Saccadic body turns in walking Drosophila

Fine-grained descending control of steering in walking Drosophila

Locomotion involves rhythmic limb movement patterns that originate in circuits outside the brain. Purposeful locomotion requires descending commands from the brain, but we do not understand how these commands are structured. Here we investigate this issue, focusing on the control of steering in walking Drosophila. First, we describe different limb "gestures" associated with different steering maneuvers. Next, we identify a set of descending neurons whose activity predicts steering. Focusing on two descending cell types downstream from distinct brain networks, we show that they evoke specific limb gestures: one lengthens strides on the outside of a turn, while the other attenuates strides on the inside of a turn. Notably, a single descending neuron can have opposite effects during different locomotor rhythm phases, and we identify networks positioned to implement this phase-specific gating. Together, our results show how purposeful locomotion emerges from brain cells that drive specific, coordinated modulations of low-level patterns.

Neural Networks for Navigation: From Connections to Computations

Many animals can navigate toward a goal they cannot see based on an internal representation of that goal in the brain's spatial maps. These maps are organized around networks with stable fixed-point dynamics (attractors), anchored to landmarks, and reciprocally connected to motor control. This review summarizes recent progress in understanding these networks, focusing on studies in arthropods. One factor driving recent progress is the availability of the Drosophila connectome; however, it is increasingly clear that navigation depends on ongoing synaptic plasticity in these networks. Functional synapses appear to be continually reselected from the set of anatomical potential synapses based on the interaction of Hebbian learning rules, sensory feedback, attractor dynamics, and neuromodulation. This can explain how the brain's maps of space are rapidly updated; it may also explain how the brain can initialize goals as stable fixed points for navigation.

Visual and motor signatures of locomotion dynamically shape a population code for feature detection in Drosophila

Natural vision is dynamic: as an animal moves, its visual input changes dramatically. How can the visual system reliably extract local features from an input dominated by self-generated signals? In Drosophila, diverse local visual features are represented by a group of projection neurons with distinct tuning properties. Here, we describe a connectome-based volumetric imaging strategy to measure visually evoked neural activity across this population. We show that local visual features are jointly represented across the population, and a shared gain factor improves trial-to-trial coding fidelity. A subset of these neurons, tuned to small objects, is modulated by two independent signals associated with self-movement, a motor-related signal, and a visual motion signal associated with rotation of the animal. These two inputs adjust the sensitivity of these feature detectors across the locomotor cycle, selectively reducing their gain during saccades and restoring it during intersaccadic intervals. This work reveals a strategy for reliable feature detection during locomotion.

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

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

Learning accurate path integration in ring attractor models of the head direction system

Ring attractor models for angular path integration have received strong experimental support. To function as integrators, head direction circuits require precisely tuned connectivity, but it is currently unknown how such tuning could be achieved. Here, we propose a network model in which a local, biologically plausible learning rule adjusts synaptic efficacies during development, guided by supervisory allothetic cues. Applied to the Drosophila head direction system, the model learns to path-integrate accurately and develops a connectivity strikingly similar to the one reported in experiments. The mature network is a quasi-continuous attractor and reproduces key experiments in which optogenetic stimulation controls the internal representation of heading in flies, and where the network remaps to integrate with different gains in rodents. Our model predicts that path integration requires self-supervised learning during a developmental phase, and proposes a general framework to learn to path-integrate with gain-1 even in architectures that lack the physical topography of a ring.

NeuroMechFly, a neuromechanical model of adult Drosophila melanogaster

Animal behavior emerges from an interaction between neural network dynamics, musculoskeletal properties and the physical environment. Accessing and understanding the interplay between these elements requires the development of integrative and morphologically realistic neuromechanical simulations. Here we present NeuroMechFly, a data-driven model of the widely studied organism, Drosophila melanogaster. NeuroMechFly combines four independent computational modules: a physics-based simulation environment, a biomechanical exoskeleton, muscle models and neural network controllers. To enable use cases, we first define the minimum degrees of freedom of the leg from real three-dimensional kinematic measurements during walking and grooming. Then, we show how, by replaying these behaviors in the simulator, one can predict otherwise unmeasured torques and contact forces. Finally, we leverage NeuroMechFly's full neuromechanical capacity to discover neural networks and muscle parameters that drive locomotor gaits optimized for speed and stability. Thus, NeuroMechFly can increase our understanding of how behaviors emerge from interactions between complex neuromechanical systems and their physical surroundings.

EasyFlyTracker: A Simple Video Tracking Python Package for Analyzing Adult Drosophila Locomotor and Sleep Activity to Facilitate Revealing the Effect of Psychiatric Drugs

The mechanism of psychiatric drugs (stimulant and non-stimulant) is still unclear. Precision medication of psychiatric disorders faces challenges in pharmacogenetics and pharmacodynamics research due to difficulties in recruiting human subjects because of possibility of substance abuse and relatively small sample sizes. Drosophila is a powerful animal model for large-scale studies of drug effects based on the precise quantification of behavior. However, a user-friendly system for high-throughput simultaneous tracking and analysis of drug-treated individual adult flies is still lacking. It is critical to quickly setup a working environment including both the hardware and software at a reasonable cost. Thus, we have developed EasyFlyTracker, an open-source Python package that can track single fruit fly in each arena and analyze Drosophila locomotor and sleep activity based on video recording to facilitate revealing the psychiatric drug effects. The current version does not support multiple fruit fly tracking. Compared with existing software, EasyFlyTracker has the advantages of low cost, easy setup and scaling, rich statistics of movement trajectories, and compatibility with different video recording systems. Also, it accepts multiple video formats such as common MP4 and AVI formats. EasyFlyTracker provides a cross-platform and user-friendly interface combining command line and graphic configurations, which allows users to intuitively understand the process of tracking and downstream analyses and automatically generates multiple files, especially plots. Users can install EasyFlyTracker, go through tutorials, and give feedback on http://easyflytracker.cibr.ac.cn. Moreover, we tested EasyFlyTracker in a study of Drosophila melanogaster on the hyperactivity-like behavior effects of two psychiatric drugs, methylphenidate and atomoxetine, which are two commonly used drugs treating attention-deficit/hyperactivity disorder (ADHD) in human. This software has the potential to accelerate basic research on drug effect studies with fruit flies.

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

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

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

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

Multiscale 'whole-cell' models to study neural information processing - New insights from fly photoreceptor studies

Understanding a neuron's input-output relationship is a longstanding challenge. Arguably, these signalling dynamics can be better understood if studied at three levels of analysis: computational, algorithmic and implementational (Marr, 1982). But it is difficult to integrate such analyses into a single platform that can realistically simulate neural information processing. Multiscale dynamical "whole-cell" modelling, a recent systems biology approach, makes this possible. Dynamical "whole-cell" models are computational models that aim to account for the integrated function of numerous genes or molecules to behave like virtual cells in silico. However, because constructing such models is laborious, only a couple of examples have emerged since the first one, built for Mycoplasma genitalium bacterium, was reported in 2012. Here, we review dynamic "whole-cell" neuron models for fly photoreceptors and how these have been used to study neural information processing. Specifically, we review how the models have helped uncover the mechanisms and evolutionary rules of quantal light information sampling and integration, which underlie light adaptation and further improve our understanding of insect vision.

Walking Drosophila navigate complex plumes using stochastic decisions biased by the timing of odor encounters

How insects navigate complex odor plumes, where the location and timing of odor packets are uncertain, remains unclear. Here we imaged complex odor plumes simultaneously with freely-walking flies, quantifying how behavior is shaped by encounters with individual odor packets. We found that navigation was stochastic and did not rely on the continuous modulation of speed or orientation. Instead, flies turned stochastically with stereotyped saccades, whose direction was biased upwind by the timing of prior odor encounters, while the magnitude and rate of saccades remained constant. Further, flies used the timing of odor encounters to modulate the transition rates between walks and stops. In more regular environments, flies continuously modulate speed and orientation, even though encounters can still occur randomly due to animal motion. We find that in less predictable environments, where encounters are random in both space and time, walking flies navigate with random walks biased by encounter timing.

Frequency-specific modification of locomotor components by the white gene in Drosophila melanogaster adult flies

The classic eye-color gene white (w) in Drosophila melanogaster (fruitfly) has unexpected behavioral consequences. How w affects locomotion of adult flies is largely unknown. Here, we show that a mutant allele (w¹¹¹⁸ ) selectively increases locomotor components at relatively high frequencies (> 0.1 Hz). The w¹¹¹⁸ flies had reduced transcripts of w⁺ from the 5' end of the gene. Male flies of w¹¹¹⁸ walked continuously in circular arenas while the wildtype Canton-S walked intermittently. Through careful control of genetic and cytoplasmic backgrounds, we found that the w¹¹¹⁸ locus was associated with continuous walking. w¹¹¹⁸ -carrying male flies showed increased median values of path length per second (PPS) and 5-min path length compared with w⁺ -carrying males. Additionally, flies carrying 2-4 genomic copies of mini-white⁺ (mw⁺ ) in the w¹¹¹⁸ background showed suppressed median PPSs and decreased 5-min path length compared with controls, and the suppression was dependent on the copy number of mw⁺ . Analysis of the time-series (i.e., PPSs over time) by Fourier transform indicated that w¹¹¹⁸ was associated with increased locomotor components at relatively high frequencies (> 0.1 Hz). The addition of multiple genomic copies of mw⁺ (2-4 copies) suppressed the high-frequency components. Lastly, the downregulation of w⁺ in neurons but not glial cells resulted in increased high-frequency components. We concluded that mutation of w modified the locomotion in adult flies by selectively increasing high-frequency locomotor components.

Tools for Rapid High-Resolution Behavioral Phenotyping of Automatically Isolated Drosophila

Sparse manipulation of neuron excitability during free behavior is critical for identifying neural substrates of behavior. Genetic tools for precise neuronal manipulation exist in the fruit fly, Drosophila melanogaster, but behavioral tools are still lacking to identify potentially subtle phenotypes only detectible using high-throughput and high spatiotemporal resolution. We developed three assay components that can be used modularly to study natural and optogenetically induced behaviors. FlyGate automatically releases flies one at a time into an assay. FlyDetect tracks flies in real time, is robust to severe occlusions, and can be used to track appendages, such as the head. GlobeDisplay is a spherical projection system covering the fly's visual receptive field with a single projector. We demonstrate the utility of these components in an integrated system, FlyPEZ, by comprehensively modeling the input-output function for directional looming-evoked escape takeoffs and describing a millisecond-timescale phenotype from genetic silencing of a single visual projection neuron type.

A locomotor assay reveals deficits in heterozygous Parkinson's disease model and proprioceptive mutants in adult Drosophila

Severe locomotor impairment is a common phenotype of neurodegenerative disorders such as Parkinson's disease (PD). Drosophila models of PD, studied for more than a decade, have helped in understanding the interaction between various genetic factors, such as parkin and PINK1, in this disease. To characterize locomotor behavioral phenotypes for these genes, fly climbing assays have been widely used. While these simple current assays for locomotor defects in Drosophila mutants measure some locomotor phenotypes well, it is possible that detection of subtle changes in behavior is important to understand the manifestation of locomotor disorders. We introduce a climbing behavior assay which provides such fine-scale behavioral data and tests this proposition for the Drosophila model. We use this inexpensive, fully automated assay to quantitatively characterize the climbing behavior at high parametric resolution in 3 contexts. First, we characterize wild-type flies and uncover a hitherto unknown sexual dimorphism in climbing behavior. Second, we study climbing behavior of heterozygous mutants of genes implicated in the fly PD model and reveal previously unreported prominent locomotor defects in some of these heterozygous fly lines. Finally, we study locomotor defects in a homozygous proprioceptory mutation (Trp-γ1 ) known to affect fine motor control in Drosophila Moreover, we identify aberrant geotactic behavior in Trp-γ1 mutants, thereby opening up a finer assay for geotaxis and its genetic basis. Our assay is therefore a cost-effective, general tool for measuring locomotor behaviors of wild-type and mutant flies in fine detail and can reveal subtle motor defects.

Strategies of locomotion composition

This review aims to highlight the importance of saccades during locomotion as a strategy to reduce sensory information loss while the subject is moving. Acquiring sensory data from the environment during movement results in a temporal flow of information, as the sensory precept changes with the position of the observer. Accordingly, the movement pattern shapes the sensory flow. Therefore, the requirements of locomotion and sensation have to be balanced in the behaviour of the organism. Insect vision provides deep insight into the interplay between action and perception. Insects can shape their optic flow by reducing their rotational movements to fast and short saccades. This generates prolonged phases of translations which provide depth information. Extensive behavioural and physiological studies on insects show how shaping the optic flow facilitates the coding of motion vision. Indeed the saccadic strategy provides an elegant solution to optimise sensory flow. Complementary studies in other taxa reported similar locomotion strategies emphasising the crucial influence of sensory flow on locomotion.

The manifold structure of limb coordination in walking Drosophila

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

Sugar Intake Elicits Intelligent Searching Behavior in Flies and Honey Bees

We present a comparison of the sugar-elicited search behavior in Drosophila melanogaster and Apis mellifera. In both species, intake of sugar-water elicits a complex of searching responses. The most obvious response was an increase in turning frequency. However, we also found that flies and honey bees returned to the location of the sugar drop. They even returned to the food location when we prevented them from using visual and chemosensory cues. Analyses of the recorded trajectories indicated that flies and bees use two mechanisms, a locomotor pattern involving an increased turning frequency and path integration to increase the probability to stay close or even return to the sugar drop location. However, evidence for the use of path integration in honey bees was less clear. In general, walking trajectories of honey bees showed a higher degree of curvature and were more spacious; two characters which likely masked evidence for the use of path integration in our experiments. Visual cues, i.e., a black dot, presented underneath the sugar drop made flies and honey bees stay closer to the starting point of the search. In honey bees, vertical black columns close to the sugar drop increased the probability to visit similar cues in the vicinity. An additional one trial learning experiment suggested that the intake of sugar-water likely has the potential to initiate an associative learning process. Together, our experiments indicate that the sugar-elicited local search is more complex than previously assumed. Most importantly, this local search behavior appeared to exhibit major behavioral capabilities of large-scale navigation. Thus, we propose that sugar-elicited search behavior has the potential to become a fruitful behavioral paradigm to identify neural and molecular mechanisms involved in general mechanisms of navigation.

Can Drosophila melanogaster tell who's who?

Drosophila melanogaster are known to live in a social but cryptic world of touch and odours, but the extent to which they can perceive and integrate static visual information is a hotly debated topic. Some researchers fixate on the limited resolution of D. melanogaster's optics, others on their seemingly identical appearance; yet there is evidence of individual recognition and surprising visual learning in flies. Here, we apply machine learning and show that individual D. melanogaster are visually distinct. We also use the striking similarity of Drosophila's visual system to current convolutional neural networks to theoretically investigate D. melanogaster's capacity for visual understanding. We find that, despite their limited optical resolution, D. melanogaster's neuronal architecture has the capability to extract and encode a rich feature set that allows flies to re-identify individual conspecifics with surprising accuracy. These experiments provide a proof of principle that Drosophila inhabit a much more complex visual world than previously appreciated.

Microsaccadic sampling of moving image information provides Drosophila hyperacute vision

Small fly eyes should not see fine image details. Because flies exhibit saccadic visual behaviors and their compound eyes have relatively few ommatidia (sampling points), their photoreceptors would be expected to generate blurry and coarse retinal images of the world. Here we demonstrate that Drosophila see the world far better than predicted from the classic theories. By using electrophysiological, optical and behavioral assays, we found that R1-R6 photoreceptors’ encoding capacity in time is maximized to fast high-contrast bursts, which resemble their light input during saccadic behaviors. Whilst over space, R1-R6s resolve moving objects at saccadic speeds beyond the predicted motion-blur-limit. Our results show how refractory phototransduction and rapid photomechanical photoreceptor contractions jointly sharpen retinal images of moving objects in space-time, enabling hyperacute vision, and explain how such microsaccadic information sampling exceeds the compound eyes’ optical limits. These discoveries elucidate how acuity depends upon photoreceptor function and eye movements.

Fruit flies have five eyes: two large compound eyes which support vision, plus three smaller single lens eyes which are used for navigation. Each compound eye monitors 180° of space and consists of roughly 750 units, each containing eight light-sensitive cells called photoreceptors. This relatively wide spacing of photoreceptors is thought to limit the sharpness, or acuity, of vision in fruit flies. The area of the human retina (the light-sensitive surface at back of our eyes) that generates our sharpest vision contains photoreceptors that are 500 times more densely packed.

Despite their differing designs, human and fruit fly eyes work via the same general principles. If we, or a fruit fly, were to hold our gaze completely steady, the world would gradually fade from view as the eye adapted to the unchanging visual stimulus. To ensure this does not happen, animals continuously make rapid, automatic eye movements called microsaccades. These refresh the image on the retina and prevent it from fading. Yet it is not known why do they not also cause blurred vision.

Standard accounts of vision assume that the retina and the brain perform most of the information processing required, with photoreceptors simply detecting how much light enters the eye. However, Juusola, Dau, Song et al. now challenge this idea by showing that photoreceptors are specially adapted to detect the fluctuating patterns of light that enter the eye as a result of microsaccades. Moreover, fruit fly eyes resolve small moving objects far better than would be predicted based on the spacing of their photoreceptors.

The discovery that photoreceptors are well adapted to deal with eye movements changes our understanding of insect vision. The findings also disprove the 100-year-old dogma that the spacing of photoreceptors limits the sharpness of vision in compound eyes. Further studies are required to determine whether photoreceptors in the retinas of other animals, including humans, have similar properties.

Dynamic structure of locomotor behavior in walking fruit flies

The function of the brain is unlikely to be understood without an accurate description of its output, yet the nature of movement elements and their organization remains an open problem. Here, movement elements are identified from dynamics of walking in flies, using unbiased criteria. On one time scale, dynamics of walking are consistent over hundreds of milliseconds, allowing elementary features to be defined. Over longer periods, walking is well described by a stochastic process composed of these elementary features, and a generative model of this process reproduces individual behavior sequences accurately over seconds or longer. Within elementary features, velocities diverge, suggesting that dynamical stability of movement elements is a weak behavioral constraint. Rather, long-term instability can be limited by the finite memory between these elementary features. This structure suggests how complex dynamics may arise in biological systems from elements whose combination need not be tuned for dynamic stability.

Saccadic movement strategy in a semiaquatic species - the harbour seal (Phoca vitulina)

Moving animals can estimate the distance of visual objects from image shift on their retina (optic flow) created during translational, but not rotational movements. To facilitate this distance estimation, many terrestrial and flying animals perform saccadic movements, thereby temporally separating translational and rotational movements, keeping rotation times short. In this study, we analysed whether a semiaquatic mammal, the harbour seal, also adopts a saccadic movement strategy. We recorded the seals' normal swimming pattern with video cameras and analysed head and body movements. The swimming seals indeed minimized rotation times by saccadic head and body turns, with top rotation speeds exceeding 350 deg s^-1 which leads to an increase of translational movements. Saccades occurred during both types of locomotion of the seals' intermittent swimming mode: active propulsion and gliding. In conclusion, harbour seals share the saccadic movement strategy of terrestrial animals. Whether this movement strategy is adopted to facilitate distance estimation from optic flow or serves a different function will be a topic of future research.

Saccadic Movement Strategy in Common Cuttlefish (Sepia officinalis)

Most moving animals segregate their locomotion trajectories in short burst like rotations and prolonged translations, to enhance distance information from optic flow, as only translational, but not rotational optic flow holds distance information. Underwater, optic flow is a valuable source of information as it is in the terrestrial habitat, however, so far, it has gained only little attention. To extend the knowledge on underwater optic flow perception and use, we filmed the movement pattern of six common cuttlefish (Sepia officinalis) with a high speed camera in this study. In the subsequent analysis, the center of mass of the cuttlefish body was manually traced to gain thrust, slip, and yaw of the cuttlefish movements over time. Cuttlefish indeed performed short rotations, saccades, with rotational velocities up to 343°/s. They clearly separated rotations from translations in line with the saccadic movement strategy documented for animals inhabiting the terrestrial habitat as well as for the semiaquatic harbor seals before. However, this separation only occurred during fin motion. In contrast, during jet propelled swimming, the separation between rotational and translational movements and thus probably distance estimation on the basis of the optic flow field is abolished in favor of high movement velocities. In conclusion, this study provides first evidence that an aquatic invertebrate, the cuttlefish, adopts a saccadic movement strategy depending on the behavioral context that could enhance the information gained from optic flow.

Neuroligins Nlg2 and Nlg4 Affect Social Behavior in Drosophila melanogaster

The genome of Drosophila melanogaster includes homologs to approximately one-third of the currently known human disease genes. Flies and humans share many biological processes, including the principles of information processing by excitable neurons, synaptic transmission, and the chemical signals involved in intercellular communication. Studies on the molecular and behavioral impact of genetic risk factors of human neuro-developmental disorders [autism spectrum disorders (ASDs), schizophrenia, attention deficit hyperactivity disorders, and Tourette syndrome] increasingly use the well-studied social behavior of D. melanogaster, an organism that is amenable to a large variety of genetic manipulations. Neuroligins (Nlgs) are a family of phylogenetically conserved postsynaptic adhesion molecules present (among others) in nematodes, insects, and mammals. Impaired function of Nlgs (particularly of Nlg 3 and 4) has been associated with ASDs in humans and impaired social and communication behavior in mice. Making use of a set of behavioral and social assays, we, here, analyzed the impact of two Drosophila Nlgs, Dnlg2 and Dnlg4, which are differentially expressed at excitatory and inhibitory central nervous synapses, respectively. Both Nlgs seem to be associated with diurnal activity and social behavior. Even though deficiencies in Dnlg2 and Dnlg4 appeared to have no effects on sensory or motor systems, they differentially impacted on social interactions, suggesting that social behavior is distinctly regulated by these Nlgs.

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

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