Quantification of gait parameters in freely walking wild type and sensory deprived Drosophila melanogaster

Inhibitory circuits generate rhythms for leg movements during Drosophila grooming

Limbs execute diverse actions coordinated by the nervous system through multiple motor programs. The basic architecture of motor neurons that activate muscles which articulate joints for antagonistic flexion and extension movements is conserved from flies to vertebrates. While excitatory premotor circuits are expected to establish sets of leg motor neurons that work together, our study uncovered an instructive role for inhibitory circuits - including their ability to generate rhythmic leg movements. Using electron microscopy data in the Drosophila nerve cord, we categorized ~120 GABAergic inhibitory neurons from the 13A and 13B hemilineages into classes based on similarities in morphology and connectivity. By mapping their connections, we uncovered pathways for inhibiting specific groups of motor neurons, disinhibiting antagonistic counterparts, and inducing alternation between flexion and extension. We tested the function of specific inhibitory neurons through optogenetic activation and silencing, using high resolution quantitative analysis of leg movements during grooming. We combined findings from anatomical and behavioral analyses to construct a computational model that can reproduce major aspects of the observed behavior, confirming sufficiency of these premotor inhibitory circuits to generate rhythms.

Sensorimotor delays constrain robust locomotion in a 3D kinematic model of fly walking

Walking animals must maintain stability in the presence of external perturbations, despite significant temporal delays in neural signaling and muscle actuation. Here, we develop a 3D kinematic model with a layered control architecture to investigate how sensorimotor delays constrain robustness of walking behavior in the fruit fly, Drosophila. Motivated by the anatomical architecture of insect locomotor control circuits, our model consists of three component layers: a neural network that generates realistic 3D joint kinematics for each leg, an optimal controller that executes the joint kinematics while accounting for delays, and an inter-leg coordinator. The model generates realistic simulated walking that resembles real fly walking kinematics and sustains walking even when subjected to unexpected perturbations, generalizing beyond its training data. However, we found that the model's robustness to perturbations deteriorates when sensorimotor delay parameters exceed the physiological range. These results suggest that fly sensorimotor control circuits operate close to the temporal limit at which they can detect and respond to external perturbations. More broadly, we show how a modular, layered model architecture can be used to investigate physiological constraints on animal behavior.

Natural variability and individuality of walking behavior in Drosophila

Insects use walking behavior in a large number of contexts, such as exploration, foraging, escape and pursuit, or migration. A lot is known about how nervous systems produce this behavior in general and also how certain parameters vary with regard to walking direction or speed, for instance. An aspect that has not received much attention is whether and how walking behavior varies across individuals of a particular species. To address this, we created a large corpus of kinematic walking data of many individuals of the fruit fly Drosophila. We only selected instances of straight walking in a narrow range of walking speeds to minimize the influence of high-level parameters, such as turning and walking speed, aiming to uncover more subtle aspects of variability. Using high-speed videography and automated annotation, we captured the positions of the six leg tips for thousands of steps and used principal components analysis to characterize the postural space individuals used during walking. Our analysis shows that the largest part of walking kinematics can be described by five principal components (PCs). Separation of these five PCs into a 2D and a 3D subspace divided the description of walking behavior into invariant features shared across individuals and features that relate to the specifics of individuals; the latter features can be regarded as idiosyncrasies. We also demonstrate that this approach can detect the effects of experimental interventions in an unbiased manner and that general aspects of individuality, such as the individual walking posture, can be described.

Neural circuit mechanisms underlying context-specific halting in Drosophila

Walking is a complex motor programme involving coordinated and distributed activity across the brain and the spinal cord. Halting appropriately at the correct time is a critical component of walking control. Despite progress in identifying neurons driving halting1-6, the underlying neural circuit mechanisms responsible for overruling the competing walking state remain unclear. Here, using connectome-informed models7-9 and functional studies, we explain two fundamental mechanisms by which Drosophila implement context-appropriate halting. The first mechanism ('walk-OFF') relies on GABAergic neurons that inhibit specific descending walking commands in the brain, whereas the second mechanism ('brake') relies on excitatory cholinergic neurons in the nerve cord that lead to an active arrest of stepping movements. We show that two neurons that deploy the walk-OFF mechanism inhibit distinct populations of walking-promotion neurons, leading to differential halting of forward walking or turning. The brake neurons, by constrast, override all walking commands by simultaneously inhibiting descending walking-promotion neurons and increasing the resistance at the leg joints. We characterized two behavioural contexts in which the distinct halting mechanisms were used by the animal in a mutually exclusive manner: the walk-OFF mechanism was engaged for halting during feeding and the brake mechanism was engaged for halting and stability during grooming.

Comparative analysis of tardigrade locomotion across life stage, species, and disulfiram treatment

Animal locomotion requires coordination between the central and peripheral nervous systems, between sensory inputs and motor outputs, and between nerves and muscles. Analysis of locomotion thus provides a comprehensive and sensitive readout of nervous system function and dysfunction. Tardigrades, the smallest known walking animals, coordinate movement of their eight legs with a relatively simple nervous system, and are a promising model for neuronal control of limb-driven locomotion. Here, we developed open-source tools for automated tracking of tardigrade locomotion in an unconstrained two-dimensional environment, for measuring multiple parameters of individual leg movements, and for quantifying interleg coordination. We used these tools to analyze >13,000 complete strides in >100 tardigrades, and identified preferred walking speeds and distinct step coordination patterns associated with those speeds. In addition, the rear legs of tardigrades, although they have distinct anatomy and step kinematics, were nonetheless incorporated into overall patterns of interleg coordination. Finally, comparisons of tardigrade locomotion across lifespan, between species, and upon disulfiram treatment suggested that neuronal regulation of high-level aspects of walking (e.g. speed, turns, walking bout initiation) operate independently from circuits controlling individual leg movements and interleg coordination.

Kinematics and coordination of moth flies walking on smooth and rough surfaces

The moth fly, Clogmia albipunctata, is a common synanthropic insect with a worldwide range that lives in nearly any area with moist, decaying organic matter. These habitats comprise both smooth, slippery substrates (e.g., bathroom drains) and heterogeneous, bumpy ground (e.g., soil in plant pots). By using terrain of varying levels of roughness, we focus specifically on how substrate roughness at the approximate size scale of the organism affects kinematics and coordination in adult moth flies. Finally, we compare and contrast our characterizations of locomotion in C. albipunctata with previous work of insect walking in naturalistic environments.

Neuronal mechanisms regulating locomotion in adult Drosophila

The coordinated action of multiple leg joints and muscles is required even for the simplest movements. Understanding the neuronal circuits and mechanisms that generate precise movements is essential for comprehending the neuronal basis of the locomotion and to infer the neuronal mechanisms underlying several locomotor-related diseases. Drosophila melanogaster provides an excellent model system for investigating the neuronal circuits underlying motor behaviors due to its simple nervous system and genetic accessibility. This review discusses current genetic methods for studying locomotor circuits and their function in adult Drosophila. We highlight recently identified neuronal pathways that modulate distinct forward and backward locomotion and describe the underlying neuronal control of leg swing and stance phases in freely moving flies. We also report various automated leg tracking methods to measure leg motion parameters and define inter-leg coordination, gait and locomotor speed of freely moving adult flies. Finally, we emphasize the role of leg proprioceptive signals to central motor circuits in leg coordination. Together, this review highlights the utility of adult Drosophila as a model to uncover underlying motor circuitry and the functional organization of the leg motor system that governs correct movement.

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.

DVT: a high-throughput analysis pipeline for locomotion and social behavior in adult Drosophila melanogaster

BACKGROUND

Drosophila melanogaster is excellent animal model for understanding the molecular basis of human neurological and motor disorders. The experimental conditions and chamber design varied between studies. Moreover, most previously established paradigms focus on fly trace detection algorithm development. A comprehensive understanding on how fly behaves in the chamber is still lacking.

RESULTS

In this report, we established 74 unique behavior metrics quantifying spatiotemporal characteristics of adult fly locomotion and social behaviors, of which 49 were newly proposed. By the aiding of the developed analysis pipeline, Drosophila video tracking (DVT), we identified siginificantly different patterns of fly behavior confronted with different chamber height, fly density, illumination and experimental time. Meanwhile, three fly strains which are widely used as control lines, Canton-S(CS), w1118 and Oregon-R (OR), were found to exhibit distinct motion explosiveness and exercise endurance.

CONCLUSIONS

We believe the proposed behavior metrics set and pipeline should help identify subtle spatial and temporal differences of drosophila behavior confronted with different environmental factors or gene variants.

Mechanosensory Control of Locomotion in Animals and Robots: Moving Forward

While animals swim, crawl, walk, and fly with apparent ease, building robots capable of robust locomotion remains a significant challenge. In this review, we draw attention to mechanosensation-the sensing of mechanical forces generated within and outside the body-as a key sense that enables robust locomotion in animals. We discuss differences between mechanosensation in animals and current robots with respect to (1) the encoding properties and distribution of mechanosensors and (2) the integration and regulation of mechanosensory feedback. We argue that robotics would benefit greatly from a detailed understanding of these aspects in animals. To that end, we highlight promising experimental and engineering approaches to study mechanosensation, emphasizing the mutual benefits for biologists and engineers that emerge from moving forward together.

Distinctive features of the central synaptic organization of Drosophila larval proprioceptors

Proprioceptive feedback is critically needed for locomotor control, but how this information is incorporated into central proprioceptive processing circuits remains poorly understood. Circuit organization emerges from the spatial distribution of synaptic connections between neurons. This distribution is difficult to discern in model systems where only a few cells can be probed simultaneously. Therefore, we turned to a relatively simple and accessible nervous system to ask: how are proprioceptors' input and output synapses organized in space, and what principles underlie this organization? Using the Drosophila larval connectome, we generated a map of the input and output synapses of 34 proprioceptors in several adjacent body segments (5-6 left-right pairs per segment). We characterized the spatial organization of these synapses, and compared this organization to that of other somatosensory neurons' synapses. We found three distinguishing features of larval proprioceptor synapses: (1) Generally, individual proprioceptor types display segmental somatotopy. (2) Proprioceptor output synapses both converge and diverge in space; they are organized into six spatial domains, each containing a unique set of one or more proprioceptors. Proprioceptors form output synapses along the proximal axonal entry pathway into the neuropil. (3) Proprioceptors receive few inhibitory input synapses. Further, we find that these three features do not apply to other larval somatosensory neurons. Thus, we have generated the most comprehensive map to date of how proprioceptor synapses are centrally organized. This map documents previously undescribed features of proprioceptors, raises questions about underlying developmental mechanisms, and has implications for downstream proprioceptive processing circuits.

Thin Glass Micro Force Plate Supported by Planar Spiral Springs for Measuring Minute Forces

Microforce plates are indispensable tools for quantitatively evaluating the behavior of small objects such as tiny insects or microdroplets. The two main measurement principles for microforce plates are: the formation of strain gauges on the beam that supports the plate and the measurement of the deformation of the plate using an external displacement meter. The latter method is characterized by its ease of fabrication and durability as strain concentration is not required. To enhance the sensitivity of the latter type of force plates with a planar structure, thinner plates are generally desired. However, brittle material force plates that are both thin and large and can be fabricated easily have not yet been developed. In this study, a force plate consisting of a thin glass plate with a planar spiral spring structure and a laser displacement meter placed under the plate center is proposed. The plate deforms downward when a force is exerted vertically on its surface, resulting in the determination of the applied force using Hooke's law. The force plate structure is easily fabricated by laser processing combined with the microelectromechanical system (MEMS) process. The fabricated force plate has a radius and thickness of 10 mm and 25 µm, respectively, with four supporting spiral beams of sub-millimeter width. A fabricated force plate featuring a sub-N/m spring constant achieves a resolution of approximately 0.01 µN.

Cross-modal modulation gates nociceptive inputs in Drosophila

Animals' response to a stimulus in one sensory modality is usually influenced by other modalities.1 One important type of multisensory integration is the cross-modal modulation, in which one sensory modality modulates (typically inhibits) another. Identification of the mechanisms underlying cross-modal modulations is crucial for understanding how sensory inputs shape animals' perception and for understanding sensory processing disorders.2,3,4 However, the synaptic and circuit mechanisms that underlie cross-modal modulation are poorly understood. This is due to the difficulty of separating cross-modal modulation from multisensory integrations in neurons that receive excitatory inputs from two or more sensory modalities5-in which case it is unclear what the modulating or modulated modality is. In this study, we report a unique system for studying cross-modal modulation by taking advantage of the genetic resources in Drosophila. We show that gentle mechanical stimuli inhibit nociceptive responses in Drosophila larvae. Low-threshold mechanosensory neurons inhibit a key second-order neuron in the nociceptive pathway through metabotropic GABA receptors on nociceptor synaptic terminals. Strikingly, this cross-modal inhibition is only effective when nociceptor inputs are weak, thus serving as a gating mechanism for filtering out weak nociceptive inputs. Our findings unveil a novel cross-modal gating mechanism for sensory pathways.

Genipin prevents alpha-synuclein aggregation and toxicity by affecting endocytosis, metabolism and lipid storage

Parkinson's Disease (PD) is a common neurodegenerative disorder affecting millions of people worldwide for which there are only symptomatic therapies. Small molecules able to target key pathological processes in PD have emerged as interesting options for modifying disease progression. We have previously shown that a (poly)phenol-enriched fraction (PEF) of Corema album L. leaf extract modulates central events in PD pathogenesis, namely α-synuclein (αSyn) toxicity, aggregation and clearance. PEF was now subjected to a bio-guided fractionation with the aim of identifying the critical bioactive compound. We identified genipin, an iridoid, which relieves αSyn toxicity and aggregation. Furthermore, genipin promotes metabolic alterations and modulates lipid storage and endocytosis. Importantly, genipin was able to prevent the motor deficits caused by the overexpression of αSyn in a Drosophila melanogaster model of PD. These findings widens the possibility for the exploitation of genipin for PD therapeutics.

Ascending neurons convey behavioral state to integrative sensory and action selection brain regions

Knowing one's own behavioral state has long been theorized as critical for contextualizing dynamic sensory cues and identifying appropriate future behaviors. Ascending neurons (ANs) in the motor system that project to the brain are well positioned to provide such behavioral state signals. However, what ANs encode and where they convey these signals remains largely unknown. Here, through large-scale functional imaging in behaving animals and morphological quantification, we report the behavioral encoding and brain targeting of hundreds of genetically identifiable ANs in the adult fly, Drosophila melanogaster. We reveal that ANs encode behavioral states, specifically conveying self-motion to the anterior ventrolateral protocerebrum, an integrative sensory hub, as well as discrete actions to the gnathal ganglia, a locus for action selection. Additionally, AN projection patterns within the motor system are predictive of their encoding. Thus, ascending populations are well poised to inform distinct brain hubs of self-motion and ongoing behaviors and may provide an important substrate for computations that are required for adaptive behavior.

A Dual-network Nerve Adhesive with Enhanced Adhesion Strength Promotes Transected Peripheral Nerve Repair

Peripheral nerve transection has a high prevalence and results in functional loss of affected limbs. The current clinical treatment using suture anastomosis significantly limits nerve recovery due to severe inflammation, secondary damage, and fibrosis. Fibrin glue, a commercial nerve adhesive as an alternative, avoids secondary damage but suffers from poor adhesion strength. To address their limitations, a highly efficacious nerve adhesive based on dual-crosslinking of dopamine-isothiocyanate modified hyaluronic acid and decellularized nerve matrix is reported in this paper. This dual-network nerve adhesive (DNNA) shows controllable gelation behaviors feasible for surgical applications, robust adhesion strength, and promoted axonal outgrowth in vitro. The in vivo therapeutic efficacy is tested using a rat-based sciatic nerve transection model. The DNNA decreases fibrosis and accelerates axon/myelin debris clearance at 10 days post-surgery, compared to suture and commercial fibrin glue treatments. At 10 weeks post-surgery, the strong adhesion and bioactivity allow DNNA to significantly decrease intraneural inflammation and fibrosis, enhance axon connection and remyelination, aid motor and sensory function recovery, as well as improve muscle contraction, compared to suture and fibrin treatments. Overall, this dual-network hydrogel with robust adhesion provides a rapid and highly efficacious nerve transection treatment to facilitate nerve repair and neuromuscular function recovery.

Descending neuron population dynamics during odor-evoked and spontaneous limb-dependent behaviors

Deciphering how the brain regulates motor circuits to control complex behaviors is an important, long-standing challenge in neuroscience. In the fly, Drosophila melanogaster, this is coordinated by a population of ~ 1100 descending neurons (DNs). Activating only a few DNs is known to be sufficient to drive complex behaviors like walking and grooming. However, what additional role the larger population of DNs plays during natural behaviors remains largely unknown. For example, they may modulate core behavioral commands or comprise parallel pathways that are engaged depending on sensory context. We evaluated these possibilities by recording populations of nearly 100 DNs in individual tethered flies while they generated limb-dependent behaviors, including walking and grooming. We found that the largest fraction of recorded DNs encode walking while fewer are active during head grooming and resting. A large fraction of walk-encoding DNs encode turning and far fewer weakly encode speed. Although odor context does not determine which behavior-encoding DNs are recruited, a few DNs encode odors rather than behaviors. Lastly, we illustrate how one can identify individual neurons from DN population recordings by using their spatial, functional, and morphological properties. These results set the stage for a comprehensive, population-level understanding of how the brain's descending signals regulate complex motor actions.

The evolutionary trajectory of drosophilid walking

Neural circuits must both execute the behavioral repertoire of individuals and account for behavioral variation across species. Understanding how this variation emerges over evolutionary time requires large-scale phylogenetic comparisons of behavioral repertoires. Here, we describe the evolution of walking in fruit flies by capturing high-resolution, unconstrained movement from 13 species and 15 strains of drosophilids. We find that walking can be captured in a universal behavior space, the structure of which is evolutionarily conserved. However, the occurrence of and transitions between specific movements have evolved rapidly, resulting in repeated convergent evolution in the temporal structure of locomotion. Moreover, a meta-analysis demonstrates that many behaviors evolve more rapidly than other traits. Thus, the architecture and physiology of locomotor circuits can execute precise individual movements in one species and simultaneously support rapid evolutionary changes in the temporal ordering of these modular elements across clades.

Motor dysfunction in Drosophila melanogaster as a biomarker for developmental neurotoxicity

Adequate alternatives to conventional animal testing are needed to study developmental neurotoxicity (DNT). Here, we used kinematic analysis to assess DNT of known (toluene (TOL) and chlorpyrifos (CPS)) and putative (β-N-methylamino-L-alanine (BMAA)) neurotoxic compounds. Drosophila melanogaster was exposed to these compounds during development and evaluated for survival and adult kinematic parameters using the FlyWalker system, a kinematics evaluation method. At concentrations that do not induce general toxicity, the solvent DMSO had a significant effect on kinematic parameters. Moreover, while TOL did not significantly induce lethality or kinematic dysfunction, CPS not only induced developmental lethality but also significantly impaired coordination in comparison to DMSO. Interestingly, BMAA, which was not lethal during development, induced motor decay in young adult animals, phenotypically resembling aged flies, an effect later attenuated upon aging. Furthermore, BMAA induced abnormal development of leg motor neuron projections. Our results suggest that our kinematic approach can assess potential DNT of chemical compounds.

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Alternatives to mammalian testing are needed to detect developmental neurotoxicity

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The pesticide chlorpyrifos causes partial lethality and motor dysfunction

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Non-lethal levels of BMAA induce motor dysfunction in a dose-dependent manner

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Kinematic profiling of adult Drosophila can identify developmental neurotoxicity

Walking strides direct rapid and flexible recruitment of visual circuits for course control in Drosophila

Flexible mapping between activity in sensory systems and movement parameters is a hallmark of motor control. This flexibility depends on the continuous comparison of short-term postural dynamics and the longer-term goals of an animal, thereby necessitating neural mechanisms that can operate across multiple timescales. To understand how such body-brain interactions emerge across timescales to control movement, we performed whole-cell patch recordings from visual neurons involved in course control in Drosophila. We show that the activity of leg mechanosensory cells, propagating via specific ascending neurons, is critical for stride-by-stride steering adjustments driven by the visual circuit, and, at longer timescales, it provides information about the moving body's state to flexibly recruit the visual circuit for course control. Thus, our findings demonstrate the presence of an elegant stride-based mechanism operating at multiple timescales for context-dependent course control. We propose that this mechanism functions as a general basis for the adaptive control of locomotion.

Advancements in Genomic and Behavioral Neuroscience Analysis for the Study of Normal and Pathological Brain Function

Psychiatric and neurological disorders are influenced by an undetermined number of genes and molecular pathways that may differ among afflicted individuals. Functionally testing and characterizing biological systems is essential to discovering the interrelationship among candidate genes and understanding the neurobiology of behavior. Recent advancements in genetic, genomic, and behavioral approaches are revolutionizing modern neuroscience. Although these tools are often used separately for independent experiments, combining these areas of research will provide a viable avenue for multidimensional studies on the brain. Herein we will briefly review some of the available tools that have been developed for characterizing novel cellular and animal models of human disease. A major challenge will be openly sharing resources and datasets to effectively integrate seemingly disparate types of information and how these systems impact human disorders. However, as these emerging technologies continue to be developed and adopted by the scientific community, they will bring about unprecedented opportunities in our understanding of molecular neuroscience and behavior.

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.

Long-Term Observation of Locomotion of Drosophila Larvae Facilitates Feasibility of Food-Choice Assays

Animal behavior is reflected by locomotor patterns. To decipher the underlying neural circuitry locomotion has to be monitored over often longer time periods. Here a simple adaptation is described to constrain movement of third instar Drosophila larvae to a defined area and use Frustrated total internal reflection based imaging method (FIM) imaging to monitor larval movements up to 1 h. It is demonstrated that the combination of FIM imaging and long analysis periods facilitates the conduction of food choice assays and provides the means to easily quantify food preferences.

Measuring the repertoire of age-related behavioral changes in Drosophila melanogaster

Aging affects almost all aspects of an organism—its morphology, its physiology, its behavior. Isolating which biological mechanisms are regulating these changes, however, has proven difficult, potentially due to our inability to characterize the full repertoire of an animal’s behavior across the lifespan. Using data from fruit flies (D. melanogaster) we measure the full repertoire of behaviors as a function of age. We observe a sexually dimorphic pattern of changes in the behavioral repertoire during aging. Although the stereotypy of the behaviors and the complexity of the repertoire overall remains relatively unchanged, we find evidence that the observed alterations in behavior can be explained by changing the fly’s overall energy budget, suggesting potential connections between metabolism, aging, and behavior.

Aging is a ubiquitous biological phenomenon that affects many aspects of an animal’s appearance, physiology, and behavior. Our understanding of how changes in physiology lead to behavioral changes, however, has been partially limited by our ability to robustly quantify how behavior alters over timescales of days and weeks. In this study, we measure a large repertoire of behaviors of fruit flies at various ages, finding how the actions the animals perform shift with age. We observe a difference between the aging dynamics of male and female flies, and we show that many of these changes can be explained with a model of energy consumption, leading us to make predictions as to the role of metabolism in changes in aging behavior.

Behavioral evidence for nested central pattern generator control of Drosophila grooming

Central pattern generators (CPGs) are neurons or neural circuits that produce periodic output without requiring patterned input. More complex behaviors can be assembled from simpler subroutines, and nested CPGs have been proposed to coordinate their repetitive elements, organizing control over different time scales. Here, we use behavioral experiments to establish that Drosophila grooming may be controlled by nested CPGs. On a short time scale (5-7 Hz, ~ 200 ms/movement), flies clean with periodic leg sweeps and rubs. More surprisingly, transitions between bouts of head sweeping and leg rubbing are also periodic on a longer time scale (0.3-0.6 Hz, ~2 s/bout). We examine grooming at a range of temperatures to show that the frequencies of both oscillations increase-a hallmark of CPG control-and also that rhythms at the two time scales increase at the same rate, indicating that the nested CPGs may be linked. This relationship holds when sensory drive is held constant using optogenetic activation, but oscillations can decouple in spontaneously grooming flies, showing that alternative control modes are possible. Loss of sensory feedback does not disrupt periodicity but slow down the longer time scale alternation. Nested CPGs simplify the generation of complex but repetitive behaviors, and identifying them in Drosophila grooming presents an opportunity to map the neural circuits that constitute them.

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.

Functional architecture of neural circuits for leg proprioception in Drosophila

To effectively control their bodies, animals rely on feedback from proprioceptive mechanosensory neurons. In the Drosophila leg, different proprioceptor subtypes monitor joint position, movement direction, and vibration. Here, we investigate how these diverse sensory signals are integrated by central proprioceptive circuits. We find that signals for leg joint position and directional movement converge in second-order neurons, revealing pathways for local feedback control of leg posture. Distinct populations of second-order neurons integrate tibia vibration signals across pairs of legs, suggesting a role in detecting external substrate vibration. In each pathway, the flow of sensory information is dynamically gated and sculpted by inhibition. Overall, our results reveal parallel pathways for processing of internal and external mechanosensory signals, which we propose mediate feedback control of leg movement and vibration sensing, respectively. The existence of a functional connectivity map also provides a resource for interpreting connectomic reconstruction of neural circuits for leg proprioception.

To understand how diverse proprioceptive signals from the Drosophila leg are integrated by downstream circuits, Chen et al. use optogenetics and calcium imaging to map functional connectivity between sensory and central neurons. This work identifies parallel neural pathways for processing leg vibration vs. joint position and movement.

Anipose: A toolkit for robust markerless 3D pose estimation

Quantifying movement is critical for understanding animal behavior. Advances in computer vision now enable markerless tracking from 2D video, but most animals move in 3D. Here, we introduce Anipose, an open-source toolkit for robust markerless 3D pose estimation. Anipose is built on the 2D tracking method DeepLabCut, so users can expand their existing experimental setups to obtain accurate 3D tracking. It consists of four components: (1) a 3D calibration module, (2) filters to resolve 2D tracking errors, (3) a triangulation module that integrates temporal and spatial regularization, and (4) a pipeline to structure processing of large numbers of videos. We evaluate Anipose on a calibration board as well as mice, flies, and humans. By analyzing 3D leg kinematics tracked with Anipose, we identify a key role for joint rotation in motor control of fly walking. To help users get started with 3D tracking, we provide tutorials and documentation at http://anipose.org/.

Phase response analyses support a relaxation oscillator model of locomotor rhythm generation in Caenorhabditis elegans

Neural circuits coordinate with muscles and sensory feedback to generate motor behaviors appropriate to an animal's environment. In C. elegans, the mechanisms by which the motor circuit generates undulations and modulates them based on the environment are largely unclear. We quantitatively analyzed C. elegans locomotion during free movement and during transient optogenetic muscle inhibition. Undulatory movements were highly asymmetrical with respect to the duration of bending and unbending during each cycle. Phase response curves induced by brief optogenetic inhibition of head muscles showed gradual increases and rapid decreases as a function of phase at which the perturbation was applied. A relaxation oscillator model based on proprioceptive thresholds that switch the active muscle moment was developed and is shown to quantitatively agree with data from free movement, phase responses, and previous results for gait adaptation to mechanical loadings. Our results suggest a neuromuscular mechanism underlying C. elegans motor pattern generation within a compact circuit.

Proprioception, the regulator of motor function

In animals, proper locomotion is crucial to find mates and foods and avoid predators or dangers. Multiple sensory systems detect external and internal cues and integrate them to modulate motor outputs. Proprioception is the internal sense of body position, and proprioceptive control of locomotion is essential to generate and maintain precise patterns of movement or gaits. This proprioceptive feedback system is conserved in many animal species and is mediated by stretch-sensitive receptors called proprioceptors. Recent studies have identified multiple proprioceptive neurons and proprioceptors and their roles in the locomotion of various model organisms. In this review we describe molecular and neuronal mechanisms underlying proprioceptive feedback systems in C. elegans, Drosophila, and mice.

Tardigrades exhibit robust interlimb coordination across walking speeds and terrains

Tardigrades must negotiate heterogeneous, fluctuating environments and accordingly utilize locomotive strategies capable of dealing with variable terrain. We analyze the kinematics and interleg coordination of freely walking tardigrades (species: Hypsibius exemplaris). We find that tardigrade walking replicates several key features of walking in insects despite disparities in size, skeleton, and habitat. To test the effect of environmental changes on tardigrade locomotor control circuits we measure kinematics and interleg coordination during walking on two substrates of different stiffnesses. We find that the phase offset between contralateral leg pairs is flexible, while ipsilateral coordination is preserved across environmental conditions. This mirrors similar results in insects and crustaceans. We propose that these functional similarities in walking coordination between tardigrades and arthropods is either due to a generalized locomotor control circuit common to panarthropods or to independent convergence onto an optimal strategy for robust multilegged control in small animals with simple circuitry. Our results highlight the value of tardigrades as a comparative system toward understanding the mechanisms-neural and/or mechanical-underlying coordination in panarthropod locomotion.

Universal Features in Panarthropod Inter-Limb Coordination during Forward Walking

Terrestrial animals must often negotiate heterogeneous, varying environments. Accordingly, their locomotive strategies must adapt to a wide range of terrain, as well as to a range of speeds to accomplish different behavioral goals. Studies in Drosophila have found that inter-leg coordination patterns (ICPs) vary smoothly with walking speed, rather than switching between distinct gaits as in vertebrates (e.g., horses transitioning between trotting and galloping). Such a continuum of stepping patterns implies that separate neural controllers are not necessary for each observed ICP. Furthermore, the spectrum of Drosophila stepping patterns includes all canonical coordination patterns observed during forward walking in insects. This raises the exciting possibility that the controller in Drosophila is common to all insects, and perhaps more generally to panarthropod walkers. Here, we survey and collate data on leg kinematics and inter-leg coordination relationships during forward walking in a range of arthropod species, as well as include data from a recent behavioral investigation into the tardigrade Hypsibius exemplaris. Using this comparative dataset, we point to several functional and morphological features that are shared among panarthropods. The goal of the framework presented in this review is to emphasize the importance of comparative functional and morphological analyses in understanding the origins and diversification of walking in Panarthropoda. Introduction.

Rest Is Required to Learn an Appetitively-Reinforced Operant Task in Drosophila

Maladaptive operant conditioning contributes to development of neuropsychiatric disorders. Candidate genes have been identified that contribute to this maladaptive plasticity, but the neural basis of operant conditioning in genetic model organisms remains poorly understood. The fruit fly Drosophila melanogaster is a versatile genetic model organism that readily forms operant associations with punishment stimuli. However, operant conditioning with a food reward has not been demonstrated in flies, limiting the types of neural circuits that can be studied. Here we present the first sucrose-reinforced operant conditioning paradigm for flies. In the paradigm, flies walk along a Y-shaped track with reward locations at the terminus of each hallway. When flies turn in the reinforced direction at the center of the track, they receive a sucrose reward at the end of the hallway. Only flies that rest early in training learn the reward contingency normally. Flies rewarded independently of their behavior do not form a learned association but have the same amount of rest as trained flies, showing that rest is not driven by learning. Optogenetically-induced sleep does not promote learning, indicating that sleep itself is not sufficient for learning the operant task. We validated the sensitivity of this assay to detect the effect of genetic manipulations by testing the classic learning mutant dunce. Dunce flies are learning-impaired in the Y-Track task, indicating a likely role for cAMP in the operant coincidence detector. This novel training paradigm will provide valuable insight into the molecular mechanisms of disease and the link between sleep and learning.

Navigation of a Freely Walking Fruit Fly in Infinite Space Using a Transparent Omnidirectional Locomotion Compensator (TOLC)

Animal behavior is an essential element in behavioral neuroscience study. However, most behavior studies in small animals such as fruit flies (Drosophilamelanogaster) have been performed in a limited spatial chamber or by tethering the fly's body on a fixture, which restricts its natural behavior. In this paper, we developed the Transparent Omnidirectional Locomotion Compensator (TOLC) for a freely walking fruit fly without tethering, which enables its navigation in infinite space. The TOLC maintains a position of a fruit fly by compensating its motion using the transparent sphere. The TOLC is capable of maintaining the position error < 1 mm for 90.3% of the time and the heading error < 5° for 80.2% of the time. The inverted imaging system with a transparent sphere secures the space for an additional experimental apparatus. Because the proposed TOLC allows us to observe a freely walking fly without physical tethering, there is no potential injury during the experiment. Thus, the TOLC will offer a unique opportunity to investigate longitudinal studies of a wide range of behavior in an unrestricted walking Drosophila.

Drosophila uses a tripod gait across all walking speeds, and the geometry of the tripod is important for speed control

Changes in walking speed are characterized by changes in both the animal's gait and the mechanics of its interaction with the ground. Here we study these changes in walking Drosophila. We measured the fly's center of mass movement with high spatial resolution and the position of its footprints. Flies predominantly employ a modified tripod gait that only changes marginally with speed. The mechanics of a tripod gait can be approximated with a simple model - angular and radial spring-loaded inverted pendulum (ARSLIP) - which is characterized by two springs of an effective leg that become stiffer as the speed increases. Surprisingly, the change in the stiffness of the spring is mediated by the change in tripod shape rather than a change in stiffness of individual legs. The effect of tripod shape on mechanics can also explain the large variation in kinematics among insects, and ARSLIP can model these variations.

Relative Contribution of Proprioceptive and Vestibular Sensory Systems to Locomotion: Opportunities for Discovery in the Age of Molecular Science

Locomotion is a fundamental animal behavior required for survival and has been the subject of neuroscience research for centuries. In terrestrial mammals, the rhythmic and coordinated leg movements during locomotion are controlled by a combination of interconnected neurons in the spinal cord, referred as to the central pattern generator, and sensory feedback from the segmental somatosensory system and supraspinal centers such as the vestibular system. How segmental somatosensory and the vestibular systems work in parallel to enable terrestrial mammals to locomote in a natural environment is still relatively obscure. In this review, we first briefly describe what is known about how the two sensory systems control locomotion and use this information to formulate a hypothesis that the weight of the role of segmental feedback is less important at slower speeds but increases at higher speeds, whereas the weight of the role of vestibular system has the opposite relation. The new avenues presented by the latest developments in molecular sciences using the mouse as the model system allow the direct testing of the hypothesis.

Dynamics of locomotion in the seed harvesting ant Messor barbarus: effect of individual body mass and transported load mass

Ants are well-known for their amazing load carriage performances. Yet, the biomechanics of locomotion during load transport in these insects has so far been poorly investigated. Here, we present a study of the biomechanics of unloaded and loaded locomotion in the polymorphic seed-harvesting ant Messor barbarus (Linnaeus, 1767). This species is characterized by a strong intra-colonial size polymorphism with allometric relationships between the different body parts of the workers. In particular, big ants have much larger heads relative to their size than small ants. Their center of mass is thus shifted forward and even more so when they are carrying a load in their mandibles. We investigated the dynamics of the ant center of mass during unloaded and loaded locomotion. We found that during both unloaded and loaded locomotion, the kinetic energy and gravitational potential energy of the ant center of mass are in phase, which is in agreement with what has been described by other authors as a grounded-running gait. During unloaded locomotion, small and big ants do not display the same posture. However, they expend the same amount of mechanical energy to raise and accelerate their center of mass per unit of distance and per unit of body mass. While carrying a load, compared to the unloaded situation, ants seem to modify their locomotion gradually with increasing load mass. Therefore, loaded and unloaded locomotion do not involve discrete types of gait. Moreover, small ants carrying small loads expend less mechanical energy per unit of distance and per unit of body mass and their locomotion thus seem more mechanically efficient.

Inexpensive Methods for Live Imaging of Central Pattern Generator Activity in the Drosophila Larval Locomotor System

Central pattern generators (CPGs) are neural networks that produce rhythmic motor activity in the absence of sensory input. CPGs produce 'fictive' behaviours in vitro which parallel activity seen in intact animals. CPG networks have been identified in a wide variety of model organisms and have been shown to be critical for generating rhythmic behaviours such as swimming, walking, chewing and breathing. Work with CPG preparations has led to fundamental advances in neuroscience; however, most CPG preparations involve intensive dissections and require sophisticated electrophysiology equipment, making export to teaching laboratories problematic. Here we present an integrated approach for bringing the study of locomotor CPGs in Drosophila larvae into teaching laboratories. First, we present freely available genetic constructs that enable educators to express genetically encoded calcium indicators in cells of interest in the larval central nervous system. Next, we describe how to isolate the larval central nervous system and prepare it for live imaging. We then show how to modify standard compound microscopes to enable fluorescent imaging using 3D printed materials and inexpensive optical components. Finally, we show how to use the free image analysis programme ImageJ and freely available features in the signal analysis programme DataView to analyse rhythmic CPG activity in the larval CNS. Comparison of results to those obtained on research equipment shows that signal-to-noise levels are comparable and core features of larval CPG activity can be observed. Overall, this work shows the viability of exporting live imaging experiments to low cost environments and paves the way for new teaching laboratory exercises revolving around optical imaging of CPG activity.

Central processing of leg proprioception in Drosophila

Proprioception, the sense of self-movement and position, is mediated by mechanosensory neurons that detect diverse features of body kinematics. Although proprioceptive feedback is crucial for accurate motor control, little is known about how downstream circuits transform limb sensory information to guide motor output. Here we investigate neural circuits in Drosophila that process proprioceptive information from the fly leg. We identify three cell types from distinct developmental lineages that are positioned to receive input from proprioceptor subtypes encoding tibia position, movement, and vibration. 13Bα neurons encode femur-tibia joint angle and mediate postural changes in tibia position. 9Aα neurons also drive changes in leg posture, but encode a combination of directional movement, high frequency vibration, and joint angle. Activating 10Bα neurons, which encode tibia vibration at specific joint angles, elicits pausing in walking flies. Altogether, our results reveal that central circuits integrate information across proprioceptor subtypes to construct complex sensorimotor representations that mediate diverse behaviors, including reflexive control of limb posture and detection of leg vibration.

The roles of ascending sensory signals and top-down central control in the entrainment of a locomotor CPG

Previous authors have proposed two basic hypotheses about the factors that form the basis of locomotor rhythms in walking insects: sensory feedback only or sensory feedback together with rhythmic activity of small neural circuits called central pattern generators (CPGs). Here we focus on the latter. Following this concept, to generate functional outputs, locomotor control must feature both rhythm generation by CPGs at the level of individual joints and coordination of their rhythmic activities, so that all muscles are activated in an appropriate pattern. This work provides an in-depth analysis of an aspect of this coordination process based on an existing network model of stick insect locomotion. Specifically, we consider how the control system for a single joint in the stick insect leg may produce rhythmic output when subjected to ascending sensory signals from other joints in the leg. In this work, the core rhythm generating CPG component of the joint under study is represented by a classical half-center oscillator constrained by a basic set of experimental observations. While the dynamical features of this CPG, including phase transitions by escape and release, are well understood, we provide novel insights about how these transition mechanisms yield entrainment to the incoming sensory signal, how entrainment can be lost under variation of signal strength and period or other perturbations, how entrainment can be restored by modulation of tonic top-down drive levels, and how these factors impact the duty cycle of the motor output.

Two Brain Pathways Initiate Distinct Forward Walking Programs in Drosophila

An animal at rest or engaged in stationary behaviors can instantaneously initiate goal-directed walking. How descending brain inputs trigger rapid transitions from a non-walking state to an appropriate walking state is unclear. Here, we identify two neuronal types, P9 and BPN, in the Drosophila brain that, upon activation, initiate and maintain two distinct coordinated walking patterns. P9 drives forward walking with ipsilateral turning, receives inputs from central courtship-promoting neurons and visual projection neurons, and is necessary for a male to pursue a female during courtship. In contrast, BPN drives straight, forward walking and is not required during courtship. BPN is instead recruited during and required for fast, straight, forward walking bouts. Thus, this study reveals separate brain pathways for object-directed walking and fast, straight, forward walking, providing insight into how the brain initiates context-appropriate walking programs.

Age-dependent degeneration of an identified adult leg motor neuron in a Drosophila SOD1 model of ALS

Mutations in superoxide dismutase 1 (SOD1) cause familial amyotrophic lateral sclerosis (ALS) in humans. ALS is a neurodegenerative disease characterized by progressive motor neuron loss leading to paralysis and inevitable death in affected individuals. Using a gene replacement strategy to introduce disease mutations into the orthologous Drosophila sod1 (dsod1) gene, here, we characterize changes at the neuromuscular junction using longer-lived dsod1 mutant adults. Homozygous dsod1H71Y/H71Y or dsod1null/null flies display progressive walking defects with paralysis of the third metathoracic leg. In dissected legs, we assessed age-dependent changes in a single identified motor neuron (MN-I2) innervating the tibia levitator muscle. At adult eclosion, MN-I2 of dsod1H71Y/H71Y or sod1null/null flies is patterned similar to wild-type flies indicating no readily apparent developmental defects. Over the course of 10 days post-eclosion, MN-I2 shows an overall reduction in arborization with bouton swelling and loss of the post-synaptic marker discs-large (dlg) in mutant dsod1 adults. In addition, increases in polyubiquitinated proteins correlate with the timing and extent of MN-I2 changes. Because similar phenotypes are observed between flies homozygous for either dsod1H71Y or dsod1null alleles, we conclude these NMJ changes are mainly associated with sod loss-of-function. Together these studies characterize age-related morphological and molecular changes associated with axonal retraction in a Drosophila model of ALS that recapitulate an important aspect of the human disease.This article has an associated First Person interview with the first author of the paper.

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.

A Systematic Nomenclature for the Drosophila Ventral Nerve Cord

Drosophila melanogaster is an established model for neuroscience research with relevance in biology and medicine. Until recently, research on the Drosophila brain was hindered by the lack of a complete and uniform nomenclature. Recognizing this, Ito et al. (2014) produced an authoritative nomenclature for the adult insect brain, using Drosophila as the reference. Here, we extend this nomenclature to the adult thoracic and abdominal neuromeres, the ventral nerve cord (VNC), to provide an anatomical description of this major component of the Drosophila nervous system. The VNC is the locus for the reception and integration of sensory information and involved in generating most of the locomotor actions that underlie fly behaviors. The aim is to create a nomenclature, definitions, and spatial boundaries for the Drosophila VNC that are consistent with other insects. The work establishes an anatomical framework that provides a powerful tool for analyzing the functional organization of the VNC.

Neurodynamic modeling of the fruit fly Drosophila melanogaster

This manuscript describes neuromechanical modeling of the fruit fly Drosophila melanogaster in the form of a hexapod robot, Drosophibot, and an accompanying dynamic simulation. Drosophibot is a testbed for real-time dynamical neural controllers modeled after the anatomy and function of the insect nervous system. As such, Drosophibot has been designed to capture features of the animal's biomechanics in order to better test the neural controllers. These features include: dynamically scaling the robot to match the fruit fly by designing its joint elasticity and movement speed; a biomimetic actuator control scheme that converts neural activity into motion in the same way as observed in insects; biomimetic sensing, including proprioception from all leg joints and strain sensing from all leg segments; and passively compliant tarsi that mimic the animal's passive compliance to the walking substrate. We incorporated these features into a dynamical simulation of Drosophibot, and demonstrate that its actuators and sensors perform in an animal-like way. We used this simulation to test a neural walking controller based on anatomical and behavioral data from insects. Finally, we describe Drosophibot's hardware and show that the animal-like features of the simulation transfer to the physical robot.

Intrinsic control of neuronal diversity and synaptic specificity in a proprioceptive circuit

Relay of muscle-derived sensory information to the CNS is essential for the execution of motor behavior, but how proprioceptive sensory neurons (pSNs) establish functionally appropriate connections is poorly understood. A prevailing model of sensory-motor circuit assembly is that peripheral, target-derived, cues instruct pSN identities and patterns of intraspinal connectivity. To date no known intrinsic determinants of muscle-specific pSN fates have been described in vertebrates. We show that expression of Hox transcription factors defines pSN subtypes, and these profiles are established independently of limb muscle. The Hoxc8 gene is expressed by pSNs and motor neurons (MNs) targeting distal forelimb muscles, and sensory-specific depletion of Hoxc8 in mice disrupts sensory-motor synaptic matching, without affecting pSN survival or muscle targeting. These results indicate that the diversity and central specificity of pSNs and MNs are regulated by a common set of determinants, thus linking early rostrocaudal patterning to the assembly of limb control circuits.

Versatile method to measure locomotion in adult Drosophila

Many studies require the ability to quantify locomotor behavior over time. The list of tracking softwares and their capabilities are constantly growing. At the 2019 CanFly Conference, we presented preliminary results from an investigation of the effects of expressing polyglutamine repeats in fly muscles on longevity, locomotion, and protein aggregation. Numerous requests have been received regarding our protocol to measure locomotion and how to use the FlyTracker MatLab software. This report describes a versatile locomotion measuring device and custom MatLab scripts for the extraction, analysis, and compilation of FlyTracker data in a format compatible with spreadsheet softwares. The measurement and analysis of multiple genotypes of both sexes across age demonstrates that this method yields reproducible results that confirm that normal aging is associated with a progressive decline in locomotion as indicated by increased immobility and reduced velocity.

A size principle for recruitment of Drosophila leg motor neurons

To move the body, the brain must precisely coordinate patterns of activity among diverse populations of motor neurons. Here, we use in vivo calcium imaging, electrophysiology, and behavior to understand how genetically-identified motor neurons control flexion of the fruit fly tibia. We find that leg motor neurons exhibit a coordinated gradient of anatomical, physiological, and functional properties. Large, fast motor neurons control high force, ballistic movements while small, slow motor neurons control low force, postural movements. Intermediate neurons fall between these two extremes. This hierarchical organization resembles the size principle, first proposed as a mechanism for establishing recruitment order among vertebrate motor neurons. Recordings in behaving flies confirmed that motor neurons are typically recruited in order from slow to fast. However, we also find that fast, intermediate, and slow motor neurons receive distinct proprioceptive feedback signals, suggesting that the size principle is not the only mechanism that dictates motor neuron recruitment. Overall, this work reveals the functional organization of the fly leg motor system and establishes Drosophila as a tractable system for investigating neural mechanisms of limb motor control.

Spatiotemporally precise optogenetic activation of sensory neurons in freely walking Drosophila

Previous work has characterized how walking Drosophila coordinate the movements of individual limbs (DeAngelis et al., 2019). To understand the circuit basis of this coordination, one must characterize how sensory feedback from each limb affects walking behavior. However, it has remained difficult to manipulate neural activity in individual limbs of freely moving animals. Here, we demonstrate a simple method for optogenetic stimulation with body side-, body segment-, and limb-specificity that does not require real-time tracking. Instead, we activate at random, precise locations in time and space and use post hoc analysis to determine behavioral responses to specific activations. Using this method, we have characterized limb coordination and walking behavior in response to transient activation of mechanosensitive bristle neurons and sweet-sensing chemoreceptor neurons. Our findings reveal that activating these neurons has opposite effects on turning, and that activations in different limbs and body regions produce distinct behaviors.

A single-cell transcriptomic atlas of the adult Drosophila ventral nerve cord

The Drosophila ventral nerve cord (VNC) receives and processes descending signals from the brain to produce a variety of coordinated locomotor outputs. It also integrates sensory information from the periphery and sends ascending signals to the brain. We used single-cell transcriptomics to generate an unbiased classification of cellular diversity in the VNC of five-day old adult flies. We produced an atlas of 26,000 high-quality cells, representing more than 100 transcriptionally distinct cell types. The predominant gene signatures defining neuronal cell types reflect shared developmental histories based on the neuroblast from which cells were derived, as well as their birth order. The relative position of cells along the anterior-posterior axis could also be assigned using adult Hox gene expression. This single-cell transcriptional atlas of the adult fly VNC will be a valuable resource for future studies of neurodevelopment and behavior.