Mechanosensation and Adaptive Motor Control in Insects

A conserved role for centriolar satellites in translation of centrosomal and ciliary proteins

Centriolar satellites are cytoplasmic particles found in the vicinity of centrosomes and cilia whose specific functional contribution has long been unclear. Here, we identify Combover as the Drosophila ortholog of the main scaffolding component of satellites, PCM1. Like PCM1, Combover localizes to cytoplasmic foci containing centrosomal proteins and its depletion or mutation results in centrosomal and ciliary phenotypes. Strikingly, however, the concentration of satellites near centrosomes and cilia is not a conserved feature, nor do Combover foci display directed movement. Proximity interaction analysis revealed not only centrosomal and ciliary proteins, but also RNA-binding proteins and proteins involved in quality control. Further work in Drosophila and vertebrate cells found satellites to be associated with centrosomal and ciliary mRNAs, as well as evidence for protein synthesis occurring directly at satellites. Given that PCM1 depletion does not affect overall protein levels, we propose that satellites instead promote the coordinate synthesis of centrosomal and ciliary proteins, thereby facilitating the formation of protein complexes.

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 the 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.

Divergent neural circuits for proprioceptive and exteroceptive sensing of the Drosophila leg

Somatosensory neurons provide the nervous system with information about mechanical forces originating inside and outside the body. Here, we use connectomics from electron microscopy to reconstruct and analyze neural circuits downstream of the largest somatosensory organ in the Drosophila leg, the femoral chordotonal organ (FeCO). The FeCO has been proposed to support both proprioceptive sensing of the fly's femur-tibia joint and exteroceptive sensing of substrate vibrations, but it was unknown which sensory neurons and central circuits contribute to each of these functions. We found that different subtypes of FeCO sensory neurons feed into distinct proprioceptive and exteroceptive pathways. Position- and movement-encoding FeCO neurons connect to local leg motor control circuits in the ventral nerve cord (VNC), indicating a proprioceptive function. In contrast, signals from the vibration-encoding FeCO neurons are integrated across legs and transmitted to mechanosensory regions in the brain, indicating an exteroceptive function. Overall, our analyses reveal the structure of specialized circuits for processing proprioceptive and exteroceptive signals from the fly leg. These findings are consistent with a growing body of work in invertebrate and vertebrate species demonstrating the existence of specialized limb mechanosensory pathways for sensing external vibrations.

The fruit fly, Drosophila melanogaster, as a microrobotics platform

Engineering small autonomous agents capable of operating in the microscale environment remains a key challenge, with current systems still evolving. Our study explores the fruit fly, Drosophila melanogaster, a classic model system in biology and a species adept at microscale interaction, as a biological platform for microrobotics. Initially, we focus on remotely directing the walking paths of fruit flies in an experimental arena. We accomplish this through two distinct approaches: harnessing the fruit flies' optomotor response and optogenetic modulation of its olfactory system. These techniques facilitate reliable and repeated guidance of flies between arbitrary spatial locations. We guide flies along predetermined trajectories, enabling them to scribe patterns resembling textual characters through their locomotion. We enhance olfactory-guided navigation through additional optogenetic activation of attraction-inducing mushroom body output neurons. We extend this control to collective behaviors in shared spaces and navigation through constrained maze-like environments. We further use our guidance technique to enable flies to carry a load across designated points in space, establishing the upper bound on their weight-carrying capabilities. Additionally, we demonstrate that visual guidance can facilitate novel interactions between flies and objects, showing that flies can consistently relocate a small spherical object over significant distances. Last, we demonstrate multiagent formation control, with flies alternating between distinct spatial patterns. Beyond expanding tools available for microrobotics, these behavioral contexts can provide insights into the neurological basis of behavior in fruit flies.

Decoding neuronal wiring by joint inference of cell identity and synaptic connectivity

Animal behaviors are executed by motor neurons (MNs), which receive information from complex pre-motor neuron (preMN) circuits and output commands to muscles. How motor circuits are established during development remains an important unsolved problem in neuroscience. Here we focus on the development of the motor circuits that control the movements of the adult legs in Drosophila melanogaster. After generating single-cell RNA sequencing (scRNAseq) datasets for leg MNs at multiple time points, we describe the time course of gene expression for multiple gene families. This analysis reveals that transcription factors (TFs) and cell adhesion molecules (CAMs) appear to drive the molecular diversity between individual MNs. In parallel, we introduce ConnectionMiner, a novel computational tool that integrates scRNAseq data with electron microscopy-derived connectomes. ConnectionMiner probabilistically refines ambiguous cell type annotations by leveraging neural wiring patterns, and, in turn, it identifies combinatorial gene expression signatures that correlate with synaptic connectivity strength. Applied to the Drosophila leg motor system, ConnectionMiner yields a comprehensive transcriptional annotation of both MNs and preMNs and uncovers candidate effector gene combinations that likely orchestrate the assembly of neural circuits from preMNs to MNs and ultimately to muscles.

Lepidopteran scale cells derive from sensory organ precursors through a canonical lineage

The success of butterflies and moths is tightly linked to the origin of scales within the group. A long-standing hypothesis postulates that scales are homologous to the well-described mechanosensory bristles found in the fruit fly Drosophila melanogaster, as both derive from an epithelial precursor. Previous histological and candidate gene approaches identified parallels in genes involved in scale and bristle development. Here, we provide developmental and transcriptomic evidence that the differentiation of lepidopteran scales derives from the sensory organ precursor (SOP). Live imaging in lepidopteran pupae shows that SOP cells undergo two asymmetric divisions that first abrogate the neurogenic lineage, and then lead to a differentiated scale precursor and its associated socket cell. Single-nucleus RNA sequencing using early pupal wings revealed differential gene expression patterns that mirror SOP development, suggesting a shared developmental program. Additionally, we recovered a newly associated gene, the transcription factor pdm3, involved in the proper differentiation of butterfly wing scales. Altogether, these data open up avenues for understanding scale type specification and development, and illustrate how single-cell transcriptomics provide a powerful platform for understanding evolution of cell types.

An evolutionarily conserved cation channel tunes the sensitivity of gustatory neurons to ephaptic inhibition in Drosophila

In ephaptic coupling, physically adjacent neurons influence one another's activity via the electric fields they generate. To date, the molecular mechanisms that mediate and modulate ephaptic coupling's effects remain poorly understood. Here, we show that the hyperpolarization-activated cyclic nucleotide-gated (HCN) channel lateralizes the potentially mutual ephaptic inhibition between Drosophila gustatory receptor neurons (GRNs). While sweet-sensing GRNs (sGRNs) engage in ephaptic suppression of the adjacent bitter-sensing GRNs (bGRNs), HCN expression in sGRNs enables them to resist ephaptic suppression from the bGRNs. This one-sided ephaptic inhibition confers sweetness dominance, facilitating ingestion of bitter-laced sweets. The role of fly HCN in this process can be replaced by human HCN2. Furthermore, unlike the mechanism in olfaction, gustatory ephaptic inhibition is independent of sensillum potential changes, suggesting that the compartmentalized arrangement of neighboring GRNs is dispensable for gustatory ephaptic inhibition. These findings indicate a role for the gating of ephaptic coding to ensure the intake of the essential nutrient despite bitter contaminants present in the feeding niche of Drosophila, and propose that studies in Drosophila gustation could reveal ephaptic principles conserved across diverse animals.

Harnessing Insect Chemosensory and Mechanosensory Receptors Involved in Feeding for Precision Pest Management

Chemosensation and mechanosensation are vital to insects' survival and behavior, shaping critical physiological processes such as feeding, metabolism, mating, and reproduction. During feeding, insects rely on diverse chemosensory and mechanosensory receptors to distinguish between nutritious and harmful substances, enabling them to select suitable food sources while avoiding toxins. These receptors are distributed across various body parts, allowing insects to detect environmental cues about food quality and adjust their behaviors accordingly. A deeper understanding of insect sensory physiology, especially during feeding, not only enhances our knowledge of insect biology but also offers significant opportunities for practical applications. This review highlights recent advancements in research on feeding-related sensory receptors, covering a wide range of insect species, from the model organism Drosophila melanogaster to agricultural and human pests. Additionally, this review examines the potential of targeting insect sensory receptors for precision pest control. Disrupting behaviors such as feeding and reproduction emerges as a promising strategy for pest management. By interfering with these essential behaviors, we can effectively control pest populations while minimizing environmental impacts and promoting ecological balance.

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.

Flexible tactile sensors inspired by bio-mechanoreceptors

Mechanoreceptors in animals and plants play a crucial role in sensing mechanical stimuli such as touch, motion, stretch, and vibration. Learning from the mechanisms of mechanoreceptors may facilitate the development of bionic tactile sensors, leading to higher sensitivity, spatial resolution, and dynamic ranges. However, very little literature has comprehensively discussed the relevance of biological tactile sensing systems and machine-learning-based bionic tactile sensors. This review first introduces the structural features, signal acquisition and transmission mechanisms, and feedback processes of both plant and animal mechanoreceptors, and then summarizes the efforts to develop bionic tactile sensors by mimicking the morphologies and structures of mechanoreceptors in plants and animals. Additionally, the integration of artificial intelligence approaches with these sensors for data processing and analysis are demonstrated, followed by the perspectives on current challenges and future trends in bionic tactile sensors. This review addresses the challenges in developing high-performance tactile sensors by focusing on surface microstructures and biological mechanoreceptors, serving as a valuable reference for developing bionic tactile sensors with enhanced sensitivity and multimodal sensing capabilities. Furthermore, it may benefit the future development of smart sensing systems integrated with artificial intelligence for more precise object and texture recognition.

Divergent neural circuits for proprioceptive and exteroceptive sensing of the Drosophila leg

Somatosensory neurons provide the nervous system with information about mechanical forces originating inside and outside the body. Here, we use connectomics from electron microscopy to reconstruct and analyze neural circuits downstream of the largest somatosensory organ in the Drosophila leg, the femoral chordotonal organ (FeCO). The FeCO has been proposed to support both proprioceptive sensing of the fly's femur-tibia joint and exteroceptive sensing of substrate vibrations, but it was unknown which sensory neurons and central circuits contribute to each of these functions. We found that different subtypes of FeCO sensory neurons feed into distinct proprioceptive and exteroceptive pathways. Position- and movement-encoding FeCO neurons connect to local leg motor control circuits in the ventral nerve cord (VNC), indicating a proprioceptive function. In contrast, signals from the vibration-encoding FeCO neurons are integrated across legs and transmitted to mechanosensory regions in the brain, indicating an exteroceptive function. Overall, our analyses reveal the structure of specialized circuits for processing proprioceptive and exteroceptive signals from the fly leg. These findings are consistent with a growing body of work in invertebrate and vertebrate species demonstrating the existence of specialized limb mechanosensory pathways for sensing external vibrations.

Perspectives on the manipulation of mosquito hearing

Vector control is essential for preventing mosquito-borne diseases. However, different challenges associated with the development of insecticide resistance and behavioural adaptations across mosquito populations means novel control strategies are urgently needed. In recent years, disrupting mosquito mating has emerged as an alternative target of control tools because of its potential to reduce mosquito population numbers. Mosquito mating relies on sophisticated auditory processing for mate finding in many medically important species. Manipulating this key process could provide novel methods for mosquito control.

Ants integrate proprioception as well as visual context and efference copies to make robust predictions

Forward models are mechanisms enabling an agent to predict the sensory outcomes of its actions. They can be implemented through efference copies: copies of motor signals inhibiting the expected sensory stimulation, literally canceling the perceptual outcome of the predicted action. In insects, efference copies are known to modulate optic flow detection for flight control in flies. Here we investigate whether forward models account for the detection of optic flow in walking ants, and how the latter is integrated for locomotion control. We mounted Cataglyphis velox ants in a virtual reality setup and manipulated the relationship between the ants' movements and the optic flow perceived. Our results show that ants compute predictions of the optic flow expected according to their own movements. However, the prediction is not solely based on efference copies, but involves proprioceptive feedbacks and is fine-tuned by the panorama's visual structure. Mismatches between prediction and perception are computed for each eye, and error signals are integrated to adjust locomotion through the modulation of internal oscillators. Our work reveals that insects' forward models are non-trivial and compute predictions based on multimodal information.

The Hawkmoth Proboscis: An Insect Model for Sensorimotor Control of Reaching and Exploration

Reaching and inspecting objects is an intricate part of human life, which is shared by a diversity of animals across phyla. In addition to appendages like legs and antennae, some insects use their mouthparts to reach and inspect targets. Hawkmoths of the family Sphingidae (Lepidoptera) use their extremely long and straw-like proboscis to drink nectar from flowers. As they approach flowers, hawkmoths uncoil their proboscis and explore the floral surface while hovering to target the proboscis to the nectary hole. Several sensory modalities provide feedback to control and guide these extremely versatile proboscis movements. The control task faced by the hawkmoths' nervous system during such behaviors is not unlike that of an animal guiding limbs or a robotic agent guiding a manipulator to a target. Hawkmoths perform these reaching maneuvers while simultaneously hovering, and hence require rapid and continuous coordination between the proboscis, neck, and flight motor systems, thereby providing a unique invertebrate model for studying appendage guidance and reaching. Here, we review what is known about how hawkmoths use their proboscis for floral inspection and nectar discovery, as well as the role of various sensors in proboscis guidance. We give a brief overview of the morphology and muscular apparatus of the hawkmoth proboscis, and discuss how multimodal sensory feedback might be turned into motor action for appendage guidance.

Moving in an Uncertain World: Robust and Adaptive Control of Locomotion from Organisms to Machine Intelligence

Whether walking, running, slithering, or flying, organisms display a remarkable ability to move through complex and uncertain environments. In particular, animals have evolved to cope with a host of uncertainties-both of internal and external origin-to maintain adequate performance in an ever-changing world. In this review, we present mathematical methods in engineering to highlight emerging principles of robust and adaptive control of organismal locomotion. Specifically, by drawing on the mathematical framework of control theory, we decompose the robust and adaptive hierarchical structure of locomotor control. We show how this decomposition along the robust-adaptive axis provides testable hypotheses to classify behavioral outcomes to perturbations. With a focus on studies in non-human animals, we contextualize recent findings along the robust-adaptive axis by emphasizing two broad classes of behaviors: (1) compensation to appendage loss and (2) image stabilization and fixation. Next, we attempt to map robust and adaptive control of locomotion across some animal groups and existing bio-inspired robots. Finally, we highlight exciting future directions and interdisciplinary collaborations that are needed to unravel principles of robust and adaptive locomotion.

Recent Advances in Artificial Sensory Neurons: Biological Fundamentals, Devices, Applications, and Challenges

Spike-based neural networks, which use spikes or action potentials to represent information, have gained a lot of attention because of their high energy efficiency and low power consumption. To fully leverage its advantages, converting the external analog signals to spikes is an essential prerequisite. Conventional approaches including analog-to-digital converters or ring oscillators, and sensors suffer from high power and area costs. Recent efforts are devoted to constructing artificial sensory neurons based on emerging devices inspired by the biological sensory system. They can simultaneously perform sensing and spike conversion, overcoming the deficiencies of traditional sensory systems. This review summarizes and benchmarks the recent progress of artificial sensory neurons. It starts with the presentation of various mechanisms of biological signal transduction, followed by the systematic introduction of the emerging devices employed for artificial sensory neurons. Furthermore, the implementations with different perceptual capabilities are briefly outlined and the key metrics and potential applications are also provided. Finally, we highlight the challenges and perspectives for the future development of artificial sensory neurons.

Cephalic ganglia transcriptomics of the American cockroach Periplaneta americana (Blattodea: Blattidae)

The American cockroach Periplaneta americana (L.) (Blattodea, Blattidae) has been a model organism for biochemical and physiological study for almost a century, however, its use does not benefit from the genetic tools found in key model species such as Drosophila melanogaster. To facilitate the use of the cockroach as a model system in neuroscience and to serve as a foundation for functional and translational experimentation, a transcriptome of the cephalic ganglia was assembled and annotated, and differential expression profiles between these ganglia were assessed. The transcriptome assembly yielded >400 k transcripts, with >40 k putative coding sequences. Gene ontology and protein domain searches indicate the cerebral and gnathal ganglia (GNG) have distinct genetic expression profiles. The developmental Toll signaling pathway appears to be active in the adult central nervous system (CNS), which may suggest a separate role for this pathway besides innate immune activation or embryonic development. The catabolic glycolytic and citric acid cycle enzymes are well represented in both ganglia, but key enzymes are more highly expressed in the GNG. Both ganglia express gluconeogenic and trehaloneogenic enzymes, suggesting a larger role of the CNS in regulating hemolymph sugar homeostasis than previously appreciated. The annotation and quantification of the cephalic ganglia transcriptome reveal both canonical and novel pathways in signaling and metabolism in an adult insect and lay a foundation for future functional and genetic analysis.

Miniature linear and split-belt treadmills reveal mechanisms of adaptive motor control in walking Drosophila

To navigate complex environments, walking animals must detect and overcome unexpected perturbations. One technical challenge when investigating adaptive locomotion is measuring behavioral responses to precise perturbations during naturalistic walking; another is that manipulating neural activity in sensorimotor circuits often reduces spontaneous locomotion. To overcome these obstacles, we introduce miniature treadmill systems for coercing locomotion and tracking 3D kinematics of walking Drosophila. By systematically comparing walking in three experimental setups, we show that flies compelled to walk on the linear treadmill have similar stepping kinematics to freely walking flies, while kinematics of tethered walking flies are subtly different. Genetically silencing mechanosensory neurons altered step kinematics of flies walking on the linear treadmill across all speeds. We also discovered that flies can maintain a forward heading on a split-belt treadmill by specifically adapting the step distance of their middle legs. These findings suggest that proprioceptive feedback contributes to leg motor control irrespective of walking speed and that the fly's middle legs play a specialized role in stabilizing locomotion.

Dynamics of neural activity in early nervous system evolution

New techniques for largescale neural recordings from diverse animals are reshaping comparative systems neuroscience. This growth necessitates fresh conceptual paradigms for comparing neural circuits and activity patterns. Here, we take a systems neuroscience approach to early neural evolution, emphasizing the importance of considering nervous systems as multiply modulated, continuous dynamical systems. We argue that endogenous neural activity likely arose early in evolution to organize behaviors and internal states at the organismal level. This connects to a rich literature on the physiology of endogenous activity in small neural circuits: a field that has built links between data and dynamical systems models. Such models offer mechanistic insight and have robust predictive power. Using these tools, we suggest that the emergence of intrinsically active neurons and periodic dynamics played a critical role in the ascendancy of nervous systems, and that dynamical systems presents an appealing framework for comparing across species.

Specialized structure and function of the apical extracellular matrix at sense organs

Apical extracellular matrix (aECM) covers every surface of the body and exhibits tissue-specific structures that carry out specialized functions. This is particularly striking at sense organs, where aECM forms the interface between sensory neurons and the environment, and thus plays critical roles in how sensory stimuli are received. Here, we review the extraordinary adaptations of aECM across sense organs and discuss how differences in protein composition and matrix structure assist in sensing mechanical forces (tactile hairs, campaniform sensilla, and the tectorial membrane of the cochlea); tastes and smells (uniporous gustatory sensilla and multiporous olfactory sensilla in insects, and salivary and olfactory mucus in vertebrates); and light (cuticle-derived lenses in arthropods and mollusks). We summarize the power of using C. elegans, in which defined sense organs associate with distinct aECM, as a model for understanding the tissue-specific structural and functional specializations of aECM. Finally, we synthesize results from recent studies in C. elegans and Drosophila into a conceptual framework for aECM patterning, including mechanisms that involve transient cellular or matrix scaffolds, mechanical pulling or pushing forces, and localized secretion or endocytosis.

Molecular regulation of axon termination in mechanosensory neurons

Spatially and temporally accurate termination of axon outgrowth, a process called axon termination, is required for efficient, precise nervous system construction and wiring. The mechanosensory neurons that sense low-threshold mechanical stimulation or gentle touch have proven exceptionally valuable for studying axon termination over the past 40 years. In this Review, we discuss progress made in deciphering the molecular and genetic mechanisms that govern axon termination in touch receptor neurons. Findings across model organisms, including Caenorhabditis elegans, Drosophila, zebrafish and mice, have revealed that complex signaling is required for termination with conserved principles and players beginning to surface. A key emerging theme is that axon termination is mediated by complex signaling networks that include ubiquitin ligase signaling hubs, kinase cascades, transcription factors, guidance/adhesion receptors and growth factors. Here, we begin a discussion about how these signaling networks could represent termination codes that trigger cessation of axon outgrowth in different species and types of mechanosensory neurons.

Drosophila HCN mediates gustatory homeostasis by preserving sensillar transepithelial potential in sweet environments

Establishing transepithelial ion disparities is crucial for sensory functions in animals. In insect sensory organs called sensilla, a transepithelial potential, known as the sensillum potential (SP), arises through active ion transport across accessory cells, sensitizing receptor neurons such as mechanoreceptors and chemoreceptors. Because multiple receptor neurons are often co-housed in a sensillum and share SP, niche-prevalent overstimulation of single sensory neurons can compromise neighboring receptors by depleting SP. However, how such potential depletion is prevented to maintain sensory homeostasis remains unknown. Here, we find that the Ih-encoded hyperpolarization-activated cyclic nucleotide-gated (HCN) channel bolsters the activity of bitter-sensing gustatory receptor neurons (bGRNs), albeit acting in sweet-sensing GRNs (sGRNs). For this task, HCN maintains SP despite prolonged sGRN stimulation induced by the diet mimicking their sweet feeding niche, such as overripe fruit. We present evidence that Ih-dependent demarcation of sGRN excitability is implemented to throttle SP consumption, which may have facilitated adaptation to a sweetness-dominated environment. Thus, HCN expressed in sGRNs serves as a key component of a simple yet versatile peripheral coding that regulates bitterness for optimal food intake in two contrasting ways: sweet-resilient preservation of bitter aversion and the previously reported sweet-dependent suppression of bitter taste.

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.

Functional fibrillar interfaces: Biological hair as inspiration across scales

Hair, or hair-like fibrillar structures, are ubiquitous in biology, from fur on the bodies of mammals, over trichomes of plants, to the mastigonemes on the flagella of single-celled organisms. While these long and slender protuberances are passive, they are multifunctional and help to mediate interactions with the environment. They provide thermal insulation, sensory information, reversible adhesion, and surface modulation (e.g., superhydrophobicity). This review will present various functions that biological hairs have been discovered to carry out, with the hairs spanning across six orders of magnitude in size, from the millimeter-thick fur of mammals down to the nanometer-thick fibrillar ultrastructures on bateriophages. The hairs are categorized according to their functions, including protection (e.g., thermal regulation and defense), locomotion, feeding, and sensing. By understanding the versatile functions of biological hairs, bio-inspired solutions may be developed across length scales.

Flow sensing on dragonfly wings

One feature of animal wings is their embedded mechanosensory system that can support flight control. Insect wings are particularly interesting as they are highly deformable yet the actuation is limited to the wing base. It is established that strain sensors on insect wings can directly mediate reflexive control; however, little is known about airflow sensing by insect wings. What information can flow sensors capture and how can flow sensing benefit flight control? Here, we use the dragonfly (Sympetrum striolatum) as a model to explore the function of wing sensory bristles in the context of flight control. Combining our detailed anatomical reconstructions of both the sensor microstructures and wing architecture, we used computational fluid dynamics simulations to ask the following questions. (1) Are there strategic locations on wings that sample flow for estimating aerodynamically relevant parameters such as the local effective angle of attack? (2) Is the sensory bristle distribution on dragonfly wings optimal for flow sensing? (3) What is the aerodynamic effect of microstructures found near the sensory bristles on dragonfly wings? We discuss the benefits of flow sensing for flexible wings and how the evolved sensor placement affects information encoding.

The physiology of coordination: self-resolving diverse affinities via the sparse order in relevant noise

Living systems at any given moment enact a very constrained set of end-directed and contextually appropriate actions that are self-initiated from among innumerable possible alternatives. However, these constrained actions are not necessarily because the system has reduced its sensitivities to themselves and their surroundings. Quite the contrary, living systems are continually open to novel and unanticipated stimulations that require a physiology of coordination. To address these competing demands, this paper offers a novel heuristic model informed by neuroscience, systems theory, biology and sign study to explain how organisms situated in diverse, complex and ever-changing environments might draw upon the sparse order made available by 'relevant noise'. This emergent order facilitates coordination, habituation and, ultimately, understanding of the world and its relevant affordances. Inspired by the burgeoning field of coordination dynamics and physiologist Denis Noble's concept of 'biological relativity', this model proposes a view of coordination on the neuronal level that is neither sequential nor stochastic, but instead implements a causal logic of phasic alignment, such that an organism's learned and inherited sets of diverse biological affinities and sympathies can be resolved into a continuous and complex range of patterns that will implement the kind of novel orientations and radical generativity required of such organisms to adaptively explore their environments and to learn from their experiences.

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.

Presynaptic inhibition selectively suppresses leg proprioception in behaving Drosophila

Controlling arms and legs requires feedback from proprioceptive sensory neurons that detect joint position and movement. Proprioceptive feedback must be tuned for different behavioral contexts, but the underlying circuit mechanisms remain poorly understood. Using calcium imaging in behaving Drosophila, we find that the axons of position-encoding leg proprioceptors are active across behaviors, whereas the axons of movement-encoding leg proprioceptors are suppressed during walking and grooming. Using connectomics, we identify a specific class of interneurons that provide GABAergic presynaptic inhibition to the axons of movement-encoding proprioceptors. The predominant synaptic inputs to these interneurons are descending neurons, suggesting they are driven by predictions of leg movement originating in the brain. Calcium imaging from both the interneurons and their descending inputs confirmed that their activity is correlated with self-generated but not passive leg movements. Overall, our findings elucidate a neural circuit for suppressing specific proprioceptive feedback signals during self-generated movements.

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.

Why animals can outrun robots

Animals are much better at running than robots. The difference in performance arises in the important dimensions of agility, range, and robustness. To understand the underlying causes for this performance gap, we compare natural and artificial technologies in the five subsystems critical for running: power, frame, actuation, sensing, and control. With few exceptions, engineering technologies meet or exceed the performance of their biological counterparts. We conclude that biology's advantage over engineering arises from better integration of subsystems, and we identify four fundamental obstacles that roboticists must overcome. Toward this goal, we highlight promising research directions that have outsized potential to help future running robots achieve animal-level performance.

Somatotopic organization among parallel sensory pathways that promote a grooming sequence in Drosophila

Mechanosensory neurons located across the body surface respond to tactile stimuli and elicit diverse behavioral responses, from relatively simple stimulus location-aimed movements to complex movement sequences. How mechanosensory neurons and their postsynaptic circuits influence such diverse behaviors remains unclear. We previously discovered that Drosophila perform a body location-prioritized grooming sequence when mechanosensory neurons at different locations on the head and body are simultaneously stimulated by dust (Hampel et al., 2017; Seeds et al., 2014). Here, we identify nearly all mechanosensory neurons on the Drosophila head that individually elicit aimed grooming of specific head locations, while collectively eliciting a whole head grooming sequence. Different tracing methods were used to reconstruct the projections of these neurons from different locations on the head to their distinct arborizations in the brain. This provides the first synaptic resolution somatotopic map of a head, and defines the parallel-projecting mechanosensory pathways that elicit head grooming.

Neuromorphic antennal sensory system

Insect antennae facilitate the nuanced detection of vibrations and deflections, and the non-contact perception of magnetic or chemical stimuli, capabilities not found in mammalian skin. Here, we report a neuromorphic antennal sensory system that emulates the structural, functional, and neuronal characteristics of ant antennae. Our system comprises electronic antennae sensor with three-dimensional flexible structures that detects tactile and magnetic stimuli. The integration of artificial synaptic devices adsorbed with solution-processable MoS2 nanoflakes enables synaptic processing of sensory information. By emulating the architecture of receptor-neuron pathway, our system realizes hardware-level, spatiotemporal perception of tactile contact, surface pattern, and magnetic field (detection limits: 1.3 mN, 50 μm, 9.4 mT). Vibrotactile-perception tasks involving profile and texture classifications were accomplished with high accuracy (> 90%), surpassing human performance in "blind" tactile explorations. Magneto-perception tasks including magnetic navigation and touchless interaction were successfully completed. Our work represents a milestone for neuromorphic sensory systems and biomimetic perceptual intelligence.

Mechanosensory encoding of forces in walking uphill and downhill: force feedback can stabilize leg movements in stick insects

Force feedback could be valuable in adapting walking to diverse terrains, but the effects of changes in substrate inclination on discharges of sensory receptors that encode forces have rarely been examined. In insects, force feedback is provided by campaniform sensilla, mechanoreceptors that monitor forces as cuticular strains. We neurographically recorded responses of stick insect tibial campaniform sensilla to "naturalistic" forces (joint torques) that occur at the hind leg femur-tibia (FT) joint in uphill, downhill, and level walking. The FT joint torques, obtained in a previous study that used inverse dynamics to analyze data from freely moving stick insects, are quite variable during level walking (including changes in sign) but are larger in magnitude and more consistent when traversing sloped surfaces. Similar to vertebrates, insects used predominantly extension torque in propulsion on uphill slopes and flexion torques to brake forward motion when going downhill. Sensory discharges to joint torques reflected the torque direction but, unexpectedly, often occurred as multiple bursts that encoded the rate of change of positive forces (dF/dt) even when force levels were high. All discharges also showed hysteresis (history dependence), as firing substantially decreased or ceased during transient force decrements. These findings have been tested in simulation in a mathematical model of the sensilla (Szczecinski NS, Dallmann CJ, Quinn RD, Zill SN. Bioinspir Biomim 16: 065001, 2021) that accurately reproduced the biological data. Our results suggest the hypothesis that sensory feedback from the femoro-tibial joint indicating force dynamics (dF/dt) can be used to counter the instability in traversing sloped surfaces in animals and, potentially, in walking machines.NEW & NOTEWORTHY Discharges of sensory receptors (campaniform sensilla) in the hind legs of stick insects can differentially signal forces that occur in walking uphill versus walking downhill. Unexpectedly, sensory firing most closely reflects the rate of change of force (dF/dt) even when the force levels are high. These signals have been replicated in a mathematical model of the receptors and could be used to stabilize leg movements both in the animal and in a walking robot.

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.

Somatotopic organization among parallel sensory pathways that promote a grooming sequence in Drosophila

Mechanosensory neurons located across the body surface respond to tactile stimuli and elicit diverse behavioral responses, from relatively simple stimulus location-aimed movements to complex movement sequences. How mechanosensory neurons and their postsynaptic circuits influence such diverse behaviors remains unclear. We previously discovered that Drosophila perform a body location-prioritized grooming sequence when mechanosensory neurons at different locations on the head and body are simultaneously stimulated by dust (Hampel et al., 2017; Seeds et al., 2014). Here, we identify nearly all mechanosensory neurons on the Drosophila head that individually elicit aimed grooming of specific head locations, while collectively eliciting a whole head grooming sequence. Different tracing methods were used to reconstruct the projections of these neurons from different locations on the head to their distinct arborizations in the brain. This provides the first synaptic resolution somatotopic map of a head, and defines the parallel-projecting mechanosensory pathways that elicit head grooming.

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.

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 hind 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 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 hind 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 receive diverse sensory inputs and synapse onto both MGT and components of its downstream pre-motor 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 mapped the pre-motor circuit downstream of MGT, including inhibitory feedback connections that may enable rhythmicity and coordination of limb movement during thoracic grooming.

Acid and Alkali Taste Sensation

Living organisms rely on pH levels for a multitude of crucial biological processes, such as the digestion of food and the facilitation of enzymatic reactions. Among these organisms, animals, including insects, possess specialized taste organs that enable them to discern between acidic and alkaline substances present in their food sources. This ability is vital, as the pH of these compounds directly influences both the nutritional value and the overall health impact of the ingested substances. In response to the various chemical properties of naturally occurring compounds, insects have evolved peripheral taste organs. These sensory structures play a pivotal role in identifying and distinguishing between nourishing and potentially harmful foods. In this concise review, we aim to provide an in-depth examination of the molecular mechanisms governing pH-dependent taste responses, encompassing both acidic and alkaline stimuli, within the peripheral taste organs of the fruit fly, Drosophila melanogaster, drawing insights from a comprehensive analysis of existing research articles.

Gravisensation and modulation of gravitactic responses by other sensory cues in the monarch butterfly (Danaus plexippus)

Using the monarch butterfly (Danaus plexippus), we studied how animals can use cues from multiple sensory modalities for deriving directional information from their environment to display oriented movement. Our work focused on determining how monarchs use gravity as a cue for oriented movement and determined how cues from other sensory modalities, cues that by themselves also produce oriented movement (visual and magnetic directional cues), might modulate gravisensation. In two tests of gravisensation (movement in a vertical tube; righting behavior), we found that monarchs display negative gravitaxis only (movement opposite to the direction of gravity). Negative gravitaxis can be modulated by either visual (light) or magnetic field cues (inclination angle) that provide directional information. The modulation of gravity-mediated responses, however, depends on the relationship between cues when presented during trials, such as when cues are in accord or in conflict. For example, when light cues that elicit positive phototaxis conflicted with negative gravitaxis (light from below the monarch), monarch gravisensation was unaffected by directional light cues. We also found that the antennae play a role in gravity-mediated movement (righting), as, with antennae removed, monarch movement behavior was no longer the same as when the antennae were intact. Our results demonstrate that monarchs can use and integrate multiple, multimodal cues for oriented movement, but that the use of such cues can be hierarchical (that is, one cue dominant for movement), and the hierarchy of cues, and the responses towards them when found together, depends on the physical relationships between cues during movement.

Mechanical vibration patterns elicit behavioral transitions and habituation in crawling Drosophila larvae

How animals respond to repeatedly applied stimuli, and how animals respond to mechanical stimuli in particular, are important questions in behavioral neuroscience. We study adaptation to repeated mechanical agitation using the Drosophila larva. Vertical vibration stimuli elicit a discrete set of responses in crawling larvae: continuation, pause, turn, and reversal. Through high-throughput larva tracking, we characterize how the likelihood of each response depends on vibration intensity and on the timing of repeated vibration pulses. By examining transitions between behavioral states at the population and individual levels, we investigate how the animals habituate to the stimulus patterns. We identify time constants associated with desensitization to prolonged vibration, with re-sensitization during removal of a stimulus, and additional layers of habituation that operate in the overall response. Known memory-deficient mutants exhibit distinct behavior profiles and habituation time constants. An analogous simple electrical circuit suggests possible neural and molecular processes behind adaptive behavior.

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.

Circuits for self-motion estimation and walking control in Drosophila

The brain's evolution and operation are inextricably linked to animal movement, and critical functions, such as motor control, spatial perception, and navigation, rely on precise knowledge of body movement. Such internal estimates of self-motion emerge from the integration of mechanosensory and visual feedback with motor-related signals. Thus, this internal representation likely depends on the activity of circuits distributed across the central nervous system. However, the circuits responsible for self-motion estimation, and the exact mechanisms by which motor-sensory coordination occurs within these circuits remain poorly understood. Recent technological advances have positioned Drosophila melanogaster as an advantageous model for investigating the emergence, maintenance, and utilization of self-motion representations during naturalistic walking behaviors. In this review, I will illustrate how the adult fly is providing insights into the fundamental problems of self-motion computations and walking control, which have relevance for all animals.

Locomotion modulates olfactory learning through proprioception in C. elegans

Locomotor activities can enhance learning, but the underlying circuit and synaptic mechanisms are largely unknown. Here we show that locomotion facilitates aversive olfactory learning in C. elegans by activating mechanoreceptors in motor neurons, and transmitting the proprioceptive information thus generated to locomotion interneurons through antidromic-rectifying gap junctions. The proprioceptive information serves to regulate experience-dependent activities and functional coupling of interneurons that process olfactory sensory information to produce the learning behavior. Genetic destruction of either the mechanoreceptors in motor neurons, the rectifying gap junctions between the motor neurons and locomotion interneurons, or specific inhibitory synapses among the interneurons impairs the aversive olfactory learning. We have thus uncovered an unexpected role of proprioception in a specific learning behavior as well as the circuit, synaptic, and gene bases for this function.

A single-cell atlas of the sexually dimorphic Drosophila foreleg and its sensory organs during development

To respond to the world around them, animals rely on the input of a network of sensory organs distributed throughout the body. Distinct classes of sensory organs are specialized for the detection of specific stimuli such as strain, pressure, or taste. The features that underlie this specialization relate both to the neurons that innervate sensory organs and the accessory cells they comprise. To understand the genetic basis of this diversity of cell types, both within and between sensory organs, we performed single-cell RNA sequencing on the first tarsal segment of the male Drosophila melanogaster foreleg during pupal development. This tissue displays a wide variety of functionally and structurally distinct sensory organs, including campaniform sensilla, mechanosensory bristles, and chemosensory taste bristles, as well as the sex comb, a recently evolved male-specific structure. In this study, we characterize the cellular landscape in which the sensory organs reside, identify a novel cell type that contributes to the construction of the neural lamella, and resolve the transcriptomic differences among support cells within and between sensory organs. We identify the genes that distinguish between mechanosensory and chemosensory neurons, resolve a combinatorial transcription factor code that defines 4 distinct classes of gustatory neurons and several types of mechanosensory neurons, and match the expression of sensory receptor genes to specific neuron classes. Collectively, our work identifies core genetic features of a variety of sensory organs and provides a rich, annotated resource for studying their development and function.

Ciliated sensory neurons can regenerate axons after complete axon removal

Axon regeneration helps maintain lifelong function of neurons in many animals. Depending on the site of injury, new axons can grow either from the axon stump (after distal injury) or from the tip of a dendrite (after proximal injury). However, some neuron types do not have dendrites to be converted to a regenerating axon after proximal injury. For example, many sensory neurons receive information from a specialized sensory cilium rather than a branched dendrite arbor. We hypothesized that the lack of traditional dendrites would limit the ability of ciliated sensory neurons to respond to proximal axon injury. We tested this hypothesis by performing laser microsurgery on ciliated lch1 neurons in Drosophila larvae and tracking cells over time. These cells survived proximal axon injury as well as distal axon injury, and, like many other neurons, initiated growth from the axon stump after distal injury. After proximal injury, neurites regrew in a surprisingly flexible manner. Most cells initiated outgrowth directly from the cell body, but neurite growth could also emerge from the short axon stump or base of the cilium. New neurites were often branched. Although outgrowth after proximal axotomy was variable, it depended on the core DLK axon injury signaling pathway. Moreover, each cell had at least one new neurite specified as an axon based on microtubule polarity and accumulation of the endoplasmic reticulum. We conclude that ciliated sensory neurons are not intrinsically limited in their ability to grow a new axon after proximal axon removal.

Two feedback mechanisms involved in the control of leaf fragment size in leaf-cutting ants

Polymorphic leaf-cutting ants harvest leaf fragments that correlate in size with the workers' body size. When cutting, workers anchor their hind legs on the leaf edge and rotate, removing approximately semicircular fragments. Workers show behavioural plasticity and modify their leg extension while holding onto the leaf edge depending on, for instance, leaf toughness, cutting smaller fragments out of tough leaves. What sensory information workers use to control the cutting trajectory remains unknown. We investigated whether sensory information from both the leg contact with the leaf edge and from head movements underlies fragment size determination. In the laboratory, we recorded Atta sexdens workers cutting standardised ®Parafilm pseudoleaves of different thickness, and quantified cutting behaviour and body reach, i.e. the distance between the mandible and the anchored hind leg tarsus. Experimentally preventing contact with the leaf edge resulted in smaller fragments, evincing that workers control the cutting trajectory using information from the contact of the hind legs with the leaf edge. However, ants were able to cut fragments even when contact of all six legs with the edge was prevented, indicating the use of additional sensory information. Ablation of mechanosensory hairs at the neck joint alone did not influence fragment size determination, yet simultaneously preventing sensory feedback from both mechanosensory hairs and edge contact led to a loss of control over the cutting trajectory. Leaf-cutting ants, therefore, control their cutting trajectory using sensory information from both the leg contact with the leaf edge and the lateral bending of the head.

Flexible neural control of transition points within the egg-laying behavioral sequence in Drosophila

Innate behaviors are frequently comprised of ordered sequences of component actions that progress to satisfy essential drives. Progression is governed by specialized sensory cues that induce transitions between components within the appropriate context. Here we have characterized the structure of the egg-laying behavioral sequence in Drosophila and found significant variability in the transitions between component actions that affords the organism an adaptive flexibility. We identified distinct classes of interoceptive and exteroceptive sensory neurons that control the timing and direction of transitions between the terminal components of the sequence. We also identified a pair of motor neurons that enact the final transition to egg expulsion. These results provide a logic for the organization of innate behavior in which sensory information processed at critical junctures allows for flexible adjustments in component actions to satisfy drives across varied internal and external environments.

Co-option of epidermal cells enables touch sensing

The epidermis is equipped with specialized mechanosensory organs that enable the detection of tactile stimuli. Here, by examining the differentiation of the tactile bristles, mechanosensory organs decorating the Drosophila adult epidermis, we show that neighbouring epidermal cells are essential for touch perception. Each mechanosensory bristle signals to the surrounding epidermis to co-opt a single epidermal cell, which we named the F-Cell. Once specified, the F-Cell adopts a specialized morphology to ensheath each bristle. Functional assays reveal that adult mechanosensory bristles require association with the epidermal F-Cell for touch sensing. Our findings underscore the importance of resident epidermal cells in the assembly of functional touch-sensitive organs.

Perspective for soft robotics: the field's past and future

Since its beginnings in the 1960s, soft robotics has been a steadily growing field that has enjoyed recent growth with the advent of rapid prototyping and the provision of new flexible materials. These two innovations have enabled the development of fully flexible and untethered soft robotic systems. The integration of novel sensors enabled by new manufacturing processes and materials shows promise for enabling the production of soft systems with 'embodied intelligence'. Here, four experts present their perspectives for the future of the field of soft robotics based on these past innovations. Their focus is on finding answers to the questions of: how to manufacture soft robots, and on how soft robots can sense, move, and think. We highlight industrial production techniques, which are unused to date for manufacturing soft robots. They discuss how novel tactile sensors for soft robots could be created to enable better interaction of the soft robot with the environment. In conclusion this article highlights how embodied intelligence in soft robots could be used to make soft robots think and to make systems that can compute, autonomously, from sensory inputs.

3D escape: an alternative paradigm for spatial orientation studies in insects

Arthropods and in particular insects show a great variety of different exoskeletal sensors. For most arthropods, spatial orientation and gravity perception is not fully understood. In particular, the interaction of the different sensors is still a subject of ongoing research. A disadvantage of most of the experimental methods used to date to study the spatial orientation of arthropods in behavioral experiments is that the body or individual body parts are fixed partly in a non-natural manner. Therefore, often only the movement of individual body segments can be used to evaluate the experiments. We here present a novel experimental method to easily study 3D-escape movements in insects and analyze whole-body reaction. The animals are placed in a transparent container, filled with a lightweight substrate and rotating around two axes. To verify our setup, house crickets (Acheta domesticus) with selectively manipulated gravity-perceiving structures were analyzed. The spatial orientation behavior was quantified by measuring the time individuals took to escape toward the surface and the angular deviation toward the gravitational vector. These experiments confirm earlier results and therefore validated our experimental setup. Our new approach thus allows to investigate several comprehensive questions regarding the spatial orientation of insects and other animals.