Body saccades of Drosophila consist of stereotyped banked turns

A neural circuit architecture for rapid learning in goal-directed navigation

Anchoring goals to spatial representations enables flexible navigation but is challenging in novel environments when both representations must be acquired simultaneously. We propose a framework for how Drosophila uses internal representations of head direction (HD) to build goal representations upon selective thermal reinforcement. We show that flies use stochastically generated fixations and directed saccades to express heading preferences in an operant visual learning paradigm and that HD neurons are required to modify these preferences based on reinforcement. We used a symmetric visual setting to expose how flies' HD and goal representations co-evolve and how the reliability of these interacting representations impacts behavior. Finally, we describe how rapid learning of new goal headings may rest on a behavioral policy whose parameters are flexible but whose form is genetically encoded in circuit architecture. Such evolutionarily structured architectures, which enable rapidly adaptive behavior driven by internal representations, may be relevant across species.

Flies tune the activity of their multifunctional gyroscope

Members of the order Diptera, the true flies, are among the most maneuverable flying animals. These aerial capabilities are partially attributed to flies' possession of halteres, tiny club-shaped structures that evolved from the hindwings and play a crucial role in flight control. Halteres are renowned for acting as biological gyroscopes that rapidly detect rotational perturbations and help flies maintain a stable flight posture. Additionally, halteres provide rhythmic input to the wing steering system that can be indirectly modulated by the visual system. The multifunctional capacity of the haltere is thought to depend on arrays of embedded mechanosensors called campaniform sensilla that are arranged in distinct groups on the haltere's dorsal and ventral surfaces. Although longstanding hypotheses suggest that each array provides different information relevant to the flight control circuitry, we know little about how the haltere campaniforms are functionally organized. Here, we use in vivo calcium imaging during tethered flight to obtain population-level recordings of the haltere sensory afferents in specific fields of sensilla. We find that haltere feedback from both dorsal fields is continuously active, modulated under closed-loop flight conditions, and recruited during saccades to help flies actively maneuver. We also find that the haltere's multifaceted role may arise from the steering muscles of the haltere itself, regulating haltere stroke amplitude to modulate campaniform activity. Taken together, our results underscore the crucial role of efferent control in regulating sensor activity and provide insight into how the sensory and motor systems of flies coevolved.

Wing deformation improves aerodynamic performance of forward flight of bluebottle flies flying in a flight mill

Insect wings are flexible structures that exhibit deformations of complex spatiotemporal patterns. Existing studies on wing deformation underscore the indispensable role of wing deformation in enhancing aerodynamic performance. Here, we investigated forward flight in bluebottle flies, flying semi-freely in a magnetic flight mill; we quantified wing surface deformation using high-speed videography and marker-less surface reconstruction and studied the effects on aerodynamic forces, power and efficiency using computational fluid dynamics. The results showed that flies' wings exhibited substantial camber near the wing root and twisted along the wingspan, as they were coupled effects of deflection primarily about the claval flexion line. Such deflection was more substantial for supination during the upstroke when most thrust was produced. Compared with deformed wings, the undeformed wings generated 59-98% of thrust and 54-87% of thrust efficiency (i.e. ratio of thrust and power). Wing twist moved the aerodynamic centre of pressure proximally and posteriorly, likely improving aerodynamic efficiency.

Machine learning reveals the control mechanics of an insect wing hinge

Insects constitute the most species-rich radiation of metazoa, a success that is due to the evolution of active flight. Unlike pterosaurs, birds and bats, the wings of insects did not evolve from legs1, but are novel structures that are attached to the body via a biomechanically complex hinge that transforms tiny, high-frequency oscillations of specialized power muscles into the sweeping back-and-forth motion of the wings2. The hinge consists of a system of tiny, hardened structures called sclerites that are interconnected to one another via flexible joints and regulated by the activity of specialized control muscles. Here we imaged the activity of these muscles in a fly using a genetically encoded calcium indicator, while simultaneously tracking the three-dimensional motion of the wings with high-speed cameras. Using machine learning, we created a convolutional neural network3 that accurately predicts wing motion from the activity of the steering muscles, and an encoder-decoder4 that predicts the role of the individual sclerites on wing motion. By replaying patterns of wing motion on a dynamically scaled robotic fly, we quantified the effects of steering muscle activity on aerodynamic forces. A physics-based simulation incorporating our hinge model generates flight manoeuvres that are remarkably similar to those of free-flying flies. This integrative, multi-disciplinary approach reveals the mechanical control logic of the insect wing hinge, arguably among the most sophisticated and evolutionarily important skeletal structures in the natural world.

Machine learning reveals the control mechanics of an insect wing hinge

Insects constitute the most species-rich radiation of metazoa, a success due to the evolution of active flight. Unlike pterosaurs, birds, and bats, the wings of insects did not evolve from legs 1 , but are novel structures attached to the body via a biomechanically complex hinge that transforms tiny, high-frequency oscillations of specialized power muscles into the sweeping back-and-forth motion of the wings 2 . The hinge consists of a system of tiny, hardened structures called sclerites that are interconnected to one another via flexible joints and regulated by the activity of specialized control muscles. Here, we imaged the activity of these muscles in a fly using a genetically encoded calcium indicator, while simultaneously tracking the 3D motion of the wings with high-speed cameras. Using machine learning approaches, we created a convolutional neural network 3 that accurately predicts wing motion from the activity of the steering muscles, and an encoder-decoder 4 that predicts the role of the individual sclerites on wing motion. By replaying patterns of wing motion on a dynamically scaled robotic fly, we quantified the effects of steering muscle activity on aerodynamic forces. A physics-based simulation that incorporates our model of the hinge generates flight maneuvers that are remarkably similar to those of free flying flies. This integrative, multi-disciplinary approach reveals the mechanical control logic of the insect wing hinge, arguably among the most sophisticated and evolutionarily important skeletal structures in the natural world.

Drosophila flying in augmented reality reveals the vision-based control autonomy of the optomotor response

For walking, swimming, and flying animals, the optomotor response is essential to stabilize gaze. How flexible is the optomotor response? Classic work in Drosophila has argued that flies adapt flight control under augmented visual feedback conditions during goal-directed bar fixation. However, whether the lower-level, reflexive optomotor response can similarly adapt to augmented visual feedback (partially autonomous) or not (autonomous) over long timescales is poorly understood. To address this question, we developed an augmented reality paradigm to study the vision-based control autonomy of the yaw optomotor response of flying fruit flies (Drosophila). Flies were placed in a flight simulator, which permitted free body rotation about the yaw axis. By feeding back body movements in real time to a visual display, we augmented and inverted visual feedback. Thus, this experimental paradigm caused a constant visual error between expected and actual visual feedback to study potential adaptive visuomotor control. By combining experiments with control theory, we demonstrate that the optomotor response is autonomous during augmented reality flight bouts of up to 30 min, which exceeds the reported learning epoch during bar fixation. Agreement between predictions from linear systems theory and experimental data supports the notion that the optomotor response is approximately linear and time invariant within our experimental assay. Even under positive visual feedback, which revealed the stability limit of flies in augmented reality, the optomotor response was autonomous. Our results support a hierarchical motor control architecture in flies with fast and autonomous reflexes at the bottom and more flexible behavior at higher levels.

The influence of saccades on yaw gaze stabilization in fly flight

In a way analogous to human vision, the fruit fly D. melanogaster and many other flying insects generate smooth and saccadic movements to stabilize and shift their gaze in flight, respectively. It has been hypothesized that this combination of continuous and discrete movements benefits both flight stability and performance, particularly at high frequencies or speeds. Here we develop a hybrid control system model to explore the effects of saccades on the yaw stabilization reflex of D. melanogaster. Inspired from experimental data, the model includes a first order plant, a Proportional-Integral (PI) continuous controller, and a saccadic reset system that fires based on the integrated error of the continuous controller. We explore the gain, delay and switching threshold parameter space to quantify the optimum regions for yaw stability and performance. We show that the addition of saccades to a continuous controller provides benefits to both stability and performance across a range of frequencies. Our model suggests that Drosophila operates near its optimal switching threshold for its experimental gain set. We also show that based on experimental data, D. melanogaster operates in a region that trades off performance and stability. This trade-off increases flight robustness to compensate for internal perturbations such as wing damage.

Drinking on the wing: water collection in polarotactic horseflies

Many insects detect water bodies by observing the linearly polarised light which is reflected from the water surface. Polarotactic horseflies exhibit acrobatic manoeuvres above the water and are able to plunge on its surface, collect a droplet and fly away. This behaviour is extremely fast and has not yet been analysed. We recorded the flight patterns and kinematics of drinking horseflies using a pair of high-speed cameras. The animals of both sexes are attracted to water puddles where they make short, millisecond pitstops to collect a droplet of water that is then presumably drank "on the wing". Before the collection, the flies perform several low-altitude flybys above the puddle. After a few passes, the fly suddenly reverses its body orientation, decelerates, briefly touches the water surface and immediately flies away, usually with a droplet carried between its front legs. During the approach flight, the horseflies fly low but do not show any angular preference. Thus, they view the reflections from the sky, sun, or vegetation with a wide band of ventral ommatidia. Polarotaxis in drinking horseflies is a very robust visually guided behaviour, which operates at a broad range of intensities and various spectral compositions of reflected light.

Direct comparison reveals algorithmic similarities in fly and mouse visual motion detection

Evolution has equipped vertebrates and invertebrates with neural circuits that selectively encode visual motion. While similarities in the computations performed by these circuits in mouse and fruit fly have been noted, direct experimental comparisons have been lacking. Because molecular mechanisms and neuronal morphology in the two species are distinct, we directly compared motion encoding in these two species at the algorithmic level, using matched stimuli and focusing on a pair of analogous neurons, the mouse ON starburst amacrine cell (ON SAC) and Drosophila T4 neurons. We find that the cells share similar spatiotemporal receptive field structures, sensitivity to spatiotemporal correlations, and tuning to sinusoidal drifting gratings, but differ in their responses to apparent motion stimuli. Both neuron types showed a response to summed sinusoids that deviates from models for motion processing in these cells, underscoring the similarities in their processing and identifying response features that remain to be explained.

Flies adaptively control flight to compensate for added inertia

Animal locomotion is highly adaptive, displaying a large degree of flexibility, yet how this flexibility arises from the integration of mechanics and neural control remains elusive. For instance, animals require flexible strategies to maintain performance as changes in mass or inertia impact stability. Compensatory strategies to mechanical loading are especially critical for animals that rely on flight for survival. To shed light on the capacity and flexibility of flight neuromechanics to mechanical loading, we pushed the performance of fruit flies (Drosophila) near its limit and implemented a control theoretic framework. Flies with added inertia were placed inside a virtual reality arena which permitted free rotation about the vertical (yaw) axis. Adding inertia increased the fly's response time yet had little influence on overall gaze stabilization performance. Flies maintained stability following the addition of inertia by adaptively modulating both visuomotor gain and damping. By contrast, mathematical modelling predicted a significant decrease in gaze stabilization performance. Adding inertia altered saccades, however, flies compensated for the added inertia by increasing saccade torque. Taken together, in response to added inertia flies increase reaction time but maintain flight performance through adaptive neural control. Overall, adding inertia decreases closed-loop flight robustness. Our work highlights the flexibility and capacity of motor control in flight.

Hummingbirds use wing inertial effects to improve manoeuvrability

Hummingbirds outperform other birds in terms of aerial agility at low flight speeds. To reveal the key mechanisms that enable such unparalleled agility, we reconstructed body and wing motion of hummingbird escape manoeuvres from high-speed videos; then, we performed computational fluid dynamics modelling and flight mechanics analysis, in which the time-dependent forces within each wingbeat were resolved. We found that the birds may use the inertia of their wings to achieve peak body rotational acceleration around wing reversal when the aerodynamic forces were small. The aerodynamic forces instead counteracted the reversed inertial forces at a different wingbeat phase, thereby stabilizing the body from inertial oscillations, or they could become dominant and provide additional rotational acceleration. Our results suggest such an inertial steering mechanism was present for all four hummingbird species considered, and it was used by the birds for both pitch-up and roll accelerations. The combined inertial steering and aerodynamic mechanisms made it possible for the hummingbirds to generate instantaneous body acceleration at any phase of a wingbeat, and this feature is probably the key to understanding the unique dexterity distinguishing hummingbirds from other small-size flyers that solely rely on aerodynamics for manoeuvering.

Disynaptic inhibition shapes tuning of OFF-motion detectors in Drosophila

The circuitry underlying the detection of visual motion in Drosophila melanogaster is one of the best studied networks in neuroscience. Lately, electron microscopy reconstructions, algorithmic models, and functional studies have proposed a common motif for the cellular circuitry of an elementary motion detector based on both supralinear enhancement for preferred direction and sublinear suppression for null-direction motion. In T5 cells, however, all columnar input neurons (Tm1, Tm2, Tm4, and Tm9) are excitatory. So, how is null-direction suppression realized there? Using two-photon calcium imaging in combination with thermogenetics, optogenetics, apoptotics, and pharmacology, we discovered that it is via CT1, the GABAergic large-field amacrine cell, where the different processes have previously been shown to act in an electrically isolated way. Within each column, CT1 receives excitatory input from Tm9 and Tm1 and provides the sign-inverted, now inhibitory input signal onto T5. Ablating CT1 or knocking down GABA-receptor subunit Rdl significantly broadened the directional tuning of T5 cells. It thus appears that the signal of Tm1 and Tm9 is used both as an excitatory input for preferred direction enhancement and, through a sign inversion within the Tm1/Tm9-CT1 microcircuit, as an inhibitory input for null-direction suppression.

A deep learning analysis of Drosophila body kinematics during magnetically tethered flight

Flying Drosophila rely on their vision to detect visual objects and adjust their flight course. Despite their robust fixation on a dark, vertical bar, our understanding of the underlying visuomotor neural circuits remains limited, in part due to difficulties in analyzing detailed body kinematics in a sensitive behavioral assay. In this study, we observed the body kinematics of flying Drosophila using a magnetically tethered flight assay, in which flies are free to rotate around their yaw axis, enabling naturalistic visual and proprioceptive feedback. Additionally, we used deep learning-based video analyses to characterize the kinematics of multiple body parts in flying animals. By applying this pipeline of behavioral experiments and analyses, we characterized the detailed body kinematics during rapid flight turns (or saccades) in two different visual conditions: spontaneous flight saccades under static screen and bar-fixating saccades while tracking a rotating bar. We found that both types of saccades involved movements of multiple body parts and that the overall dynamics were comparable. Our study highlights the importance of sensitive behavioral assays and analysis tools for characterizing complex visual behaviors.

Optic flow based spatial vision in insects

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

Kinematic and hydrodynamic analyses of turning manoeuvres in penguins: body banking and wing upstroke generate centripetal force

Penguins perform lift-based swimming by flapping their wings. Previous kinematic and hydrodynamic studies have revealed the basics of wing motion and force generation in penguins. Although these studies have focused on steady forward swimming, the mechanism of turning manoeuvres is not well understood. In this study, we examined the horizontal turning of penguins via 3D motion analysis and quasi-steady hydrodynamic analysis. Free swimming of gentoo penguins (Pygoscelis papua) at an aquarium was recorded, and body and wing kinematics were analysed. In addition, quasi-steady calculations of the forces generated by the wings were performed. Among the selected horizontal swimming manoeuvres, turning was distinguished from straight swimming by the body trajectory for each wingbeat. During the turns, the penguins maintained outward banking through a wingbeat cycle and utilized a ventral force during the upstroke as a centripetal force to turn. Within a single wingbeat during the turns, changes in the body heading and bearing also mainly occurred during the upstroke, while the subsequent downstroke accelerated the body forward. We also found contralateral differences in the wing motion, i.e. the inside wing of the turn became more elevated and pronated. Quasi-steady calculations of the wing force confirmed that the asymmetry of the wing motion contributes to the generation of the centripetal force during the upstroke and the forward force during the downstroke. The results of this study demonstrate that the hydrodynamic force of flapping wings, in conjunction with body banking, is actively involved in the mechanism of turning manoeuvres in penguins.

Flies trade off stability and performance via adaptive compensation to wing damage

Physical injury often impairs mobility, which can have dire consequences for survival in animals. Revealing mechanisms of robust biological intelligence to prevent system failure can provide critical insights into how complex brains generate adaptive movement and inspiration to design fault-tolerant robots. For flying animals, physical injury to a wing can have severe consequences, as flight is inherently unstable. Using a virtual reality flight arena, we studied how flying fruit flies compensate for damage to one wing. By combining experimental and mathematical methods, we show that flies compensate for wing damage by corrective wing movement modulated by closed-loop sensing and robust mechanics. Injured flies actively increase damping and, in doing so, modestly decrease flight performance but fly as stably as uninjured flies. Quantifying responses to injury can uncover the flexibility and robustness of biological systems while informing the development of bio-inspired fault-tolerant strategies.

Active anemosensing hypothesis: how flying insects could estimate ambient wind direction through sensory integration and active movement

Estimating the direction of ambient fluid flow is a crucial step during chemical plume tracking for flying and swimming animals. How animals accomplish this remains an open area of investigation. Recent calcium imaging with tethered flying Drosophila has shown that flies encode the angular direction of multiple sensory modalities in their central complex: orientation, apparent wind (or airspeed) direction and direction of motion. Here, we describe a general framework for how these three sensory modalities can be integrated over time to provide a continuous estimate of ambient wind direction. After validating our framework using a flying drone, we use simulations to show that ambient wind direction can be most accurately estimated with trajectories characterized by frequent, large magnitude turns. Furthermore, sensory measurements and estimates of their derivatives must be integrated over a period of time that incorporates at least one of these turns. Finally, we discuss approaches that insects might use to simplify the required computations, and present a list of testable predictions. Together, our results suggest that ambient flow estimation may be an important driver underlying the zigzagging manoeuvres characteristic of plume tracking animals’ trajectories.

A Cyborg Insect Reveals a Function of a Muscle in Free Flight

While engineers put lots of effort, resources, and time in building insect scale micro aerial vehicles (MAVs) that fly like insects, insects themselves are the real masters of flight. What if we would use living insect as platform for MAV instead? Here, we reported a flight control via electrical stimulation of a flight muscle of an insect-computer hybrid robot, which is the interface of a mountable wireless backpack controller and a living beetle. The beetle uses indirect flight muscles to drive wing flapping and three major direct flight muscles (basalar, subalar, and third axilliary (3Ax) muscles) to control the kinematics of the wings for flight maneuver. While turning control was already achieved by stimulating basalar and 3Ax muscles, electrical stimulation of subalar muscles resulted in braking and elevation control in flight. We also demonstrated around 20 degrees of contralateral yaw and roll by stimulating individual subalar muscle. Stimulating both subalar muscles lead to an increase of 20 degrees in pitch and decelerate the flight by 1.5 m/s² as well as an induce in elevation of 2 m/s².

Flying Into the Wind: Insects and Bio-Inspired Micro-Air-Vehicles With a Wing-Stroke Dihedral Steer Passively Into Wind-Gusts

Natural fliers utilize passive and active flight control strategies to cope with windy conditions. This capability makes them incredibly agile and resistant to wind gusts. Here, we study how insects achieve this, by combining Computational Fluid Dynamics (CFD) analyses of flying fruit flies with freely-flying robotic experiments. The CFD analysis shows that flying flies are partly passively stable in side-wind conditions due to their dorsal-ventral wing-beat asymmetry defined as wing-stroke dihedral. Our robotic experiments confirm that this mechanism also stabilizes free-moving flapping robots with similar asymmetric dihedral wing-beats. This shows that both animals and robots with asymmetric wing-beats are dynamically stable in sideways wind gusts. Based on these results, we developed an improved model for the aerodynamic yaw and roll torques caused by the coupling between lateral motion and the stroke dihedral. The yaw coupling passively steers an asymmetric flapping flyer into the direction of a sideways wind gust; in contrast, roll torques are only stabilizing at high air gust velocities, due to non-linear coupling effects. The combined CFD simulations, robot experiments, and stability modeling help explain why the majority of flying insects exhibit wing-beats with positive stroke dihedral and can be used to develop more stable and robust flapping-wing Micro-Air-Vehicles.

A population of descending neurons that regulates the flight motor of Drosophila

Like 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 length³, 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 both the damaged and intact wings⁴. 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 neuron (DNg02) that projects directly from visual output regions of the brain to the dorsal flight neuropil of the ventral nerve cord. Unlike many 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.

Using an activation screen in flying flies, Namiki et al. identify a population of descending neurons that regulates wing amplitude over a large dynamic range. Via functional imaging and activation of different numbers of cells, they show that this population is a core component of the flight circuit, allowing the fly to steer and fly straight.

A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selection

Flexible behaviors over long timescales are thought to engage recurrent neural networks in deep brain regions, which are experimentally challenging to study. In insects, recurrent circuit dynamics in a brain region called the central complex (CX) enable directed locomotion, sleep, and context- and experience-dependent spatial navigation. We describe the first complete electron-microscopy-based connectome of the Drosophila CX, including all its neurons and circuits at synaptic resolution. We identified new CX neuron types, novel sensory and motor pathways, and network motifs that likely enable the CX to extract the fly's head-direction, maintain it with attractor dynamics, and combine it with other sensorimotor information to perform vector-based navigational computations. We also identified numerous pathways that may facilitate the selection of CX-driven behavioral patterns by context and internal state. The CX connectome provides a comprehensive blueprint necessary for a detailed understanding of network dynamics underlying sleep, flexible navigation, and state-dependent action selection.

Mechanisms of punctuated vision in fly flight

To guide locomotion, animals control gaze via movements of their eyes, head, and/or body, but how the nervous system controls gaze during complex motor tasks remains elusive. In many animals, shifts in gaze consist of periods of smooth movement punctuated by rapid eye saccades. Notably, eye movements are constrained by anatomical limits, which requires resetting eye position. By studying tethered, flying fruit flies (Drosophila), we show that flies perform stereotyped head saccades to reset gaze, analogous to optokinetic nystagmus in primates. Head-reset saccades interrupted head smooth movement for as little as 50 ms-representing less than 5% of the total flight time-thereby enabling punctuated gaze stabilization. By revealing the passive mechanics of the neck joint, we show that head-reset saccades leverage the neck's natural elastic recoil, enabling mechanically assisted redirection of gaze. The consistent head orientation at saccade initiation, the influence of the head's angular position on saccade rate, the decrease in wing saccade frequency in head-fixed flies, and the decrease in head-reset saccade rate in flies with their head range of motion restricted together implicate proprioception as the primary trigger of head-reset saccades. Wing-reset saccades were influenced by head orientation, establishing a causal link between neck sensory signals and the execution of body saccades. Head-reset saccades were abolished when flies switched to a landing state, demonstrating that head movements are gated by behavioral state. We propose a control architecture for active vision systems with limits in sensor range of motion. VIDEO ABSTRACT.

Maximally efficient prediction in the early fly visual system may support evasive flight maneuvers

The visual system must make predictions to compensate for inherent delays in its processing. Yet little is known, mechanistically, about how prediction aids natural behaviors. Here, we show that despite a 20-30ms intrinsic processing delay, the vertical motion sensitive (VS) network of the blowfly achieves maximally efficient prediction. This prediction enables the fly to fine-tune its complex, yet brief, evasive flight maneuvers according to its initial ego-rotation at the time of detection of the visual threat. Combining a rich database of behavioral recordings with detailed compartmental modeling of the VS network, we further show that the VS network has axonal gap junctions that are critical for optimal prediction. During evasive maneuvers, a VS subpopulation that directly innervates the neck motor center can convey predictive information about the fly’s future ego-rotation, potentially crucial for ongoing flight control. These results suggest a novel sensory-motor pathway that links sensory prediction to behavior.

Survival-critical behaviors shape neural circuits to translate sensory information into strikingly fast predictions, e.g. in escaping from a predator faster than the system’s processing delay. We show that the fly visual system implements fast and accurate prediction of its visual experience. This provides crucial information for directing fast evasive maneuvers that unfold over just 40ms. Our work shows how this fast prediction is implemented, mechanistically, and suggests the existence of a novel sensory-motor pathway from the fly visual system to a wing steering motor neuron. Echoing and amplifying previous work in the retina, our work hypothesizes that the efficient encoding of predictive information is a universal design principle supporting fast, natural behaviors.

Hybrid visual control in fly flight: insights into gaze shift via saccades

Flies fly by alternating between periods of fixation and body saccades, analogous to how our own eyes move. Gaze fixation via smooth movement in fly flight has been studied extensively, but comparatively less is known about the mechanism by which flies trigger and control body saccades to shift their gaze. Why do flies implement a hybrid fixate-and-saccade locomotion strategy? Here we review recent developments that provide new insights into this question. We focus on the interplay between smooth movement and saccades, the trigger classes of saccades, and the timeline of saccade execution. We emphasize recent mechanistic advances in Drosophila, where genetic tools have enabled cellular circuit analysis at an unprecedented level in a flying insect. In addition, we review trade-offs in behavioral paradigms used to study saccades. Throughout we highlight exciting avenues for future research in the control of fly flight.

A simplified dynamic model for controlled insect hovering flight and control stability analysis

In this paper, the controlled stability of insect hovering flight is analyzed in detail based on a simplified dynamic model of the flyer and flow. The simplified dynamic model incorporates PID-based wing-kinematic controllers. The control stability of the hovering flight is evaluated based on the cycle-mean dynamic equations. The stability analyses and the simplified dynamic model allow us to derive and test the control coefficients for stable free hovering, firstly in the longitudinal mode of flight and then the lateral mode. In this manner, coefficients for wing-kinematic control for full CFD-FSI simulation could be obtained very efficiently. The coefficients thus determined are verified against full-fidelity CFD-FSI free flight simulations.

A chordwise offset of the wing-pitch axis enhances rotational aerodynamic forces on insect wings: a numerical study

Most flying animals produce aerodynamic forces by flapping their wings back and forth with a complex wingbeat pattern. The fluid dynamics that underlies this motion has been divided into separate aerodynamic mechanisms of which rotational lift, that results from fast wing pitch rotations, is particularly important for flight control and manoeuvrability. This rotational force mechanism has been modelled using Kutta-Joukowski theory, which combines the forward stroke motion of the wing with the fast pitch motion to compute forces. Recent studies, however, suggest that hovering insects can produce rotational forces at stroke reversal, without a forward motion of the wing. We have conducted a broad numerical parametric study over a range of wing morphologies and wing kinematics to show that rotational force production depends on two mechanisms: (i) conventional Kutta-Joukowski-based rotational forces and (ii) a rotational force mechanism that enables insects with an offset of the pitch axis relative to the wing's chordwise symmetry axis to generate rotational forces in the absence of forward wing motion. Because flying animals produce control actions frequently near stroke reversal, this pitch-axis-offset dependent aerodynamic mechanism may be particularly important for understanding control and manoeuvrability in natural flyers.

The manifold structure of limb coordination in walking Drosophila

Terrestrial locomotion requires animals to coordinate their limb movements to efficiently traverse their environment. While previous studies in hexapods have reported that limb coordination patterns can vary substantially, the structure of this variability is not yet well understood. Here, we characterized the symmetric and asymmetric components of variation in walking kinematics in the genetic model organism Drosophila. We found that Drosophila use a single continuum of coordination patterns without evidence for preferred configurations. Spontaneous symmetric variability was associated with modulation of a single control parameter-stance duration-while asymmetric variability consisted of small, limb-specific modulations along multiple dimensions of the underlying symmetric pattern. Commands that modulated walking speed, originating from artificial neural activation or from the visual system, evoked modulations consistent with spontaneous behavior. Our findings suggest that Drosophila employ a low-dimensional control architecture, which provides a framework for understanding the neural circuits that regulate hexapod legged locomotion.

Visuomotor strategies for object approach and aversion in Drosophila melanogaster

Animals classify stimuli to generate appropriate motor actions. In flight, Drosophila melanogaster classify equidistant large and small objects with categorically different behaviors: a tall object evokes approach whereas a small object elicits avoidance. We studied visuomotor behavior in rigidly and magnetically tethered D. melanogaster to reveal strategies that generate aversion to a small object. We discovered that small-object aversion in tethered flight is enabled by aversive saccades and smooth movement, which vary with the stimulus type. Aversive saccades in response to a short bar had different dynamics from approach saccades in response to a tall bar and the distribution of pre-saccade error angles was more stochastic for a short bar. Taken together, we show that aversive responses in D. melanogaster are driven in part by processes that elicit signed saccades with distinct dynamics and trigger mechanisms. Our work generates new hypotheses to study brain circuits that underlie classification of objects in D. melanogaster.

A songbird compensates for wing molt during escape flights by reducing the molt gap and increasing angle-of-attack

During molt, birds replace their feathers to retain feather quality and maintain flight performance. However, wing gaps inherent of this process can also reduce flight capacities, which could be detrimental when foraging or escaping predators. Still, many bird species will not stop their normal activities when molting. In this study, we investigated whether and how birds adjust their escape flight behavior to compensate for the reduction in performance when flying with wing gaps. Using stereoscopic high-speed videography, we filmed 146 upward-directed escape flights of 19 and 22 pied flycatchers (Ficedula hypoleuca) with and without simulated molt gaps, respectively. We then reconstructed the three-dimensional body and wing movements throughout each maneuver. By comparing flights with and without gaps, we determined how wing molt gaps affected wing morphology, escape flight performance, and how the birds adjusted their flight kinematics in order to negate possible negative aerodynamic effects. Our manipulations resulted in a lower second-moment-of-area of the wings, but flight speed and net aerodynamic force production did not differ between the two groups. We found that in manipulated birds, the size of the gap was reduced as the flight feathers adjacent to the gap had moved towards each other. Moreover, the experimental decrease in second-moment-of-area was associated with an increase in angle-of-attack, whereas changes in wingbeat-induced speeds were associated with variations in aerodynamic force production. This suggests that the control of escape flight in molting birds might be modular, allowing relatively simple flight control, thus reducing the burden on the neuro-muscular flight control system.

Coordinated Turning Behaviour of Loitering Honeybees

Turning during flight is a complex behaviour that requires coordination to ensure that the resulting centrifugal force is never large enough to disrupt the intended turning trajectory. The centrifugal force during a turn increases with the curvature (sharpness) of the turn, as well as the speed of flight. Consequently, sharp turns would require lower flight speeds, in order to limit the centrifugal force to a manageable level and prevent unwanted sideslips. We have video-filmed honeybees flying near a hive entrance when the entrance is temporarily blocked. A 3D reconstruction and analysis of the flight trajectories executed during this loitering behaviour reveals that sharper turns are indeed executed at lower speeds. During a turn, the flight speed is matched to the curvature, moment to moment, in such a way as to maintain the centrifugal force at an approximately constant, low level of about 30% of the body weight, irrespective of the instantaneous speed or curvature of the turn. This ensures that turns are well coordinated, with few or no sideslips - as it is evident from analysis of other properties of the flight trajectories.

Multisensory Control of Orientation in Tethered Flying Drosophila

A longstanding goal of systems neuroscience is to quantitatively describe how the brain integrates sensory cues over time. Here, we develop a closed-loop orienting paradigm in Drosophila to study the algorithms by which cues from two modalities are integrated during ongoing behavior. We find that flies exhibit two behaviors when presented simultaneously with an attractive visual stripe and aversive wind cue. First, flies perform a turn sequence where they initially turn away from the wind but later turn back toward the stripe, suggesting dynamic sensory processing. Second, turns toward the stripe are slowed by the presence of competing wind, suggesting summation of turning drives. We develop a model in which signals from each modality are filtered in space and time to generate turn commands and then summed to produce ongoing orienting behavior. This computational framework correctly predicts behavioral dynamics for a range of stimulus intensities and spatial arrangements.

Bees with attitude: the effects of directed gusts on flight trajectories

Flight is a complicated task at the centimetre scale particularly due to unsteady air fluctuations which are ubiquitous in outdoor flight environments. Flying organisms deal with these difficulties using active and passive control mechanisms to steer their body motion. Body attitudes of flapping organisms are linked with their resultant flight trajectories and performance, yet little is understood about how isolated unsteady aerodynamic phenomena affect the interlaced dynamics of such systems. In this study, we examined freely flying bumblebees subject to a single isolated gust to emulate aerodynamic disturbances encountered in nature. Bumblebees are expert commanders of the aerial domain as they persistently forage within complex terrain elements. By tracking the three-dimensional dynamics of bees flying through gusts, we determined the sequences of motion that permit flight in three disturbance conditions: sideward, upward and downward gusts. Bees executed a series of passive impulsive maneuvers followed by active recovery maneuvers. Impulsive motion was unique in each gust direction, maintaining control by passive manipulation of the body. Bees pitched up and slowed down at the beginning of recovery in every disturbance, followed by corrective maneuvers which brought body attitudes back to their original state. Bees were displaced the most by the sideward gust, displaying large lateral translations and roll deviations. Upward gusts were easier for bees to fly through, causing only minor flight changes and minimal recovery times. Downward gusts severely impaired the control response of bees, inflicting strong adverse forces which sharply upset trajectories. Bees used a variety of control strategies when flying in each disturbance, offering new insights into insect-scale flapping flight and bio-inspired robotic systems.This article has an associated First Person interview with the first author of the paper.

A tailless aerial robotic flapper reveals that flies use torque coupling in rapid banked turns

Insects are among the most agile natural flyers. Hypotheses on their flight control cannot always be validated by experiments with animals or tethered robots. To this end, we developed a programmable and agile autonomous free-flying robot controlled through bio-inspired motion changes of its flapping wings. Despite being 55 times the size of a fruit fly, the robot can accurately mimic the rapid escape maneuvers of flies, including a correcting yaw rotation toward the escape heading. Because the robot’s yaw control was turned off, we showed that these yaw rotations result from passive, translation-induced aerodynamic coupling between the yaw torque and the roll and pitch torques produced throughout the maneuver. The robot enables new methods for studying animal flight, and its flight characteristics allow for real-world flight missions.

Identification of optimal feedback control rules from micro-quadrotor and insect flight trajectories

This paper presents "optimal identification," a framework for using experimental data to identify the optimality conditions associated with the feedback control law implemented in the measurements. The technique compares closed loop trajectory measurements against a reduced order model of the open loop dynamics, and uses linear matrix inequalities to solve an inverse optimal control problem as a convex optimization that estimates the controller optimality conditions. In this study, the optimal identification technique is applied to two examples, that of a millimeter-scale micro-quadrotor with an engineered controller on board, and the example of a population of freely flying Drosophila hydei maneuvering about forward flight. The micro-quadrotor results show that the performance indices used to design an optimal flight control law for a micro-quadrotor may be recovered from the closed loop simulated flight trajectories, and the Drosophila results indicate that the combined effect of the insect longitudinal flight control sensing and feedback acts principally to regulate pitch rate.

Feedback Control-Based Navigation of a Flying Insect-Machine Hybrid Robot

This study reports the first ever demonstration of the aero navigation of a free-flying insect based on feedback control. Instead of imitating the complicated kinetics and mechanisms of insect locomotion, a live insect can be directly transformed into a soft robot by embedding it with artificial devices. Since many insects can perform acrobatics aerially, thereby exhibiting far greater flexibility than current man-made flyers, correctly commanding the internal structures of an insect to perform based on the instructions would be a breakthrough. Herein, beetles (Mecynorrhina torquata) were chosen as the flying platform, and an inertial measurement unit-implemented electronic backpack was designed and manufactured to remotely command the beetles. To achieve horizontal flight control, multiple flight muscles of the beetles, that is, the basalar and third axillary muscles were stimulated to control the flight directions. However, the beetles were found to gradually adapt to the electrical stimulation, and the flight corrections were elicited by generating compensatory flight forces during a long-lasting stimulation (>300 ms), which were revealed by the decrease in induced lateral force. Based on this finding, a proportional derivative feedback controller was designed to navigate the flying beetles based on the predetermined path using frequency-dependent electrical pulses. To avoid a continuous stimulation, we proposed a stimulation protocol which separated two stimulations with a 50-ms rest. Compared to long stimulations (>300 ms), a 150-ms stimulation with 200-ms update interval was more efficient in correcting the flight direction of the beetles.

Abolishment of Spontaneous Flight Turns in Visually Responsive Drosophila

Animals react rapidly to external stimuli, such as an approaching predator, but in other circumstances, they seem to act spontaneously, without any obvious external trigger. How do the neural processes mediating the execution of reflexive and spontaneous actions differ? We studied this question in tethered, flying Drosophila. We found that silencing a large but genetically defined set of non-motor neurons virtually eliminates spontaneous flight turns while preserving the tethered flies' ability to perform two types of visually evoked turns, demonstrating that, at least in flies, these two modes of action are almost completely dissociable.

Speed control and force-vectoring of blue bottle flies in a magnetically-levitated flight mill

Flies fly at a broad range of speeds and produce sophisticated aerial maneuvers with precisely controlled wing movements. Remarkably, only subtle changes in wing motion are used by flies to produce aerial maneuvers, resulting in little directional tilt of aerodynamic force vector relative to the body. Therefore, it is often considered that flies fly according to a helicopter model and control speed mainly via force-vectoring by body-pitch change. Here we examined the speed control of blue bottle flies using a magnetically-levitated (MAGLEV) flight mill, as they fly at different body pitch angles and with different augmented aerodynamic damping. We identified wing kinematic contributors to the changes of estimated aerodynamic force through testing and comparing two force-vectoring models: i.e., a constant force-vectoring model and a variable force-vectoring model, while using the Akaike's information criterion for the selection of best-approximating model. Results show that the best-approximating variable force-vectoring model, which includes the effects of wing kinematic changes, yields a considerably more accurate prediction of flight speed, particularly in higher velocity range, as compared with those of the constant force-vectoring model. Examining the variable force-vectoring model reveals that, in the flight-mill tethered flight, flies use a collection of wing kinematic variables to control primarily the force magnitude, while the force direction is also modulated, albeit to a smaller extent compared to those due to the changes in body pitch. The roles of these wing kinematic variables are analogous to those of throttle, and collective and cyclic pitch of helicopters.

Drosophila Spatiotemporally Integrates Visual Signals to Control Saccades

Like many visually active animals, including humans, flies generate both smooth and rapid saccadic movements to stabilize their gaze. How rapid body saccades and smooth movement interact for simultaneous object pursuit and gaze stabilization is not understood. We directly observed these interactions in magnetically tethered Drosophila free to rotate about the yaw axis. A moving bar elicited sustained bouts of saccades following the bar, with surprisingly little smooth movement. By contrast, a moving panorama elicited robust smooth movement interspersed with occasional optomotor saccades. The amplitude, angular velocity, and torque transients of bar-fixation saccades were finely tuned to the speed of bar motion and were triggered by a threshold in the temporal integral of the bar error angle rather than its absolute retinal position error. Optomotor saccades were tuned to the dynamics of panoramic image motion and were triggered by a threshold in the integral of velocity over time. A hybrid control model based on integrated motion cues simulates saccade trigger and dynamics. We propose a novel algorithm for tuning fixation saccades in flies.

An Array of Descending Visual Interneurons Encoding Self-Motion in Drosophila

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 STATEMENT

Most 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.

Limitations of rotational manoeuvrability in insects and hummingbirds: evaluating the effects of neuro-biomechanical delays and muscle mechanical power

Flying animals ranging in size from fruit flies to hummingbirds are nimble fliers with remarkable rotational manoeuvrability. The degrees of manoeuvrability among these animals, however, are noticeably diverse and do not simply follow scaling rules of flight dynamics or muscle power capacity. As all manoeuvres emerge from the complex interactions of neural, physiological and biomechanical processes of an animal's flight control system, these processes give rise to multiple limiting factors that dictate the maximal manoeuvrability attainable by an animal. Here using functional models of an animal's flight control system, we investigate the effects of three such limiting factors, including neural and biomechanical (from limited flapping frequency) delays and muscle mechanical power, for two insect species and two hummingbird species, undergoing roll, pitch and yaw rotations. The results show that for animals with similar degree of manoeuvrability, for example, fruit flies and hummingbirds, the underlying limiting factors are different, as the manoeuvrability of fruit flies is only limited by neural delays and that of hummingbirds could be limited by all three factors. In addition, the manoeuvrability also appears to be the highest about the roll axis as it requires the least muscle mechanical power and can tolerate the largest neural delays.

Sensorimotor Neuroscience: Motor Precision Meets Vision

Visual motion sensing neurons in the fly also encode a range of behavior-related signals. These nonvisual inputs appear to be used to correct some of the challenges of visually guided locomotion.

Generation of the pitch moment during the controlled flight after takeoff of fruitflies

In the present paper, the controlled flight of fruitflies after voluntary takeoff is studied. Wing and body kinematics of the insects after takeoff are measured using high-speed video techniques, and the aerodynamic force and moment are calculated by the computational fluid dynamics method based on the measured data. How the control moments are generated is analyzed by correlating the computed moments with the wing kinematics. A fruit-fly has a large pitch-up angular velocity owing to the takeoff jump and the fly controls its body attitude by producing pitching moments. It is found that the pitching moment is produced by changes in both the aerodynamic force and the moment arm. The change in the aerodynamic force is mainly due to the change in angle of attack. The change in the moment arm is mainly due to the change in the mean stroke angle and deviation angle, and the deviation angle plays a more important role than the mean stroke angle in changing the moment arm (note that change in deviation angle implies variation in the position of the aerodynamic stroke plane with respect to the anatomical stroke plane). This is unlike the case of fruitflies correcting pitch perturbations in steady free flight, where they produce pitching moment mainly by changes in mean stroke angle.

Flies compensate for unilateral wing damage through modular adjustments of wing and body kinematics

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.

The Function and Organization of the Motor System Controlling Flight Maneuvers in Flies

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.

Quantitative Predictions Orchestrate Visual Signaling in Drosophila

Vision influences behavior, but ongoing behavior also modulates vision in animals ranging from insects to primates. The function and biophysical mechanisms of most such modulations remain unresolved. Here, we combine behavioral genetics, electrophysiology, and high-speed videography to advance a function for behavioral modulations of visual processing in Drosophila. We argue that a set of motion-sensitive visual neurons regulate gaze-stabilizing head movements. We describe how, during flight turns, Drosophila perform a set of head movements that require silencing their gaze-stability reflexes along the primary rotation axis of the turn. Consistent with this behavioral requirement, we find pervasive motor-related inputs to the visual neurons, which quantitatively silence their predicted visual responses to rotations around the relevant axis while preserving sensitivity around other axes. This work proposes a function for a behavioral modulation of visual processing and illustrates how the brain can remove one sensory signal from a circuit carrying multiple related signals.

Neural control and precision of flight muscle activation in Drosophila

Precision of motor commands is highly relevant in a large context of various locomotor behaviors, including stabilization of body posture, heading control and directed escape responses. While posture stability and heading control in walking and swimming animals benefit from high friction via ground reaction forces and elevated viscosity of water, respectively, flying animals have to cope with comparatively little aerodynamic friction on body and wings. Although low frictional damping in flight is the key to the extraordinary aerial performance and agility of flying birds, bats and insects, it challenges these animals with extraordinary demands on sensory integration and motor precision. Our review focuses on the dynamic precision with which Drosophila activates its flight muscular system during maneuvering flight, considering relevant studies on neural and muscular mechanisms of thoracic propulsion. In particular, we tackle the precision with which flies adjust power output of asynchronous power muscles and synchronous flight control muscles by monitoring muscle calcium and spike timing within the stroke cycle. A substantial proportion of the review is engaged in the significance of visual and proprioceptive feedback loops for wing motion control including sensory integration at the cellular level. We highlight that sensory feedback is the basis for precise heading control and body stability in flies.

Hummingbirds control turning velocity using body orientation and turning radius using asymmetrical wingbeat kinematics

Turning in flight requires reorientation of force, which birds, bats and insects accomplish either by shifting body position and total force in concert or by using left-right asymmetries in wingbeat kinematics. Although both mechanisms have been observed in multiple species, it is currently unknown how each is used to control changes in trajectory. We addressed this problem by measuring body and wingbeat kinematics as hummingbirds tracked a revolving feeder, and estimating aerodynamic forces using a quasi-steady model. During arcing turns, hummingbirds symmetrically banked the stroke plane of both wings, and the body, into turns, supporting a body-dependent mechanism. However, several wingbeat asymmetries were present during turning, including a higher and flatter outer wingtip path and a lower more deviated inner wingtip path. A quasi-steady analysis of arcing turns performed with different trajectories revealed that changes in radius were associated with asymmetrical kinematics and forces, and changes in velocity were associated with symmetrical kinematics and forces. Collectively, our results indicate that both body-dependent and -independent force orientation mechanisms are available to hummingbirds, and that these kinematic strategies are used to meet the separate aerodynamic challenges posed by changes in velocity and turning radius.