Nonlinear integration of visual and haltere inputs in fly neck motor neurons

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.

The neuron mixer and its impact on human brain dynamics

A signal mixer facilitates rich computation, which has been the building block of modern telecommunication. This frequency mixing produces new signals at the sum and difference frequencies of input signals, enabling powerful operations such as heterodyning and multiplexing. Here, we report that a neuron is a signal mixer. We found through ex vivo and in vivo whole-cell measurements that neurons mix exogenous (controlled) and endogenous (spontaneous) subthreshold membrane potential oscillations, producing new oscillation frequencies, and that neural mixing originates in voltage-gated ion channels. Furthermore, we demonstrate that mixing is evident in human brain activity and is associated with cognitive functions. We found that the human electroencephalogram displays distinct clusters of local and inter-region mixing and that conversion of the salient posterior alpha-beta oscillations into gamma-band oscillations regulates visual attention. Signal mixing may enable individual neurons to sculpt the spectrum of neural circuit oscillations and utilize them for computational operations.

Asynchronous haltere input drives specific wing and head movements in Drosophila

Halteres are multifunctional mechanosensory organs unique to the true flies (Diptera). A set of reduced hindwings, the halteres beat at the same frequency as the lift-generating forewings and sense inertial forces via mechanosensory campaniform sensilla. Though haltere ablation makes stable flight impossible, the specific role of wing-synchronous input has not been established. Using small iron filings attached to the halteres of tethered flies and an alternating electromagnetic field, we experimentally decoupled the wings and halteres of flying Drosophila and observed the resulting changes in wingbeat amplitude and head orientation. We find that asynchronous haltere input results in fast amplitude changes in the wing (hitches), but does not appreciably move the head. In multi-modal experiments, we find that wing and gaze optomotor responses are disrupted differently by asynchronous input. These effects of wing-asynchronous haltere input suggest that specific sensory information is necessary for maintaining wing amplitude stability and adaptive gaze control.

Motor neurons generate pose-targeted movements via proprioceptive sculpting

Motor neurons are the final common pathway1 through which the brain controls movement of the body, forming the basic elements from which all movement is composed. Yet how a single motor neuron contributes to control during natural movement remains unclear. Here we anatomically and functionally characterize the individual roles of the motor neurons that control head movement in the fly, Drosophila melanogaster. Counterintuitively, we find that activity in a single motor neuron rotates the head in different directions, depending on the starting posture of the head, such that the head converges towards a pose determined by the identity of the stimulated motor neuron. A feedback model predicts that this convergent behaviour results from motor neuron drive interacting with proprioceptive feedback. We identify and genetically2 suppress a single class of proprioceptive neuron3 that changes the motor neuron-induced convergence as predicted by the feedback model. These data suggest a framework for how the brain controls movements: instead of directly generating movement in a given direction by activating a fixed set of motor neurons, the brain controls movements by adding bias to a continuing proprioceptive-motor loop.

Multiplicative processing in the modeling of cognitive activities in large neural networks

Explaining the foundation of cognitive abilities in the processing of information by neural systems has been in the beginnings of biophysics since McCulloch and Pitts pioneered work within the biophysics school of Chicago in the 1940s and the interdisciplinary cybernetists meetings in the 1950s, inseparable from the birth of computing and artificial intelligence. Since then, neural network models have traveled a long path, both in the biophysical and the computational disciplines. The biological, neurocomputational aspect reached its representational maturity with the Distributed Associative Memory models developed in the early 70 s. In this framework, the inclusion of signal-signal multiplication within neural network models was presented as a necessity to provide matrix associative memories with adaptive, context-sensitive associations, while greatly enhancing their computational capabilities. In this review, we show that several of the most successful neural network models use a form of multiplication of signals. We present several classical models that included such kind of multiplication and the computational reasons for the inclusion. We then turn to the different proposals about the possible biophysical implementation that underlies these computational capacities. We pinpoint the important ideas put forth by different theoretical models using a tensor product representation and show that these models endow memories with the context-dependent adaptive capabilities necessary to allow for evolutionary adaptation to changing and unpredictable environments. Finally, we show how the powerful abilities of contemporary computationally deep-learning models, inspired in neural networks, also depend on multiplications, and discuss some perspectives in view of the wide panorama unfolded. The computational relevance of multiplications calls for the development of new avenues of research that uncover the mechanisms our nervous system uses to achieve multiplication.

Development and evaluation of haltere-mimicking gyroscope for three-axis angular velocity sensing using a haltere-mimicking structure pair

This paper presents a three-axis biomimetic gyroscope, mimicking the haltere of Diptera. Diptera use a club-shaped mechanosensory organ called the haltere to get the three-axis angular velocity information, namely roll, pitch and yaw axes, for flight control. One pair of halteres is physically connected to the wings of Diptera that vibrate in antiphase to the flapping wings in ambient air. They sense the Coriolis force and relay angular velocity information to the Diptera. As an alternative to the conventional micro-electro-mechanical system gyroscopes which are widely used in robotics, many research groups have attempted to mimic the haltere. However, no previous study succeeded in measuring all three-axis components of angular velocity, due to various shortcomings. In this paper, we developed the first three-axis haltere-mimicking gyroscope. Two perpendicularly positioned haltere-mimicking structures that can vibrate at a 180° amplitude were mechanically integrated into a robot actuator. Two accelerometers, placed at the tip of each structure, were employed to measure the Coriolis force. The performance of the novel biomimetic gyroscope was measured in all rotational directions, using a motion capture system as the ground truth. One-axis input experiments were performed 240 times at different input magnitudes and directions, and the measured orientation error was less than ±2.0% in all experiments. In 80 three-axis input experiments, the orientation error was less than ±3.5%.

Impact of walking speed and motion adaptation on optokinetic nystagmus-like head movements in the blowfly Calliphora

The optokinetic nystagmus is a gaze-stabilizing mechanism reducing motion blur by rapid eye rotations against the direction of visual motion, followed by slower syndirectional eye movements minimizing retinal slip speed. Flies control their gaze through head turns controlled by neck motor neurons receiving input directly, or via descending neurons, from well-characterized directional-selective interneurons sensitive to visual wide-field motion. Locomotion increases the gain and speed sensitivity of these interneurons, while visual motion adaptation in walking animals has the opposite effects. To find out whether flies perform an optokinetic nystagmus, and how it may be affected by locomotion and visual motion adaptation, we recorded head movements of blowflies on a trackball stimulated by progressive and rotational visual motion. Flies flexibly responded to rotational stimuli with optokinetic nystagmus-like head movements, independent of their locomotor state. The temporal frequency tuning of these movements, though matching that of the upstream directional-selective interneurons, was only mildly modulated by walking speed or visual motion adaptation. Our results suggest flies flexibly control their gaze to compensate for rotational wide-field motion by a mechanism similar to an optokinetic nystagmus. Surprisingly, the mechanism is less state-dependent than the response properties of directional-selective interneurons providing input to the neck motor system.

Integration of visual and antennal mechanosensory feedback during head stabilization in hawkmoths

During flight maneuvers, insects exhibit compensatory head movements which are essential for stabilizing the visual field on their retina, reducing motion blur, and supporting visual self-motion estimation. In Diptera, such head movements are mediated via visual feedback from their compound eyes that detect retinal slip, as well as rapid mechanosensory feedback from their halteres – the modified hindwings that sense the angular rates of body rotations. Because non-Dipteran insects lack halteres, it is not known if mechanosensory feedback about body rotations plays any role in their head stabilization response. Diverse non-Dipteran insects are known to rely on visual and antennal mechanosensory feedback for flight control. In hawkmoths, for instance, reduction of antennal mechanosensory feedback severely compromises their ability to control flight. Similarly, when the head movements of freely flying moths are restricted, their flight ability is also severely impaired. The role of compensatory head movements as well as multimodal feedback in insect flight raises an interesting question: in insects that lack halteres, what sensory cues are required for head stabilization? Here, we show that in the nocturnal hawkmoth Daphnis nerii, compensatory head movements are mediated by combined visual and antennal mechanosensory feedback. We subjected tethered moths to open-loop body roll rotations under different lighting conditions, and measured their ability to maintain head angle in the presence or absence of antennal mechanosensory feedback. Our study suggests that head stabilization in moths is mediated primarily by visual feedback during roll movements at lower frequencies, whereas antennal mechanosensory feedback is required when roll occurs at higher frequency. These findings are consistent with the hypothesis that control of head angle results from a multimodal feedback loop that integrates both visual and antennal mechanosensory feedback, albeit at different latencies. At adequate light levels, visual feedback is sufficient for head stabilization primarily at low frequencies of body roll. However, under dark conditions, antennal mechanosensory feedback is essential for the control of head movements at high frequencies of body roll.

The two-body problem: Proprioception and motor control across the metamorphic divide

Like a rocket being propelled into space, evolution has engineered flies to launch into adulthood via multiple stages. Flies develop and deploy two distinct bodies, linked by the transformative process of metamorphosis. The fly larva is a soft hydraulic tube that can crawl to find food and avoid predators. The adult fly has a stiff exoskeleton with articulated limbs that enable long-distance navigation and rich social interactions. Because the larval and adult forms are so distinct in structure, they require distinct strategies for sensing and moving the body. The metamorphic divide thus presents an opportunity for comparative analysis of neural circuits. Here, we review recent progress toward understanding the neural mechanisms of proprioception and motor control in larval and adult Drosophila. We highlight commonalities that point toward general principles of sensorimotor control and differences that may reflect unique constraints imposed by biomechanics. Finally, we discuss emerging opportunities for comparative analysis of neural circuit architecture in the fly and other animal species.

A biophysical account of multiplication by a single neuron

Nonlinear, multiplication-like operations carried out by individual nerve cells greatly enhance the computational power of a neural system1-3, but our understanding of their biophysical implementation is scant. Here we pursue this problem in the Drosophila melanogaster ON motion vision circuit4,5, in which we record the membrane potentials of direction-selective T4 neurons and of their columnar input elements6,7 in response to visual and pharmacological stimuli in vivo. Our electrophysiological measurements and conductance-based simulations provide evidence for a passive supralinear interaction between two distinct types of synapse on T4 dendrites. We show that this multiplication-like nonlinearity arises from the coincidence of cholinergic excitation and release from glutamatergic inhibition. The latter depends on the expression of the glutamate-gated chloride channel GluClα8,9 in T4 neurons, which sharpens the directional tuning of the cells and shapes the optomotor behaviour of the animals. Interacting pairs of shunting inhibitory and excitatory synapses have long been postulated as an analogue approximation of a multiplication, which is integral to theories of motion detection10,11, sound localization12 and sensorimotor control13.

The impulse response of optic flow-sensitive descending neurons to roll m-sequences

When animals move through the world, their own movements generate widefield optic flow across their eyes. In insects, such widefield motion is encoded by optic lobe neurons. These lobula plate tangential cells (LPTCs) synapse with optic flow-sensitive descending neurons, which in turn project to areas that control neck, wing and leg movements. As the descending neurons play a role in sensorimotor transformation, it is important to understand their spatio-temporal response properties. Recent work shows that a relatively fast and efficient way to quantify such response properties is to use m-sequences or other white noise techniques. Therefore, here we used m-sequences to quantify the impulse responses of optic flow-sensitive descending neurons in male Eristalis tenax hoverflies. We focused on roll impulse responses as hoverflies perform exquisite head roll stabilizing reflexes, and the descending neurons respond particularly well to roll. We found that the roll impulse responses were fast, peaking after 16.5–18.0 ms. This is similar to the impulse response time to peak (18.3 ms) to widefield horizontal motion recorded in hoverfly LPTCs. We found that the roll impulse response amplitude scaled with the size of the stimulus impulse, and that its shape could be affected by the addition of constant velocity roll or lift. For example, the roll impulse response became faster and stronger with the addition of excitatory stimuli, and vice versa. We also found that the roll impulse response had a long return to baseline, which was significantly and substantially reduced by the addition of either roll or lift.

Summary: The impulse response of hoverfly optic flow-sensitive descending neurons to roll m-sequences reaches its time to peak within 20 ms and slowly returns to baseline over the next 100 ms.

Fast tuning of posture control by visual feedback underlies gaze stabilization in walking Drosophila

Locomotion requires a balance between mechanical stability and movement flexibility to achieve behavioral goals despite noisy neuromuscular systems, but rarely is it considered how this balance is orchestrated. We combined virtual reality tools with quantitative analysis of behavior to examine how Drosophila uses self-generated visual information (reafferent visual feedback) to control gaze during exploratory walking. We found that flies execute distinct motor programs coordinated across the body to maximize gaze stability. However, the presence of inherent variability in leg placement relative to the body jeopardizes fine control of gaze due to posture-stabilizing adjustments that lead to unintended changes in course direction. Surprisingly, whereas visual feedback is dispensable for head-body coordination, we found that self-generated visual signals tune postural reflexes to rapidly prevent turns rather than to promote compensatory rotations, a long-standing idea for visually guided course control. Together, these findings support a model in which visual feedback orchestrates the interplay between posture and gaze stability in a manner that is both goal dependent and motor-context specific.

Multimodal integration across spatiotemporal scales to guide invertebrate locomotion

Locomotion is a hallmark of organisms that has enabled adaptive radiation to an extraordinarily diverse class of ecological niches, and allows animals to move across vast distances. Sampling from multiple sensory modalities enables animals to acquire rich information to guide locomotion. Locomotion without sensory feedback is haphazard, therefore sensory and motor systems have evolved complex interactions to generate adaptive behavior. Notably, sensory-guided locomotion acts over broad spatial and temporal scales to permit goal-seeking behavior, whether to localize food by tracking an attractive odor plume or to search for a potential mate. How does the brain integrate multimodal stimuli over different temporal and spatial scales to effectively control behavior? In this review, we classify locomotion into three ordinally ranked hierarchical layers that act over distinct spatiotemporal scales: stabilization, motor primitives, and higher-order tasks, respectively. We discuss how these layers present unique challenges and opportunities for sensorimotor integration. We focus on recent advances in invertebrate locomotion due to their accessible neural and mechanical signals from the whole brain, limbs and sensors. Throughout, we emphasize neural-level description of computations for multimodal integration in genetic model systems, including the fruit fly, Drosophila melanogaster, and the yellow fever mosquito, Aedes aegypti. We identify that summation (e.g. gating) and weighting-which are inherent computations of spiking neurons-underlie multimodal integration across spatial and temporal scales, therefore suggesting collective strategies to guide locomotion.

Haltere and visual inputs sum linearly to predict wing (but not gaze) motor output in tethered flying Drosophila

In the true flies (Diptera), the hind wings have evolved into specialized mechanosensory organs known as halteres, which are sensitive to gyroscopic and other inertial forces. Together with the fly's visual system, the halteres direct head and wing movements through a suite of equilibrium reflexes that are crucial to the fly's ability to maintain stable flight. As in other animals (including humans), this presents challenges to the nervous system as equilibrium reflexes driven by the inertial sensory system must be integrated with those driven by the visual system in order to control an overlapping pool of motor outputs shared between the two of them. Here, we introduce an experimental paradigm for reproducibly altering haltere stroke kinematics and use it to quantify multisensory integration of wing and gaze equilibrium reflexes. We show that multisensory wing-steering responses reflect a linear superposition of haltere-driven and visually driven responses, but that multisensory gaze responses are not well predicted by this framework. These models, based on populations, extend also to the responses of individual flies.

Timing precision in fly flight control: integrating mechanosensory input with muscle physiology

Animals rapidly collect and act on incoming information to navigate complex environments, making the precise timing of sensory feedback critical in the context of neural circuit function. Moreover, the timing of sensory input determines the biomechanical properties of muscles that undergo cyclic length changes, as during locomotion. Both of these issues come to a head in the case of flying insects, as these animals execute steering manoeuvres at timescales approaching the upper limits of performance for neuromechanical systems. Among insects, flies stand out as especially adept given their ability to execute manoeuvres that require sub-millisecond control of steering muscles. Although vision is critical, here I review the role of rapid, wingbeat-synchronous mechanosensory feedback from the wings and structures unique to flies, the halteres. The visual system and descending interneurons of the brain employ a spike rate coding scheme to relay commands to the wing steering system. By contrast, mechanosensory feedback operates at faster timescales and in the language of motor neurons, i.e. spike timing, allowing wing and haltere input to dynamically structure the output of the wing steering system. Although the halteres have been long known to provide essential input to the wing steering system as gyroscopic sensors, recent evidence suggests that the feedback from these vestigial hindwings is under active control. Thus, flies may accomplish manoeuvres through a conserved hindwing circuit, regulating the firing phase-and thus, the mechanical power output-of the wing steering muscles.

Significance of the Asymmetry of the Haltere: A Microscale Vibratory Gyroscope

Nature has evolved a beautiful design for small-scale vibratory gyroscopes in the form of halteres located in the metathorax region of the dipteran flies that detect body rotations based on the Coriolis principle. The specific design of the haltere is in contrast to the existing MEMS vibratory gyroscope, where the elastic beams supporting the proof mass are typically designed with symmetric cross-sections so that there is a mode matching between the actuation and sensing vibrations. The mode matching provides high sensitivity and low bandwidth. Hence, the objective of the manuscript is to understand the mechanical significance of the haltere's asymmetry. In this study, the distributed Coriolis force and the corresponding bending stress by incorporating the actual mass variations along the haltere length are estimated. In addition, it is hypothesied that sensilla sense the rate of rotation based on the differential strain (difference between the final strain (strain due to the inertial and Coriolis forces) and the reference strain (strain due to inertial force)). This differential strain always occurs either on the dorsal or ventral surface of the haltere and at a distance away from the base, where the campaniform sensilla are located. This study brings out one specific feature—the asymmetric geometry of the haltere structure—that is not found in current vibratory gyroscope designs. This finding will inspire new designs of MEMS gyroscopes that have elegance and simplicity of the haltere along with the desired performance.

How do hoverflies use their righting reflex?

When taking off from a sloping surface, flies have to reorient themselves dorsoventrally and stabilize their body by actively controlling their flapping wings. We have observed that righting is achieved solely by performing a rolling manoeuvre. How flies manage to do this has not yet been elucidated. It was observed here for the first time that hoverfly reorientation is entirely achieved within 6 wingbeats (48.8 ms) at angular roll velocities of up to 10×103 deg s-1 and that the onset of their head rotation consistently follows that of their body rotation after a time lag of 16 ms. The insects' body roll was found to be triggered by the asymmetric wing stroke amplitude, as expected. The righting process starts immediately with the first wingbeat and seems unlikely to depend on visual feedback. A dynamic model for the fly's righting reflex is presented, which accounts for the head/body movements and the time lag recorded in these experiments. This model consists of a closed-loop control of the body roll, combined with a feedforward control of the head/body angle. During the righting manoeuvre, a strong coupling seems to exist between the activation of the halteres (which measure the body's angular speed) and the gaze stabilization reflex. These findings again confirm the fundamental role played by the halteres in both body and head stabilization processes.

Coriolis and centrifugal forces drive haltere deformations and influence spike timing

The halteres of flies are mechanosensory organs that serve a crucial role in the control of agile flight, providing sensory input for rapid course corrections to perturbations. Derived from hind wings, halteres are actively flapped and are thus subject to a variety of inertial forces as the fly undergoes complex flight trajectories. Previous analyses of halteres modelled them as a point mass, showing that Coriolis forces lead to subtle deflections orthogonal to the plane of flapping. By design, these models could not consider the effects of force gradients associated with a mass distribution, nor could they reveal three-dimensional spatio-temporal patterns of strain that result from those forces. In addition, diversity in the geometry of halteres, such as shape and asymmetries, could not be simply modelled with a point mass on a massless rod. To study the effects of mass distributions and asymmetries, we examine the haltere subject to both flapping and body rotations using three-dimensional finite-element simulations. We focus on a set of simplified geometries, in which we vary the stalk and bulb shape. We find that haltere mass distribution gives rise to two unreported deformation modes: (i) halteres twist with a magnitude that strongly depends on stalk and bulb geometry and (ii) halteres with an asymmetric mass distribution experience out-of-plane bending due to centrifugal forces, independent of body rotation. Since local strains at the base of the haltere drive deformations of mechanosensory neurons, we combined measured neural encoding mechanisms with our structural analyses to predict the spatial and temporal patterns of neural activity. This activity depends on both the flapping and rotation dynamics, and we show how the timing of neural activity is a viable mechanism for rotation-rate encoding. Our results provide new insights in haltere dynamics and show the viability for timing-based encoding of fly body rotations by halteres.

Sensory processing by motoneurons: a numerical model for low-level flight control in flies

Rhythmic locomotor behaviour in animals requires exact timing of muscle activation within the locomotor cycle. In rapidly oscillating motor systems, conventional control strategies may be affected by neural delays, making these strategies inappropriate for precise timing control. In flies, wing control thus requires sensory processing within the peripheral nervous system, circumventing the central brain. The underlying mechanism, with which flies integrate graded depolarization of visual interneurons and spiking proprioceptive feedback for precise muscle activation, is under debate. Based on physiological parameters, we developed a numerical model of spike initiation in flight muscles of a blowfly. The simulated Hodgkin–Huxley neuron reproduces multiple experimental findings and explains on the cellular level how vision might control wing kinematics. Sensory processing by single motoneurons appears to be sufficient for control of muscle power during flight in flies and potentially other flying insects, reducing computational load on the central brain during body posture reflexes and manoeuvring flight.

Flies Regulate Wing Motion via Active Control of a Dual-Function Gyroscope

Flies execute their remarkable aerial maneuvers using a set of wing steering muscles, which are activated at specific phases of the stroke cycle [1-3]. The activation phase of these muscles-which determines their biomechanical output [4-6]-arises via feedback from mechanoreceptors at the base of the wings and structures unique to flies called halteres [7-9]. 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 [10-15]. 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.

A biohybrid fly-robot interface system that performs active collision avoidance

We have designed a bio-hybrid fly-robot interface (FRI) to study sensorimotor control in insects. The FRI consists of a miniaturized recording platform mounted on a two-wheeled robot and is controlled by the neuronal spiking activity of an identified visual interneuron, the blowfly H1-cell. For a given turning radius of the robot, we found a proportional relationship between the spike rate of the H1-cell and the relative distance of the FRI from the patterned wall of an experimental arena. Under closed-loop conditions during oscillatory forward movements biased towards the wall, collision avoidance manoeuvres were triggered whenever the H1-cell spike rate exceeded a certain threshold value. We also investigated the FRI behaviour in corners of the arena. The ultimate goal is to enable autonomous and energy-efficient manoeuvrings of the FRI within arbitrary visual environments.

State-dependent decoupling of sensory and motor circuits underlies behavioral flexibility in Drosophila

An approaching predator and self-motion towards an object can generate similar looming patterns on the retina, but these situations demand different rapid responses. How central circuits flexibly process visual cues to activate appropriate, fast motor pathways remains unclear. Here, we identify two descending neuron (DN) types that control landing and contribute to visuomotor flexibility in Drosophila. For each, silencing impairs visually-evoked landing, activation drives landing, and spike rate determines leg extension amplitude. Critically, visual responses of both DNs are severely attenuated during non-flight periods, effectively decoupling visual stimuli from the landing motor pathway when landing is inappropriate. The flight-dependence mechanism differs between DN types. Octopamine exposure mimics flight effects in one, whereas the other likely receives neuronal feedback from flight motor circuits. Thus, this sensorimotor flexibility arises from distinct mechanisms for gating action-specific descending pathways, such that sensory and motor networks are coupled or decoupled according to the behavioral state.

Role of the light source position in freely falling hoverflies' stabilization performances

The stabilization of plummeting hoverflies was filmed and analysed in terms of their wingbeat initiation times as well as the crash and stabilization rates. The flies experienced near-weightlessness for a period of time that depended on their ability to counteract the free fall by triggering their wingbeats. In this paradigm, hoverflies' flight stabilization strategies were investigated here for the first time under two different positions of the light source (overhead and bottom lighting). The crash rates were higher in bottom lighting conditions than with top lighting. In addition, adding a texture to the walls reduced the crash rates only in the overhead lighting condition. The position of the lighting also significantly affected both the stabilization rates and the time taken by the flies to stabilize, which decreased and increased under bottom lighting conditions, respectively, whereas textured walls increased the stabilization rates under both lighting conditions. These results support the idea that flies may mainly base their flight control strategy on visual cues and particularly that the light distribution in the visual field may provide reliable, efficient cues for estimating their orientation with respect to an allocentric reference frame. In addition, the finding that the hoverflies' optic flow-based motion detection ability is affected by the position of the light source in their visual field suggests the occurrence of interactions between movement perception and this visual vertical perception process.

Representation of Haltere Oscillations and Integration with Visual Inputs in the Fly Central Complex

The reduced hindwings of flies, known as halteres, are specialized mechanosensory organs that detect body rotations during flight. Primary afferents of the haltere encode its oscillation frequency linearly over a wide bandwidth and with precise phase-dependent spiking. However, it is not currently known whether information from haltere primary afferent neurons is sent to higher brain centers where sensory information about body position could be used in decision making, or whether precise spike timing is useful beyond the peripheral circuits that drive wing movements. We show that in cells in the central brain, the timing and rates of neural spiking can be modulated by sensory input from experimental haltere movements (driven by a servomotor). Using multichannel extracellular recording in restrained flesh flies (Sarcophaga bullata of both sexes), we examined responses of central complex cells to a range of haltere oscillation frequencies alone, and in combination with visual motion speeds and directions. Haltere-responsive units fell into multiple response classes, including those responding to any haltere motion and others with firing rates linearly related to the haltere frequency. Cells with multisensory responses showed higher firing rates than the sum of the unisensory responses at higher haltere frequencies. They also maintained visual properties, such as directional selectivity, while increasing response gain nonlinearly with haltere frequency. Although haltere inputs have been described extensively in the context of rapid locomotion control, we find haltere sensory information in a brain region known to be involved in slower, higher-order behaviors, such as navigation.SIGNIFICANCE STATEMENT Many animals use vision for navigation; however, these cues must be interpreted in the context of the body's position. In mammalian brains, hippocampal cells combine visual and vestibular information to encode head direction. A region of the arthropod brain, known as the central complex (CX), similarly encodes heading information, but it is unknown whether proprioceptive information is integrated here as well. We show that CX neurons respond to input from halteres, specialized proprioceptors in flies that detect body rotations. These neurons also respond to visual input, providing one of the few examples of multiple sensory modalities represented in individual CX cells. Haltere stimulation modifies neural responses to visual signals, providing a mechanism for integrating vision with proprioception.

Inertial Sensing and Encoding of Self-Motion: Structural and Functional Similarities across Metazoan Taxa

To properly orient and navigate, moving animals must obtain information about the position and motion of their bodies. Animals detect inertial signals resulting from body accelerations and rotations using a variety of sensory systems. In this review, we briefly summarize current knowledge on inertial sensing across widely disparate animal taxa with an emphasis on neuronal coding and sensory transduction. We outline systems built around mechanosensory hair cells, including the chordate vestibular complex and the statocysts seen in many marine invertebrates. We next compare these to schemes employed by flying insects for managing inherently unstable aspects of flapping flight, built around comparable mechanosensory cells but taking unique advantage of the physics of rotating systems to facilitate motion encoding. Finally, we highlight fundamental similarities across taxa with respect to the partnering of inertial senses with visual senses and conclude with a discussion of the functional utility of maintaining a multiplicity of encoding schemes for self-motion information.

Integration of Small- and Wide-Field Visual Features in Target-Selective Descending Neurons of both Predatory and Nonpredatory Dipterans

For many animals, target motion carries high ecological significance as this may be generated by a predator, prey, or potential mate. Indeed, animals whose survival depends on early target detection are often equipped with a sharply tuned visual system, yielding robust performance in challenging conditions. For example, many fast-flying insects use visual cues for identifying targets, such as prey (e.g., predatory dragonflies and robberflies) or conspecifics (e.g., nonpredatory hoverflies), and can often do so against self-generated background optic flow. Supporting these behaviors, the optic lobes of insects that pursue targets harbor neurons that respond robustly to the motion of small moving objects, even when displayed against syn-directional background clutter. However, in diptera, the encoding of target information by the descending neurons, which are more directly involved in generating the behavioral output, has received less attention. We characterized target-selective neurons by recording in the ventral nerve cord of male and female predatory Holcocephala fusca robberflies and of male nonpredatory Eristalis tenax hoverflies. We show that both species have dipteran target-selective descending neurons that only respond to target motion if the background is stationary or moving slowly, moves in the opposite direction, or has un-naturalistic spatial characteristics. The response to the target is suppressed when background and target move at similar velocities, which is strikingly different to the response of target neurons in the optic lobes. As the neurons we recorded from are premotor, our findings affect our interpretation of the neurophysiology underlying target-tracking behaviors.

SIGNIFICANCE STATEMENT Many animals use sensory cues to detect moving targets that may represent predators, prey, or conspecifics. For example, birds of prey show superb sensitivity to the motion of small prey, and intercept these at high speeds. In a similar manner, predatory insects visually track moving prey, often against cluttered backgrounds. Accompanying this behavior, the brains of insects that pursue targets contain neurons that respond exclusively to target motion. We here show that dipteran insects also have target-selective descending neurons in the part of their nervous system that corresponds to the vertebrate spinal cord. Surprisingly, and in contrast to the neurons in the brain, these premotor neurons are inhibited by background patterns moving in the same direction as the target.

Single mechanosensory neurons encode lateral displacements using precise spike timing and thresholds

During locomotion, animals rely on multiple sensory modalities to maintain stability. External cues may guide behaviour, but they must be interpreted in the context of the animal's own body movements. Mechanosensory cues that can resolve dynamic internal and environmental conditions, like those from vertebrate vestibular systems or other proprioceptors, are essential for guided movement. How do afferent proprioceptor neurons transform movement into a neural code? In flies, modified hindwings known as halteres detect forces produced by body rotations and are essential for flight. However, the mechanisms by which haltere neurons transform forces resulting from three-dimensional body rotations into patterns of neural spikes are unknown. We use intracellular electrodes to record from haltere primary afferent neurons during a range of haltere motions. We find that spike timing activity of individual neurons changes with displacement and propose a mechanism by which single neurons can encode three-dimensional haltere movements during flight.

Neural-inspired sensors enable sparse, efficient classification of spatiotemporal data

Winged insects perform remarkable aerial feats in uncertain, complex fluid environments. This ability is enabled by sensation of mechanical forces to inform rapid corrections in body orientation. Curiously, mechanoreceptor neurons do not faithfully report forces; instead, they are activated by specific time histories of forcing. We find that, far from being a bug, neural encoding by biological sensors is a feature that acts as built-in temporal filtering superbly matched to detect body rotation. Indeed, this encoding further enables surprisingly efficient detection using only a small handful of neurons at key locations. Nature suggests smart data as an alternative strategy to big data, and neural-inspired sensors establish a paradigm in hyperefficient sensing of complex systems.

Sparse sensor placement is a central challenge in the efficient characterization of complex systems when the cost of acquiring and processing data is high. Leading sparse sensing methods typically exploit either spatial or temporal correlations, but rarely both. This work introduces a sparse sensor optimization that is designed to leverage the rich spatiotemporal coherence exhibited by many systems. Our approach is inspired by the remarkable performance of flying insects, which use a few embedded strain-sensitive neurons to achieve rapid and robust flight control despite large gust disturbances. Specifically, we identify neural-inspired sensors at a few key locations on a flapping wing that are able to detect body rotation. This task is particularly challenging as the rotational twisting mode is three orders of magnitude smaller than the flapping modes. We show that nonlinear filtering in time, built to mimic strain-sensitive neurons, is essential to detect rotation, whereas instantaneous measurements fail. Optimized sparse sensor placement results in efficient classification with approximately 10 sensors, achieving the same accuracy and noise robustness as full measurements consisting of hundreds of sensors. Sparse sensing with neural-inspired encoding establishes an alternative paradigm in hyperefficient, embodied sensing of spatiotemporal data and sheds light on principles of biological sensing for agile flight control.

Modeling visual-based pitch, lift and speed control strategies in hoverflies

To avoid crashing onto the floor, a free falling fly needs to trigger its wingbeats quickly and control the orientation of its thrust accurately and swiftly to stabilize its pitch and hence its speed. Behavioural data have suggested that the vertical optic flow produced by the fall and crossing the visual field plays a key role in this anti-crash response. Free fall behavior analyses have also suggested that flying insect may not rely on graviception to stabilize their flight. Based on these two assumptions, we have developed a model which accounts for hoverflies´ position and pitch orientation recorded in 3D with a fast stereo camera during experimental free falls. Our dynamic model shows that optic flow-based control combined with closed-loop control of the pitch suffice to stabilize the flight properly. In addition, our model sheds a new light on the visual-based feedback control of fly´s pitch, lift and thrust. Since graviceptive cues are possibly not used by flying insects, the use of a vertical reference to control the pitch is discussed, based on the results obtained on a complete dynamic model of a virtual fly falling in a textured corridor. This model would provide a useful tool for understanding more clearly how insects may or not estimate their absolute attitude.

On the basis of vision-based feedback control of optic flow occurring during insects’ flight, we developed a dynamic model that accounts for the pitch orientation and speed in plummeting flies. We compared the hoverflies’ responses with our model and showed that an optic-flow based control strategy can be used to correct the initial pitch misorientation caused by the free fall situation. To complete the model, we combined the closed-loop control of the vertical optic flow with an additional feedback control loop based on the value of the absolute pitch orientation. The need for this measurement to stabilize the pitch orientation raises the question as whether this is also the case in dipterans. After ruling out the possibility that insects may use gravity acceleration cues to control their flight, for which no experimental evidence has been found so far, we discussed the three main sensory processes possibly involved in in their ability to control their attitude. Our model provides a useful tool for studying the various sensory processes possibly involved in dipterans’ flight stabilization abilities as well as the interactions between these processes.

Evolution of Biological Image Stabilization

The use of vision to coordinate behavior requires an efficient control design that stabilizes the world on the retina or directs the gaze towards salient features in the surroundings. With a level gaze, visual processing tasks are simplified and behaviorally relevant features from the visual environment can be extracted. No matter how simple or sophisticated the eye design, mechanisms have evolved across phyla to stabilize gaze. In this review, we describe functional similarities in eyes and gaze stabilization reflexes, emphasizing their fundamental role in transforming sensory information into motor commands that support postural and locomotor control. We then focus on gaze stabilization design in flying insects and detail some of the underlying principles. Systems analysis reveals that gaze stabilization often involves several sensory modalities, including vision itself, and makes use of feedback as well as feedforward signals. Independent of phylogenetic distance, the physical interaction between an animal and its natural environment - its available senses and how it moves - appears to shape the adaptation of all aspects of gaze stabilization.

Haltere morphology and campaniform sensilla arrangement across Diptera

One of the primary specializations of true flies (order Diptera) is the modification of the hind wings into club-shaped halteres. Halteres are complex mechanosensory structures that provide sensory feedback essential for stable flight control via an array of campaniform sensilla at the haltere base. The morphology of these sensilla has previously been described in a small number of dipteran species, but little is known about how they vary across fly taxa. Using a synoptic set of specimens representing 42 families from all of the major infraorders of Diptera, we used scanning electron microscopy to map the gross and fine structures of halteres, including sensillum shape and arrangement. We found that several features of haltere morphology correspond with dipteran phylogeny: Schizophora generally have smaller halteres with stereotyped and highly organized sensilla compared to nematoceran flies. We also found a previously undocumented high variation of haltere sensillum shape in nematoceran dipterans, as well as the absence of a dorsal sensillum field in multiple families. Overall, variation in haltere sensillar morphology across the dipteran phylogeny provides insight into the evolution of a highly specialized proprioceptive organ and a basis for future studies on haltere sensory function.

Cross-modal influence of mechanosensory input on gaze responses to visual motion in Drosophila

Animals typically combine inertial and visual information to stabilize their gaze against confounding self-generated visual motion, and to maintain a level gaze when the body is perturbed by external forces. In vertebrates, an inner ear vestibular system provides information about body rotations and accelerations, but gaze stabilization is less understood in insects, which lack a vestibular organ. In flies, the halteres, reduced hindwings imbued with hundreds of mechanosensory cells, sense inertial forces and provide input to neck motoneurons that control gaze. These neck motoneurons also receive input from the visual system. Head movement responses to visual motion and physical rotations of the body have been measured independently, but how inertial information might influence gaze responses to visual motion has not been fully explored. We measured the head movement responses to visual motion in intact and haltere-ablated tethered flies to explore the haltere's role in modulating visually-guided head movements in the absence of rotation. We note that visually-guided head movements occur only during flight. Although halteres are not necessary for head movements, the amplitude of the response is smaller in haltereless flies at higher speeds of visual motion. This modulation occurred in the absence of rotational body movements, demonstrating that the inertial forces associated with straight tethered flight are important for gaze-control behavior. The cross-modal influence of halteres on the fly's responses to fast visual motion indicates that the haltere's role in gaze stabilization extends beyond its canonical function as a sensor of angular rotations of the thorax.

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.

Integration of parallel mechanosensory and visual pathways resolved through sensory conflict

The acquisition of information from parallel sensory pathways is a hallmark of coordinated movement in animals. Insect flight, for example, relies on both mechanosensory and visual pathways. Our challenge is to disentangle the relative contribution of each modality to the control of behavior. Toward this end, we show an experimental and analytical framework leveraging sensory conflict, a means for independently exciting and modeling separate sensory pathways within a multisensory behavior. As a model, we examine the hovering flower-feeding behavior in the hawkmoth Manduca sexta In the laboratory, moths feed from a robotically actuated two-part artificial flower that allows independent presentation of visual and mechanosensory cues. Freely flying moths track lateral flower motion stimuli in an assay spanning both coupled motion, in which visual and mechanosensory cues follow the same motion trajectory, and sensory conflict, in which the two sensory modalities encode different motion stimuli. Applying a frequency-domain system identification analysis, we find that the tracking behavior is, in fact, multisensory and arises from a linear summation of visual and mechanosensory pathways. The response dynamics are highly preserved across individuals, providing a model for predicting the response to novel multimodal stimuli. Surprisingly, we find that each pathway in and of itself is sufficient for driving tracking behavior. When multiple sensory pathways elicit strong behavioral responses, this parallel architecture furnishes robustness via redundancy.

Dipteran Halteres: Perspectives on Function and Integration for a Unique Sensory Organ

The halteres of dipteran insects (true flies) are essential mechanosensory organs for flight. These are modified hindwings with several arrays of sensory cells at their base, and they are one of the characteristic features of flies. Mechanosensory information from the halteres is sent with low latency to wing-steering and head movement motoneurons, allowing direct control of body position and gaze. Analyses of the structure and dynamics of halteres indicate that they experience very small aerodynamic forces but significant inertial forces, including Coriolis forces associated with body rotations. The sensory cells at the base of the haltere detect these forces and allow the fly to correct for perturbations during flight, but new evidence suggests that this may not be their only role. This review will examine our current understanding of how these organs move, encode forces, and transmit information about these forces to the nervous system to guide behavior.

Proprioceptive feedback determines visuomotor gain in Drosophila

Multisensory integration is a prerequisite for effective locomotor control in most animals. Especially, the impressive aerial performance of insects relies on rapid and precise integration of multiple sensory modalities that provide feedback on different time scales. In flies, continuous visual signalling from the compound eyes is fused with phasic proprioceptive feedback to ensure precise neural activation of wing steering muscles (WSM) within narrow temporal phase bands of the stroke cycle. This phase-locked activation relies on mechanoreceptors distributed over wings and gyroscopic halteres. Here we investigate visual steering performance of tethered flying fruit flies with reduced haltere and wing feedback signalling. Using a flight simulator, we evaluated visual object fixation behaviour, optomotor altitude control and saccadic escape reflexes. The behavioural assays show an antagonistic effect of wing and haltere signalling on visuomotor gain during flight. Compared with controls, suppression of haltere feedback attenuates while suppression of wing feedback enhances the animal's wing steering range. Our results suggest that the generation of motor commands owing to visual perception is dynamically controlled by proprioception. We outline a potential physiological mechanism based on the biomechanical properties of WSM and sensory integration processes at the level of motoneurons. Collectively, the findings contribute to our general understanding how moving animals integrate sensory information with dynamically changing temporal structure.

Behavioural evidence for a visual and proprioceptive control of head roll in hoverflies (Episyrphus balteatus)

The ability of hoverflies to control their head orientation with respect to their body contributes importantly to their agility and their autonomous navigation abilities. Many tasks performed by this insect during flight, especially while hovering, involve a head stabilization reflex. This reflex, which is mediated by multisensory channels, prevents the visual processing from being disturbed by motion blur and maintains a consistent perception of the visual environment. The so-called dorsal light response (DLR) is another head control reflex, which makes insects sensitive to the brightest part of the visual field. In this study, we experimentally validate and quantify the control loop driving the head roll with respect to the horizon in hoverflies. The new approach developed here consisted of using an upside-down horizon in a body roll paradigm. In this unusual configuration, tethered flying hoverflies surprisingly no longer use purely vision-based control for head stabilization. These results shed new light on the role of neck proprioceptor organs in head and body stabilization with respect to the horizon. Based on the responses obtained with male and female hoverflies, an improved model was then developed in which the output signals delivered by the neck proprioceptor organs are combined with the visual error in the estimated position of the body roll. An internal estimation of the body roll angle with respect to the horizon might explain the extremely accurate flight performances achieved by some hovering insects.

Axon terminals from the nucleus isthmi pars parvocellularis control the ascending retinotectofugal output through direct synaptic contact with tectal ganglion cell dendrites

The optic tectum in birds and its homologue the superior colliculus in mammals both send major bilateral, nontopographic projections to the nucleus rotundus and caudal pulvinar, respectively. These projections originate from widefield tectal ganglion cells (TGCs) located in layer 13 in the avian tectum and in the lower superficial layers in the mammalian colliculus. The TGCs characteristically have monostratified arrays of brush-like dendritic terminations and respond mostly to bidimensional motion or looming features. In birds, this TGC-mediated tectofugal output is controlled by feedback signals from the nucleus isthmi pars parvocellularis (Ipc). The Ipc neurons display topographically organized axons that densely ramify in restricted columnar terminal fields overlapping various neural elements that could mediate this tectofugal control, including the retinal terminals and the TGC dendrites themselves. Whether the Ipc axons make synaptic contact with these or other tectal neural elements remains undetermined. We double labeled Ipc axons and their presumptive postsynaptic targets in the tectum of chickens (Gallus gallus) with neural tracers and performed an ultrastructural analysis. We found that the Ipc terminal boutons form glomerulus-like structures in the superficial and intermediate tectal layers, establishing asymmetric synapses with several dendritic profiles. In these glomeruli, at least two of the postsynaptic dendrites originated from TGCs. We also found synaptic contacts between retinal terminals and TGC dendrites. These findings suggest that, in birds, Ipc axons control the ascending tectal outflow of retinal signals through direct synaptic contacts with the TGCs.

Haltere mechanosensory influence on tethered flight behavior in Drosophila

In flies, mechanosensory information from modified hindwings known as halteres is combined with visual information for wing-steering behavior. Haltere input is necessary for free flight, making it difficult to study the effects of haltere ablation under natural flight conditions. We thus used tethered Drosophila melanogaster flies to examine the relationship between halteres and the visual system, using wide-field motion or moving figures as visual stimuli. Haltere input was altered by surgically decreasing its mass, or by removing it entirely. Haltere removal does not affect the flies' ability to flap or steer their wings, but it does increase the temporal frequency at which they modify their wingbeat amplitude. Reducing the haltere mass decreases the optomotor reflex response to wide-field motion, and removing the haltere entirely does not further decrease the response. Decreasing the mass does not attenuate the response to figure motion, but removing the entire haltere does attenuate the response. When flies are allowed to control a visual stimulus in closed-loop conditions, haltereless flies fixate figures with the same acuity as intact flies, but cannot stabilize a wide-field stimulus as accurately as intact flies can. These manipulations suggest that the haltere mass is influential in wide-field stabilization, but less so in figure tracking. In both figure and wide-field experiments, we observe responses to visual motion with and without halteres, indicating that during tethered flight, intact halteres are not strictly necessary for visually guided wing-steering responses. However, the haltere feedback loop may operate in a context-dependent way to modulate responses to visual motion.

Complementary motion tuning in frontal nerve motor neurons of the blowfly

Flies actively turn their head during flight to stabilize their gaze and reduce motion blur. This optomotor response is triggered by wide-field motion indicating a deviation from a desired flight path. We focus on the neuronal circuit that underlies this behavior in the blowfly Calliphora, studying the integration of optic flow in neck motor neurons that innervate muscles controlling head rotations. Frontal nerve motor neurons (FNMNs) have been described anatomically and recorded from extracellularly before. Here, we assign for the first time to five anatomical classes of FNMNs their visual motion tuning. We measured their responses to optic flow, as produced by rotations around particular body axes, recording intracellularly from single axons. Simultaneous injection of Neurobiotin allowed for the anatomical characterization of the recorded cells and revealed coupling patterns with neighboring neurons. The five FNMN classes can be divided into two groups that complement each other, regarding their preferred axes of rotation. The tuning matches the pulling planes of their innervated neck muscles, serving to rotate the head around its longitudinal axis. Anatomical and physiological findings demonstrate a synaptic connection between one FNMN and a well-described descending neuron, elucidating one important step from visual motion integration to neck motor output.

Modelling of soldier fly halteres for gyroscopic oscillations

Nature has evolved a beautiful design for small-scale vibratory rate-gyro in the form of dipteran halteres that detect body rotations via Coriolis acceleration. In most Diptera, including soldier fly, Hermetia illucens, halteres are a pair of special organs, located in the space between the thorax and the abdomen. The halteres along with their connecting joint with the fly's body constitute a mechanism that is used for muscle-actuated oscillations of the halteres along the actuation direction. These oscillations lead to bending vibrations in the sensing direction (out of the haltere's actuation plane) upon any impressed rotation due to the resulting Coriolis force. This induced vibration is sensed by the sensory organs at the base of the haltere in order to determine the rate of rotation. In this study, we evaluate the boundary conditions and the stiffness of the anesthetized halteres along the actuation and the sensing direction. We take several cross-sectional SEM (scanning electron microscope) images of the soldier fly haltere and construct its three dimensional model to get the mass properties. Based on these measurements, we estimate the natural frequency along both actuation and sensing directions, propose a finite element model of the haltere's joint mechanism, and discuss the significance of the haltere's asymmetric cross-section. The estimated natural frequency along the actuation direction is within the range of the haltere's flapping frequency. However, the natural frequency along the sensing direction is roughly double the haltere's flapping frequency that provides a large bandwidth for sensing the rate of rotation to the soldier flies.

Pitch perfect: how fruit flies control their body pitch angle

Flapping insect flight is a complex and beautiful phenomenon that relies on fast, active control mechanisms to counter aerodynamic instability. To directly investigate how freely-flying D. melanogaster control their body pitch angle against such instability, we perturb them using impulsive mechanical torques and film their corrective maneuvers with high-speed video. Combining experimental observations and numerical simulation, we find that flies correct for pitch deflections of up to 40° in 29±8 ms by bilaterally modulating their wings' front-most stroke angle in a manner well-described by a linear proportional-integral (PI) controller. Flies initiate this corrective process only 10±2 ms after the perturbation onset, indicating that pitch stabilization involves a fast reflex response. Remarkably, flies can also correct for very large-amplitude pitch perturbations–greater than 150°–providing a regime in which to probe the limits of the linear-response framework. Together with previous studies regarding yaw and roll control, our results on pitch show that flies' stabilization of each of these body angles is consistent with PI control

Impact of stride-coupled gaze shifts of walking blowflies on the neuronal representation of visual targets

During locomotion animals rely heavily on visual cues gained from the environment to guide their behavior. Examples are basic behaviors like collision avoidance or the approach to a goal. The saccadic gaze strategy of flying flies, which separates translational from rotational phases of locomotion, has been suggested to facilitate the extraction of environmental information, because only image flow evoked by translational self-motion contains relevant distance information about the surrounding world. In contrast to the translational phases of flight during which gaze direction is kept largely constant, walking flies experience continuous rotational image flow that is coupled to their stride-cycle. The consequences of these self-produced image shifts for the extraction of environmental information are still unclear. To assess the impact of stride-coupled image shifts on visual information processing, we performed electrophysiological recordings from the HSE cell, a motion sensitive wide-field neuron in the blowfly visual system. This cell has been concluded to play a key role in mediating optomotor behavior, self-motion estimation and spatial information processing. We used visual stimuli that were based on the visual input experienced by walking blowflies while approaching a black vertical bar. The response of HSE to these stimuli was dominated by periodic membrane potential fluctuations evoked by stride-coupled image shifts. Nevertheless, during the approach the cell's response contained information about the bar and its background. The response components evoked by the bar were larger than the responses to its background, especially during the last phase of the approach. However, as revealed by targeted modifications of the visual input during walking, the extraction of distance information on the basis of HSE responses is much impaired by stride-coupled retinal image shifts. Possible mechanisms that may cope with these stride-coupled responses are discussed.

Fly visual course control: behaviour, algorithms and circuits

Understanding how the brain controls behaviour is undisputedly one of the grand goals of neuroscience research, and the pursuit of this goal has a long tradition in insect neuroscience. However, appropriate techniques were lacking for a long time. Recent advances in genetic and recording techniques now allow the participation of identified neurons in the execution of specific behaviours to be interrogated. By focusing on fly visual course control, I highlight what has been learned about the neuronal circuit modules that control visual guidance in Drosophila melanogaster through the use of these techniques.

Dynamic use of optic flow during pheromone tracking by the male silkmoth, Bombyx mori

Several insects require both olfactory and visual cues during odour-source localisation to successfully locate an odour source. In the male silkmoth, Bombyx mori, detection of the female sex pheromone triggers a programmed walking pattern, starting from a surge (straight-line walking) followed by zigzag walking. Although pheromone-triggered behaviour in silkmoths is well understood, the role of visual cues remains obscure. To address this question, we performed behavioural experiments on tethered-walking moths by recording their locomotion during stimulation with a pheromone and a visual motion pattern (optic flow). The experiments were conducted under open- and closed-loop visual stimuli. We found that the use of optic flow input was determined by the behavioural state of surge and zigzagging. Silkmoths exhibited an optomotor response, which is a behavioural visual response, by turning towards the same direction as optic flow stimuli only during surge, but not during zigzagging. In addition, modulation of the zigzag walking pattern was observed when the moths were presented with biased closed-loop visual stimuli (visual feedback with biased constant optic flow); however, the directional preference mechanism was different from that of the optomotor response. Based on these findings, we suggest that the optomotor response is utilised for course control during straight-line walking, whereas the absence of optomotor response during zigzagging is used to effectively perform the programmed walking pattern. Considering the neural basis of programmed behaviour, we speculate that at least two visual pathways are involved in the state-dependent use of optic flow during odour tracking behaviour in silkmoths.

Control of moth flight posture is mediated by wing mechanosensory feedback

Flying insects rapidly stabilize after perturbations using both visual and mechanosensory inputs for active control. Insect halteres are mechanosensory organs that encode inertial forces to aid rapid course correction during flight but serve no aerodynamic role and are specific to two orders of insects (Diptera and Strepsiptera). Aside from the literature on halteres and recent work on the antennae of the hawkmoth Manduca sexta, it is unclear how other flying insects use mechanosensory information to control body dynamics. The mechanosensory structures found on the halteres, campaniform sensilla, are also present on wings, suggesting that the wings can encode information about flight dynamics. We show that the neurons innervating these sensilla on the forewings of M. sexta exhibit spike-timing precision comparable to that seen in previous reports of campaniform sensilla, including haltere neurons. In addition, by attaching magnets to the wings of moths and subjecting these animals to a simulated pitch stimulus via a rotating magnetic field during tethered flight, we elicited the same vertical abdominal flexion reflex these animals exhibit in response to visual or inertial pitch stimuli. Our results indicate that, in addition to their role as actuators during locomotion, insect wings serve as sensors that initiate reflexes that control body dynamics.

Figure-ground discrimination behavior in Drosophila. II. Visual influences on head movement behavior

Visual identification of small moving targets is a challenge for all moving animals. Their own motion generates displacement of the visual surroundings, inducing wide-field optic flow across the retina. Wide-field optic flow is used to sense perturbations in the flight course. Both ego-motion and corrective optomotor responses confound any attempt to track a salient target moving independently of the visual surroundings. What are the strategies that flying animals use to discriminate small-field figure motion from superimposed wide-field background motion? We examined how fruit flies adjust their gaze in response to a compound visual stimulus comprising a small moving figure against an independently moving wide-field ground, which they do by re-orienting their head or their flight trajectory. We found that fixing the head in place impairs object fixation in the presence of ground motion, and that head movements are necessary for stabilizing wing steering responses to wide-field ground motion when a figure is present. When a figure is moving relative to a moving ground, wing steering responses follow components of both the figure and ground trajectories, but head movements follow only the ground motion. To our knowledge, this is the first demonstration that wing responses can be uncoupled from head responses and that the two follow distinct trajectories in the case of simultaneous figure and ground motion. These results suggest that whereas figure tracking by wing kinematics is independent of head movements, head movements are important for stabilizing ground motion during active figure tracking.

Optogenetic control of fly optomotor responses

When confronted with a large-field stimulus rotating around the vertical body axis, flies display a following behavior called "optomotor response." As neural control elements, the large tangential horizontal system (HS) cells of the lobula plate have been prime candidates for long. Here, we applied optogenetic stimulation of HS cells to evaluate their behavioral role in Drosophila. To minimize interference of the optical activation of channelrhodopsin-2 with the visual perception of the flies, we used a bistable variant called ChR2-C128S. By applying pulses of blue and yellow light, we first demonstrate electrophysiologically that lobula plate tangential cells can be activated and deactivated repeatedly with no evident change in depolarization strength over trials. We next show that selective optogenetic activation of HS cells elicits robust yaw head movements and yaw turning responses in fixed and tethered flying flies, respectively.

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

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

Feed-forward and visual feedback control of head roll orientation in wasps (Polistes humilis, Vespidae, Hymenoptera)

Flying insects keep their visual system horizontally aligned, suggesting that gaze stabilization is a crucial first step in flight control. Unlike flies, hymenopteran insects such as bees and wasps do not have halteres that provide fast, feed-forward angular rate information to stabilize head orientation in the presence of body rotations. We tested whether hymenopteran insects use inertial (mechanosensory) information to control head orientation from other sources, such as the wings, by applying periodic roll perturbations to male Polistes humilis wasps flying in tether under different visual conditions indoors and in natural outdoor conditions. We oscillated the thorax of the insects with frequency-modulated sinusoids (chirps) with frequencies increasing from 0.2 to 2 Hz at a maximal amplitude of 50 deg peak-to-peak and maximal angular velocity of ±245 deg s(-1). We found that head roll stabilization is best outdoors, but completely absent in uniform visual conditions and in darkness. Step responses confirm that compensatory head roll movements are purely visually driven. Modelling step responses indicates that head roll stabilization is achieved by merging information on head angular velocity, presumably provided by motion-sensitive neurons and information on head orientation, presumably provided by light level integration across the compound eyes and/or ocelli (dorsal light response). Body roll in free flight reaches amplitudes of ±40 deg and angular velocities greater than 1000 deg s(-1), while head orientation remains horizontal for most of the time to within ±10 deg. In free flight, we did not find a delay between spontaneous body roll and compensatory head movements, and suggest that this is evidence for the contribution of a feed-forward control to head stabilization.