A spike-timing mechanism for action selection

Neural Control of Naturalistic Behavior Choices

In the natural world, animals make decisions on an ongoing basis, continuously selecting which action to undertake next. In the lab, however, the neural bases of decision processes have mostly been studied using artificial trial structures. New experimental tools based on the genetic toolkit of model organisms now make it experimentally feasible to monitor and manipulate neural activity in small subsets of neurons during naturalistic behaviors. We thus propose a new approach to investigating decision processes, termed reverse neuroethology. In this approach, experimenters select animal models based on experimental accessibility and then utilize cutting-edge tools such as connectomes and genetically encoded reagents to analyze the flow of information through an animal's nervous system during naturalistic choice behaviors. We describe how the reverse neuroethology strategy has been applied to understand the neural underpinnings of innate, rapid decision making, with a focus on defensive behavioral choices in the vinegar fly Drosophila melanogaster.

Mechanosensory bristles mediate avoidance behavior by triggering sustained local motor activity in Drosophila melanogaster

During locomotion, most vertebrates-and invertebrates such as Drosophila melanogaster-are able to quickly adapt to terrain irregularities or avoid physical threats by integrating sensory information along with motor commands. Key to this adaptability are leg mechanosensory structures, which assist in motor coordination by transmitting external cues and proprioceptive information to motor centers in the central nervous system. Nevertheless, how different mechanosensory structures engage these locomotor centers remains poorly understood. Here, we tested the role of mechanosensory structures in movement initiation by optogenetically stimulating specific classes of leg sensory structures. We found that stimulation of leg mechanosensory bristles (MsBs) and the femoral chordotonal organ (ChO) is sufficient to initiate forward movement in immobile animals. While the stimulation of the ChO required brain centers to induce forward movement, unexpectedly, brief stimulation of leg MsBs triggered a fast response and sustained motor activity dependent only on the ventral nerve cord (VNC). Moreover, this leg-MsB-mediated movement lacked inter- and intra-leg coordination but preserved antagonistic muscle activity within joints. Finally, we show that leg-MsB activation mediates strong avoidance behavior away from the stimulus source, which is preserved even in the absence of a central brain. Overall, our data show that mechanosensory stimulation can elicit a fast motor response, independently of central brain commands, to evade potentially harmful stimuli. In addition, it sheds light on how specific sensory circuits modulate motor control, including initiation of movement, allowing a better understanding of how different levels of coordination are controlled by the VNC and central brain locomotor circuits.

Loss of Fic causes progressive neurodegeneration in a Drosophila model of hereditary spastic paraplegia

Hereditary Spastic Paraplegia (HSP) is a group of rare inherited disorders characterized by progressive weakness and spasticity of the legs. Recent newly discovered biallelic variants in the gene FICD were found in patients with a highly similar phenotype to early onset HSP. FICD encodes filamentation induced by cAMP domain protein. FICD is involved in the AMPylation and deAMPylation protein modifications of the endoplasmic reticulum (ER) chaperone BIP, a major constituent of the ER that regulates the unfolded protein response. Although several biochemical properties of FICD have been characterized, the neurological function of FICD and the pathological mechanism underlying HSP are unknown. We established a Drosophila model to gain mechanistic understanding of the function of FICD in HSP pathogenesis, and specifically the role of BIP in neuromuscular physiology. Our studies on Drosophila Fic null mutants uncovered that loss of Fic resulted in locomotor impairment and reduced levels of BIP in the motor neuron circuitry, as well as increased reactive oxygen species (ROS) in the ventral nerve cord of Fic null mutants. Finally, feeding Drosophila Fic null mutants with chemical chaperones PBA or TUDCA, or treatment of patient fibroblasts with PBA, reduced the ROS accumulation. The neuronal phenotypes of Fic null mutants recapitulate several clinical features of HSP patients and further reveal cellular patho-mechanisms. By modeling FICD in Drosophila, we provide potential targets for intervention for HSP, and advance fundamental biology that is important for understanding related rare and common neuromuscular diseases.

Connectomic reconstruction of a female Drosophila ventral nerve cord

A deep understanding of how the brain controls behaviour requires mapping neural circuits down to the muscles that they control. Here, we apply automated tools to segment neurons and identify synapses in an electron microscopy dataset of an adult female Drosophila melanogaster ventral nerve cord (VNC)1, which functions like the vertebrate spinal cord to sense and control the body. We find that the fly VNC contains roughly 45 million synapses and 14,600 neuronal cell bodies. To interpret the output of the connectome, we mapped the muscle targets of leg and wing motor neurons using genetic driver lines2 and X-ray holographic nanotomography3. With this motor neuron atlas, we identified neural circuits that coordinate leg and wing movements during take-off. We provide the reconstruction of VNC circuits, the motor neuron atlas and tools for programmatic and interactive access as resources to support experimental and theoretical studies of how the nervous system controls behaviour.

Neuronal identity control at the resolution of a single transcription factor isoform

The brain exhibits remarkable neuronal diversity which is critical for its functional integrity. From the sheer number of cell types emerging from extensive transcriptional, morphological, and connectome datasets, the question arises of how the brain is capable of generating so many unique identities. 'Terminal selectors' are transcription factors hypothesized to determine the final identity characteristics in post-mitotic cells. Which transcription factors function as terminal selectors and the level of control they exert over different terminal characteristics are not well defined. Here, we establish a novel role for the transcription factor broad as a terminal selector in Drosophila melanogaster. We capitalize on existing large sequencing and connectomics datasets and employ a comprehensive characterization of terminal characteristics including Perturb-seq and whole-cell electrophysiology. We find a single isoform broad-z4 serves as the switch between the identity of two visual projection neurons LPLC1 and LPLC2. Broad-z4 is natively expressed in LPLC1, and is capable of transforming the transcriptome, morphology, and functional connectivity of LPLC2 cells into LPLC1 cells when perturbed. Our comprehensive work establishes a single isoform as the smallest unit underlying an identity switch, which may serve as a conserved strategy replicated across developmental programs.

Recent advances in insect vision in a 3D world: looming stimuli and escape behaviour

Detecting looming motion directly towards the insect is vital to its survival. Looming detection in two insects, flies and locusts, is described and contrasted. Pathways using looming detectors to trigger action and their topographical layout in the brain is explored in relation to facilitating behavioural selection. Similar visual stimuli, such as looming motion, are processed by nearby glomeruli in the brain. Insect-inspired looming motion detectors are combined to detect and avoid collision in different scenarios by robots, vehicles and unmanned aerial vehicle (UAV)s.

Descending networks transform command signals into population motor control

To convert intentions into actions, movement instructions must pass from the brain to downstream motor circuits through descending neurons (DNs). These include small sets of command-like neurons that are sufficient to drive behaviours1-the circuit mechanisms for which remain unclear. Here we show that command-like DNs in Drosophila directly recruit networks of additional DNs to orchestrate behaviours that require the active control of numerous body parts. Specifically, we found that command-like DNs previously thought to drive behaviours alone2-4 in fact co-activate larger populations of DNs. Connectome analyses and experimental manipulations revealed that this functional recruitment can be explained by direct excitatory connections between command-like DNs and networks of interconnected DNs in the brain. Descending population recruitment is necessary for behavioural control: DNs with many downstream descending partners require network co-activation to drive complete behaviours and drive only simple stereotyped movements in their absence. These DN networks reside within behaviour-specific clusters that inhibit one another. These results support a mechanism for command-like descending control in which behaviours are generated through the recruitment of increasingly large DN networks that compose behaviours by combining multiple motor subroutines.

Mechanosensory and command contributions to the Drosophila grooming sequence

Flies groom in response to competing mechanosensory cues in an anterior-to-posterior order using specific legs. From behavior screens, we identified a pair of cholinergic command-like neurons, Mago-no-Te (MGT), whose optogenetic activation elicits thoracic grooming by the back legs. Thoracic grooming is typically composed of body sweeps and leg rubs in alternation, but clonal analysis coupled with amputation experiments revealed that MGT activation only commands the body sweeps: initiation of leg rubbing requires contact between the leg and thorax. With new electron microscopy (EM) connectome data for the ventral nerve cord (VNC), we uncovered a circuit-based explanation for why stimulation of posterior thoracic mechanosensory bristles initiates cleaning by the back legs. Our previous work showed that flies weigh mechanosensory inputs across the body to select which part to groom, but we did not know why the thorax was always cleaned last. Here, the connectome for the VNC enabled us to identify a pair of GABAergic inhibitory neurons, UMGT1, that receives diverse sensory inputs and synapses onto both MGT and components of its downstream circuits. Optogenetic activation of UMGT1 suppresses thoracic cleaning, representing a mechanism by which mechanosensory stimuli on other body parts could take precedence in the grooming hierarchy. We also anatomically mapped the pre-motor circuit downstream of MGT, including inhibitory feedback connections that may enable rhythmicity and coordination of limb movement during thoracic grooming. The combination of behavioral screens and connectome analysis allowed us to identify a neural circuit connecting sensory-to-motor neurons that contributes to thoracic grooming.

Morphology and synapse topography optimize linear encoding of synapse numbers in Drosophila looming responsive descending neurons

Synapses are often precisely organized on dendritic arbors, yet the role of synaptic topography in dendritic integration remains poorly understood. Utilizing electron microscopy (EM) connectomics we investigate synaptic topography in Drosophila melanogaster looming circuits, focusing on retinotopically tuned visual projection neurons (VPNs) that synapse onto descending neurons (DNs). Synapses of a given VPN type project to non-overlapping regions on DN dendrites. Within these spatially constrained clusters, synapses are not retinotopically organized, but instead adopt near random distributions. To investigate how this organization strategy impacts DN integration, we developed multicompartment models of DNs fitted to experimental data and using precise EM morphologies and synapse locations. We find that DN dendrite morphologies normalize EPSP amplitudes of individual synaptic inputs and that near random distributions of synapses ensure linear encoding of synapse numbers from individual VPNs. These findings illuminate how synaptic topography influences dendritic integration and suggest that linear encoding of synapse numbers may be a default strategy established through connectivity and passive neuron properties, upon which active properties and plasticity can then tune as needed.

Synaptic architecture of leg and wing premotor control networks in Drosophila

Animal movement is controlled by motor neurons (MNs), which project out of the central nervous system to activate muscles. MN activity is coordinated by complex premotor networks that allow individual muscles to contribute to many different behaviors. Here, we use connectomics to analyze the wiring logic of premotor circuits controlling the Drosophila leg and wing. We find that both premotor networks cluster into modules that link MNs innervating muscles with related functions. Within most leg motor modules, the synaptic weights of each premotor neuron are proportional to the size of their target MNs, establishing a circuit basis for hierarchical MN recruitment. In contrast, wing premotor networks lack proportional synaptic connectivity, which may allow wing steering muscles to be recruited with different relative timing. By comparing the architecture of distinct limb motor control systems within the same animal, we identify common principles of premotor network organization and specializations that reflect the unique biomechanical constraints and evolutionary origins of leg and wing motor control.

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.

Descending control and regulation of spontaneous flight turns in Drosophila

The clumped distribution of resources in the world has influenced the pattern of foraging behavior since the origins of locomotion, selecting for a common search motif in which straight movements through resource-poor regions alternate with zig-zag exploration in resource-rich domains. For example, during local search, flying flies spontaneously execute rapid flight turns, called body saccades, but suppress these maneuvers during long-distance dispersal or when surging upstream toward an attractive odor. Here, we describe the key cellular components of a neural network in flies that generate spontaneous turns as well as a specialized pair of neurons that inhibits the network and suppresses turning. Using 2-photon imaging, optogenetic activation, and genetic ablation, we show that only four descending neurons appear sufficient to generate the descending commands to execute flight saccades. The network is organized into two functional units-one for right turns and one for left-with each unit consisting of an excitatory (DNae014) and an inhibitory (DNb01) neuron that project to the flight motor neuropil within the ventral nerve cord. Using resources from recently published connectomes of the fly, we identified a pair of large, distinct interneurons (VES041) that form inhibitory connections to all four saccade command neurons and created specific genetic driver lines for this cell. As predicted by its connectivity, activation of VES041 strongly suppresses saccades, suggesting that it promotes straight flight to regulate the transition between local search and long-distance dispersal. These results thus identify the key elements of a network that may play a crucial role in foraging ecology.

Descending control of motor sequences in Drosophila

The descending neurons connecting the fly's brain to its ventral nerve cord respond to sensory stimuli and evoke motor programs of varying complexity. Anatomical characterization of the descending neurons and their synaptic connections suggests how these circuits organize movements, while optogenetic manipulation of their activity reveals what behaviors they can induce. Monitoring their responses to sensory stimuli or during behavior performance indicates what information they may encode. Recent advances in all three approaches make the descending neurons an excellent place to better understand the sensorimotor integration and transformation required for nervous systems to govern the motor sequences that constitute animal behavior.

The processing of proprioceptive signals in distributed networks: insights from insect motor control

The integration of sensory information is required to maintain body posture and to generate robust yet flexible locomotion through unpredictable environments. To anticipate required adaptations in limb posture and enable compensation of sudden perturbations, an animal's nervous system assembles external (exteroception) and internal (proprioception) cues. Coherent neuronal representations of the proprioceptive context of the body and the appendages arise from the concerted action of multiple sense organs monitoring body kinetics and kinematics. This multimodal proprioceptive information, together with exteroceptive signals and brain-derived descending motor commands, converges onto premotor networks - i.e. the local neuronal circuitry controlling motor output and movements - within the ventral nerve cord (VNC), the insect equivalent of the vertebrate spinal cord. This Review summarizes existing knowledge and recent advances in understanding how local premotor networks in the VNC use convergent information to generate contextually appropriate activity, focusing on the example of posture control. We compare the role and advantages of distributed sensory processing over dedicated neuronal pathways, and the challenges of multimodal integration in distributed networks. We discuss how the gain of distributed networks may be tuned to enable the behavioral repertoire of these systems, and argue that insect premotor networks might compensate for their limited neuronal population size by, in comparison to vertebrate networks, relying more heavily on the specificity of their connections. At a time in which connectomics and physiological recording techniques enable anatomical and functional circuit dissection at an unprecedented resolution, insect motor systems offer unique opportunities to identify the mechanisms underlying multimodal integration for flexible motor control.

Neurons with names: Descending control and sensorimotor processing in insect motor control

Technical and methodological advances in recent years have brought new ways to tackle major classical questions in insect motor control. Particularly, significant advancements were achieved in comprehending brain descending control by characterizing descending neurons, their targets in the ventral nerve cord (VNC), and how local networks there integrate sensory information. While physiological experiments in larger insects brought us a better understanding of how sensory modalities are processed locally in the VNC, the development and improvement of genetic tools, principally in Drosophila, opened the door to individually characterize actors at these three levels of information flow in behavioral control. This brief review brings together the names and roles of some of those actors, by highlighting the most significant findings from our perspective.

Different spectral sensitivities of ON- and OFF-motion pathways enhance the detection of approaching color objects in Drosophila

Color and motion are used by many species to identify salient objects. They are processed largely independently, but color contributes to motion processing in humans, for example, enabling moving colored objects to be detected when their luminance matches the background. Here, we demonstrate an unexpected, additional contribution of color to motion vision in Drosophila. We show that behavioral ON-motion responses are more sensitive to UV than for OFF-motion, and we identify cellular pathways connecting UV-sensitive R7 photoreceptors to ON and OFF-motion-sensitive T4 and T5 cells, using neurogenetics and calcium imaging. Remarkably, this contribution of color circuitry to motion vision enhances the detection of approaching UV discs, but not green discs with the same chromatic contrast, and we show how this could generalize for systems with ON- and OFF-motion pathways. Our results provide a computational and circuit basis for how color enhances motion vision to favor the detection of saliently colored objects.

A Miniature Ultrasound Source for Neural Modulation

This work describes a unique ultrasound (US) exposure system designed to create very localized ( [Formula: see text]) sound fields at operating frequencies that are currently being used for preclinical US neuromodulation. This system can expose small clusters of neuronal tissue, such as cell cultures or intact brain structures in target animal models, opening up opportunities to examine possible mechanisms of action. We modified a dental descaler and drove it at a resonance frequency of 96 kHz, well above its nominal operating point of 28 kHz. A ceramic microtip from an ultrasonic wire bonder was attached to the end of the applicator, creating a 100- [Formula: see text] point source. The device was calibrated with a polyvinylidene difluoride (PVDF) membrane hydrophone, in a novel, air-backed, configuration. The experimental results were confirmed by simulation using a monopole model. The results show a consistent decaying sound field from the tip, well-suited to neural stimulation. The system was tested on an existing neurological model, Drosophila melanogaster, which has not previously been used for US neuromodulation experiments. The results show brain-directed US stimulation induces or suppresses motor actions, demonstrated through synchronized tracking of fly limb movements. These results provide the basis for ongoing and future studies of US interaction with neuronal tissue, both at the level of single neurons and intact organisms.

Descending control and regulation of spontaneous flight turns in Drosophila

The clumped distribution of resources in the world has influenced the pattern of foraging behavior since the origins of life, selecting for a common locomotor search motif in which straight movements through resource-poor regions alternate with zig -zag exploration in resource-rich domains. For example, flies execute rapid changes in flight heading called body saccades during local search, but suppress these turns during long-distance dispersal or when surging upwind after encountering an attractive odor plume. Here, we describe the key cellular components of a neural network in flies that generates spontaneous turns as well as a specialized neuron that inhibits the network to promote straight flight. Using 2-photon imaging, optogenetic activation, and genetic ablation, we show that only four descending neurons appear sufficient to generate the descending commands to execute flight saccades. The network is organized into two functional couplets-one for right turns and one for left-with each couplet consisting of an excitatory (DNae014) and inhibitory (DNb01) neuron that project to the flight motor neuropil within the ventral nerve cord. Using resources from recently published connectomes of the fly brain, we identified a large, unique interneuron (VES041) that forms inhibitory connections to all four saccade command neurons and created specific genetic driver lines for this cell. As suggested by its connectivity, activation of VES041 strongly suppresses saccades, suggesting that it regulates the transition between local search and long-distance dispersal. These results thus identify the critical elements of a network that not only structures the locomotor behavior of flies, but may also play a crucial role in their natural foraging ecology.

Multilevel visuomotor control of locomotion in Drosophila

Vision is critical for the control of locomotion, but the underlying neural mechanisms by which visuomotor circuits contribute to the movement of the body through space are yet not well understood. Locomotion engages multiple control systems, forming distinct interacting "control levels" driven by the activity of distributed and overlapping circuits. Therefore, a comprehensive understanding of the mechanisms underlying locomotion control requires the consideration of all control levels and their necessary coordination. Due to their small size and the wide availability of experimental tools, Drosophila has become an important model system to study this coordination. Traditionally, insect locomotion has been divided into studying either the biomechanics and local control of limbs, or navigation and course control. However, recent developments in tracking techniques, and physiological and genetic tools in Drosophila have prompted researchers to examine multilevel control coordination in flight and walking.

Convergent escape behaviour from distinct visual processing of impending collision in fish and grasshoppers

In animal species ranging from invertebrate to mammals, visually guided escape behaviours have been studied using looming stimuli, the two-dimensional expanding projection on a screen of an object approaching on a collision course at constant speed. The peak firing rate or membrane potential of neurons responding to looming stimuli often tracks a fixed threshold angular size of the approaching stimulus that contributes to the triggering of escape behaviours. To study whether this result holds more generally, we designed stimuli that simulate acceleration or deceleration over the course of object approach on a collision course. Under these conditions, we found that the angular threshold conveyed by collision detecting neurons in grasshoppers was sensitive to acceleration whereas the triggering of escape behaviours was less so. In contrast, neurons in goldfish identified through the characteristic features of the escape behaviours they trigger, showed little sensitivity to acceleration. This closely mirrored a broader lack of sensitivity to acceleration of the goldfish escape behaviour. Thus, although the sensory coding of simulated colliding stimuli with non-zero acceleration probably differs in grasshoppers and goldfish, the triggering of escape behaviours converges towards similar characteristics. Approaching stimuli with non-zero acceleration may help refine our understanding of neural computations underlying escape behaviours in a broad range of animal species. KEY POINTS: A companion manuscript showed that two mathematical models of collision-detecting neurons in grasshoppers and goldfish make distinct predictions for the timing of their responses to simulated objects approaching on a collision course with non-zero acceleration. Testing these experimental predictions showed that grasshopper neurons are sensitive to acceleration while goldfish neurons are not, in agreement with the distinct models proposed previously in these species using constant velocity approaches. Grasshopper and goldfish escape behaviours occurred after the stimulus reached a fixed angular size insensitive to acceleration, suggesting further downstream processing in grasshopper motor circuits to match what was observed in goldfish. Thus, in spite of different sensory processing in the two species, escape behaviours converge towards similar solutions. The use of object acceleration during approach on a collision course may help better understand the neural computations implemented for collision avoidance in a broad range of species.

A rise-to-threshold process for a relative-value decision

Whereas progress has been made in the identification of neural signals related to rapid, cued decisions1-3, less is known about how brains guide and terminate more ethologically relevant decisions in which an animal's own behaviour governs the options experienced over minutes4-6. Drosophila search for many seconds to minutes for egg-laying sites with high relative value7,8 and have neurons, called oviDNs, whose activity fulfills necessity and sufficiency criteria for initiating the egg-deposition motor programme9. Here we show that oviDNs express a calcium signal that (1) dips when an egg is internally prepared (ovulated), (2) drifts up and down over seconds to minutes-in a manner influenced by the relative value of substrates-as a fly determines whether to lay an egg and (3) reaches a consistent peak level just before the abdomen bend for egg deposition. This signal is apparent in the cell bodies of oviDNs in the brain and it probably reflects a behaviourally relevant rise-to-threshold process in the ventral nerve cord, where the synaptic terminals of oviDNs are located and where their output can influence behaviour. We provide perturbational evidence that the egg-deposition motor programme is initiated once this process hits a threshold and that subthreshold variation in this process regulates the time spent considering options and, ultimately, the choice taken. Finally, we identify a small recurrent circuit that feeds into oviDNs and show that activity in each of its constituent cell types is required for laying an egg. These results argue that a rise-to-threshold process regulates a relative-value, self-paced decision and provide initial insight into the underlying circuit mechanism for building this process.

An information theoretic method to resolve millisecond-scale spike timing precision in a comprehensive motor program

Sensory inputs in nervous systems are often encoded at the millisecond scale in a precise spike timing code. There is now growing evidence in behaviors ranging from slow breathing to rapid flight for the prevalence of precise timing encoding in motor systems. Despite this, we largely do not know at what scale timing matters in these circuits due to the difficulty of recording a complete set of spike-resolved motor signals and assessing spike timing precision for encoding continuous motor signals. We also do not know if the precision scale varies depending on the functional role of different motor units. We introduce a method to estimate spike timing precision in motor circuits using continuous MI estimation at increasing levels of added uniform noise. This method can assess spike timing precision at fine scales for encoding rich motor output variation. We demonstrate the advantages of this approach compared to a previously established discrete information theoretic method of assessing spike timing precision. We use this method to analyze the precision in a nearly complete, spike resolved recording of the 10 primary wing muscles control flight in an agile hawk moth, Manduca sexta. Tethered moths visually tracked a robotic flower producing a range of turning (yaw) torques. We know that all 10 muscles in this motor program encode the majority of information about yaw torque in spike timings, but we do not know whether individual muscles encode motor information at different levels of precision. We demonstrate that the scale of temporal precision in all motor units in this insect flight circuit is at the sub-millisecond or millisecond-scale, with variation in precision scale present between muscle types. This method can be applied broadly to estimate spike timing precision in sensory and motor circuits in both invertebrates and vertebrates.

Neural Circuit Mechanisms Involved in Animals' Detection of and Response to Visual Threats

Evading or escaping from predators is one of the most crucial issues for survival across the animal kingdom. The timely detection of predators and the initiation of appropriate fight-or-flight responses are innate capabilities of the nervous system. Here we review recent progress in our understanding of innate visually-triggered defensive behaviors and the underlying neural circuit mechanisms, and a comparison among vinegar flies, zebrafish, and mice is included. This overview covers the anatomical and functional aspects of the neural circuits involved in this process, including visual threat processing and identification, the selection of appropriate behavioral responses, and the initiation of these innate defensive behaviors. The emphasis of this review is on the early stages of this pathway, namely, threat identification from complex visual inputs and how behavioral choices are influenced by differences in visual threats. We also briefly cover how the innate defensive response is processed centrally. Based on these summaries, we discuss coding strategies for visual threats and propose a common prototypical pathway for rapid innate defensive responses.

Visual processing in the fly, from photoreceptors to behavior

Originally a genetic model organism, the experimental use of Drosophila melanogaster has grown to include quantitative behavioral analyses, sophisticated perturbations of neuronal function, and detailed sensory physiology. A highlight of these developments can be seen in the context of vision, where pioneering studies have uncovered fundamental and generalizable principles of sensory processing. Here we begin with an overview of vision-guided behaviors and common methods for probing visual circuits. We then outline the anatomy and physiology of brain regions involved in visual processing, beginning at the sensory periphery and ending with descending motor control. Areas of focus include contrast and motion detection in the optic lobe, circuits for visual feature selectivity, computations in support of spatial navigation, and contextual associative learning. Finally, we look to the future of fly visual neuroscience and discuss promising topics for further study.

retro-Tango enables versatile retrograde circuit tracing in Drosophila

Transsynaptic tracing methods are crucial tools in studying neural circuits. Although a couple of anterograde tracing methods and a targeted retrograde tool have been developed in Drosophila melanogaster, there is still need for an unbiased, user-friendly, and flexible retrograde tracing system. Here, we describe retro-Tango, a method for transsynaptic, retrograde circuit tracing and manipulation in Drosophila. In this genetically encoded system, a ligand-receptor interaction at the synapse triggers an intracellular signaling cascade that results in reporter gene expression in presynaptic neurons. Importantly, panneuronal expression of the elements of the cascade renders this method versatile, enabling its use not only to test hypotheses but also to generate them. We validate retro-Tango in various circuits and benchmark it by comparing our findings with the electron microscopy reconstruction of the Drosophila hemibrain. Our experiments establish retro-Tango as a key method for circuit tracing in neuroscience research.

Approaching object acceleration differentially affects the predictions of neuronal collision avoidance models

The processing of visual information for collision avoidance has been investigated at the biophysical level in several model systems. In grasshoppers, the (so-called) [Formula: see text] model captures reasonably well the visual processing performed by an identified neuron called the lobular giant movement detector as it tracks approaching objects. Similar phenomenological models have been used to describe either the firing rate or the membrane potential of neurons responsible for visually guided collision avoidance in other animals. Specifically, in goldfish, the [Formula: see text] model has been proposed to describe the Mauthner cell, an identified neuron involved in startle escape responses. In the vinegar fly, a third model was developed for the giant fiber neuron, which triggers last resort escapes immediately before an impending collision. One key property of these models is their prediction that peak neuronal responses occur at a fixed delay after the simulated approaching object reaches a threshold angular size on the retina. This prediction is valid for simulated objects approaching at a constant speed. We tested whether it remains valid when approaching objects accelerate. After characterizing and comparing the models' responses to accelerating and constant speed stimuli, we find that the prediction holds true for the [Formula: see text] and the giant fiber model, but not for the [Formula: see text] model. These results suggest that acceleration in the approach trajectory of an object may help distinguish and further constrain the neuronal computations required for collision avoidance in grasshoppers, fish and vinegar flies.

Optic flow based spatial vision in insects

The optic flow, i.e., the displacement of retinal images of objects in the environment induced by self-motion, is an important source of spatial information, especially for fast-flying insects. Spatial information over a wide range of distances, from the animal's immediate surroundings over several hundred metres to kilometres, is necessary for mediating behaviours, such as landing manoeuvres, collision avoidance in spatially complex environments, learning environmental object constellations and path integration in spatial navigation. To facilitate the processing of spatial information, the complexity of the optic flow is often reduced by active vision strategies. These result in translations and rotations being largely separated by a saccadic flight and gaze mode. Only the translational components of the optic flow contain spatial information. In the first step of optic flow processing, an array of local motion detectors provides a retinotopic spatial proximity map of the environment. This local motion information is then processed in parallel neural pathways in a task-specific manner and used to control the different components of spatial behaviour. A particular challenge here is that the distance information extracted from the optic flow does not represent the distances unambiguously, but these are scaled by the animal's speed of locomotion. Possible ways of coping with this ambiguity are discussed.

Synaptic gradients transform object location to action

To survive, animals must convert sensory information into appropriate behaviours^1,2. Vision is a common sense for locating ethologically relevant stimuli and guiding motor responses^3-5. How circuitry converts object location in retinal coordinates to movement direction in body coordinates remains largely unknown. Here we show through behaviour, physiology, anatomy and connectomics in Drosophila that visuomotor transformation occurs by conversion of topographic maps formed by the dendrites of feature-detecting visual projection neurons (VPNs)^6,7 into synaptic weight gradients of VPN outputs onto central brain neurons. We demonstrate how this gradient motif transforms the anteroposterior location of a visual looming stimulus into the fly's directional escape. Specifically, we discover that two neurons postsynaptic to a looming-responsive VPN type promote opposite takeoff directions. Opposite synaptic weight gradients onto these neurons from looming VPNs in different visual field regions convert localized looming threats into correctly oriented escapes. For a second looming-responsive VPN type, we demonstrate graded responses along the dorsoventral axis. We show that this synaptic gradient motif generalizes across all 20 primary VPN cell types and most often arises without VPN axon topography. Synaptic gradients may thus be a general mechanism for conveying spatial features of sensory information into directed motor outputs.

The calcium-sensing receptor (CaSR) regulates zebrafish sensorimotor decision making via a genetically defined cluster of hindbrain neurons

Decision making is a fundamental nervous system function that ranges widely in complexity and speed of execution. We previously established larval zebrafish as a model for sensorimotor decision making and identified the G-protein-coupled calcium-sensing receptor (CaSR) to be critical for this process. Here, we report that CaSR functions in neurons to dynamically regulate the bias between two behavioral outcomes: escapes and reorientations. By employing a computational guided transgenic strategy, we identify a genetically defined neuronal cluster in the hindbrain as a key candidate site for CaSR function. Finally, we demonstrate that transgenic CaSR expression targeting this cluster consisting of a few hundred neurons shifts behavioral bias in wild-type animals and restores decision making deficits in CaSR mutants. Combined, our data provide a rare example of a G-protein-coupled receptor that biases vertebrate sensorimotor decision making via a defined neuronal cluster.

Fiddler crabs are unique in timing their escape responses based on speed-dependent visual cues

Predation risk imposes strong selection pressures on visual systems to quickly and accurately identify the position and movement of potential predators.^1,2 Many invertebrates and other small animals, however, have limited capacity for distance perception due to their low spatial resolution and closely situated eyes.^3,4 Consequently, they often rely on simplified decision criteria, essentially heuristics or "rules of thumb", to make decisions. The visual cues animals use to make escape decisions are surprisingly consistent, especially among arthropods, with the timing of escape commonly triggered by size-dependent visual cues such as angular size or angular size increment.^5,6,7,8,9,10 Angular size, however, confuses predator size and distance and provides no information about the speed of the attack. Here, we show that fiddler crabs (Gelasimus dampieri) are unique among the arthropods studied to date as they timed their escape response based on the speed of an object's angular expansion. The crabs responded reliably by running away from visual stimuli that expanded at approximately 1.7 degrees/s, irrespective of stimulus size, speed, or its initial distance from the crabs. Though the threshold expansion speed was consistent across different stimulus conditions, we found that the escape timing was modulated by the elevation at which the stimulus approached, suggesting that other risk factors can bias the expansion speed threshold. The results suggest that the visual escape cues used by arthropods are less conserved than previously thought and that lifestyle and environment are significant drivers determining the escape cues used by different species.

Fear conditioning in invertebrates

Learning to identify and predict threats is a basic skill that allows animals to avoid harm. Studies in invertebrates like Aplysia californica, Drosophila melanogaster, and Caenorhabditis elegans have revealed that the basic mechanisms of learning and memory are conserved. We will summarize these studies and highlight the common pathways and mechanisms in invertebrate fear-associated behavioral changes. Fear conditioning studies utilizing electric shock in Aplysia and Drosophila have demonstrated that serotonin or dopamine are typically involved in relaying aversive stimuli, leading to changes in intracellular calcium levels and increased presynaptic neurotransmitter release and short-term changes in behavior. Long-term changes in behavior typically require multiple, spaced trials, and involve changes in gene expression. C. elegans studies have demonstrated these basic aversive learning principles as well; however, fear conditioning has yet to be explicitly demonstrated in this model due to stimulus choice. Because predator-prey relationships can be used to study learned fear in a naturalistic context, this review also summarizes what is known about predator-induced behaviors in these three organisms, and their potential applications for future investigations into fear conditioning.

A neurogenetic mechanism of experience-dependent suppression of aggression

Aggression is an ethologically important social behavior, but excessive aggression can be detrimental to fitness. Social experiences among conspecific individuals reduce aggression in many species, the mechanism of which is largely unknown. We found that loss-of-function mutation of nervy (nvy), a Drosophila homolog of vertebrate myeloid translocation genes (MTGs), increased aggressiveness only in socially experienced flies and that this could be reversed by neuronal expression of human MTGs. A subpopulation of octopaminergic/tyraminergic neurons labeled by nvy was specifically required for such social experience-dependent suppression of aggression, in both males and females. Cell type-specific transcriptomic analysis of these neurons revealed aggression-controlling genes that are likely downstream of nvy. Our results illustrate both genetic and neuronal mechanisms by which the nervous system suppresses aggression in a social experience-dependent manner, a poorly understood process that is considered important for maintaining the fitness of animals.

Modeling relationships between rhythmic processes and neuronal spike timing

Neurons are embedded in complex networks, where they participate in repetitive, coordinated interactions with other neurons. Neuronal spike timing is thus predictably constrained by a range of ionic currents that shape activity at both short (milliseconds) and longer (tens to hundreds of milliseconds) timescales, but we lack analytical tools to rigorously identify these relationships. Here, we innovate a modeling approach to test the relationship between oscillations in the local field potential (LFP) and neuronal spike timing. We use kernel density estimation to relate single neuron spike timing and the phase of LFP rhythms (in simulated and hippocampal CA1 neuronal spike trains). We then combine phase and short (3 ms) spike history information within a logistic regression framework ("phaseSH models"), and show that models that leverage refractory constraints and oscillatory phase information can effectively test whether-and the degree to which-rhythmic currents (as measured from the LFP) reliably explain variance in neuronal spike trains. This approach allows researchers to systematically test the relationship between oscillatory activity and neuronal spiking dynamics as they unfold over time and as they shift to adapt to distinct behavioral conditions.

Social Cues of Safety Can Override Differences in Threat Level

Animals in groups integrate social with directly gathered information about the environment to guide decisions regarding reproduction, foraging, and defence against predatory threats. In the context of predation, usage of social information has acute fitness benefits, aiding the detection of predators, the mounting of concerted defensive responses, or allowing the inference of safety, permitting other beneficial behaviors, such as foraging for food. We previously showed that Drosophila melanogaster exposed to an inescapable visual threat use freezing by surrounding flies as a cue of danger and movement resumption as a cue of safety. Moreover, group responses were primarily guided by the safety cues, resulting in a net social buffering effect, i.e., a graded decrease in freezing behavior with increasing group sizes, similar to other animals. Whether and how different threat levels affect the use of social cues to guide defense responses remains elusive. Here, we investigated this issue by exposing flies individually and in groups to two threat imminences using looms of different speeds. We showed that freezing responses are stronger to the faster looms regardless of social condition. However, social buffering was stronger for groups exposed to the fast looms, such that the increase in freezing caused by the higher threat was less prominent in flies tested in groups than those tested individually. Through artificial control of movement, we created groups composed of moving and freezing flies and by varying group composition, we titrated the motion cues that surrounding flies produce, which were held constant across threat levels. We found that the same level of safety motion cues had a bigger weight on the flies’ decisions when these were exposed to the higher threat, thus overriding differences in perceived threat levels. These findings shed light on the “safety in numbers” effect, revealing the modulation of the saliency of social safety cues across threat intensities, a possible mechanism to regulate costly defensive responses.

Behavioural and neural responses of crabs show evidence for selective attention in predator avoidance

Selective attention, the ability to focus on a specific stimulus and suppress distractions, plays a fundamental role for animals in many contexts, such as mating, feeding, and predation. Within natural environments, animals are often confronted with multiple stimuli of potential importance. Such a situation significantly complicates the decision-making process and imposes conflicting information on neural systems. In the context of predation, selectively attending to one of multiple threats is one possible solution. However, how animals make such escape decisions is rarely studied. A previous field study on the fiddler crab, Gelasimus dampieri, provided evidence of selective attention in the context of escape decisions. To identify the underlying mechanisms that guide their escape decisions, we measured the crabs' behavioural and neural responses to either a single, or two simultaneously approaching looming stimuli. The two stimuli were either identical or differed in contrast to represent different levels of threat certainty. Although our behavioural data provides some evidence that crabs perceive signals from both stimuli, we show that both the crabs and their looming-sensitive neurons almost exclusively respond to only one of two simultaneous threats. The crabs' body orientation played an important role in their decision about which stimulus to run away from. When faced with two stimuli of differing contrasts, both neurons and crabs were much more likely to respond to the stimulus with the higher contrast. Our data provides evidence that the crabs' looming-sensitive neurons play an important part in the mechanism that drives their selective attention in the context of predation. Our results support previous suggestions that the crabs' escape direction is calculated downstream of their looming-sensitive neurons by means of a population vector of the looming sensitive neuronal ensemble.

An optogenetics device with smartphone video capture to introduce neurotechnology and systems neuroscience to high school students

Although neurotechnology careers are on the rise, and neuroscience curriculums have significantly grown at the undergraduate and graduate levels, increasing neuroscience and neurotechnology exposure in high school curricula has been an ongoing challenge. This is due, in part, to difficulties in converting cutting-edge neuroscience research into hands-on activities that are accessible for high school students and affordable for high school educators. Here, we describe and characterize a low-cost, easy-to-construct device to enable students to record rapid Drosophila melanogaster (fruit fly) behaviors during optogenetics experiments. The device is generated from inexpensive Arduino kits and utilizes a smartphone for video capture, making it easy to adopt in a standard biology laboratory. We validate this device is capable of replicating optogenetics experiments performed with more sophisticated setups at leading universities and institutes. We incorporate the device into a high school neuroengineering summer workshop. We find student participation in the workshop significantly enhances their understanding of key neuroscience and neurotechnology concepts, demonstrating how this device can be utilized in high school settings and undergraduate research laboratories seeking low-cost alternatives.

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.

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HS cells receive stride-coupled signals via ascending neurons

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The stride-coupled signals reflect an internal motor context

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Motor context modulates HS cells at multiple timescales

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HS cells drive rapid steering depending on motor context

From Photons to Behaviors: Neural Implementations of Visual Behaviors in Drosophila

Neural implementations of visual behaviors in Drosophila have been dissected intensively in the past couple of decades. The availability of premiere genetic toolkits, behavioral assays in tethered or freely moving conditions, and advances in connectomics have permitted the understanding of the physiological and anatomical details of the nervous system underlying complex visual behaviors. In this review, we describe recent advances on how various features of a visual scene are detected by the Drosophila visual system and how the neural circuits process these signals and elicit an appropriate behavioral response. Special emphasis was laid on the neural circuits that detect visual features such as brightness, color, local motion, optic flow, and translating or approaching visual objects, which would be important for behaviors such as phototaxis, optomotor response, attraction (or aversion) to moving objects, navigation, and visual learning. This review offers an integrative framework for how the fly brain detects visual features and orchestrates an appropriate behavioral response.

Roles of neural communication between the brain and thoracic ganglia in the selection and regulation of the cricket escape behavior

To survive a predator's attack, prey animals must exhibit escape responses that are appropriately regulated in terms of their moving speed, distance, and direction. Insect locomotion is considered to be controlled by an interaction between the brain, which is involved in behavioral decision-making, and the thoracic ganglia (TG), which are primary motor centers. However, it remains unknown which descending and ascending signals between these neural centers are involved in the regulation of the escape behavior. We addressed the distinct roles of the brain and TG in the wind-elicited escape behavior of crickets by assessing the effects of partial ablation of the intersegmental communications on escape responses. We unilaterally cut the ventral nerve cord (VNC) at different locations, between the brain and TG, or between the TG and terminal abdominal ganglion (TAG), a primary sensory center of the cercal system. The partial ablation of ascending signals to the brain greatly reduced the jumping response rather than running, indicating that sensory information processing in the brain is essential for the choice of escape responses. The ablation of descending signals from the brain to the TG impaired locomotor performance and directional control of the escape responses, suggesting that locomotion in the escape behavior largely depends on the descending signals from the brain. Finally, the extracellular recording from the cervical VNC indicated a difference in the descending activities preceding the escape responses between running and jumping. Our results demonstrated that the brain sends the descending signals encoding the behavioral choice and locomotor regulation to the TG, while the TG seem to have other specific roles, such as in the preparation of escape movement.

Neural mechanisms to exploit positional geometry for collision avoidance

Visual motion provides rich geometrical cues about the three-dimensional configuration of the world. However, how brains decode the spatial information carried by motion signals remains poorly understood. Here, we study a collision-avoidance behavior in Drosophila as a simple model of motion-based spatial vision. With simulations and psychophysics, we demonstrate that walking Drosophila exhibit a pattern of slowing to avoid collisions by exploiting the geometry of positional changes of objects on near-collision courses. This behavior requires the visual neuron LPLC1, whose tuning mirrors the behavior and whose activity drives slowing. LPLC1 pools inputs from object and motion detectors, and spatially biased inhibition tunes it to the geometry of collisions. Connectomic analyses identified circuitry downstream of LPLC1 that faithfully inherits its response properties. Overall, our results reveal how a small neural circuit solves a specific spatial vision task by combining distinct visual features to exploit universal geometrical constraints of the visual world.

Bottlenecks, Modularity, and the Neural Control of Behavior

In almost all animals, the transfer of information from the brain to the motor circuitry is facilitated by a relatively small number of neurons, leading to a constraint on the amount of information that can be transmitted. Our knowledge of how animals encode information through this pathway, and the consequences of this encoding, however, is limited. In this study, we use a simple feed-forward neural network to investigate the consequences of having such a bottleneck and identify aspects of the network architecture that enable robust information transfer. We are able to explain some recently observed properties of descending neurons—that they exhibit a modular pattern of connectivity and that their excitation leads to consistent alterations in behavior that are often dependent upon the desired behavioral state of the animal. Our model predicts that in the presence of an information bottleneck, such a modular structure is needed to increase the efficiency of the network and to make it more robust to perturbations. However, it does so at the cost of an increase in state-dependent effects. Despite its simplicity, our model is able to provide intuition for the trade-offs faced by the nervous system in the presence of an information processing constraint and makes predictions for future experiments.

Identifying Inputs to Visual Projection Neurons in Drosophila Lobula by Analyzing Connectomic Data

Electron microscopy (EM)-based connectomes provide important insights into how visual circuitry of fruit fly Drosophila computes various visual features, guiding and complementing behavioral and physiological studies. However, connectomic analyses of the lobula, a neuropil putatively dedicated to detecting object-like features, remains underdeveloped, largely because of incomplete data on the inputs to the brain region. Here, we attempted to map the columnar inputs into the Drosophila lobula neuropil by performing connectivity-based and morphology-based clustering on a densely reconstructed connectome dataset. While the dataset mostly lacked visual neuropils other than lobula, which would normally help identify inputs to lobula, our clustering analysis successfully extracted clusters of cells with homogeneous connectivity and morphology, likely representing genuine cell types. We were able to draw a correspondence between the resulting clusters and previously identified cell types, revealing previously undocumented connectivity between lobula input and output neurons. While future, more complete connectomic reconstructions are necessary to verify the results presented here, they can serve as a useful basis for formulating hypotheses on mechanisms of visual feature detection in lobula.

A pair of commissural command neurons induces Drosophila wing grooming

In many behaviors such walking and swimming, animals need to coordinate their left and right limbs. In Drosophila, wing grooming can be induced by activation of sensory organs called campaniform sensilla. Flies usually clean one wing at a time, coordinating their left and right hind legs to sweep the dorsal and ventral surfaces of the wing. Here, we identify a pair of interneurons located in the ventral nerve cord that we name wing projection neurons 1 (wPN1) whose optogenetic activation induces wing grooming. Inhibition of wPN1 activity reduces wing grooming. They receive synaptic input from ipsilateral wing campaniform sensilla and wing mechanosensory bristle neurons, and they extend axonal arbors to the hind leg neuropils. Although they project contralaterally, their activation induces ipsilateral wing grooming. Anatomical and behavioral data support a role for wPN1 as command neurons coordinating both hind legs to work together to clean the stimulated wing.

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A pair of ventral cord neurons, wPN1, is sufficient and necessary for wing grooming

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wPN1 receive contacts from two types of wing mechanosensors

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wPN1 are cholinergic and have commissural projections

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Single-side activation of wPN1 drives both hind legs to clean the ipsilateral wing

Descending neurons coordinate anterior grooming behavior in Drosophila

The brain coordinates the movements that constitute behavior, but how descending neurons convey the myriad of commands required to activate the motor neurons of the limbs in the right order and combinations to produce those movements is not well understood. For anterior grooming behavior in the fly, we show that its component head sweeps and leg rubs can be initiated separately, or as a set, by different descending neurons. Head sweeps and leg rubs are mutually exclusive movements of the front legs that normally alternate, and we show that circuits in the ventral nerve cord as well as in the brain can resolve competing commands. Finally, the left and right legs must work together to remove debris. The coordination for leg rubs can be achieved by unilateral activation of a single descending neuron, while a similar manipulation of a different descending neuron decouples the legs to produce single-sided head sweeps. Taken together, these results demonstrate that distinct descending neurons orchestrate the complex alternation between the movements that make up anterior grooming.

Shallow neural networks trained to detect collisions recover features of visual loom-selective neurons

Animals have evolved sophisticated visual circuits to solve a vital inference problem: detecting whether or not a visual signal corresponds to an object on a collision course. Such events are detected by specific circuits sensitive to visual looming, or objects increasing in size. Various computational models have been developed for these circuits, but how the collision-detection inference problem itself shapes the computational structures of these circuits remains unknown. Here, inspired by the distinctive structures of LPLC2 neurons in the visual system of Drosophila, we build anatomically-constrained shallow neural network models and train them to identify visual signals that correspond to impending collisions. Surprisingly, the optimization arrives at two distinct, opposing solutions, only one of which matches the actual dendritic weighting of LPLC2 neurons. Both solutions can solve the inference problem with high accuracy when the population size is large enough. The LPLC2-like solutions reproduces experimentally observed LPLC2 neuron responses for many stimuli, and reproduces canonical tuning of loom sensitive neurons, even though the models are never trained on neural data. Thus, LPLC2 neuron properties and tuning are predicted by optimizing an anatomically-constrained neural network to detect impending collisions. More generally, these results illustrate how optimizing inference tasks that are important for an animal's perceptual goals can reveal and explain computational properties of specific sensory neurons.

Neural Circuits Underlying Behavioral Flexibility: Insights From Drosophila

Behavioral flexibility is critical to survival. Animals must adapt their behavioral responses based on changes in the environmental context, internal state, or experience. Studies in Drosophila melanogaster have provided insight into the neural circuit mechanisms underlying behavioral flexibility. Here we discuss how Drosophila behavior is modulated by internal and behavioral state, environmental context, and learning. We describe general principles of neural circuit organization and modulation that underlie behavioral flexibility, principles that are likely to extend to other species.

Transforming representations of movement from body- to world-centric space

When an animal moves through the world, its brain receives a stream of information about the body's translational velocity from motor commands and sensory feedback signals. These incoming signals are referenced to the body, but ultimately, they must be transformed into world-centric coordinates for navigation1,2. Here we show that this computation occurs in the fan-shaped body in the brain of Drosophila melanogaster. We identify two cell types, PFNd and PFNv3-5, that conjunctively encode translational velocity and heading as a fly walks. In these cells, velocity signals are acquired from locomotor brain regions6 and are multiplied with heading signals from the compass system. PFNd neurons prefer forward-ipsilateral movement, whereas PFNv neurons prefer backward-contralateral movement, and perturbing PFNd neurons disrupts idiothetic path integration in walking flies7. Downstream, PFNd and PFNv neurons converge onto hΔB neurons, with a connectivity pattern that pools together heading and translation direction combinations corresponding to the same movement in world-centric space. This network motif effectively performs a rotation of the brain's representation of body-centric translational velocity according to the current heading direction. Consistent with our predictions, we observe that hΔB neurons form a representation of translational velocity in world-centric coordinates. By integrating this representation over time, it should be possible for the brain to form a working memory of the path travelled through the environment8-10.

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.