Search

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

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

Many animals use visual cues like object shape, color, and motion to detect and pursue conspecific mates. Contrast is another possibly informative visual cue, but has not been studied in great detail. In this study, we presented male Drosophila melanogaster with small, fly-sized, moving objects painted either black, white, or grey to test if they use contrast cues to identify mates. We found that males frequently chased grey objects and rarely chased white or black objects. Although males started chasing black objects as often as grey objects, the resulting chases were much shorter. To test whether the attraction to grey objects was mediated via contrast, we fabricated black and grey behavioral chambers. However, wildtype males almost never chased any objects in these darkly colored chambers. To circumvent this limitation, we increased baseline levels of chasing by thermogenetically activating P1 neurons to promote courtship. Males with thermogenetically activated P1 neurons maintained a similar preference for grey objects despite elevated levels of courtship behavior. When placed in a black chamber, males with activated P1 neurons switched their preference and chased black objects more than grey objects. We also tested whether males use contrast cues to orient to particular parts of the female's body during courtship. When presented with moving objects painted two colors, males positioned themselves next to the grey half regardless of whether the other half was painted black or white. These results suggest that males can use contrast to recognize potential mates and to position themselves during courtship.

Foraging animals may benefit from remembering the location of a newly discovered food patch while continuing to explore nearby [1, 2]. For example, after encountering a drop of yeast or sugar, hungry flies often perform a local search [3, 4]. That is, rather than remaining on the food or simply walking away, flies execute a series of exploratory excursions during which they repeatedly depart and return to the resource. Fruit flies, Drosophila melanogaster, can perform this food-centered search behavior in the absence of external landmarks, instead relying on internal (idiothetic) cues [5]. This path-integration behavior may represent a deeply conserved navigational capacity in insects [6, 7], but its underlying neural basis remains unknown. Here, we used optogenetic activation to screen candidate cell classes and found that local searches can be initiated by diverse sensory neurons. Optogenetically induced searches resemble those triggered by actual food, are modulated by starvation state, and exhibit key features of path integration. Flies perform tightly centered searches around the fictive food site, even within a constrained maze, and they can return to the fictive food site after long excursions. Together, these results suggest that flies enact local searches in response to a wide variety of food-associated cues and that these sensory pathways may converge upon a common neural system for navigation. Using a virtual reality system, we demonstrate that local searches can be optogenetically induced in tethered flies walking on a spherical treadmill, laying the groundwork for future studies to image the brain during path integration. VIDEO ABSTRACT.

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

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

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

Despite their small brains, insects can navigate over long distances by orienting using visual landmarks [1], skylight polarization [2, 3, 4, 5, 6, 7, 8, 9], and sun position [3, 4, 6, 10]. Although Drosophila are not generally renowned for their navigational abilities, mark-and-recapture experiments in Death Valley revealed that they can fly nearly 15 km in a single evening [11]. To accomplish such feats on available energy reserves [12], flies would have to maintain relatively straight headings, relying on celestial cues [13]. Cues such as sun position and polarized light are likely integrated throughout the sensory-motor pathway [14], including the highly conserved central complex [4, 15, 16]. Recently, a group of Drosophila central complex cells (E-PG neurons) have been shown to function as an internal compass [17, 18, 19], similar to mammalian head-direction cells [20]. Using an array of genetic tools, we set out to test whether flies can navigate using the sun and to identify the role of E-PG cells in this behavior. Using a flight simulator, we found that Drosophila adopt arbitrary headings with respect to a simulated sun, thus performing menotaxis, and individuals remember their heading preference between successive flights—even over several hours. Imaging experiments performed on flying animals revealed that the E-PG cells track sun stimulus motion. When these neurons are silenced, flies no longer adopt and maintain arbitrary headings relative to the sun stimulus but instead exhibit frontal phototaxis. Thus, without the compass system, flies lose the ability to execute menotaxis and revert to a simpler, reflexive behavior.

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

After discovering a small drop of food, hungry flies exhibit a peculiar behavior in which they repeatedly stray from, but then return to, the newly discovered resource. To study this behavior in more detail, we tracked hungry Drosophila as they explored a large arena, focusing on the question of how flies remain near the food. To determine whether flies use external stimuli, we individually eliminated visual, olfactory, and pheromonal cues. In all cases, flies still exhibited a centralized search behavior, suggesting that none of these cues are absolutely required for navigation back to the food. To simultaneously eliminate visual and olfactory cues associated with the position of the food, we constructed an apparatus in which the food could be rapidly translated from the center of the arena. Flies continued to search around the original location, even after the food was moved to a new position. A random search model based on measured locomotor statistics could not reproduce the centered nature of the animal's trajectory. We conclude that this behavior is best explained by a form of path integration in which the flies use idiothetic cues to search near the location of the food. We argue that the use of path integration to perform a centered local search is not a specialization of Drosophila but rather represents an ancient behavioral mode that is homologous to the more elaborate foraging strategies of central place foragers such as ants.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Fruit flies adeptly coordinate flight maneuvers to seek, avoid, or otherwise interact with salient objects in their environment. In the laboratory, tethered flies modulate yaw torque to steer towards a dark vertical visual stimulus. This stripe-fixation behavior is robust and repeatable, making it a powerful paradigm for the study of optomotor control in flies. In this work, we study stripe fixation through a series of closed-loop perturbation experiments; flies are observed stabilizing moving stripes oscillating over a range of frequencies. A system identification analysis of input-output data furnishes a frequency response function (FRF), a nonparametric description of the behavior. We parameterize this FRF description to hypothesize a Proportional-Integral-Derivative (PID) control model for the fixation behavior. Lastly, we revisit previous work in which discrepancies in open- and closed-loop performance in stripe fixation were used to support the reafference principle.We demonstrate that our hypothesized PID model (with a modest biologically plausible nonlinearity) provides a more parsimonious explanation for these previously reported discrepancies.

Experimental biology is a dynamic and rapidly evolving area of research. Consequently, new techniques and concepts are constantly appearing. As this occurs, The Journal of Experimental Biology (JEB) also adapts to keep pace as we see manuscript submissions increasingly using new approaches to better

Flies display transient social interactions in groups. However, whether fly–fly interactions are stochastic or structured remains unknown. We hypothesized that groups of flies exhibit patterns of social dynamics that would manifest as nonrandom social interaction networks. To test this, we applied a machine vision system to track the position and orientation of flies in an arena and designed a classifier to detect interactions between pairs of flies. We show that the vinegar fly, Drosophila melanogaster , forms nonrandom social interaction networks, distinct from virtual network controls (constructed from the intersections of individual locomotor trajectories). In addition, the formation of interaction networks depends on chemosensory cues. Gustatory mutants form networks that cannot be distinguished from their virtual network controls. Olfactory mutants form networks that are greatly disrupted compared with control flies. Different wild-type strains form social interaction networks with quantitatively different properties, suggesting that the genes that influence this network phenotype vary across and within wild-type populations. We have established a paradigm for studying social behaviors at a group level in Drosophila and expect that a genetic dissection of this phenomenon will identify conserved molecular mechanisms of social organization in other species.

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.

SUMMARYLanding behavior is one of the most critical, yet least studied, aspects of insect flight. In order to land safely, an insect must recognize a visual feature, navigate towards it, decelerate, and extend its legs in preparation for touchdown. Although previous studies have focused on the visual stimuli that trigger these different components, the complete sequence has not been systematically studied in a free-flying animal. Using a real-time 3D tracking system in conjunction with high speed digital imaging, we were able to capture the landing sequences of fruit flies (Drosophila melanogaster) from the moment they first steered toward a visual target, to the point of touchdown. This analysis was made possible by a custom-built feedback system that actively maintained the fly in the focus of the high speed camera. The results suggest that landing is composed of three distinct behavioral modules. First, a fly actively turns towards a stationary target via a directed body saccade. Next, it begins to decelerate at a point determined by both the size of the visual target and its rate of expansion on the retina. Finally, the fly extends its legs when the visual target reaches a threshold retinal size of approximately 60 deg. Our data also let us compare landing sequences with flight trajectories that, although initially directed toward a visual target, did not result in landing. In these ‘fly-by’ trajectories, flies steer toward the target but then exhibit a targeted aversive saccade when the target subtends a retinal size of approximately 33 deg. Collectively, the results provide insight into the organization of sensorimotor modules that underlie the landing and search behaviors of insects.

SummaryAn important role of visual systems is to detect nearby predators, prey, and potential mates [1], which may be distinguished in part by their motion. When an animal is at rest, an object moving in any direction may easily be detected by motion-sensitive visual circuits [2, 3]. During locomotion, however, this strategy is compromised because the observer must detect a moving object within the pattern of optic flow created by its own motion through the stationary background. However, objects that move creating back-to-front (regressive) motion may be unambiguously distinguished from stationary objects because forward locomotion creates only front-to-back (progressive) optic flow. Thus, moving animals should exhibit an enhanced sensitivity to regressively moving objects. We explicitly tested this hypothesis by constructing a simple fly-sized robot that was programmed to interact with a real fly. Our measurements indicate that whereas walking female flies freeze in response to a regressively moving object, they ignore a progressively moving one. Regressive motion salience also explains observations of behaviors exhibited by pairs of walking flies. Because the assumptions underlying the regressive motion salience hypothesis are general, we suspect that the behavior we have observed in Drosophila may be widespread among eyed, motile organisms.

SummaryAs an animal translates through the world, its eyes will experience a radiating pattern of optic flow in which there is a focus of expansion directly in front and a focus of contraction behind. For flying fruit flies, recent experiments indicate that flies actively steer away from patterns of expansion. Whereas such a reflex makes sense for avoiding obstacles, it presents a paradox of sorts because an insect could not navigate stably through a visual scene unless it tolerated flight towards a focus of expansion during episodes of forward translation. One possible solution to this paradox is that a fly's behavior might change such that it steers away from strong expansion, but actively steers toward weak expansion. In this study, we use a tethered flight arena to investigate the influence of stimulus strength on the magnitude and direction of turning responses to visual expansion in flies. These experiments indicate that the expansion-avoidance behavior exhibits a speed-dependent inversion. At slower speeds of expansion, flies exhibit an attraction to the focus of expansion, whereas the behavior transforms to expansion avoidance at higher speeds. Open-loop experiments indicate that this inversion of the expansion-avoidance response depends on whether or not the head is fixed to the thorax. The inversion of the expansion-avoidance response with stimulus strength has a clear manifestation under closed-loop conditions. Flies will actively orient toward a focus of expansion at low temporal frequency but steer away from it at high temporal frequency. The change in the response with temporal frequency does not require motion stimuli directly in front or behind the fly. Animals in which the stimulus was presented within 120° sectors on each side consistently steered toward expansion at low temporal frequency and steered toward contraction at high temporal frequency. A simple model based on an array of Hassenstein-Reichardt type elementary movement detectors suggests that the inversion of the expansion-avoidance reflex can explain the spatial distribution of straight flight segments and collision-avoidance saccades when flies fly freely within an open circular arena.

SUMMARY Freely flying Drosophila melanogaster respond to odors by increasing their flight speed and turning upwind. Both these flight behaviors can be recapitulated in a tethered fly, which permits the odor stimulus to be precisely controlled. In this study, we investigated the relationship between these behaviors and odor-evoked activity in primary sensory neurons. First, we verified that these behaviors are abolished by mutations that silence olfactory receptor neurons (ORNs). We also found that antennal mechanosensors in Johnston's organ are required to guide upwind turns. Flight responses to an odor depend on the identity of the ORNs that are active, meaning that these behaviors involve odor discrimination and not just odor detection. Flight modulation can begin rapidly (within about 85 ms) after the onset of olfactory transduction. Moreover, just a handful of spikes in a single ORN type is sufficient to trigger these behaviors. Finally, we found that the upwind turn is triggered independently from the increase in wingbeat frequency, implying that ORN signals diverge to activate two independent and parallel motor commands. Together, our results show that odor-evoked flight modulations are rapid and sensitive responses to specific patterns of sensory neuron activity. This makes these behaviors a useful paradigm for studying the relationship between sensory neuron activity and behavioral decision-making in a simple and genetically tractable organism.

Unlike creatures that walk, flying animals need to control their horizontal motion as well as their height above the ground. Research on insects, the first animals to evolve flight, has revealed several visual reflexes that are used to govern horizontal course. For example, insects orient toward prominent vertical features in their environment [1], [2], [3], [4] and [5] and generate compensatory reactions to both rotations [6] and [7] and translations [1], [8], [9], [10] and [11] of the visual world. Insects also avoid impending collisions by veering away from visual expansion [9], [12], [13] and [14]. In contrast to this extensive understanding of the visual reflexes that regulate horizontal course, the sensory-motor mechanisms that animals use to control altitude are poorly understood. Using a 3D virtual reality environment, we found that Drosophila utilize three reflexes—edge tracking, wide-field stabilization, and expansion avoidance—to control altitude. By implementing a dynamic visual clamp, we found that flies do not regulate altitude by maintaining a fixed value of optic flow beneath them, as suggested by a recent model [15]. The results identify a means by which insects determine their absolute height above the ground and uncover a remarkable correspondence between the sensory-motor algorithms used to regulate motion in the horizontal and vertical domains.

SUMMARYFlies, like all animals that depend on vision to navigate through the world, must integrate the optic flow created by self-motion with the images generated by prominent features in their environment. Although much is known about the responses of Drosophila melanogaster to rotating flow fields, their reactions to the more complex patterns of motion that occur as they translate through the world are not well understood. In the present study we explore the interactions between two visual reflexes in Drosophila: object fixation and expansion avoidance. As a fly flies forward, it encounters an expanding visual flow field. However, recent results have demonstrated that Drosophila strongly turn away from patterns of expansion. Given the strength of this reflex, it is difficult to explain how flies make forward progress through a visual landscape. This paradox is partially resolved by the finding reported here that when undergoing flight directed towards a conspicuous object, Drosophila will tolerate a level of expansion that would otherwise induce avoidance. This navigation strategy allows flies to fly straight when orienting towards prominent visual features.

We have approached the problem of reverse-engineering the flight control mechanism of the fruit fly by studying the dynamics of the responses to a visual stimulus during takeoff. Building upon a prior framework [G. Card and M. Dickinson, J. Exp. Biol., vol. 211, pp. 341-353, 2008], we seek to understand the strategies employed by the animal to stabilize attitude and orientation during these evasive, highly dynamical maneuvers. As a first step, we consider the dynamics from a gray-box perspective: examining lumped forces produced by the insect's legs and wings. The reconstruction of the flight initiation dynamics, based on the unconstrained motion formulation for a rigid body, allows us to assess the fly's responses to a variety of initial conditions induced by its jump. Such assessment permits refinement by using a visual tracking algorithm to extract the kinematic envelope of the wings [E. I. Fontaine, F. Zabala, M. Dickinson, and J. Burdick, "Wing and body motion during flight initiation in Drosophila revealed by automated visual tracking," submitted for publication] in order to estimate lift and drag forces [F. Zabala, M. Dickinson, and R. Murray, "Control and stability of insect flight during highly dynamical maneuvers," submitted for publication], and recording actual leg-joint kinematics and using them to estimate jump forces [F. Zabala, "A bio-inspired model for directionality control of flight initiation," to be published.]. In this paper, we present the details of our approach in a comprehensive manner, including the salient results.

Background Video cameras sense passively from a distance, offer a rich information stream, and provide intuitively meaningful raw data. Camera-based imaging has thus proven critical for many advances in neuroscience and biology, with applications ranging from cellular imaging of fluorescent dyes to tracking of whole-animal behavior at ecologically relevant spatial scales. Results Here we present 'Motmot': an open-source software suite for acquiring, displaying, saving, and analyzing digital video in real-time. At the highest level, Motmot is written in the Python computer language. The large amounts of data produced by digital cameras are handled by low-level, optimized functions, usually written in C. This high-level/low-level partitioning and use of select external libraries allow Motmot, with only modest complexity, to perform well as a core technology for many high-performance imaging tasks. In its current form, Motmot allows for: (1) image acquisition from a variety of camera interfaces (package motmot.cam_iface), (2) the display of these images with minimal latency and computer resources using wxPython and OpenGL (package motmot.wxglvideo), (3) saving images with no compression in a single-pass, low-CPU-use format (package motmot.FlyMovieFormat), (4) a pluggable framework for custom analysis of images in realtime and (5) firmware for an inexpensive USB device to synchronize image acquisition across multiple cameras, with analog input, or with other hardware devices (package motmot.fview_ext_trig). These capabilities are brought together in a graphical user interface, called 'FView', allowing an end user to easily view and save digital video without writing any code. One plugin for FView, 'FlyTrax', which tracks the movement of fruit flies in real-time, is included with Motmot, and is described to illustrate the capabilities of FView. Conclusion Motmot enables realtime image processing and display using the Python computer language. In addition to the provided complete applications, the architecture allows the user to write relatively simple plugins, which can accomplish a variety of computer vision tasks and be integrated within larger software systems. The software is available at http://code.astraw.com/projects/motmot

The paper describes an indoor helicopter testbed that allows implementing and testing of bio-inspired control algorithms developed from scientific studies on insects. The helicopter receives and is controlled by simulated sensory inputs (e.g. visual stimuli) generated in a virtual 3D environment, where the connection between the physical world and the virtual world is provided by a video camera tracking system. The virtual environment is specified by a 3D computer model and is relatively simple to modify compared to realistic scenes. This enables rapid examinations of whether a certain control law is robust under various environments, an important feature of insect behavior. As a first attempt, flight stabilization and yaw rate control near hover are demonstrated, utilizing biologically realistic visual stimuli as in the fruit fly Drosophila melanogaster.

We investigated whether flapping flight has an inherent stability by analyzing the inertial and aerodynamic effects of flapping wings on body dynamics. Based on wing and body kinematics of free flying fruit flies during rapid maneuvers, we found a passive counter torque due to body rotation. It is indentified both in simulation through quasi-steady state aerodynamic model and through experiments on a dynamically scaled robotic wing. An analytical form is derived correspondingly. In the turning yaw axis, the estimated damping coefficient of flapping wings is significantly higher than body frictional damping; this indicates a passive deceleration during turning. By simulating insect to rotate about each principal axis of inertial and body frames, we calculated the corresponding damping coefficients, and further analyzed the attitude stability. The result reveals that, passive damping of flapping flight, while does not necessarily lead to a stable full body dynamics, provides a considerable passive restoring torque that could be critical for flight stabilization and control in the design of micro aerial vehicles. Preliminary analysis on the scaling parameters of passive damping was also performed.

SUMMARYThe fruit fly Drosophila melanogaster is a widely used model organism in studies of genetics, developmental biology and biomechanics. One limitation for exploiting Drosophila as a model system for behavioral neurobiology is that measuring body kinematics during behavior is labor intensive and subjective. In order to quantify flight kinematics during different types of maneuvers, we have developed a visual tracking system that estimates the posture of the fly from multiple calibrated cameras. An accurate geometric fly model is designed using unit quaternions to capture complex body and wing rotations, which are automatically fitted to the images in each time frame. Our approach works across a range of flight behaviors, while also being robust to common environmental clutter. The tracking system is used in this paper to compare wing and body motion during both voluntary and escape take-offs. Using our automated algorithms, we are able to measure stroke amplitude, geometric angle of attack and other parameters important to a mechanistic understanding of flapping flight. When compared with manual tracking methods, the algorithm estimates body position within 4.4±1.3%of the body length, while body orientation is measured within 6.5±1.9 deg. (roll), 3.2±1.3 deg. (pitch) and 3.4±1.6 deg. (yaw) on average across six videos. Similarly, stroke amplitude and deviation are estimated within 3.3 deg. and 2.1 deg., while angle of attack is typically measured within 8.8 deg. comparing against a human digitizer. Using our automated tracker, we analyzed a total of eight voluntary and two escape take-offs. These sequences show that Drosophila melanogaster do not utilize clap and fling during take-off and are able to modify their wing kinematics from one wingstroke to the next. Our approach should enable biomechanists and ethologists to process much larger datasets than possible at present and, therefore, accelerate insight into the mechanisms of free-flight maneuvers of flying insects.

SUMMARYThe fruit fly Drosophila melanogaster performs at least two distinct types of flight initiation. One kind is a stereotyped escape response to a visual stimulus that is mediated by the hard-wired giant fiber neural pathway, and the other is a more variable `voluntary' response that can be performed without giant fiber activation. Because the simpler escape take-offs are apparently successful, it is unclear why the fly has multiple pathways to coordinate flight initiation. In this study we use high-speed videography to observe flight initiation in unrestrained wild-type flies and assess the flight performance of each of the two types of take-off. Three-dimensional kinematic analysis of take-off sequences indicates that wing use during the jumping phase of flight initiation is essential for stabilizing flight. During voluntary take-offs, early wing elevation leads to a slower and more stable take-off. In contrast, during visually elicited escapes, the wings are pulled down close to the body during take-off, resulting in tumbling flights in which the fly translates faster but also rotates rapidly about all three of its body axes. Additionally, we find evidence that the power delivered by the legs is substantially greater during visually elicited escapes than during voluntary take-offs. Thus, we find that the two types of Drosophila flight initiation result in different flight performances once the fly is airborne,and that these performances are distinguished by a trade-off between speed and stability.

SUMMARYIt has long been known that many flying insects use visual cues to orient with respect to the wind and to control their groundspeed in the face of varying wind conditions. Much less explored has been the role of mechanosensory cues in orienting insects relative to the ambient air. Here we show that Drosophila melanogaster, magnetically tethered so as to be able to rotate about their yaw axis, are able to detect and orient into a wind, as would be experienced during forward flight. Further, this behavior is velocity dependent and is likely subserved, at least in part, by the Johnston's organs, chordotonal organs in the antennae also involved in near-field sound detection. These wind-mediated responses may help to explain how flies are able to fly forward despite visual responses that might otherwise inhibit this behavior. Expanding visual stimuli, such as are encountered during forward flight, are the most potent aversive visual cues known for D. melanogaster flying in a tethered paradigm. Accordingly,tethered flies strongly orient towards a focus of contraction, a problematic situation for any animal attempting to fly forward. We show in this study that wind stimuli, transduced via mechanosensory means, can compensate for the aversion to visual expansion and thus may help to explain how these animals are indeed able to maintain forward flight.

SUMMARYThe flight trajectories of fruit flies consist of straight flight segments interspersed with rapid turns called body saccades. Although the saccades are stereotyped, it is not known whether their brief time course is due to a feed-forward (predetermined) motor program or due to feedback from sensory systems that are reflexively activated by the rapid rotation. Two sensory modalities, the visual system and the mechanosensory halteres, are likely sources of such feedback because they are sensitive to angular velocities within the range experienced during saccades. Utilizing a magnetic tether in which flies are fixed in space but free to rotate about their yaw axis, we systematically manipulated the feedback from the visual and haltere systems to test their role in determining the time course of body saccades. We found that altering visual feedback had no significant effect on the dynamics of saccades, whereas increasing and decreasing the amount of haltere-mediated feedback decreased and increased saccade amplitude, respectively. In other experiments, we altered the aerodynamic surface of the wings such that the flies had to actively modify their wing-stroke kinematics to maintain straight flight on the magnetic tether. Flies exhibit such modification, but the control is compromised in the dark, indicating that the visual system does provide feedback for flight stability at lower angular velocities, to which the haltere system is less sensitive. Cutting the wing surface disrupted the time course of the saccades, indicating that although flies employ sensory feedback to modulate saccade dynamics, it is not precise or fast enough to compensate for large changes in wing efficacy.

Insects exhibit incredibly robust closed loop fight dynamics in the face of uncertainties. A fundamental principle contributing to this unparalleled behavior is rapid processing and convergence of visual sensory information to fight motor commands via spatial wide-field integration, accomplished by retinal motion pattern sensitive interneurons (LPTCs) in the lobula plate portion of the visual ganglia. With in a control- theoretic frame work, models for spatially continuous retinal image flow and wide-field integration processing are developed, establishing the connection between image flow kernels (retinal motion pattern sensitivities) and the feedback terms they represent. It is shown that these out puts are sufficient to stabilize speed regulation and terrain following tasks. Hence, extraction of global retinal motion cues through computationally efficient wide-field integration processing provides a novel and promising methodology for utilizing visual sensory information in autonomous robotic navigation and fight control applications.

Insects exhibit incredibly robust closed loop flight dynamics in the face of uncertainties. A fundamental principle contributing to this unparalleled behavior is rapid processing and convergence of visual sensory information to flight motor commands via spatial wide-field integration, accomplished by retinal motion pattern sensitive interneurons (LPTCs) in the lobula plate portion of the visual ganglia. Within a control-theoretic framework, an inner product model for wide-field integration of retinal image flow is presented, representing the spatial decompositions performed by LPTCs in the insect visuomotor system. The correspondence between image flow kernels and the output feedback terms they represent is developed, establishing the connection between LPTC motion sensitivity shape and closed loop behavior. It is shown that these outputs are sufficient to stabilize pitch and altitude flight modes for obstacle avoidance and terrain following navigational tasks. Hence, extraction of global retinal motion cues through computationally efficient wide-field integration processing provides a novel and promising methodology for utilizing visual sensory information in autonomous robotic navigation and flight control applications.