set of highly constrained actuators. This problem is particularly demanding for insects such as Drosophila, which must adjust wing motion for both quick voluntary maneuvers and slow compensatory reflexes using only a dozen pairs of muscles. To identify strategies by which animals execute precise actions using sparse motor networks, we imaged the activity of a complete ensemble of wing control muscles in intact, flying flies. Our experiments uncovered a remarkably efficient logic in which each of the four skeletal elements at the base of the wing are equipped with both large phasically active muscles capable of executing large changes and smaller tonically active muscles specialized for continuous fine-scaled adjustments. Based on the responses to a broad panel of visual motion stimuli, we have developed a model by which the motor array regulates aerodynamically functional features of wing motion. VIDEO ABSTRACT.

The means by which brains transform sensory information into coherent motor actions is poorly understood. In flies, a relatively small set of descending interneurons are responsible for conveying sensory information and higher-order commands from the brain to motor circuits in the ventral nerve cord. Here, we describe three pairs of genetically identified descending interneurons that integrate information from wide-field visual interneurons and project directly to motor centers controlling flight behavior. We measured the physiological responses of these three cells during flight and found that they respond maximally to visual movement corresponding to rotation around three distinct body axes. After characterizing the tuning properties of an array of nine putative upstream visual interneurons, we show that simple linear combinations of their outputs can predict the responses of the three descending cells. Last, we developed a machine vision-tracking system that allows us to monitor multiple motor systems simultaneously and found that each visual descending interneuron class is correlated with a discrete set of motor programs.SIGNIFICANCE STATEMENTMost animals possess specialized sensory systems for encoding body rotation, which they use for stabilizing posture and regulating motor actions. In flies and other insects, the visual system contains an array of specialized neurons that integrate local optic flow to estimate body rotation during locomotion. However, the manner in which the output of these cells is transformed by the downstream neurons that innervate motor centers is poorly understood. We have identified a set of three visual descending neurons that integrate the output of nine large-field visual interneurons and project directly to flight motor centers. Our results provide new insight into how the sensory information that encodes body motion is transformed into a code that is appropriate for motor actions.

Insects maintain a constant bearing across a wide range of spatial scales. Monarch butterflies and locusts traverse continents [[1] and [2]], and foraging bees and ants travel hundreds of meters to return to their nests [[1], [3] and [4]], whereas many other insects fly straight for only a few centimeters before changing direction. Despite this variation in spatial scale, the brain region thought to underlie long-distance navigation is remarkably conserved [[5] and [6]], suggesting that the use of a celestial compass is a general and perhaps ancient capability of insects. Laboratory studies of Drosophila have identified a local search mode in which short, straight segments are interspersed with rapid turns [[7] and [8]]. However, this flight mode is inconsistent with measured gene flow between geographically separated populations [[9], [10] and [11]], and individual Drosophila can travel 10 km across desert terrain in a single night [[9], [12] and [13]]—a feat that would be impossible without prolonged periods of straight flight. To directly examine orientation behavior under outdoor conditions, we built a portable flight arena in which a fly viewed the natural sky through a liquid crystal device that could experimentally rotate the polarization angle. Our findings indicate that Drosophila actively orient using the sky's natural polarization pattern.

Insects use feedback from a variety of sensory modalities, including mechanoreceptors on their antennae, to stabilize the direction and speed of flight. Like all arthropod appendages, antennae not only supply sensory information but may also be actively positioned by control muscles. However, how flying insects move their antennae during active turns and how such movements might influence steering responses are currently unknown. Here we examined the antennal movements of flyingDrosophiladuring visually induced turns in a tethered flight arena. In response to both rotational and translational patterns of visual motion,Drosophilaactively moved their antennae in a direction opposite to that of the visual motion. We also observed two types of passive antennal movements: small tonic deflections of the antenna and rapid oscillations at wing beat frequency. These passive movements are likely the result of wing-induced airflow and increased in magnitude when the angular distance between the wing and the antenna decreased. In response to rotational visual motion, increases in passive antennal movements appear to trigger a reflex that reduces the stroke amplitude of the contralateral wing, thereby enhancing the visually induced turn. Although the active antennal movements significantly increased antennal oscillation by bringing the arista closer to the wings, it did not significantly affect the turning response in our head-fixed, tethered flies. These results are consistent with the hypothesis that flyingDrosophilause mechanosensory feedback to detect changes in the wing induced airflow during visually induced turns and that this feedback plays a role in regulating the magnitude of steering responses.

SUMMARYRecent studies suggest that fruit flies use subtle changes to their wing motion to actively generate forces during aerial maneuvers. In addition, it has been estimated that the passive rotational damping caused by the flapping wings of an insect is around two orders of magnitude greater than that for the body alone. At present, however, the relationships between the active regulation of wing kinematics, passive damping produced by the flapping wings and the overall trajectory of the animal are still poorly understood. In this study, we use a dynamically scaled robotic model equipped with a torque feedback mechanism to study the dynamics of yaw turns in the fruit fly Drosophila melanogaster. Four plausible mechanisms for the active generation of yaw torque are examined. The mechanisms deform the wing kinematics of hovering in order to introduce asymmetry that results in the active production of yaw torque by the flapping wings. The results demonstrate that the stroke-averaged yaw torque is well approximated by a model that is linear with respect to both the yaw velocity and the magnitude of the kinematic deformations. Dynamic measurements, in which the yaw torque produced by the flapping wings was used in real-time to determine the rotation of the robot, suggest that a first-order linear model with stroke-average coefficients accurately captures the yaw dynamics of the system. Finally, an analysis of the stroke-average dynamics suggests that both damping and inertia will be important factors during rapid body saccades of a fruit fly.

SUMMARY Walking fruit flies, Drosophila melanogaster, use visual information to orient towards salient objects in their environment, presumably as a search strategy for finding food, shelter or other resources. Less is known, however, about the role of vision or other sensory modalities such as mechanoreception in the evaluation of objects once they have been reached. To study the role of vision and mechanoreception in exploration behavior, we developed a large arena in which we could track individual fruit flies as they walked through either simple or more topologically complex landscapes. When exploring a simple, flat environment lacking three-dimensional objects, flies used visual cues from the distant background to stabilize their walking trajectories. When exploring an arena containing an array of cones, differing in geometry, flies actively oriented towards, climbed onto, and explored the objects, spending most of their time on the tallest, steepest object. A fly's behavioral response to the geometry of an object depended upon the intrinsic properties of each object and not a relative assessment to other nearby objects. Furthermore, the preference was not due to a greater attraction towards tall, steep objects, but rather a change in locomotor behavior once a fly reached and explored the surface. Specifically, flies are much more likely to stop walking for long periods when they are perched on tall, steep objects. Both the vision system and the antennal chordotonal organs (Johnston's organs) provide sufficient information about the geometry of an object to elicit the observed change in locomotor behavior. Only when both these sensory systems were impaired did flies not show the behavioral preference for the tall, steep objects.

Automated tracking of animal movement allows analyses that would not otherwise be possible by providing great quantities of data. The additional capability of tracking in real time—with minimal latency—opens up the experimental possibility of manipulating sensory feedback, thus allowing detailed explorations of the neural basis for control of behaviour. Here, we describe a system capable of tracking the three-dimensional position and body orientation of animals such as flies and birds. The system operates with less than 40 ms latency and can track multiple animals simultaneously. To achieve these results, a multi-target tracking algorithm was developed based on the extended Kalman filter and the nearest neighbour standard filter data association algorithm. In one implementation, an 11-camera system is capable of tracking three flies simultaneously at 60 frames per second using a gigabit network of nine standard Intel Pentium 4 and Core 2 Duo computers. This manuscript presents the rationale and details of the algorithms employed and shows three implementations of the system. An experiment was performed using the tracking system to measure the effect of visual contrast on the flight speed ofDrosophila melanogaster. At low contrasts, speed is more variable and faster on average than at high contrasts. Thus, the system is already a useful tool to study the neurobiology and behaviour of freely flying animals. If combined with other techniques, such as ‘virtual reality’-type computer graphics or genetic manipulation, the tracking system would offer a powerful new way to investigate the biology of flying animals.

SUMMARYThe aerodynamic performance of hovering insects is largely explained by the presence of a stably attached leading edge vortex (LEV) on top of their wings. Although LEVs have been visualized on real, physically modeled, and simulated insects, the physical mechanisms responsible for their stability are poorly understood. To gain fundamental insight into LEV stability on flapping fly wings we expressed the Navier–Stokes equations in a rotating frame of reference attached to the wing's surface. Using these equations we show that LEV dynamics on flapping wings are governed by three terms: angular,centripetal and Coriolis acceleration. Our analysis for hovering conditions shows that angular acceleration is proportional to the inverse of dimensionless stroke amplitude, whereas Coriolis and centripetal acceleration are proportional to the inverse of the Rossby number. Using a dynamically scaled robot model of a flapping fruit fly wing to systematically vary these dimensionless numbers, we determined which of the three accelerations mediate LEV stability. Our force measurements and flow visualizations indicate that the LEV is stabilized by the `quasi-steady' centripetal and Coriolis accelerations that are present at low Rossby number and result from the propeller-like sweep of the wing. In contrast, the unsteady angular acceleration that results from the back and forth motion of a flapping wing does not appear to play a role in the stable attachment of the LEV. Angular acceleration is, however, critical for LEV integrity as we found it can mediate LEV spiral bursting, a high Reynolds number effect. Our analysis and experiments further suggest that the mechanism responsible for LEV stability is not dependent on Reynolds number, at least over the range most relevant for insect flight (100

We present a camera-based method for automatically quantifying the individual and social behaviors of fruit flies, Drosophila melanogaster, interacting within a planar arena. Our system includes machine vision algorithms that accurately track many individuals without swapping identities and classification algorithms that detect behaviors. The data may be represented as an ethogram that plots the time course of behaviors exhibited by each fly, or as a vector that concisely captures the statistical properties of all behaviors displayed within a given period. We found that behavioral differences between individuals are consistent over time and are sufficient to accurately predict gender and genotype. In addition, we show that the relative positions of flies during social interactions vary according to gender, genotype, and social environment. We expect that our software, which permits high-throughput screening, will complement existing molecular methods available in Drosophila, facilitating new investigations into the genetic and cellular basis of behavior.

This paper presents a framework for simulating the flight dynamics and control strategies of the fruit fly Drosophila melanogaster. The framework consists of five main components: an articulated rigid-body simulation, a model of the aerodynamic forces and moments, a sensory systems model, a control model, and an environment model. In the rigid-body simulation the fly is represented by a system of three rigid bodies connected by a pair of actuated ball joints. At each instant of the simulation, the aerodynamic forces and moments acting on the wings and body of the fly are calculated using an empirically derived quasi-steady model. The pattern of wing kinematics is based on data captured from high-speed video sequences. The forces and moments produced by the wings are modulated by deforming the base wing kinematics along certain characteristic actuation modes. Models of the fly’s visual and mechanosensory systems are used to generate inputs to a controller that sets the magnitude of each actuation mode, thus modulating the forces produced by the wings. This simulation framework provides a quantitative test bed for examining the possible control strategies employed by flying insects. Examples demonstrating pitch rate, velocity, altitude, and flight speed control, as well as visually guided centering in a corridor are presented.

SummaryA key feature of reactive behaviors is the ability to spatially localize a salient stimulus and act accordingly. Such sensory-motor transformations must be particularly fast and well tuned in escape behaviors, in which both the speed and accuracy of the evasive response determine whether an animal successfully avoids predation [1]. We studied the escape behavior of the fruit fly, Drosophila, and found that flies can use visual information to plan a jump directly away from a looming threat. This is surprising, given the architecture of the pathway thought to mediate escape [2, 3]. Using high-speed videography, we found that approximately 200 ms before takeoff, flies begin a series of postural adjustments that determine the direction of their escape. These movements position their center of mass so that leg extension will push them away from the expanding visual stimulus. These preflight movements are not the result of a simple feed-forward motor program because their magnitude and direction depend on the flies' initial postural state. Furthermore, flies plan a takeoff direction even in instances when they choose not to jump. This sophisticated motor program is evidence for a form of rapid, visually mediated motor planning in a genetically accessible model organism.

Modern neuroscience and the interest in biomimetic control design demand increasingly sophisticated experimental techniques that can be applied in freely moving animals under realistic behavioral conditions. To explore sensorimotor flight control mechanisms in free-flying fruit flies ( Drosophila melanogaster ), we equipped a wind tunnel with a Virtual Reality (VR) display system based on standard digital hardware and a 3D path tracking system. We demonstrate the experimental power of this approach by example of a ‘one-parameter open loop’ testing paradigm. It provided (1) a straightforward measure of transient responses in presence of open loop visual stimulation; (2) high data throughput and standardized measurement conditions from process automation; and (3) simplified data analysis due to well-defined testing conditions. Being based on standard hardware and software techniques, our methods provide an affordable, easy to replicate and general solution for a broad range of behavioral applications in freely moving animals. Particular relevance for advanced behavioral research tools originates from the need to perform detailed behavioral analyses in genetically modified organisms and animal models for disease research.

Flying insects exhibit stunning behavioral repertoires that are largely mediated by the visual control of flight. For this reason, presenting a controlled visual environment to tethered insects has been and continues to be a powerful tool for studying the sensory control of complex behaviors. To create an easily controlled, scalable, and customizable visual stimulus, we have designed a modular system, based on panels composed of an 8 x 8 array of individual LEDs, that may be connected together to 'tile' an experimental environment with controllable displays. The panels have been designed to be extremely bright, with the added flexibility of individual-pixel brightness control, allowing experimentation over a broad range of behaviorally relevant conditions. Patterns to be displayed may be designed using custom software, downloaded to a controller board, and displayed on the individually addressed panels via a rapid communication interface. The panels are controlled by a microprocessor-based display controller which, for most experiments, will not require a computer in the loop, greatly reducing the experimental infrastructure. This technology allows an experimenter to build and program a visual arena with a customized geometry in a matter of hours. To demonstrate the utility of this system, we present results from experiments with tethered Drosophila melanogaster: (1) in a cylindrical arena composed of 44 panels, used to test the contrast dependence of object orientation behavior, and (2) above a 30-panel floor display, used to examine the effects of ground motion on orientation during flight.

Brains and sensory systems evolved to guide motion. Central to this task is controlling the approach to stationary obstacles and detecting moving organisms. Looming has been proposed as the main monocular visual cue for detecting the approach of other animals and avoiding collisions with stationary obstacles. Elegant neural mechanisms for looming detection have been found in the brain of insects and vertebrates. However, looming has not been analyzed in the context of collisions between two moving animals. We propose an alternative strategy, Generalized Regressive Motion (GRM), which is consistent with recently observed behavior in fruit flies. Geometric analysis proves that GRM is a reliable cue to collision among conspecifics, whereas agent-based modeling suggests that GRM is a better cue than looming as a means to detect approach, prevent collisions and maintain mobility.

Although anatomy is often the first step in assigning functions to neural structures, it is not always clear whether architecturally distinct regions of the brain correspond to operational units. Whereas neuroarchitecture remains relatively static, functional connectivity may change almost instantaneously according to behavioral context. We imaged panneuronal responses to visual stimuli in a highly conserved central brain region in the fruit fly, Drosophila, during flight. In one substructure, the fan-shaped body, automated analysis revealed three layers that were unresponsive in quiescent flies but became responsive to visual stimuli when the animal was flying. The responses of these regions to a broad suite of visual stimuli suggest that they are involved in the regulation of flight heading. To identify the cell types that underlie these responses, we imaged activity in sets of genetically defined neurons with arborizations in the targeted layers. The responses of this collection during flight also segregated into three sets, confirming the existence of three layers, and they collectively accounted for the panneuronal activity. Our results provide an atlas of flight-gated visual responses in a central brain circuit.

SUMMARYFlying fruit flies, Drosophila melanogaster, perform `body saccades', in which they change heading by about 90° in roughly 70 ms. In free flight, visual expansion can evoke saccades, and saccade-like turns are triggered by similar stimuli in tethered flies. However, because the fictive turns in rigidly tethered flies follow a much longer time course, the extent to which these two behaviors share a common neural basis is unknown. A key difference between tethered and free flight conditions is the presence of additional sensory cues in the latter, which might serve to modify the time course of the saccade motor program. To study the role of sensory feedback in saccades, we have developed a new preparation in which a fly is tethered to a fine steel pin that is aligned within a vertically oriented magnetic field,allowing it to rotate freely around its yaw axis. In this experimental paradigm, flies perform rapid turns averaging 35° in 80 ms, similar to the kinematics of free flight saccades. Our results indicate that tethered and free flight saccades share a common neural basis, but that the lack of appropriate feedback signals distorts the behavior performed by rigidly fixed flies. Using our new paradigm, we also investigated the features of visual stimuli that elicit saccades. Our data suggest that saccades are triggered when expanding objects reach a critical threshold size, but that their timing depends little on the precise time course of expansion. These results are consistent with expansion detection circuits studied in other insects, but do not exclude other models based on the integration of local movement detectors.

The understanding of the physics of flapping flight has long been limited due to the obvious experimental difficulties in studying the flow field around real insects. In this study the time-dependent three-dimensional velocity field around a flapping wing was measured quantitatively for the first time. This was done using a dynamically-scaled wing moving in mineral oil in a pattern based on the kinematics obtained from real insects. The periodic flow is very reproducible, due to the relatively low Reynolds number and precise control of the wing. This repeatability was used to reconstruct the full evolving flow field around the wing from separate stereoscopic particle image velocimetry measurements for a number of spanwise planes and time steps. Typical results for two cases (an impulsive start and a simplified flapping pattern) are reported. Visualizations of the obtained data confirm the general picture of the leading-edge vortex that has been reported in recent publications, but allow a refinement of the detailed structure: rather than a single strand of vorticity, we find a stable pair of counter-rotating structures. We show that the data can also be used for quantitative studies, such as lift and drag prediction.