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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.

Using high-speed videography, we investigated how fruit flies compensate for unilateral wing damage, in which loss of area on one wing compromises both weight support and roll torque equilibrium. Our results show that flies control for unilateral damage by rolling their body towards the damaged wing and by adjusting the kinematics of both the intact and damaged wings. To compensate for the reduction in vertical lift force due to damage, flies elevate wingbeat frequency. Because this rise in frequency increases the flapping velocity of both wings, it has the undesired consequence of further increasing roll torque. To compensate for this effect, flies increase the stroke amplitude and advance the timing of pronation and supination of the damaged wing, while making the opposite adjustments on the intact wing. The resulting increase in force on the damaged wing and decrease in force on the intact wing function to maintain zero net roll torque. However, the bilaterally asymmetrical pattern of wing motion generates a finite lateral force, which flies balance by maintaining a constant body roll angle. Based on these results and additional experiments using a dynamically scaled robotic fly, we propose a simple bioinspired control algorithm for asymmetric wing damage.

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.

Cues from both an animal’s internal physiological state and its local environment may influence its decision to disperse. However, identifying and quantifying the causative factors underlying the initiation of dispersal is difficult in uncontrolled natural settings. In this study, we automatically monitored the movement of fruit flies and examined the influence of food availability, sex, and reproductive status on their dispersal between laboratory environments. In general, flies with mating experience behave as if they are hungrier than virgin flies, leaving at a greater rate when food is unavailable and staying longer when it is available. Males dispersed at a higher rate and were more active than females when food was unavailable, but tended to stay longer in environments containing food than did females. We found no significant relationship between weight and activity, suggesting the behavioral differences between males and females are caused by an intrinsic factor relating to the sex of a fly and not simply its body size. Finally, we observed a significant difference between the dispersal of the natural isolate used throughout this study and the widely-used laboratory strain, Canton-S, and show that the difference cannot be explained by allelic differences in the foraging gene.

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.

Despite recent advances in the study of animal flight, the biomechanical determinants of maneuverability are poorly understood. It is thought that maneuverability may be influenced by intrinsic body mass and wing morphology, and by physiological muscle capacity, but this hypothesis has not yet been evaluated because it requires tracking a large number of free flight maneuvers from known individuals. We used an automated tracking system to record flight sequences from 20 Anna's hummingbirds flying solo and in competition in a large chamber. We found that burst muscle capacity predicted most performance metrics. Hummingbirds with higher burst capacity flew with faster velocities, accelerations, and rotations, and they used more demanding complex turns. In contrast, body mass did not predict variation in maneuvering performance, and wing morphology predicted only the use of arcing turns and high centripetal accelerations. Collectively, our results indicate that burst muscle capacity is a key predictor of maneuverability. DOI: http://dx.doi.org/10.7554/eLife.11159.001, eLife digest The ability of an animal to maneuver can determine its success at avoiding predators, catching prey, and outperforming its competitors. However, little is known about the characteristics that determine maneuverability. Why are some individuals more maneuverable than others? To investigate this question, Segre et al. used an automated video tracking system to track male Anna's hummingbirds as they flew around a large chamber. These tracks were then compared with the physical characteristics of the birds to see which, if any, affect the birds’ maneuverability. This revealed that body size did not affect how well the birds could maneuver. Instead, the muscle capacity of the birds – their ability to generate force rapidly – determined how well the birds performed most types of movement. Birds with higher muscle capacity flew faster, had faster accelerations and decelerations, could rotate their bodies more quickly, and performed more demanding and complex turns. Segre et al. also found that wing shape is important for a type of maneuver called an arcing turn. Hummingbirds with a more slender wing shape were able to execute more demanding arcing turns involving higher accelerations, and they used arcing turns more often than birds with wider wings. Future research will aim to determine whether these relationships are also found in other species of birds. DOI: http://dx.doi.org/10.7554/eLife.11159.002

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.

Most insects are thought to fly by creating a leading-edge vortex that remains attached to the wing as it translates through a stroke. In the species examined so far, stroke amplitude is large, and most of the aerodynamic force is produced halfway through a stroke when translation velocities are highest. Here we demonstrate that honeybees use an alternative strategy, hovering with relatively low stroke amplitude (approximate to 90 degrees) and high wingbeat frequency (approximate to 230 Hz). When measured on a dynamically scaled robot, the kinematics of honeybee wings generate prominent force peaks during the beginning, middle, and end of each stroke, indicating the importance of additional unsteady mechanisms at stroke reversal. When challenged to fly in low-density heliox, bees responded by maintaining nearly constant wingbeat frequency while increasing stroke amplitude by nearly 50%. We examined the aerodynamic consequences of this change in wing motion by using artificial kinematic patterns in which amplitude was systematically increased in 5 degrees increments. To separate the aerodynamic effects of stroke velocity from those due to amplitude, we performed this analysis under both constant frequency and constant velocity conditions. The results indicate that unsteady forces during stroke reversal make a large contribution to net upward force during hovering but play a diminished role as the animal increases stroke amplitude and flight power. We suggest that the peculiar kinematics of bees may reflect either a specialization for increasing load capacity or a physiological limitation of their flight muscles.

Insects exhibit unparalleled and incredibly robust flight dynamics in the face of uncertainties. A fundamental principle contributing to this amazing behavior is rapid processing and convergence of visual sensory information to flight motor commands via spatial wide-field integration, accomplished by motion pattern sensitive interneurons in the lobula plate portion of the visual ganglia. Within a control-theoretic framework, a model for wide-field integration of retinal image flow is developed, establishing the connection between image flow kernels (retinal motion pattern sensitivities) and the feedback terms they represent. It is demonstrated that the proposed output feedback methodology is sufficient to give rise to experimentally observed navigational heuristics as the centering and forward speed regulation responses exhibited by honeybees.

SUMMARYAnimals actively seeking food and oviposition sites must integrate feedback from multiple sensory modalities. Here, we examine visual and olfactory sensorimotor interactions in Drosophila. In a tethered-flight simulator, flies modulate wingbeat frequency and amplitude in response to visual and olfactory stimuli. Responses to both cues presented simultaneously are nearly identical to the sum of responses to stimuli presented in isolation for the onset and duration of odor delivery, suggesting independent sensorimotor pathways. Visual feedback does, however, alter the time course of the odor-off response. Based on the physiology of the flight motor system and recent free-flight analyses, we present a hypothetical model to account for the summation or superposition of sensorimotor responses during flight.

SUMMARYThe fruit fly Drosophila melanogaster relies on feedback from multiple sensory modalities to control flight maneuvers. Two sensory organs,the compound eyes and mechanosensory hindwings called halteres, are capable of encoding angular velocity of the body during flight. Although motor reflexes driven by the two modalities have been studied individually, little is known about how the two sensory feedback channels are integrated during flight. Using a specialized flight simulator we presented tethered flies with simultaneous visual and mechanosensory oscillations while measuring compensatory changes in stroke kinematics. By varying the relative amplitude,phase and axis of rotation of the visual and mechanical stimuli, we were able to determine the contribution of each sensory modality to the compensatory motor reflex. Our results show that over a wide range of experimental conditions sensory inputs from halteres and the visual system are combined in a weighted sum. Furthermore, the weighting structure places greater influence on feedback from the halteres than from the visual system.

SUMMARYWe used two-dimensional digital particle image velocimetry (DPIV) to visualize flow patterns around the flapping wing of a dynamically scaled robot for a series of reciprocating strokes starting from rest. The base of the wing was equipped with strain gauges so that the pattern of fluid motion could be directly compared with the time history of force production. The results show that the development and shedding of vortices throughout each stroke are highly stereotyped and influence force generation in subsequent strokes. When a wing starts from rest, it generates a transient force as the leading edge vortex (LEV) grows. This early peak, previously attributed to added-mass acceleration, is not amenable to quasi-steady models but corresponds well to calculations based on the time derivative of the first moment of vorticity within a sectional slice of fluid. Forces decay to a stable level as the LEV reaches a constant size and remains attached throughout most of the stroke. The LEV grows as the wing supinates prior to stroke reversal, accompanied by an increase in total force. At stroke reversal, both the LEV and a rotational starting vortex (RSV) are shed into the wake, forming a counter-rotating pair that directs a jet of fluid towards the underside of the wing at the start of the next stroke. We isolated the aerodynamic influence of the wake by subtracting forces and flow fields generated in the first stroke, when the wake is just developing, from those produced during the fourth stroke, when the pattern of both the forces and wake dynamics has reached a limit cycle. This technique identified two effects of the wake on force production by the wing: an early augmentation followed by a small attenuation. The later decrease in force is consistent with the influence of a decreased aerodynamic angle of attack on translational forces caused by downwash within the wake and is well explained by a quasi-steady model. The early effect of the wake is not well approximated by a quasi-steady model, even when the magnitude and orientation of the instantaneous velocity field are taken into account. Thus,the wake capture force represents a truly unsteady phenomenon dependent on temporal changes in the distribution and magnitude of vorticity during stroke reversal.

SUMMARY We used a dynamically scaled model insect to measure the rotational forces produced by a flapping insect wing. A steadily translating wing was rotated at a range of constant angular velocities, and the resulting aerodynamic forces were measured using a sensor attached to the base of the wing. These instantaneous forces were compared with quasi-steady estimates based on translational force coefficients. Because translational and rotational velocities were constant, the wing inertia was negligible, and any difference between measured forces and estimates based on translational force coefficients could be attributed to the aerodynamic effects of wing rotation. By factoring out the geometry and kinematics of the wings from the rotational forces, we determined rotational force coefficients for a range of angular velocities and different axes of rotation. The measured coefficients were compared with a mathematical model developed for two-dimensional motions in inviscid fluids, which we adapted to the three-dimensional case using blade element theory. As predicted by theory, the rotational coefficient varied linearly with the position of the rotational axis for all angular velocities measured. The coefficient also, however, varied with angular velocity, in contrast to theoretical predictions. Using the measured rotational coefficients, we modified a standard quasi-steady model of insect flight to include rotational forces, translational forces and the added mass inertia. The revised model predicts the time course of force generation for several different patterns of flapping kinematics more accurately than a model based solely on translational force coefficients. By subtracting the improved quasi-steady estimates from the measured forces, we isolated the aerodynamic forces due to wake capture.

SUMMARYTo study the visual cues that control steering behavior in the fruit fly Drosophila melanogaster, we reconstructed three-dimensional trajectories from images taken by stereo infrared video cameras during free flight within structured visual landscapes. Flies move through their environment using a series of straight flight segments separated by rapid turns, termed saccades, during which the fly alters course by approximately 90° in less than 100 ms. Altering the amount of background visual contrast caused significant changes in the fly’s translational velocity and saccade frequency. Between saccades, asymmetries in the estimates of optic flow induce gradual turns away from the side experiencing a greater motion stimulus, a behavior opposite to that predicted by a flight control model based upon optomotor equilibrium. To determine which features of visual motion trigger saccades, we reconstructed the visual environment from the fly’s perspective for each position in the flight trajectory. From these reconstructions, we modeled the fly’s estimation of optic flow on the basis of a two-dimensional array of Hassenstein–Reichardt elementary motion detectors and, through spatial summation, the large-field motion stimuli experienced by the fly during the course of its flight. Event-triggered averages of the large-field motion preceding each saccade suggest that image expansion is the signal that triggers each saccade. The asymmetry in output of the local motion detector array prior to each saccade influences the direction (left versus right) but not the magnitude of the rapid turn. Once initiated, visual feedback does not appear to influence saccade kinematics further. The total expansion experienced before a saccade was similar for flight within both uniform and visually textured backgrounds. In summary, our data suggest that complex behavioral patterns seen during free flight emerge from interactions between the flight control system and the visual environment.

Food ingestion is one of the defining behaviours of all animals, but its quantification and analysis remain challenging. This is especially the case for feeding behaviour in small, genetically tractable animals such as Drosophila melanogaster. Here, we present a method based on capacitive measurements, which allows the detailed, automated and high-throughput quantification of feeding behaviour. Using this method, we were able to measure the volume ingested in single sips of an individual, and monitor the absorption of food with high temporal resolution. We demonstrate that flies ingest food by rhythmically extending their proboscis with a frequency that is not modulated by the internal state of the animal. Instead, hunger and satiety homeostatically modulate the microstructure of feeding. These results highlight similarities of food intake regulation between insects, rodents, and humans, pointing to a common strategy in how the nervous systems of different animals control food intake., Feeding is an important behaviour, but its quantification remains challenging, particularly in small animal models like Drosophila melanogaster. Here the authors describe a method which uses capacitive sensing for automated high-resolution measuring of feeding behaviour in individual flies.

Recent evidence suggests that flies’ sensitivity to large field optic flow is increased by the release of octopamine during flight. This increase in gain presumably enhances visually-mediated behaviors such as the active regulation of forward speed, a process that involves the comparison of a vision-based estimate of velocity with an internal set point. To determine where in the neural circuit this comparison is made, we selectively silenced the octopamine neurons in the fruit fly, Drosophila, and examined the effect on vision-based velocity regulation in free flying flies. We found that flies with inactivated octopamine neurons accelerated more slowly in response to visual motion than control flies, but maintained nearly the same baseline flight speed. Our results are parsimonious with a circuit architecture in which the internal control signal is injected into the visual motion pathway upstream of the interneuron network that estimates groundspeed.

Sensory feedback is a ubiquitous feature of guidance systems in both animals and engineered vehicles. For example, a common strategy for moving along a straight path is to turn such that the measured rate of rotation is zero. This task can be accomplished by using a feedback signal that is proportional to the instantaneous value of the measured sensory signal. In such a system, the addition of an integral term depending on past values of the sensory input is needed to eliminate steady-state error [proportional-integral (PI) control]. However, the means by which nervous systems implement such a computation are poorly understood. Here, we show that the optomotor responses of flying Drosophila follow a time course consistent with temporal integration of horizontal motion input. To investigate the cellular basis of this effect, we performed whole-cell patch-clamp recordings from the set of identified visual interneurons [horizontal system (HS) cells] thought to control this reflex during tethered flight. At high stimulus speeds, HS cells exhibit steady-state responses during flight that are absent during quiescence, a state-dependent difference in physiology that is explained by changes in their presynaptic inputs. However, even during flight, the membrane potential of the large-field interneurons exhibits no evidence for integration that could explain the behavioral responses. However, using a genetically encoded indicator, we found that calcium accumulates in the terminals of the interneurons along a time course consistent with the behavior and propose that this accumulation provides a mechanism for temporal integration of sensory feedback consistent with PI control.

Background: For a fruit fly, locating fermenting fruit where it can feed, find mates, and lay eggs is an essential and difficult task requiring the integration of olfactory and visual cues. Here, we develop an approach to correlate flies’ free-flight behavior with their olfactory experience under different wind and visual conditions, yielding new insight into plume tracking based on over 70 hr of data. Results: To localize an odor source, flies exhibit three iterative, independent, reflex-driven behaviors, which remain constant through repeated encounters of the same stimulus: (1) 190 ± 75 ms after encountering a plume, flies increase their flight speed and turn upwind, using visual cues to determine wind direction. Due to this substantial response delay, flies pass through the plume shortly after entering it. (2) 450 ± 165 ms after losing the plume, flies initiate a series of vertical and horizontal casts, using visual cues to maintain a crosswind heading. (3) After sensing an attractive odor, flies exhibit an enhanced attraction to small visual features, which increases their probability of finding the plume’s source. Conclusions: Due to plume structure and sensory-motor delays, a fly’s olfactory experience during foraging flights consists of short bursts of odor stimulation. As a consequence, delays in the onset of crosswind casting and the increased attraction to visual features are necessary behavioral components for efficiently locating an odor source. Our results provide a quantitative behavioral background for elucidating the neural basis of plume tracking using genetic and physiological approaches.

Animals rely on sensory cues to classify objects in their environment and respond appropriately. However, the spatial structure of those sensory cues can greatly impact when, where, and how they are perceived. In this study, we examined the relative roles of visual and chemosensory cues in the mate recognition behavior of fruit flies (Drosophila melanogaster) by using a robotic fly dummy that was programmed to interact with individual males. By pairing male flies with dummies of various shapes, sizes, and speeds, or coated with different pheromones, we determined that visual and chemical cues play specific roles at different points in the courtship sequence. Vision is essential for determining whether to approach a moving object and initiate courtship, and males were more likely to begin chasing objects with the same approximate dimensions as another fly. However, whereas males were less likely to begin chasing larger dummies, once started, they would continue chasing for a similar length of time regardless of the dummy's shape. The presence of female pheromones on the moving dummy did not affect the probability that males would initiate a chase, but it did influence how long they would continue chasing. Male pheromone both inhibits chase initiation and shortens chase duration. Collectively, these results suggest that male Drosophila use different sensory cues to progress through the courtship sequence: visual cues are dominant when deciding whether to approach an object whereas chemosensory cues determine how long the male pursues its target.

Taking Flight Anyone who has tried to swat a fly knows that their powers of avoidance are impressive. Executing such rapid avoidance requires that the sensory recognition of an approaching threat be translated into evasive movement almost instantaneously. Muijres et al. (p. 172 ) used high-speed videos and winged robots to show that flies respond to approaching threats by making rapid banked turns initiated through subtle wing changes over just a few wing beats. The rapid nature of the turns suggests the existence of dedicated sensory-motor circuits that allow the flies to respond within a fraction of a second.

Flies exhibit a repertoire of aerial acrobatics unmatched in robustness and aerodynamic sophistication. The exquisite control of this complex behavior emerges from encoding intricate patterns of optic flow, and the translation of these visual signals into the mechanical language of the motor system. Recent advances in experimental design toward more naturalistic visual and mechanosensory stimuli have served to reinforce fly flight as a key model system for understanding how feedback from multiple sensory modalities is integrated to control complex and robust motor behaviors across taxa.

The flow structure that is largely responsible for the good performance of insect wings has recently been identified as a leading-edge vortex. But because such vortices become detached from a wing in two-dimensional flow, an unknown mechanism must keep them attached to (three-dimensional) flapping wings. The current explanation, analogous to a mechanism operating on delta-wing aircraft, is that spanwise flow through a spiral vortex drains energy from the vortex core. We have tested this hypothesis by systematically mapping the flow generated by a dynamically scaled model insect while simultaneously measuring the resulting aerodynamic forces. Here we report that, at the Reynolds numbers matching the flows relevant for most insects, flapping wings do not generate a spiral vortex akin to that produced by delta-wing aircraft. We also find that limiting spanwise flow with fences and edge baffles does not cause detachment of the leading-edge vortex. The data support an alternative hypothesis-that downward flow induced by tip vortices limits the growth of the leading-edge vortex.

The Drosophila myosin regulatory light chain (DMLC2) is homologous to MLC2s of vertebrate organisms, except for the presence of a unique 46-amino acid N-terminal extension. To study the role of the DMLC2 N-terminal extension in Drosophila flight muscle, we constructed a truncated form of the Dmlc2 gene lacking amino acids 2-46 (Dmlc2(Delta2-46)). The mutant gene was expressed in vivo, with no wild-type Dmlc2 gene expression, via P-element-mediated germline transformation. Expression of the truncated DMLC2 rescues the recessive lethality and dominant flightless phenotype of the Dmlc2 null, with no discernible effect on indirect flight muscle (IFM) sarcomere assembly. Homozygous Dmlc2(Delta2-46) flies have reduced IFM dynamic stiffness and elastic modulus at the frequency of maximum power output. The viscous modulus, a measure of the fly's ability to perform oscillatory work, was not significantly affected in Dmlc2(Delta2-46) IFM. In vivo flight performance measurements of Dmlc2(Delta2-46) flies using a visual closed-loop flight arena show deficits in maximum metabolic power (P(*)(CO(2))), mechanical power (P(*)(mech)), and flight force. However, mutant flies were capable of generating flight force levels comparable to body weight, thus enabling them to fly, albeit with diminished performance. The reduction in elastic modulus in Dmlc2(Delta2-46) skinned fibers is consistent with the N-terminal extension being a link between the thick and thin filaments that is parallel to the cross-bridges. Removal of this parallel link causes an unfavorable shift in the resonant properties of the flight system, thus leading to attenuated flight performance.

The enhanced aerodynamic performance of insects results from an interaction of three distinct yet interactive mechanisms: delayed stall, rotational circulation, and wake capture. Delayed stall functions during the translational portions of the stroke, when the wings sweep through the air with a large angle of attack. In contrast, rotational circulation and wake capture generate aerodynamic forces during stroke reversals, when the wings rapidly rotate and change direction. In addition to contributing to the lift required to keep an insect aloft, these two rotational mechanisms provide a potent means by which the animal can modulate the direction and magnitude of flight forces during steering maneuvers. A comprehensive theory incorporating both translational and rotational mechanisms may explain the diverse patterns of wing motion displayed by different species of insects.

SummaryBiologists and engineers have long struggled to understand the hovering flight of insects, birds, and bats. The enormous diversity of these groups would suggest they fly using a variety of mechanisms, but a new study shows that hovering bats use the same aerodynamic mechanisms as do moths and other insects.

SYNOPSIS. The cost of locomotion is rarely constant, but rather varies as an animal changes speed and direction. Ultimately, the locomotory muscles of an animal must compensate for these changing requirements by varying the amount of mechanical power that they produce. In this paper, we consider the mechanisms by which the mechanical power generated by the asynchronous flight muscles of the fruit fly, Drosophila melanogaster , is regulated to match the changing requirements during flight control behaviors. Our data come from individual flies flown in a flight arena under conditions in which stroke kinematics, total metabolic cost, and flight force are simultaneously measured. In order to increase force production, flies must increase wing beat frequency and wing stroke amplitude. Theory predicts that these kinematics changes should result in a roughly cubic increase in the mechanical power requirements for flight. However, the mechanical energy generated by muscle should increase only linearly with stroke amplitude and frequency. This discrepancy implies that flight muscles must either recruit myofibrils or increase activation in order to generate sufficient mechanical power to sustain elevated force production. By comparing respirometrically measured total metabolic power with kinematically estimated mechanical power, we have calculated that the stress in the flight muscles of Drosophila must increase by 50% to accommodate a doubling of flight force. Electrophysiological evidence suggests that this change in stress may be accomplished by an increased neural drive to the asynchronous muscles, which in turn may act to recruit additional cross bridges through an increase in cytosolic calcium.

Dipterous insects (the true flies) have a sophisticated pair of equilibrium organs called halteres that evolved from hind wings. The halteres are sensitive to Coriolis forces that result from angular rotations of the body and mediate corrective reflexes during flight. Like the aerodynamically functional fore wings, the halteres beat during flight and are equipped with their own set of control muscles. It is shown that motoneurons innervating muscles of the haltere receive strong excitatory input from directionally sensitive visual interneurons. Visually guided flight maneuvers of flies may be mediated in part by efferent modulation of hard-wired equilibrium reflexes.

By simultaneously measuring flight forces and stroke kinematics in several species of fruit flies in the genus Drosophila, we have investigated the relationship between wing motion and aerodynamic force production. We induced tethered flies to vary their production of total flight force by presenting them with a vertically oscillating visual background within a closed-loop flight arena. In response to the visual motion, flies modulated their flight force by changing the translational velocity of their wings, which they accomplished via changes in both stroke amplitude and stroke frequency. Changes in wing velocity could not, however, account for all the modulation in flight force, indicating that the mean force coefficient of the wings also increases with increasing force production. The mean force coefficients were always greater than those expected under steady-state conditions under a variety of assumptions, verifying that force production in Drosophila spp. must involve non-steady-state mechanisms. The subtle changes in kinematics and force production within individual flight sequences demonstrate that flies possess a flexible control system for flight maneuvers in which they can independently control the stroke amplitude, stroke frequency and force coefficient of their wings. By studying four different-sized species, we examined the effects of absolute body size on the production and control of aerodynamic forces. With decreasing body size, the mean angular wing velocity that is required to support the body weight increases. This change is due almost entirely to an increase in stroke frequency, whereas mean stroke amplitude was similar in all four species. Despite the elevated stroke frequency and angular wing velocity, the translational velocity of the wings in small flies decreases with the reduction in absolute wing length. To compensate for their small size, D. nikananu must use higher mean force coefficients than their larger relatives.