Spatial organization of visuomotor reflexes in Drosophila

Method and software for using m-sequences to characterize parallel components of higher-order visual tracking behavior in Drosophila

A moving visual figure may contain first-order signals defined by variation in mean luminance, as well as second-order signals defined by constant mean luminance and variation in luminance envelope, or higher-order signals that cannot be estimated by taking higher moments of the luminance distribution. Separating these properties of a moving figure to experimentally probe the visual subsystems that encode them is technically challenging and has resulted in debated mechanisms of visual object detection by flies. Our prior work took a white noise systems identification approach using a commercially available electronic display system to characterize the spatial variation in the temporal dynamics of two distinct subsystems for first- and higher-order components of visual figure tracking. The method relied on the use of single pixel displacements of two visual stimuli according to two binary maximum length shift register sequences (m-sequences) and cross-correlation of each m-sequence with time-varying flight steering measurements. The resultant spatio-temporal action fields represent temporal impulse responses parameterized by the azimuthal location of the visual figure, one STAF for first-order and another for higher-order components of compound stimuli. Here we review m-sequence and reverse correlation procedures, then describe our application in detail, provide Matlab code, validate the STAFs, and demonstrate the utility and robustness of STAFs by predicting the results of other published experimental procedures. This method has demonstrated how two relatively modest innovations on classical white noise analysis—the inclusion of space as a way to organize response kernels and the use of linear decoupling to measure the response to two channels of visual information simultaneously—could substantially improve our basic understanding of visual processing in the fly.

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.

Through the eyes of a bird: modelling visually guided obstacle flight

Various flight navigation strategies for birds have been identified at the large spatial scales of migratory and homing behaviours. However, relatively little is known about close-range obstacle negotiation through cluttered environments. To examine obstacle flight guidance, we tracked pigeons (Columba livia) flying through an artificial forest of vertical poles. Interestingly, pigeons adjusted their flight path only approximately 1.5 m from the forest entry, suggesting a reactive mode of path planning. Combining flight trajectories with obstacle pole positions, we reconstructed the visual experience of the pigeons throughout obstacle flights. Assuming proportional-derivative control with a constant delay, we searched the relevant parameter space of steering gains and visuomotor delays that best explained the observed steering. We found that a pigeon's steering resembles proportional control driven by the error angle between the flight direction and the desired opening, or gap, between obstacles. Using this pigeon steering controller, we simulated obstacle flights and showed that pigeons do not simply steer to the nearest opening in the direction of flight or destination. Pigeons bias their flight direction towards larger visual gaps when making fast steering decisions. The proposed behavioural modelling method converts the obstacle avoidance behaviour into a (piecewise) target-aiming behaviour, which is better defined and understood. This study demonstrates how such an approach decomposes open-loop free-flight behaviours into components that can be independently evaluated.

Cellular mechanisms for integral feedback in visually guided behavior

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

To keep on track during flight, fruitflies discount the skyward view

When small flying insects go off their intended course, they use the resulting pattern of motion on their eye, or optic flow, to guide corrective steering. A change in heading generates a unique, rotational motion pattern and a change in position generates a translational motion pattern, and each produces corrective responses in the wingbeats. Any image in the flow field can signal rotation, but owing to parallax, only the images of nearby objects can signal translation. Insects that fly near the ground might therefore respond more strongly to translational optic flow that occurs beneath them, as the nearby ground will produce strong optic flow. In these experiments, rigidly tethered fruitflies steered in response to computer-generated flow fields. When correcting for unintended rotations, flies weight the motion in their upper and lower visual fields equally. However, when correcting for unintended translations, flies weight the motion in the lower visual fields more strongly. These results are consistent with the interpretation that fruitflies stabilize by attending to visual areas likely to contain the strongest signals during natural flight conditions.

Motion-detecting circuits in flies: coming into view

Visual motion cues provide animals with critical information about their environment and guide a diverse array of behaviors. The neural circuits that carry out motion estimation provide a well-constrained model system for studying the logic of neural computation. Through a confluence of behavioral, physiological, and anatomical experiments, taking advantage of the powerful genetic tools available in the fruit fly Drosophila melanogaster, an outline of the neural pathways that compute visual motion has emerged. Here we describe these pathways, the evidence supporting them, and the challenges that remain in understanding the circuits and computations that link sensory inputs to behavior. Studies in flies and vertebrates have revealed a number of functional similarities between motion-processing pathways in different animals, despite profound differences in circuit anatomy and structure. The fact that different circuit mechanisms are used to achieve convergent computational outcomes sheds light on the evolution of the nervous system.

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.

Figure-ground discrimination behavior in Drosophila. I. Spatial organization of wing-steering responses

The behavioral algorithms and neural subsystems for visual figure–ground discrimination are not sufficiently described in any model system. The fly visual system shares structural and functional similarity with that of vertebrates and, like vertebrates, flies robustly track visual figures in the face of ground motion. This computation is crucial for animals that pursue salient objects under the high performance requirements imposed by flight behavior. Flies smoothly track small objects and use wide-field optic flow to maintain flight-stabilizing optomotor reflexes. The spatial and temporal properties of visual figure tracking and wide-field stabilization have been characterized in flies, but how the two systems interact spatially to allow flies to actively track figures against a moving ground has not. We took a systems identification approach in flying Drosophila and measured wing-steering responses to velocity impulses of figure and ground motion independently. We constructed a spatiotemporal action field (STAF) – the behavioral analog of a spatiotemporal receptive field – revealing how the behavioral impulse responses to figure tracking and concurrent ground stabilization vary for figure motion centered at each location across the visual azimuth. The figure tracking and ground stabilization STAFs show distinct spatial tuning and temporal dynamics, confirming the independence of the two systems. When the figure tracking system is activated by a narrow vertical bar moving within the frontal field of view, ground motion is essentially ignored despite comprising over 90% of the total visual input.

Death Valley, Drosophila, and the Devonian toolkit

Most experiments on the flight behavior of Drosophila melanogaster have been performed within confined laboratory chambers, yet the natural history of these animals involves dispersal that takes place on a much larger spatial scale. Thirty years ago, a group of population geneticists performed a series of mark-and-recapture experiments on Drosophila flies, which demonstrated that even cosmopolitan species are capable of covering 10 km of open desert, probably in just a few hours and without the possibility of feeding along the way. In this review I revisit these fascinating and informative experiments and attempt to explain how-from takeoff to landing-the flies might have made these journeys based on our current knowledge of flight behavior. This exercise provides insight into how animals generate long behavioral sequences using sensory-motor modules that may have an ancient evolutionary origin.

Contributions of the 12 neuron classes in the fly lamina to motion vision

Motion detection is a fundamental neural computation performed by many sensory systems. In the fly, local motion computation is thought to occur within the first two layers of the visual system, the lamina and medulla. We constructed specific genetic driver lines for each of the 12 neuron classes in the lamina. We then depolarized and hyperpolarized each neuron type and quantified fly behavioral responses to a diverse set of motion stimuli. We found that only a small number of lamina output neurons are essential for motion detection, while most neurons serve to sculpt and enhance these feedforward pathways. Two classes of feedback neurons (C2 and C3), and lamina output neurons (L2 and L4), are required for normal detection of directional motion stimuli. Our results reveal a prominent role for feedback and lateral interactions in motion processing and demonstrate that motion-dependent behaviors rely on contributions from nearly all lamina neuron classes.

Modular use of peripheral input channels tunes motion-detecting circuitry

In the visual system, peripheral processing circuits are often tuned to specific stimulus features. How this selectivity arises and how these circuits are organized to inform specific visual behaviors is incompletely understood. Using forward genetics and quantitative behavioral studies, we uncover an input channel to motion detecting circuitry in Drosophila. The second-order neuron L3 acts combinatorially with two previously known inputs, L1 and L2, to inform circuits specialized to detect moving light and dark edges. In vivo calcium imaging of L3, combined with neuronal silencing experiments, suggests a neural mechanism to achieve selectivity for moving dark edges. We further demonstrate that different innate behaviors, turning and forward movement, can be independently modulated by visual motion. These two behaviors make use of different combinations of input channels. Such modular use of input channels to achieve feature extraction and behavioral specialization likely represents a general principle in sensory systems.

GABAergic lateral interactions tune the early stages of visual processing in Drosophila

Early stages of visual processing must capture complex, dynamic inputs. While peripheral neurons often implement efficient encoding by exploiting natural stimulus statistics, downstream neurons are specialized to extract behaviorally relevant features. How do these specializations arise? We use two-photon imaging in Drosophila to characterize a first-order interneuron, L2, that provides input to a pathway specialized for detecting moving dark edges. GABAergic interactions, mediated in part presynaptically, create an antagonistic and anisotropic center-surround receptive field. This receptive field is spatiotemporally coupled, applying differential temporal processing to large and small dark objects, achieving significant specialization. GABAergic circuits also mediate OFF responses and balance these with responses to ON stimuli. Remarkably, the functional properties of L2 are strikingly similar to those of bipolar cells, yet emerge through different molecular and circuit mechanisms. Thus, evolution appears to have converged on a common strategy for processing visual information at the first synapse.

Discriminating external and internal causes for heading changes in freely flying Drosophila

As animals move through the world in search of resources, they change course in reaction to both external sensory cues and internally-generated programs. Elucidating the functional logic of complex search algorithms is challenging because the observable actions of the animal cannot be unambiguously assigned to externally- or internally-triggered events. We present a technique that addresses this challenge by assessing quantitatively the contribution of external stimuli and internal processes. We apply this technique to the analysis of rapid turns (“saccades”) of freely flying Drosophila melanogaster. We show that a single scalar feature computed from the visual stimulus experienced by the animal is sufficient to explain a majority (93%) of the turning decisions. We automatically estimate this scalar value from the observable trajectory, without any assumption regarding the sensory processing. A posteriori, we show that the estimated feature field is consistent with previous results measured in other experimental conditions. The remaining turning decisions, not explained by this feature of the visual input, may be attributed to a combination of deterministic processes based on unobservable internal states and purely stochastic behavior. We cannot distinguish these contributions using external observations alone, but we are able to provide a quantitative bound of their relative importance with respect to stimulus-triggered decisions. Our results suggest that comparatively few saccades in free-flying conditions are a result of an intrinsic spontaneous process, contrary to previous suggestions. We discuss how this technique could be generalized for use in other systems and employed as a tool for classifying effects into sensory, decision, and motor categories when used to analyze data from genetic behavioral screens.

Researchers have spent considerable effort studying how specific sensory stimuli elicit behavioral responses and how other behaviors may arise independent of external inputs in conditions of sensory deprivation. Yet an animal in its natural context, such as searching for food or mates, turns both in response to external stimuli and intrinsic, possibly stochastic, decisions. We show how to estimate the contribution of vision and internal causes on the observable behavior of freely flying Drosophila. We developed a dimensionality reduction scheme that finds a one-dimensional feature of the visual stimulus that best predicts turning decisions. This visual feature extraction is consistent with previous literature on visually elicited fly turning and predicts a large majority of turns in the tested environment. The rarity of stimulus-independent events suggests that fly behavior is more deterministic than previously suggested and that, more generally, animal search strategies may be dominated by responses to stimuli with only modest contributions from internal causes.

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.

Visual motion speed determines a behavioral switch from forward flight to expansion avoidance in Drosophila

As 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 towards 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 is speed dependent. 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 towards 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 deg sectors on each side consistently steered towards expansion at low temporal frequency and steered towards 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.

Lobula-specific visual projection neurons are involved in perception of motion-defined second-order motion in Drosophila

A wide variety of animal species including humans and fruit flies see second-order motion although they lack coherent spatiotemporal correlations in luminance. Recent electrophysiological recordings, together with intensive psychophysical studies, are bringing to light the neural underpinnings of second-order motion perception in mammals. However, where and how the higher-order motion signals are processed in the fly brain is poorly understood. Using the rich genetic tools available in Drosophila and examining optomotor responses in fruit flies to several stimuli, we revealed that two lobula-specific visual projection neurons, specifically connecting the lobula and the central brain, are involved in the perception of motion-defined second-order motion, independent of whether the second-order feature is moving perpendicular or opposite to the local first-order motion. By contrast, blocking these neurons has no effect on first-order and flicker-defined second-order stimuli in terms of response delay. Our results suggest that visual neuropils deep in the optic lobe and the central brain, whose functional roles in motion processing were previously unclear, may be specifically required for motion-defined motion processing.

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

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

Vision in Drosophila: seeing the world through a model's eyes

The fruit fly, Drosophila melanogaster, has been used for decades as a genetic model for unraveling mechanisms of development and behavior. In order to efficiently assign gene functions to cellular and behavioral processes, early measures were often necessarily simple. Much of what is known of developmental pathways was based on disrupting highly regular structures, such as patterns of cells in the eye. Similarly, reliable visual behaviors such as phototaxis and motion responses provided a solid foundation for dissecting vision. Researchers have recently begun to examine how this model organism responds to more complex or naturalistic stimuli by designing novel paradigms that more closely mimic visual behavior in the wild. Alongside these advances, the development of brain-recording strategies allied with novel genetic tools has brought about a new era of Drosophila vision research where neuronal activity can be related to behavior in the natural world.

Bursts and isolated spikes code for opposite movement directions in midbrain electrosensory neurons

Directional selectivity, in which neurons respond strongly to an object moving in a given direction but weakly or not at all to the same object moving in the opposite direction, is a crucial computation that is thought to provide a neural correlate of motion perception. However, directional selectivity has been traditionally quantified by using the full spike train, which does not take into account particular action potential patterns. We investigated how different action potential patterns, namely bursts (i.e. packets of action potentials followed by quiescence) and isolated spikes, contribute to movement direction coding in a mathematical model of midbrain electrosensory neurons. We found that bursts and isolated spikes could be selectively elicited when the same object moved in opposite directions. In particular, it was possible to find parameter values for which our model neuron did not display directional selectivity when the full spike train was considered but displayed strong directional selectivity when bursts or isolated spikes were instead considered. Further analysis of our model revealed that an intrinsic burst mechanism based on subthreshold T-type calcium channels was not required to observe parameter regimes for which bursts and isolated spikes code for opposite movement directions. However, this burst mechanism enhanced the range of parameter values for which such regimes were observed. Experimental recordings from midbrain neurons confirmed our modeling prediction that bursts and isolated spikes can indeed code for opposite movement directions. Finally, we quantified the performance of a plausible neural circuit and found that it could respond more or less selectively to isolated spikes for a wide range of parameter values when compared with an interspike interval threshold. Our results thus show for the first time that different action potential patterns can differentially encode movement and that traditional measures of directional selectivity need to be revised in such cases.

EMULATION OF HUMAN FEELINGS AND BEHAVIORS IN AN ANIMATED ARTWORK

The behavior of an animated artwork, survivor — a classroom chair which walks, with a dynamics which some viewers find haunting — reflects an attempt to emulate (and suggest to viewers) some feelings and behaviors that are typical of survivors of landmine blasts, learning to use crutches. The artwork itself is intended for sensitizing viewers to the horror experienced by those who survive, and those who do not. The behavior of such a survivor is affected by several factors: some are due to the objective difficulty of using prosthetic legs, and some are due to emotional factors, e.g., fear, "shame" of being in such situation, and pain. The mechanical structure, strongly conditioned by artistic requirements, was combined with a control system that exhibits appropriate behaviors. Behavioral control, a technique developed for the control of mobile robots, was used in survivor, and implemented over a modified version of the traditional Brooks' subsumption architecture. This technique makes it possible to emulate normal locomotion behaviors such as the need of avoiding obstacles and typical animal feelings such as curiosity, hunger, fatigue and fear. We describe the mechanics and viewers' response, and formalize aesthetic response. We briefly survey computer modelling of emotions, robotic art, and biomimetic locomotion in robotics.

Binocular interactions underlying the classic optomotor responses of flying flies

In response to imposed course deviations, the optomotor reactions of animals reduce motion blur and facilitate the maintenance of stable body posture. In flies, many anatomical and electrophysiological studies suggest that disparate motion cues stimulating the left and right eyes are not processed in isolation but rather are integrated in the brain to produce a cohesive panoramic percept. To investigate the strength of such inter-ocular interactions and their role in compensatory sensory–motor transformations, we utilize a virtual reality flight simulator to record wing and head optomotor reactions by tethered flying flies in response to imposed binocular rotation and monocular front-to-back and back-to-front motion. Within a narrow range of stimulus parameters that generates large contrast insensitive optomotor responses to binocular rotation, we find that responses to monocular front-to-back motion are larger than those to panoramic rotation, but are contrast sensitive. Conversely, responses to monocular back-to-front motion are slower than those to rotation and peak at the lowest tested contrast. Together our results suggest that optomotor responses to binocular rotation result from the influence of non-additive contralateral inhibitory as well as excitatory circuit interactions that serve to confer contrast insensitivity to flight behaviors influenced by rotatory optic flow.

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

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

An olfactory circuit increases the fidelity of visual behavior

Multimodal integration allows neural circuits to be activated in a behaviorally context-specific manner. In the case of odor plume tracking by Drosophila, an attractive odorant increases the influence of yaw-optic flow on steering behavior in flight, which enhances visual stability reflexes, resulting in straighter flight trajectories within an odor plume. However, it is not well understood whether context-specific changes in optomotor behavior are the result of an increased sensitivity to motion inputs (e.g., through increased visual attention) or direct scaling of motor outputs (i.e., increased steering gain). We address this question by examining the optomotor behavior of Drosophila melanogaster in a tethered flight assay and demonstrate that whereas olfactory cues decrease the gain of the optomotor response to sideslip optic flow, they concomitantly increase the gain of the yaw optomotor response by enhancing the animal's ability to follow transient visual perturbations. Furthermore, ablating the mushroom bodies (MBs) of the fly brain via larval hydroxyurea (HU) treatment results in a loss of olfaction-dependent increase in yaw optomotor fidelity. By expressing either tetanus toxin light chain or diphtheria toxin in gal4-defined neural circuits, we were able to replicate the loss of function observed in the HU treatment within the lines expressing broadly in the mushroom bodies, but not within specific mushroom body lobes. Finally, we were able to genetically separate the yaw responses and sideslip responses in our behavioral assay. Together, our results implicate the MBs in a fast-acting, memory-independent olfactory modification of a visual reflex that is critical for flight control.

First controlled vertical flight of a biologically inspired microrobot

In this paper, we present experimental results on altitude control of a flying microrobot. The problem is approached in two stages. In the first stage, system identification of two relevant subsystems composing the microrobot is performed, using a static flapping experimental setup. In the second stage, the information gathered through the static flapping experiments is employed to design the controller used in vertical flight. The design of the proposed controller relies on the idea of treating an exciting signal as a subsystem of the microrobot. The methods and results presented here are a key step toward achieving total autonomy of bio-inspired flying microrobots.

Defining the computational structure of the motion detector in Drosophila

Many animals rely on visual motion detection for survival. Motion information is extracted from spatiotemporal intensity patterns on the retina, a paradigmatic neural computation. A phenomenological model, the Hassenstein-Reichardt correlator (HRC), relates visual inputs to neural activity and behavioral responses to motion, but the circuits that implement this computation remain unknown. By using cell-type specific genetic silencing, minimal motion stimuli, and in vivo calcium imaging, we examine two critical HRC inputs. These two pathways respond preferentially to light and dark moving edges. We demonstrate that these pathways perform overlapping but complementary subsets of the computations underlying the HRC. A numerical model implementing differential weighting of these operations displays the observed edge preferences. Intriguingly, these pathways are distinguished by their sensitivities to a stimulus correlation that corresponds to an illusory percept, "reverse phi," that affects many species. Thus, this computational architecture may be widely used to achieve edge selectivity in motion detection.

Active and passive antennal movements during visually guided steering in flying Drosophila

Insects use feedback from a variety of sensory modalities, including mechanoreceptors on their antennae, to stabilize the direction and speed of flight. Like all arthropod appendages, antennae not only supply sensory information but may also be actively positioned by control muscles. However, how flying insects move their antennae during active turns and how such movements might influence steering responses are currently unknown. Here we examined the antennal movements of flying Drosophila during visually induced turns in a tethered flight arena. In response to both rotational and translational patterns of visual motion, Drosophila actively moved their antennae in a direction opposite to that of the visual motion. We also observed two types of passive antennal movements: small tonic deflections of the antenna and rapid oscillations at wing beat frequency. These passive movements are likely the result of wing-induced airflow and increased in magnitude when the angular distance between the wing and the antenna decreased. In response to rotational visual motion, increases in passive antennal movements appear to trigger a reflex that reduces the stroke amplitude of the contralateral wing, thereby enhancing the visually induced turn. Although the active antennal movements significantly increased antennal oscillation by bringing the arista closer to the wings, it did not significantly affect the turning response in our head-fixed, tethered flies. These results are consistent with the hypothesis that flying Drosophila use mechanosensory feedback to detect changes in the wing induced airflow during visually induced turns and that this feedback plays a role in regulating the magnitude of steering responses.

Neural correlates of illusory motion perception in Drosophila

When the contrast of an image flickers as it moves, humans perceive an illusory reversal in the direction of motion. This classic illusion, called reverse-phi motion, has been well-characterized using psychophysics, and several models have been proposed to account for its effects. Here, we show that Drosophila melanogaster also respond behaviorally to the reverse-phi illusion and that the illusion is present in dendritic calcium signals of motion-sensitive neurons in the fly lobula plate. These results closely match the predictions of the predominant model of fly motion detection. However, high flicker rates cause an inversion of the reverse-phi behavioral response that is also present in calcium signals of lobula plate tangential cell dendrites but not predicted by the model. The fly's behavioral and neural responses to the reverse-phi illusion reveal unexpected interactions between motion and flicker signals in the fly visual system and suggest that a similar correlation-based mechanism underlies visual motion detection across the animal kingdom.

Attention in Drosophila

As bluntly summarized by a psychologist over a century ago, everyone knows what attention is [James (1890). The Principles of Psychology]. Attention describes our capacity to focus perception on one or a group of related stimuli while filtering out irrelevant stimuli. The ease we have in recognizing this astounding capacity in ourselves is matched by a surprising difficulty in identifying it in others, and this is especially the case for measuring attention in other animals. Identifying and measuring attention-like processes in simple animals such as flies requires, to some extent, even more rigor than asking the same question for our closer animal relatives, such as apes and monkeys. This is because flies have completely different brains than humans do, so to study attention in these creatures one must rely purely on operational or behavioral measures rather than comparative neuroanatomy. There is a long history of using sophisticated behavioral paradigms to study visual responses in Drosophila melanogaster, and these studies have often provided early evidence of attention-like processes in flies. More recently, these fly paradigms have been applied to measuring visual attention directly, and the combination of electrophysiology with these preparations has provided insight into how a fly might pay attention. Together with more efficient methods for measuring some aspects of attention, such as stimulus suppression, these approaches should begin to uncover how visual attention might work in a small brain.

Intrinsic activity in the fly brain gates visual information during behavioral choices

The small insect brain is often described as an input/output system that executes reflex-like behaviors. It can also initiate neural activity and behaviors intrinsically, seen as spontaneous behaviors, different arousal states and sleep. However, less is known about how intrinsic activity in neural circuits affects sensory information processing in the insect brain and variability in behavior. Here, by simultaneously monitoring Drosophila's behavioral choices and brain activity in a flight simulator system, we identify intrinsic activity that is associated with the act of selecting between visual stimuli. We recorded neural output (multiunit action potentials and local field potentials) in the left and right optic lobes of a tethered flying Drosophila, while its attempts to follow visual motion (yaw torque) were measured by a torque meter. We show that when facing competing motion stimuli on its left and right, Drosophila typically generate large torque responses that flip from side to side. The delayed onset (0.1–1 s) and spontaneous switch-like dynamics of these responses, and the fact that the flies sometimes oppose the stimuli by flying straight, make this behavior different from the classic steering reflexes. Drosophila, thus, seem to choose one stimulus at a time and attempt to rotate toward its direction. With this behavior, the neural output of the optic lobes alternates; being augmented on the side chosen for body rotation and suppressed on the opposite side, even though the visual input to the fly eyes stays the same. Thus, the flow of information from the fly eyes is gated intrinsically. Such modulation can be noise-induced or intentional; with one possibility being that the fly brain highlights chosen information while ignoring the irrelevant, similar to what we know to occur in higher animals.

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

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

Drosophila fly straight by fixating objects in the face of expanding optic flow

Flies, 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.

Theta motion processing in fruit flies

The tiny brains of insects presumably impose significant computational limitations on algorithms controlling their behavior. Nevertheless, they perform fast and sophisticated visual maneuvers. This includes tracking features composed of second-order motion, in which the feature is defined by higher-order image statistics, but not simple correlations in luminance. Flies can track the true direction of even theta motions, in which the first-order (luminance) motion is directed opposite the second-order moving feature. We exploited this paradoxical feature tracking response to dissect the particular image properties that flies use to track moving objects. We find that theta motion detection is not simply a result of steering toward any spatially restricted flicker. Rather, our results show that fly high-order feature tracking responses can be broken down into positional and velocity components – in other words, the responses can be modeled as a superposition of two independent steering efforts. We isolate these elements to show that each has differing influence on phase and amplitude of steering responses, and together they explain the time course of second-order motion tracking responses during flight. These observations are relevant to natural scenes, where moving features can be much more complex.

Dynamics of optomotor responses in Drosophila to perturbations in optic flow

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

Processing of horizontal optic flow in three visual interneurons of the Drosophila brain

Motion vision is essential for navigating through the environment. Due to its genetic amenability, the fruit fly Drosophila has been serving for a lengthy period as a model organism for studying optomotor behavior as elicited by large-field horizontal motion. However, the neurons underlying the control of this behavior have not been studied in Drosophila so far. Here we report the first whole cell recordings from three cells of the horizontal system (HSN, HSE, and HSS) in the lobula plate of Drosophila. All three HS cells are tuned to large-field horizontal motion in a direction-selective way; they become excited by front-to-back motion and inhibited by back-to-front motion in the ipsilateral field of view. The response properties of HS cells such as contrast and velocity dependence are in accordance with the correlation-type model of motion detection. Neurobiotin injection suggests extensive coupling among ipsilateral HS cells and additional coupling to tangential cells that have their dendrites in the contralateral hemisphere of the brain. This connectivity scheme accounts for the complex layout of their receptive fields and explains their sensitivity both to ipsilateral and to contralateral motion. Thus the main response properties of Drosophila HS cells are strikingly similar to the responses of their counterparts in the blowfly Calliphora, although we found substantial differences with respect to their dendritic structure and connectivity. This long-awaited functional characterization of HS cells in Drosophila provides the basis for the future dissection of optomotor behavior and the underlying neural circuitry by combining genetics, physiology, and behavior.

Visual stabilization dynamics are enhanced by standing flight velocity

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

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

Sideslip force, longitudinal force, rolling moment, and pitching moment generated by tethered fruit flies, Drosophila melanogaster, were measured during optomotor reactions within an electronic flight simulator. Forces and torques were acquired by optically measuring the angular deflections of the beam to which the flies were tethered using a laser and a photodiode. Our results indicate that fruit flies actively generate both sideslip and roll in response to a lateral focus of expansion (FOE). The polarity of this behavior was such that the animal's aerodynamic response would carry it away from the expanding pattern, suggesting that it constitutes an avoidance reflex or centering response. Sideslip forces and rolling moments were sinusoidal functions of FOE position, whereas longitudinal force was proportional to the absolute value of the sine of FOE position. Pitching moments remained nearly constant irrespective of stimulus position or strength, with a direction indicating a tonic nose-down pitch under tethered conditions. These experiments expand our understanding of the degrees of freedom that a fruit fly can actually control in flight.

Context-dependent olfactory enhancement of optomotor flight control in Drosophila

Sensing and following the chemical plume of food odors is a fundamental challenge faced by many organisms. For flying insects, the task is complicated by wind that distorts the plume and buffets the fly. To maintain an upwind heading, and thus stabilize their orientation in a plume, insects such as flies and moths make use of strong context-specific visual equilibrium reflexes. For example, flying straight requires the regulation of image rotation across the eye, whereas minimizing side-slip and avoiding a collision require regulation of image expansion. In flies, visual rotation stabilizes plume tracking, but rotation and expansion optomotor responses are controlled by separate visual pathways. Are olfactory signals integrated with optomotor responses in a manner dependent upon visual context? We addressed this question by investigating the effect of an attractive food odor on active optomotor flight control. Odorant caused flies both to increase aerodynamic power output and to steer straighter. However, when challenged with wide-field optic flow, odor resulted in enhanced amplitude rotation responses but reduced amplitude expansion responses. For both visual conditions, flies tracked motion signals more closely in odor, an indication of increased saliency. These results suggest a simple search algorithm by which olfactory signals improve the salience of visual stimuli and modify optomotor control in a context-dependent manner, thereby enabling an animal to fly straight up a plume and approach odiferous objects.

The free-flight response of Drosophila to motion of the visual environment

In the present study we investigated the behavioural strategies with which freely flying fruit flies (Drosophila) control their flight trajectories during active optomotor stimulation in a free-flight arena. We measured forward, turning and climbing velocities of single flies using high-speed video analysis and estimated the output of a 'Hassenstein-Reichardt' elementary motion detector (EMD) array and the fly's gaze to evaluate flight behaviour in response to a rotating visual panorama. In a stationary visual environment, flight is characterized by flight saccades during which the animals turn on average 120 degrees within 130 ms. In a rotating environment, the fly's behaviour typically changes towards distinct, concentric circular flight paths where the radius of the paths increases with increasing arena velocity. The EMD simulation suggests that this behaviour is driven by a rotation-sensitive EMD detector system that minimizes retinal slip on each compound eye, whereas an expansion-sensitive EMD system with a laterally centred visual focus potentially helps to achieve centring response on the circular flight path. We developed a numerical model based on force balance between horizontal, vertical and lateral forces that allows predictions of flight path curvature at a given locomotor capacity of the fly. The model suggests that turning flight in Drosophila is constrained by the production of centripetal forces needed to avoid side-slip movements. At maximum horizontal velocity this force may account for up to 70% of the fly's body weight during yaw turning. Altogether, our analyses are widely consistent with previous studies on Drosophila free flight and those on the optomotor response under tethered flight conditions.

Synaptic plasticity can produce and enhance direction selectivity

The discrimination of the direction of movement of sensory images is critical to the control of many animal behaviors. We propose a parsimonious model of motion processing that generates direction selective responses using short-term synaptic depression and can reproduce salient features of direction selectivity found in a population of neurons in the midbrain of the weakly electric fish Eigenmannia virescens. The model achieves direction selectivity with an elementary Reichardt motion detector: information from spatially separated receptive fields converges onto a neuron via dynamically different pathways. In the model, these differences arise from convergence of information through distinct synapses that either exhibit or do not exhibit short-term synaptic depression—short-term depression produces phase-advances relative to nondepressing synapses. Short-term depression is modeled using two state-variables, a fast process with a time constant on the order of tens to hundreds of milliseconds, and a slow process with a time constant on the order of seconds to tens of seconds. These processes correspond to naturally occurring time constants observed at synapses that exhibit short-term depression. Inclusion of the fast process is sufficient for the generation of temporal disparities that are necessary for direction selectivity in the elementary Reichardt circuit. The addition of the slow process can enhance direction selectivity over time for stimuli that are sustained for periods of seconds or more. Transient (i.e., short-duration) stimuli do not evoke the slow process and therefore do not elicit enhanced direction selectivity. The addition of a sustained global, synchronous oscillation in the gamma frequency range can, however, drive the slow process and enhance direction selectivity to transient stimuli. This enhancement effect does not, however, occur for all combinations of model parameters. The ratio of depressing and nondepressing synapses determines the effects of the addition of the global synchronous oscillation on direction selectivity. These ingredients, short-term depression, spatial convergence, and gamma-band oscillations, are ubiquitous in sensory systems and may be used in Reichardt-style circuits for the generation and enhancement of a variety of biologically relevant spatiotemporal computations.

Short-term synaptic plasticity is ubiquitous in brain circuits, but its function in sensorimotor processing remains unclear. We propose a parsimonious model of motion processing using short-term depression to produce directionally selective responses. In the model circuit, information from two spatially separated receptive fields is combined after being asymmetrically processed by synapses that either exhibit short-term synaptic depression or do not. Motion in a preferred direction leads to a constructive interaction between the two channels; motion in the opposite direction does not. The model represents short-term synaptic depression as two processes with distinct time constants. The faster process alone suffices to generate direction selectivity in the circuit. The slow process, in contrast, can enhance direction selectivity to sustained stimuli. Therefore, the slow process mediates a form of attentional shift from alert, where the neuron responds more vigorously, to discriminating, where the neuron responds more selectively with fewer spikes. This explains a previously observed enhancement of direction selectivity in weakly electric fish in the presence of global synchronous gamma-band oscillations. These findings suggest a mechanistic connection between gamma-band oscillations and attention.

Crossmodal visual input for odor tracking during fly flight

Flies generate robust and high-performance olfactory and visual behaviors. Adult fruit flies can distinguish small differences in odor concentration across antennae separated by less than 1 mm [1], and a single olfactory sensory neuron is sufficient for near-normal gradient tracking in larvae [2]. During flight a male housefly chasing a female executes a corrective turn within 40 ms after a course deviation by its target [3]. The challenges imposed by flying apparently benefit from the tight integration of unimodal sensory cues. Crossmodal interactions reduce the discrimination threshold for unimodal memory retrieval by enhancing stimulus salience [4], and dynamic crossmodal processing is required for odor search during free flight because animals fail to locate an odor source in the absence of rich visual feedback [5]. The visual requirements for odor localization are unknown. We tethered a hungry fly in a magnetic field, allowing it to yaw freely, presented odor plumes, and examined how visual cues influence odor tracking. We show that flies are unable to use a small-field object or landmark to assist plume tracking, whereas odor activates wide-field optomotor course control to enable accurate orientation toward an attractive food odor.

The spatial, temporal and contrast properties of expansion and rotation flight optomotor responses inDrosophila

Fruit flies respond to panoramic retinal patterns of visual expansion with robust steering maneuvers directed away from the focus of expansion to avoid collisions and maintain an upwind flight posture. Panoramic rotation elicits comparatively weak syndirectional steering maneuvers, which also maintain visual stability. Full-field optic flow patterns like expansion and rotation are elicited by distinct flight maneuvers such as body translation during straight flight or body rotation during hovering, respectively. Recent analyses suggest that under some experimental conditions the rotation optomotor response reflects the linear sum of different expansion response components. Are expansion and rotation-mediated visual stabilization responses part of a single optomotor response subserved by a neural circuit that is differentially stimulated by the two flow fields, or rather do the two behavioral responses reflect two distinct control systems? Guided by the principle that the properties of neural circuits are revealed in the behaviors they mediate, we systematically varied the spatial, temporal and contrast properties of expansion and rotation stimuli, and quantified the time course and amplitude of optomotor responses during tethered flight. Our results support the conclusion that expansion and rotation optomotor responses are indeed two separate reflexes, which draw from the same system of elementary motion detectors, but are likely mediated by separate pre-motor circuits having different spatial integration properties, low-pass characteristics and contrast sensitivity.

A modular display system for insect behavioral neuroscience

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.

A comparison of visual and haltere-mediated feedback in the control of body saccades in Drosophila melanogaster

The 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.

Dynamic properties of large-field and small-field optomotor flight responses in Drosophila

Optomotor flight control in houseflies shows bandwidth fractionation such that steering responses to an oscillating large-field rotating panorama peak at low frequency, whereas responses to small-field objects peak at high frequency. In fruit flies, steady-state large-field translation generates steering responses that are three times larger than large-field rotation. Here, we examine the optomotor steering reactions to dynamically oscillating visual stimuli consisting of large-field rotation, large-field expansion, and small-field motion. The results show that, like in larger flies, large-field optomotor steering responses peak at low frequency, whereas small-field responses persist under high frequency conditions. However, in fruit flies large-field expansion elicits higher magnitude and tighter phase-locked optomotor responses than rotation throughout the frequency spectrum, which may suggest a further segregation within the large-field pathway. An analysis of wing beat frequency and amplitude reveals that mechanical power output during flight varies according to the spatial organization and motion dynamics of the visual scene. These results suggest that, like in larger flies, the optomotor control system is organized into parallel large-field and small-field pathways, and extends previous analyses to quantify expansion-sensitivity for steering reflexes and flight power output across the frequency spectrum.

The critical role of locomotion mechanics in decoding sensory systems

How do neural systems process sensory information to control locomotion? The weakly electric knifefish Eigenmannia, an ideal model for studying sensorimotor control, swims to stabilize the sensory image of a sinusoidally moving refuge. Tracking performance is best at stimulus frequencies less than approximately 1 Hz. Kinematic analysis, which is widely used in the study of neural control of movement, predicts commensurately low-pass sensory processing for control. The inclusion of Newtonian mechanics in the analysis of the behavior, however, categorically shifts the prediction: this analysis predicts that sensory processing is high pass. The counterintuitive prediction that a low-pass behavior is controlled by a high-pass neural filter nevertheless matches previously reported but poorly understood high-pass filtering seen in electrosensory afferents and downstream neurons. Furthermore, a model incorporating the high-pass controller matches animal behavior, whereas the model with the low-pass controller does not and is unstable. Because locomotor mechanics are similar in a wide array of animals, these data suggest that such high-pass sensory filters may be a general mechanism used for task-level locomotion control. Furthermore, these data highlight the critical role of mechanical analyses in addition to widely used kinematic analyses in the study of neural control systems.

Visual stimulation of saccades in magnetically tetheredDrosophila

Flying 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.