The generation of forces and moments during visual-evoked steering maneuvers in flying Drosophila

Fly Me to the Micron: Microtechnologies for Drosophila Research

Multicellular model organisms, such as Drosophila melanogaster (fruit fly), are frequently used in a myriad of biological research studies due to their biological significance and global standardization. However, traditional tools used in these studies generally require manual handling, subjective phenotyping, and bulk treatment of the organisms, resulting in laborious experimental protocols with limited accuracy. Advancements in microtechnology over the course of the last two decades have allowed researchers to develop automated, high-throughput, and multifunctional experimental tools that enable novel experimental paradigms that would not be possible otherwise. We discuss recent advances in microtechnological systems developed for small model organisms using D. melanogaster as an example. We critically analyze the state of the field by comparing the systems produced for different applications. Additionally, we suggest design guidelines, operational tips, and new research directions based on the technical and knowledge gaps in the literature. This review aims to foster interdisciplinary work by helping engineers to familiarize themselves with model organisms while presenting the most recent advances in microengineering strategies to biologists.

Flight control of fruit flies: dynamic response to optic-flow and headwind

Insects are magnificent fliers that are capable of performing many complex tasks such as speed regulation, smooth landings, and collision avoidance, even though their computational abilities are limited by their small brain. To investigate how flying insects respond to changes in wind speed and surrounding optic flow, the open-loop sensorimotor response of female Queensland fruit flies (Bactrocera tryoni) was examined. 136 flies were exposed to stimuli comprising sinusoidally varying optic flow and air flow (simulating forward movement) under tethered conditions in a virtual reality arena. Two responses were measured: the thrust, and the abdomen pitch. The dynamics of the responses to optic flow and air flow were measured at various frequencies, and modelled as a multicompartment linear system, which accurately captures the fruit flies' behavioural responses. The results indicate that these two behavioural responses are concurrently sensitive to changes of optic flow as well as wind. The abdomen pitch showed a streamlining response, where the abdomen was raised higher as the magnitude of either stimulus was increased. The thrust, on the other hand, exhibited a counter-phase response where maximum thrust occurred when the optic flow or wind flow was at a minimum, indicating that the flies were attempting to maintain an ideal flight speed. When the changes in the wind and optic flow were in phase (i.e. did not contradict each other), the net responses (thrust and abdomen pitch) were well approximated by an equally weighted sum of the responses to the individual stimuli. However, when the optic flow and wind stimuli were presented in counterphase, the flies seemed to respond to only one stimulus or the other, demonstrating a form of ‘selective attention’.

Body appendages fine-tune posture and moments in freely manoeuvring fruit flies

The precise control of body posture by turning moments is key to elevated locomotor performance in flying animals. Although elevated moments for body stabilization are typically produced by wing aerodynamics, animals also steer using drag on body appendages, shifting their centre of body mass, and changing moments of inertia caused by active alterations in body shape. To estimate the instantaneous contribution of each of these components for posture control in an insect, we three-dimensionally reconstructed body posture and movements of body appendages in freely manoeuvring fruit flies (Drosophila melanogaster) by high-speed video and experimentally scored drag coefficients of legs and body trunk at low Reynolds number. The results show that the sum of leg- and abdomen-induced yaw moments dominates wing-induced moments during 17% of total flight time but is, on average, 7.2-times (roll, 3.4-times) smaller during manoeuvring. Our data reject a previous hypothesis on synergistic moment support, indicating that drag on body appendages and mass-shift inhibit rather than support turning moments produced by the wings. Numerical modelling further shows that hind leg extension alters the moments of inertia around the three main body axes of the animal by not more than 6% during manoeuvring, which is significantly less than previously reported for other insects. In sum, yaw, pitch and roll steering by body appendages probably fine-tune turning behaviour and body posture, without providing a significant advantage for posture stability and moment support. Motion control of appendages might thus be part of the insect's trimming reflexes, which reduce imbalances in moment generation caused by unilateral wing damage and abnormal asymmetries of the flight apparatus.

Antennal mechanosensory neurons mediate wing motor reflexes in flying Drosophila

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

Controlling roll perturbations in fruit flies

Owing to aerodynamic instabilities, stable flapping flight requires ever-present fast corrective actions. Here, we investigate how flies control perturbations along their body roll angle, which is unstable and their most sensitive degree of freedom. We glue a magnet to each fly and apply a short magnetic pulse that rolls it in mid-air. Fast video shows flies correct perturbations up to 100° within 30 ± 7 ms by applying a stroke-amplitude asymmetry that is well described by a linear proportional-integral controller. For more aggressive perturbations, we show evidence for nonlinear and hierarchical control mechanisms. Flies respond to roll perturbations within 5 ms, making this correction reflex one of the fastest in the animal kingdom.

Strategies for the stabilization of longitudinal forward flapping flight revealed using a dynamically-scaled robotic fly

The ability to regulate forward speed is an essential requirement for flying animals. Here, we use a dynamically-scaled robot to study how flapping insects adjust their wing kinematics to regulate and stabilize forward flight. The results suggest that the steady-state lift and thrust requirements at different speeds may be accomplished with quite subtle changes in hovering kinematics, and that these adjustments act primarily by altering the pitch moment. This finding is consistent with prior hypotheses regarding the relationship between body pitch and flight speed in fruit flies. Adjusting the mean stroke position of the wings is a likely mechanism for trimming the pitch moment at all speeds, whereas changes in the mean angle of attack may be required at higher speeds. To ensure stability, the flapping system requires additional pitch damping that increases in magnitude with flight speed. A compensatory reflex driven by fast feedback of pitch rate from the halteres could provide such damping, and would automatically exhibit gain scheduling with flight speed if pitch torque was regulated via changes in stroke deviation. Such a control scheme would provide an elegant solution for stabilization across a wide range of forward flight speeds.

Responses of a pair of flying locusts to lateral looming visual stimuli

We presented a pair of locusts flying loosely tethered with laterally looming discs. Two experiments tested whether looming-evoked flight behaviour was affected by the presence (1) or relative position (2) of a conspecific. We recorded: the type of behavioural response, motion within 6 degrees of freedom, behavioural onset time and duration, distance between individuals and relative direction of motion. Response distributions of the locust furthest from the stimulus (L1) were not affected by the presence or relative position of a conspecific, whereas distributions of the closer locust (L2) were affected by its position relative to the stimulus. Motion tracks of L1 were affected by the presence of L2, which generated relatively robust responses directed forward and away from the stimulus. Translational and rotational motion of L1 differed across treatments in both experiments, whereas L2 motion was less sensitive to the presence or position of a conspecific. The start and duration of the behaviour were invariant to the presence or position of a conspecific and locust pairs maintained a fixed distance during responses to looming. Results suggest that looming-evoked behaviour is influenced by visual cues from a conspecific in the vicinity.

Flying fruit flies correct for visual sideslip depending on relative speed of forward optic flow

As a fly flies through its environment, static objects produce moving images on its retina, and this optic flow is essential for steering and course corrections. Different types of rotation and translation produce unique flow fields, which fly brains are wired to identify. However, a feature of optic flow unique to translational motion is that adjacent images may move across the retina at different speeds, depending on their distance from the observer. Many insects take advantage of this depth cue, called motion parallax, to determine the distance to objects. We wanted to know if differential object speeds affect the corrective responses of fruit flies when they experience unplanned course deviations. We presented tethered flying flies with optic flow and measured their corrective responses to sideways perturbations of images with different relative forward speeds. We found that flying flies attend to the relative speed of dots during forward motion, and adjust their corrective responses to sideslip deviations depending on this cue. With no other distinguishing features (such as brightness or size), flies mounted a greater response to sideways deviations that were signaled by faster moving dots in the forward flow field, those that appeared radially closer by their speeds. This is consistent with the interpretation that fruit flies attend to seemingly nearer objects, and correct more strongly when they indicate a perturbation.

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

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

The influence of sensory delay on the yaw dynamics of a flapping insect

In closed-loop systems, sensor feedback delays may have disastrous implications for performance and stability. Flies have evolved multiple specializations to reduce this latency, but the fastest feedback during flight involves a delay that is still significant on the timescale of body dynamics. We explored the effect of sensor delay on flight stability and performance for yaw turns using a dynamically scaled robotic model of the fruitfly, Drosophila. The robot was equipped with a real-time feedback system that performed active turns in response to measured torque about the functional yaw axis. We performed system response experiments for a proportional controller in yaw velocity for a range of feedback delays, similar in dimensionless timescale to those experienced by a fly. The results show a fundamental trade-off between sensor delay and permissible feedback gain, and suggest that fast mechanosensory feedback in flies, and most probably in other insects, provide a source of active damping which compliments that contributed by passive effects. Presented in the context of these findings, a control architecture whereby a haltere-mediated inner-loop proportional controller provides damping for slower visually mediated feedback is consistent with tethered-flight measurements, free-flight observations and engineering design principles.

Pigeons steer like helicopters and generate down- and upstroke lift during low speed turns

Turning is crucial for animals, particularly during predator-prey interactions and to avoid obstacles. For flying animals, turning consists of changes in (i) flight trajectory, or path of travel, and (ii) body orientation, or 3D angular position. Changes in flight trajectory can only be achieved by modulating aerodynamic forces relative to gravity. How birds coordinate aerodynamic force production relative to changes in body orientation during turns is key to understanding the control strategies used in avian maneuvering flight. We hypothesized that pigeons produce aerodynamic forces in a uniform direction relative to their bodies, requiring changes in body orientation to redirect those forces to turn. Using detailed 3D kinematics and body mass distributions, we examined net aerodynamic forces and body orientations in slowly flying pigeons (Columba livia) executing level 90° turns. The net aerodynamic force averaged over the downstroke was maintained in a fixed direction relative to the body throughout the turn, even though the body orientation of the birds varied substantially. Early in the turn, changes in body orientation primarily redirected the downstroke aerodynamic force, affecting the bird's flight trajectory. Subsequently, the pigeon mainly reacquired the body orientation used in forward flight without affecting its flight trajectory. Surprisingly, the pigeon's upstroke generated aerodynamic forces that were approximately 50% of those generated during the downstroke, nearly matching the relative upstroke forces produced by hummingbirds. Thus, pigeons achieve low speed turns much like helicopters, by using whole-body rotations to alter the direction of aerodynamic force production to change their flight trajectory.

A model of visual-olfactory integration for odour localisation in free-flying fruit flies

Flying fruit flies (Drosophila melanogaster) locate a concealed appetitive odour source most accurately in environments containing vertical visual contrasts. To investigate how visuomotor and olfactory responses may be integrated, we examine the free-flight behaviour of flies in three visual conditions, with and without food odour present. While odour localisation is facilitated by uniformly distributed vertical contrast as compared with purely horizontal contrast, localised vertical contrast also facilitates odour localisation, but only if the odour source is situated close to it. We implement a model of visuomotor control consisting of three parallel subsystems: an optomotor response stabilising the model fly's yaw orientation; a collision avoidance system to saccade away from looming obstacles; and a speed regulation system. This model reproduces many of the behaviours we observe in flies, including visually mediated 'rebound' turns following saccades. Using recordings of real odour plumes, we simulate the presence of an odorant in the arena, and investigate ways in which the olfactory input could modulate visuomotor control. We reproduce the experimental results by using the change in odour intensity to regulate the sensitivity of collision avoidance, resulting in visually mediated chemokinesis. Additionally, it is necessary to amplify the optomotor response whenever odour is present, increasing the model fly's tendency to steer towards features of the visual environment. We conclude that visual and olfactory responses of Drosophila are not independent, but that relatively simple interaction between these modalities can account for the observed visual dependence of odour source localisation.

Dynamics of optomotor responses in Drosophila to perturbations in optic flow

For a small flying insect, correcting unplanned course perturbations is essential for navigating through the world. Visual course control relies on estimating optic flow patterns which, in flies, are encoded by interneurons of the third optic ganglion. However, the rules that translate optic flow into flight motor commands remain poorly understood. Here, we measured the temporal dynamics of optomotor responses in tethered flies to optic flow fields about three cardinal axes. For each condition, we used white noise analysis to determine the optimal linear filters linking optic flow to the sum and difference of left and right wing beat amplitudes. The estimated filters indicate that flies react very quickly to perturbations of the motion field, with pure delays in the order of approximately 20 ms and time-to-peak of approximately 100 ms. By convolution the filters also predict responses to arbitrary stimulus sequences, accounting for over half the variance in 5 of our 6 stimulus types, demonstrating the approximate linearity of the system with respect to optic flow variables. In the remaining case of yaw optic flow we improved predictability by measuring individual flies, which also allowed us to analyze the variability of optomotor responses within a population. Finally, the linear filters at least partly explain the optomotor responses to superimposed and decomposed compound flow fields.

Visual stabilization dynamics are enhanced by standing flight velocity

A flying insect must travel to find food, mates and sites for oviposition, but for a small animal in a turbulent world this means dealing with frequent unplanned deviations from course. We measured a fly's sensory-motor impulse response to perturbations in optic flow. After an abrupt change in its apparent visual position, a fly generates a compensatory dynamical steering response in the opposite direction. The response dynamics, however, may be influenced by superimposed background velocity generated by the animal's flight direction. Here we show that constant forward velocity has no effect on the steering responses to orthogonal sideslip perturbations, whereas constant parallel sideslip substantially shortens the lags and relaxation times of the linear dynamical responses. This implies that for flies stabilizing in sideslip, the control effort is strongly affected by the direction of background motion.