Adaptive motor behavior in insects

Active and passive mechanics for rugose terrain traversal in centipedes

Centipedes coordinate body and limb flexion to generate propulsion. On flat, solid surfaces, the limb-stepping patterns can be characterized according to the direction in which limb-aggregates propagate, opposite to (retrograde) or with the direction of motion (direct). It is unknown how limb and body dynamics are modified in terrain with terradynamic complexity more representative of these animal's natural heterogeneous environments. Here, we investigated how centipedes that use retrograde and direct limb-stepping patterns, Scolopendra polymorpha and Scolopocryptops sexspinosus, respectively, coordinate their body and limbs to navigate laboratory environments which present footstep challenges and terrain rugosity. We recorded the kinematics and measured the locomotive performance of these animals traversing two rugose terrains with randomly distributed step heights and compared the kinematics with those on a flat frictional surface. Scolopendra polymorpha exhibited similar body and limb dynamics across all terrains and a decrease in speed with increased terrain rugosity. Unexpectedly, when placed in a rugose terrain, S. sexspinosus changed the direction of the limb-stepping pattern from direct to retrograde. Further, for both species, traversal of these rugose terrains was facilitated by hypothesized passive mechanics: upon horizontal collision of a limb with a block, the limb bent and later continued the stepping pattern. Although centipedes have many degrees of freedom, our results suggest these animals negotiate limb-substrate interactions and navigate complex terrains leveraging the innate flexibility of their limbs to simplify control.

Locomotion in the pseudoscorpion Chelifer cancroides - forward, backward and upside down walking in an eight-legged arthropod

While insect locomotion has been intensively studied, there are comparably few studies investigating octopedal walking behaviour, and very little is known about pseudoscorpions in particular. Therefore, we performed an extensive locomotion analysis during forward, backward and upside down walking in the cosmopolitan pseudoscorpion Chelifer cancroides. During forward locomotion, we observed C. cancroides to freeze locomotion frequently for short time periods. These microstops were barely visible to the naked eye with a duration of 100-200 ms. Our locomotion analysis revealed that C. cancroides performs a statically stable and highly coordinated alternating tetrapod gait during forward and backward walking, with almost complete inversion of the tetrapod schemes, but no rigidly fixed leg coordination during upside down walks with low walking speeds up to 4 body lengths per second. Highest speeds (up to 17 body lengths per second), mainly achieved by consistent leg coordination and strong phase shifts, were observed during backward locomotion (escape behaviour), while forward walking was characterised by lower speeds and phase shifts around 10% between two loosely coupled leg groups within one tetrapod. That is, during the movement of one tetrapod group, the last and the third leg are almost synchronous in their swing phases, as are the second and the first leg. A special role of the second leg pair was demonstrated, probably mainly for stability reasons and related to the large pedipalps.

Descending and Ascending Signals That Maintain Rhythmic Walking Pattern in Crickets

The cricket is one of the model animals used to investigate the neuronal mechanisms underlying adaptive locomotion. An intact cricket walks mostly with a tripod gait, similar to other insects. The motor control center of the leg movements is located in the thoracic ganglia. In this study, we investigated the walking gait patterns of the crickets whose ventral nerve cords were surgically cut to gain an understanding of how the descending signals from the head ganglia and ascending signals from the abdominal nervous system into the thoracic ganglia mediate the initiation and coordination of the walking gait pattern. Crickets whose paired connectives between the brain and subesophageal ganglion (SEG) (circumesophageal connectives) were cut exhibited a tripod gait pattern. However, when one side of the circumesophageal connectives was cut, the crickets continued to turn in the opposite direction to the connective cut. Crickets whose paired connectives between the SEG and prothoracic ganglion were cut did not walk, whereas the crickets exhibited an ordinal tripod gait pattern when one side of the connectives was intact. Crickets whose paired connectives between the metathoracic ganglion and abdominal ganglia were cut initiated walking, although the gait was not a coordinated tripod pattern, whereas the crickets exhibited a tripod gait when one side of the connectives was intact. These results suggest that the brain plays an inhibitory role in initiating leg movements and that both the descending signals from the head ganglia and the ascending signals from the abdominal nervous system are important in initiating and coordinating insect walking gait patterns.

Central pattern generating networks in insect locomotion

Central pattern generators (CPGs) are neural circuits that based on their connectivity can generate rhythmic and patterned output in the absence of rhythmic external inputs. This property makes CPGs crucial elements in the generation of many kinds of rhythmic motor behaviors in insects, such as flying, walking, swimming, or crawling. Arguably representing the most diverse group of animals, insects utilize at least one of these types of locomotion during one stage of their ontogenesis. Insects have been extensively used to study the neural basis of rhythmic motor behaviors, and particularly the structure and operation of CPGs involved in locomotion. Here, we review insect locomotion with regard to flying, walking, and crawling, and we discuss the contribution of central pattern generation to these three forms of locomotion. In each case, we compare and contrast the topology and structure of the CPGs, and we point out how these factors are involved in the generation of the respective motor pattern. We focus on the importance of sensory information for establishing a functional motor output and we indicate behavior-specific adaptations. Furthermore, we report on the mechanisms underlying coordination between different body parts. Last but not least, by reviewing the state-of-the-art knowledge concerning the role of CPGs in insect locomotion, we endeavor to create a common ground, upon which future research in the field of motor control in insects can build.

Serotonergic Modulation of Walking in Drosophila

To navigate complex environments, animals must generate highly robust, yet flexible, locomotor behaviors. For example, walking speed must be tailored to the needs of a particular environment. Not only must animals choose the correct speed and gait, they must also adapt to changing conditions and quickly respond to sudden and surprising new stimuli. Neuromodulators, particularly the small biogenic amine neurotransmitters, have the ability to rapidly alter the functional outputs of motor circuits. Here, we show that the serotonergic system in the vinegar fly, Drosophila melanogaster, can modulate walking speed in a variety of contexts and also change how flies respond to sudden changes in the environment. These multifaceted roles of serotonin in locomotion are differentially mediated by a family of serotonergic receptors with distinct activities and expression patterns.

Body side-specific changes in sensorimotor processing of movement feedback in a walking insect

Feedback from load and movement sensors can modify timing and magnitude of the motor output in the stepping stick insect. One source of feedback is stretch reception by the femoral chordotonal organ (fCO), which encodes such parameters as the femorotibial (FTi) joint angle, the angular velocity, and its acceleration. Stimulation of the fCO causes a postural resistance reflex, during quiescence, and can elicit the opposite, so-called active reaction (AR), which assists ongoing flexion during active movements. In the present study, we investigated the role of fCO feedback for the difference in likelihood of generating ARs on the inside vs. the outside during curve stepping. We analyzed the effects of fCO stimulation on the motor output to the FTi and the neighboring coxa-trochanter and thorax-coxa joints of the middle leg. In inside and outside turns, the probability for ARs increases with increasing starting angle and decreasing stimulus velocity; furthermore, it is independent of the total angular excursion. However, the transition between stance and swing motor activity always occurs after a specific angular excursion, independent of the turning direction. Feedback from the fCO also has an excitatory influence on levator trochanteris motoneurons (MNs) during inside and outside turns, whereas the same feedback affects protractor coxae MNs only during outside steps. Our results suggest joint- and body side-dependent processing of fCO feedback. A shift in gain may be responsible for different AR probabilities between inside and outside turning, whereas the general control mechanism for ARs is unchanged.NEW & NOTEWORTHY We show that parameters of movement feedback from the tibia in an insect during curve walking are processed in a body side-specific manner, and how. From our results it is highly conceivable that the difference in motor response to the feedback supports the body side-specific leg kinematics during turning. Future studies will need to determine the source for the inputs that determine the local changes in sensory-motor processing.

Predatory behavior changes with satiety or increased insulin levels in the praying mantis (Tenodera sinensis)

At any given moment, behavior is controlled by a combination of external stimuli and an animal's internal state. As physiological conditions change, vastly different behaviors might result from the same stimuli. For example, the motivation to hunt and hunting strategy are influenced by satiety. Here, we describe how sensory responsiveness and motor activity of a praying mantis (Tenodera sinensis) change as the insect feeds, leading to an altered hunting strategy. We further show that these changes can be induced by injection of insulin, which likely functions as a metabotropic indicator. Praying mantises directed their attention toward real and simulated prey less often as they fed and became sated. The range of distance and azimuth at which prey was detected decreased as did pursuit of prey, while opportunistic close-range attacks persisted. Together, these sensorimotor changes are indicative of a behavioral paradigm shift from 'pursuit' to 'ambush'. A similar effect was induced in starved praying mantises injected with 0.05 ml of 200 μg ml^-1 bovine insulin. These experiments showed that insulin injection into the circulating hemolymph is sufficient to decrease prey orientation as well as in prey-directed locomotor behaviors (tracking and pursuit). The effects of prey consumption and insulin injection were similarly dose dependent. These results suggest that insulin is a signal of internal, physiological conditions that can modify responses to external stimuli. A change in hunting strategy thus results from coordinated effects of a neurohormone on a set of independent sensorimotor processes and the overall activity level of the animal.

Recent advances in neuropeptide signaling in Drosophila, from genes to physiology and behavior

This review focuses on neuropeptides and peptide hormones, the largest and most diverse class of neuroactive substances, known in Drosophila and other animals to play roles in almost all aspects of daily life, as w;1;ell as in developmental processes. We provide an update on novel neuropeptides and receptors identified in the last decade, and highlight progress in analysis of neuropeptide signaling in Drosophila. Especially exciting is the huge amount of work published on novel functions of neuropeptides and peptide hormones in Drosophila, largely due to the rapid developments of powerful genetic methods, imaging techniques and innovative assays. We critically discuss the roles of peptides in olfaction, taste, foraging, feeding, clock function/sleep, aggression, mating/reproduction, learning and other behaviors, as well as in regulation of development, growth, metabolic and water homeostasis, stress responses, fecundity, and lifespan. We furthermore provide novel information on neuropeptide distribution and organization of peptidergic systems, as well as the phylogenetic relations between Drosophila neuropeptides and those of other phyla, including mammals. As will be shown, neuropeptide signaling is phylogenetically ancient, and not only are the structures of the peptides, precursors and receptors conserved over evolution, but also many functions of neuropeptide signaling in physiology and behavior.

The Metastability of the Double-Tripod Gait in Locust Locomotion

Insect locomotion represents a fundamental example of neuronal oscillating circuits generating different motor patterns or gaits by controlling their phase coordination. Walking gaits are assumed to represent stable states of the system, often modeled as coupled oscillators. This view is challenged, however, by recent experimental observations, in which in vitro locust preparations consistently converged to synchronous rhythms (all legs oscillating as one), a locomotive pattern never seen in vivo. To reconcile this inconsistency, we developed a modeling framework to capture the trade-off between the two competing mechanisms: the endogenous neuronal circuitry, expressed in vitro, and the feedback mechanisms from sensory and descending inputs, active only in vivo. We show that the ubiquitously observed double-tripod walking gait emerges precisely from this balance. The outcome is a short-lived meta-stable double-tripod gait, which transitions and alternates with stable idling, thus recovering the observed intermittent bouts of locomotion, typical of many insects' locomotion behavior.

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Isolated in vitro locust preparations indicate that idling is a stable fictive gait

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This is in contrast to the dominant in vivo locomotive pattern (i.e., double tripod)

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Hence functional locomotion behavior is dependent on descending and sensory inputs

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The presented model generates intermittent double-tripod bouts as seen empirically

Force dynamics and synergist muscle activation in stick insects: the effects of using joint torques as mechanical stimuli

Many sensory systems are tuned to specific parameters of behaviors and have effects that are task-specific. We have studied how force feedback contributes to activation of synergist muscles in serially homologous legs of stick insects. Forces were applied using conventional half-sine or ramp and hold functions. We also utilized waveforms of joint torques calculated from experiments in freely walking animals. In all legs, forces applied to either the tarsus (foot) or proximal leg segment (trochanter) activated synergist muscles that generate substrate grip and support, but coupling of the depressor muscle to tarsal forces was weak in the front legs. Activation of trochanteral receptors using ramp and hold functions generated positive feedback to the depressor muscle in all legs when animals were induced to seek substrate grip. However, discharges of the synergist flexor muscle showed adaptation at moderate force levels. In contrast, application of forces using torque waveforms, which do not have a static hold phase, produced sustained discharges in muscle synergies with little adaptation. Firing frequencies reflected the magnitude of ground reaction forces, were graded to changes in force amplitude, and could also be modulated by transient force perturbations added to the waveforms. Comparison of synergist activation by torques and ramp and hold functions revealed a strong influence of force dynamics (dF/d t). These studies support the idea that force receptors can act to tune muscle synergies synchronously to the range of force magnitudes and dynamics that occur in each leg according to their specific use in behavior. NEW & NOTEWORTHY The effects of force receptors (campaniform sensilla) on leg muscles and synergies were characterized in stick insects using both ramp and hold functions and waveforms of joint torques calculated by inverse dynamics. Motor responses were sustained and showed reduced adaptation to the more "natural" and nonlinear torque stimuli. Calculation of the first derivative (dF/d t) of the torque waveforms demonstrated that this difference was correlated with the dynamic sensitivities of the system.

Optogenetic dissection of descending behavioral control in Drosophila

In most animals, the brain makes behavioral decisions that are transmitted by descending neurons to the nerve cord circuitry that produces behaviors. In insects, only a few descending neurons have been associated with specific behaviors. To explore how descending neurons control an insect’s movements, we developed a novel method to systematically assay the behavioral effects of activating individual neurons on freely behaving terrestrial D. melanogaster. We calculated a two-dimensional representation of the entire behavior space explored by these flies, and we associated descending neurons with specific behaviors by identifying regions of this space that were visited with increased frequency during optogenetic activation. Applying this approach across a large collection of descending neurons, we found that (1) activation of most of the descending neurons drove stereotyped behaviors, (2) in many cases multiple descending neurons activated similar behaviors, and (3) optogenetically activated behaviors were often dependent on the behavioral state prior to activation.

A load-based mechanism for inter-leg coordination in insects

Animals rely on an adaptive coordination of legs during walking. However, which specific mechanisms underlie coordination during natural locomotion remains largely unknown. One hypothesis is that legs can be coordinated mechanically based on a transfer of body load from one leg to another. To test this hypothesis, we simultaneously recorded leg kinematics, ground reaction forces and muscle activity in freely walking stick insects (Carausius morosus). Based on torque calculations, we show that load sensors (campaniform sensilla) at the proximal leg joints are well suited to encode the unloading of the leg in individual steps. The unloading coincides with a switch from stance to swing muscle activity, consistent with a load reflex promoting the stance-to-swing transition. Moreover, a mechanical simulation reveals that the unloading can be ascribed to the loading of a specific neighbouring leg, making it exploitable for inter-leg coordination. We propose that mechanically mediated load-based coordination is used across insects analogously to mammals.

Substrate texture affects female cricket walking response to male calling song

Field crickets are extensively used as a model organism to study female phonotactic walking behaviour, i.e. their attraction to the male calling song. Laboratory-based phonotaxis experiments generally rely on arena or trackball-based settings; however, no attention has been paid to the effect of substrate texture on the response. Here, we tested phonotaxis in female Gryllus bimaculatus, walking on trackballs machined from methyl-methacrylate foam with different cell sizes. Surface height variations of the trackballs, due to the cellular composition of the material, were measured with profilometry and characterized as smooth, medium or rough, with roughness amplitudes of 7.3, 16 and 180 µm. Female phonotaxis was best on a rough and medium trackball surface, a smooth surface resulted in a significant lower phonotactic response. Claws of the cricket foot were crucial for effective walking. Females insert their claws into the surface pores to allow mechanical interlocking with the substrate texture and a high degree of attachment, which cannot be established on smooth surfaces. These findings provide insight to the biomechanical basis of insect walking and may inform behavioural studies that the surface texture on which walking insects are tested is crucial for the resulting behavioural response.

A Scalable Weight-Free Learning Algorithm for Regulatory Control of Cell Activity in Spiking Neuronal Networks

Recent developments in neural stimulation and recording technologies are providing scientists with the ability of recording and controlling the activity of individual neurons in vitro or in vivo, with very high spatial and temporal resolution. Tools such as optogenetics, for example, are having a significant impact in the neuroscience field by delivering optical firing control with the precision and spatiotemporal resolution required for investigating information processing and plasticity in biological brains. While a number of training algorithms have been developed to date for spiking neural network (SNN) models of biological neuronal circuits, exiting methods rely on learning rules that adjust the synaptic strengths (or weights) directly, in order to obtain the desired network-level (or functional-level) performance. As such, they are not applicable to modifying plasticity in biological neuronal circuits, in which synaptic strengths only change as a result of pre- and post-synaptic neuron firings or biological mechanisms beyond our control. This paper presents a weight-free training algorithm that relies solely on adjusting the spatiotemporal delivery of neuron firings in order to optimize the network performance. The proposed weight-free algorithm does not require any knowledge of the SNN model or its plasticity mechanisms. As a result, this training approach is potentially realizable in vitro or in vivo via neural stimulation and recording technologies, such as optogenetics and multielectrode arrays, and could be utilized to control plasticity at multiple scales of biological neuronal circuits. The approach is demonstrated by training SNNs with hundreds of units to control a virtual insect navigating in an unknown environment.

Six-legged walking in insects: how CPGs, peripheral feedback, and descending signals generate coordinated and adaptive motor rhythms

Walking is a rhythmic locomotor behavior of legged animals, and its underlying mechanisms have been the subject of neurobiological research for more than 100 years. In this article, we review relevant historical aspects and contemporary studies in this field of research with a particular focus on the role of central pattern generating networks (CPGs) and their contribution to the generation of six-legged walking in insects. Aspects of importance are the generation of single-leg stepping, the generation of interleg coordination, and how descending signals influence walking. We first review how CPGs interact with sensory signals from the leg in the generation of leg stepping. Next, we summarize how these interactions are modified in the generation of motor flexibility for forward and backward walking, curve walking, and speed changes. We then review the present state of knowledge with regard to the role of CPGs in intersegmental coordination and how CPGs might be involved in mediating descending influences from the brain for the initiation, maintenance, modification, and cessation of the motor output for walking. Throughout, we aim to specifically address gaps in knowledge, and we describe potential future avenues and approaches, conceptual and methodological, with the latter emphasizing in particular options arising from the advent of neurogenetic approaches to this field of research and its combination with traditional approaches.

Predictive control of intersegmental tarsal movements in an insect

In many animals intersegmental reflexes are important for postural and movement control but are still poorly undesrtood. Mathematical methods can be used to model the responses to stimulation, and thus go beyond a simple description of responses to specific inputs. Here we analyse an intersegmental reflex of the foot (tarsus) of the locust hind leg, which raises the tarsus when the tibia is flexed and depresses it when the tibia is extended. A novel method is described to measure and quantify the intersegmental responses of the tarsus to a stimulus to the femoro-tibial chordotonal organ. An Artificial Neural Network, the Time Delay Neural Network, was applied to understand the properties and dynamics of the reflex responses. The aim of this study was twofold: first to develop an accurate method to record and analyse the movement of an appendage and second, to apply methods to model the responses using Artificial Neural Networks. The results show that Artificial Neural Networks provide accurate predictions of tarsal movement when trained with an average reflex response to Gaussian White Noise stimulation compared to linear models. Furthermore, the Artificial Neural Network model can predict the individual responses of each animal and responses to others inputs such as a sinusoid. A detailed understanding of such a reflex response could be included in the design of orthoses or functional electrical stimulation treatments to improve walking in patients with neurological disorders as well as the bio/inspired design of robots.

Mechanosensation and Adaptive Motor Control in Insects

The ability of animals to flexibly navigate through complex environments depends on the integration of sensory information with motor commands. The sensory modality most tightly linked to motor control is mechanosensation. Adaptive motor control depends critically on an animal's ability to respond to mechanical forces generated both within and outside the body. The compact neural circuits of insects provide appealing systems to investigate how mechanical cues guide locomotion in rugged environments. Here, we review our current understanding of mechanosensation in insects and its role in adaptive motor control. We first examine the detection and encoding of mechanical forces by primary mechanoreceptor neurons. We then discuss how central circuits integrate and transform mechanosensory information to guide locomotion. Because most studies in this field have been performed in locusts, cockroaches, crickets, and stick insects, the examples we cite here are drawn mainly from these 'big insects'. However, we also pay particular attention to the tiny fruit fly, Drosophila, where new tools are creating new opportunities, particularly for understanding central circuits. Our aim is to show how studies of big insects have yielded fundamental insights relevant to mechanosensation in all animals, and also to point out how the Drosophila toolkit can contribute to future progress in understanding mechanosensory processing.

Joint torques in a freely walking insect reveal distinct functions of leg joints in propulsion and posture control

Determining the mechanical output of limb joints is critical for understanding the control of complex motor behaviours such as walking. In the case of insect walking, the neural infrastructure for single-joint control is well described. However, a detailed description of the motor output in form of time-varying joint torques is lacking. Here, we determine joint torques in the stick insect to identify leg joint function in the control of body height and propulsion. Torques were determined by measuring whole-body kinematics and ground reaction forces in freely walking animals. We demonstrate that despite strong differences in morphology and posture, stick insects show a functional division of joints similar to other insect model systems. Propulsion was generated by strong depression torques about the coxa-trochanter joint, not by retraction or flexion/extension torques. Torques about the respective thorax-coxa and femur-tibia joints were often directed opposite to fore-aft forces and joint movements. This suggests a posture-dependent mechanism that counteracts collapse of the leg under body load and directs the resultant force vector such that strong depression torques can control both body height and propulsion. Our findings parallel propulsive mechanisms described in other walking, jumping and flying insects, and challenge current control models of insect walking.

Advantage of straight walk instability in turning maneuver of multilegged locomotion: a robotics approach

Multilegged locomotion improves the mobility of terrestrial animals and artifacts. Using many legs has advantages, such as the ability to avoid falling and to tolerate leg malfunction. However, many intrinsic degrees of freedom make the motion planning and control difficult, and many contact legs can impede the maneuverability during locomotion. The underlying mechanism for generating agile locomotion using many legs remains unclear from biological and engineering viewpoints. The present study used a centipede-like multilegged robot composed of six body segments and twelve legs. The body segments are passively connected through yaw joints with torsional springs. The dynamic stability of the robot walking in a straight line changes through a supercritical Hopf bifurcation due to the body axis flexibility. We focused on a quick turning task of the robot and quantitatively investigated the relationship between stability and maneuverability in multilegged locomotion by using a simple control strategy. Our experimental results show that the straight walk instability does help the turning maneuver. We discuss the importance and relevance of our findings for biological systems and propose a design principle for a simple control scheme to create maneuverable locomotion of multilegged robots.

Fluctuation-Driven Neural Dynamics Reproduce Drosophila Locomotor Patterns

The neural mechanisms determining the timing of even simple actions, such as when to walk or rest, are largely mysterious. One intriguing, but untested, hypothesis posits a role for ongoing activity fluctuations in neurons of central action selection circuits that drive animal behavior from moment to moment. To examine how fluctuating activity can contribute to action timing, we paired high-resolution measurements of freely walking Drosophila melanogaster with data-driven neural network modeling and dynamical systems analysis. We generated fluctuation-driven network models whose outputs-locomotor bouts-matched those measured from sensory-deprived Drosophila. From these models, we identified those that could also reproduce a second, unrelated dataset: the complex time-course of odor-evoked walking for genetically diverse Drosophila strains. Dynamical models that best reproduced both Drosophila basal and odor-evoked locomotor patterns exhibited specific characteristics. First, ongoing fluctuations were required. In a stochastic resonance-like manner, these fluctuations allowed neural activity to escape stable equilibria and to exceed a threshold for locomotion. Second, odor-induced shifts of equilibria in these models caused a depression in locomotor frequency following olfactory stimulation. Our models predict that activity fluctuations in action selection circuits cause behavioral output to more closely match sensory drive and may therefore enhance navigation in complex sensory environments. Together these data reveal how simple neural dynamics, when coupled with activity fluctuations, can give rise to complex patterns of animal behavior.

Synaptic plasticity in a recurrent neural network for versatile and adaptive behaviors of a walking robot

Walking animals, like insects, with little neural computing can effectively perform complex behaviors. For example, they can walk around their environment, escape from corners/deadlocks, and avoid or climb over obstacles. While performing all these behaviors, they can also adapt their movements to deal with an unknown situation. As a consequence, they successfully navigate through their complex environment. The versatile and adaptive abilities are the result of an integration of several ingredients embedded in their sensorimotor loop. Biological studies reveal that the ingredients include neural dynamics, plasticity, sensory feedback, and biomechanics. Generating such versatile and adaptive behaviors for a many degrees-of-freedom (DOFs) walking robot is a challenging task. Thus, in this study, we present a bio-inspired approach to solve this task. Specifically, the approach combines neural mechanisms with plasticity, exteroceptive sensory feedback, and biomechanics. The neural mechanisms consist of adaptive neural sensory processing and modular neural locomotion control. The sensory processing is based on a small recurrent neural network consisting of two fully connected neurons. Online correlation-based learning with synaptic scaling is applied to adequately change the connections of the network. By doing so, we can effectively exploit neural dynamics (i.e., hysteresis effects and single attractors) in the network to generate different turning angles with short-term memory for a walking robot. The turning information is transmitted as descending steering signals to the neural locomotion control which translates the signals into motor actions. As a result, the robot can walk around and adapt its turning angle for avoiding obstacles in different situations. The adaptation also enables the robot to effectively escape from sharp corners or deadlocks. Using backbone joint control embedded in the the locomotion control allows the robot to climb over small obstacles. Consequently, it can successfully explore and navigate in complex environments. We firstly tested our approach on a physical simulation environment and then applied it to our real biomechanical walking robot AMOSII with 19 DOFs to adaptively avoid obstacles and navigate in the real world.

A neural command circuit for grooming movement control

Animals perform many stereotyped movements, but how nervous systems are organized for controlling specific movements remains unclear. Here we use anatomical, optogenetic, behavioral, and physiological techniques to identify a circuit in Drosophila melanogaster that can elicit stereotyped leg movements that groom the antennae. Mechanosensory chordotonal neurons detect displacements of the antennae and excite three different classes of functionally connected interneurons, which include two classes of brain interneurons and different parallel descending neurons. This multilayered circuit is organized such that neurons within each layer are sufficient to specifically elicit antennal grooming. However, we find differences in the durations of antennal grooming elicited by neurons in the different layers, suggesting that the circuit is organized to both command antennal grooming and control its duration. As similar features underlie stimulus-induced movements in other animals, we infer the possibility of a common circuit organization for movement control that can be dissected in Drosophila.

Controlling legs for locomotion-insights from robotics and neurobiology

Walking is the most common terrestrial form of locomotion in animals. Its great versatility and flexibility has led to many attempts at building walking machines with similar capabilities. The control of walking is an active research area both in neurobiology and robotics, with a large and growing body of work. This paper gives an overview of the current knowledge on the control of legged locomotion in animals and machines and attempts to give walking control researchers from biology and robotics an overview of the current knowledge in both fields. We try to summarize the knowledge on the neurobiological basis of walking control in animals, emphasizing common principles seen in different species. In a section on walking robots, we review common approaches to walking controller design with a slight emphasis on biped walking control. We show where parallels between robotic and neurobiological walking controllers exist and how robotics and biology may benefit from each other. Finally, we discuss where research in the two fields diverges and suggest ways to bridge these gaps.

Task-dependent modification of leg motor neuron synaptic input underlying changes in walking direction and walking speed

Animals modify their behavior constantly to perform adequately in their environment. In terrestrial locomotion many forms of adaptation exist. Two tasks are changes of walking direction and walking speed. We investigated these two changes in motor output in the stick insect Cuniculina impigra to see how they are brought about at the level of leg motor neurons. We used a semi-intact preparation in which we can record intracellularly from leg motor neurons during walking. In this single-leg preparation the middle leg of the animal steps in a vertical plane on a treadwheel. Stimulation of either abdomen or head reliably elicits fictive forward or backward motor activity, respectively, in the fixed and otherwise deafferented thorax-coxa joint. With a change of walking direction only thorax-coxa-joint motor neurons protractor and retractor changed their activity. The protractor switched from swing activity during forward to stance activity during backward walking, and the retractor from stance to swing. This phase switch was due to corresponding change of phasic synaptic inputs from inhibitory to excitatory and vice versa at specific phases of the step cycle. In addition to phasic synaptic input a tonic depolarization of the motor neurons was present. Analysis of changes in stepping velocity during stance showed only a significant correlation to flexor motor neuron activity, but not to that of retractor and depressor motor neurons during forward walking. These results show that different tasks in the stick insect walking system are generated by altering synaptic inputs to specific leg joint motor neurons only.

Investigating inter-segmental connections between thoracic ganglia in the stick insect by means of experimental and simulated phase response curves

The neuronal networks that control the motion of the individual legs in insects, in particular in the stick insect, are located in the pro-, meso- and meta-thoracic ganglia. They ensure high flexibility of movement control. Thus, the legs can move in an apparently independent way, e.g., during search movements, but also in tight coordination during locomotion. The latter is evidently a very important behavioural mode. It has, therefore, inspired a large number of studies, all aiming at uncovering the nature of the inter-leg coordination. One of the basic questions has been as to how the individual control networks in the three thoracic ganglia are connected to each other. One way to study this problem is to use phase response curves. They can reveal properties of the coupling between oscillatory systems, such as the central pattern generators in the control networks in the thoracic ganglia. In this paper, we report results that we have achieved by means of a combined experimental and modelling approach. We have calculated phase response curves from data obtained in as yet unpublished experiments as well as from those in previously published ones. By using models of the connected pro- and meso-thoracic control networks of the protractor and retractor neuromuscular systems, we have also produced simulated phase response curves and compared them with the experimental ones. In this way, we could gain important information of the nature of the connections between the aforementioned control networks. Specifically, we have found that connections from both the protractor and the retractor "sides" of the pro-thoracic network to the meso-thoracic one are necessary for producing phase response curves that show close similarity to the experimental ones. Furthermore, the strength of the excitatory connections has been proven to be crucial, while the inhibitory connections have essentially been irrelevant. We, thus, suggest that this type of connection might also be present in the stick insect, and possibly in other insect species.

Specification of individual adult motor neuron morphologies by combinatorial transcription factor codes

How the highly stereotyped morphologies of individual neurons are genetically specified is not well understood. We identify six transcription factors (TFs) expressed in a combinatorial manner in seven post-mitotic adult leg motor neurons (MNs) that are derived from a single neuroblast in Drosophila. Unlike TFs expressed in mitotically active neuroblasts, these TFs do not regulate each other's expression. Removing the activity of a single TF resulted in specific morphological defects, including muscle targeting and dendritic arborization, and in a highly specific walking defect in adult flies. In contrast, when the expression of multiple TFs was modified, nearly complete transformations in MN morphologies were generated. These results show that the morphological characteristics of a single neuron are dictated by a combinatorial code of morphology TFs (mTFs). mTFs function at a previously unidentified regulatory tier downstream of factors acting in the NB but independently of factors that act in terminally differentiated neurons.

A network model comprising 4 segmental, interconnected ganglia, and its application to simulate multi-legged locomotion in crustaceans

Inter-segmental coordination is crucial for the locomotion of animals. Arthropods show high variability of leg numbers, from 6 in insects up to 750 legs in millipedes. Despite this fact, the anatomical and functional organization of their nervous systems show basic similarities. The main similarities are the segmental organization, and the way the function of the segmental units is coordinated. We set out to construct a model that could describe locomotion (walking) in animals with more than 6 legs, as well as in 6-legged animals (insects). To this end, we extended a network model by Daun-Gruhn and Tóth (Journal of Computational Neuroscience, doi: 10.1007/s10827-010-0300-1 , 2011). This model describes inter-segmental coordination of the ipsilateral legs in the stick insect during walking. Including an additional segment (local network) into the original model, we could simulate coordination patterns that occur in animals walking on eight legs (e.g., crayfish). We could improve the model by modifying its original cyclic connection topology. In all model variants, the phase relations between the afferent segmental excitatory sensory signals and the oscillatory activity of the segmental networks played a crucial role. Our results stress the importance of this sensory input on the generation of different stable coordination patterns. The simulations confirmed that using the modified connection topology, the flexibility of the model behaviour increased, meaning that changing a single phase parameter, i.e., gating properties of just one afferent sensory signal was sufficient to reproduce all coordination patterns seen in the experiments.

Comparative whole-body kinematics of closely related insect species with different body morphology

Legged locomotion through natural environments is very complex and variable. For example, leg kinematics may differ strongly between species, but even within the same species it is adaptive and context-dependent. Inter-species differences in locomotion are often difficult to interpret, because both morphological and ecological differences among species may be strong and, as a consequence, confound each other's effects. In order to understand better how body morphology affects legged locomotion, we compare unrestrained whole-body kinematics of three stick insect species with different body proportions, but similar feeding ecology: Carausius morosus, Aretaon asperrimus and Medauroidea extradentata (=Cuniculina impigra). In order to co-vary locomotory context, we introduced a gradually increasing demand for climbing by varying the height of stairs in the setup. The species were similar in many aspects, for example in using distinct classes of steps, with minor differences concerning the spread of corrective short steps. Major differences were related to antenna length, segment lengths of thorax and head, and the ratio of leg length to body length. Whereas all species continuously moved their antennae, only Medauroidea executed high swing movements with its front legs to search for obstacles in the near-range environment. Although all species adjusted their body inclination, the range in which body segments moved differed considerably, with longer thorax segments tending to be moved more. Finally, leg posture, time courses of leg joint angles and intra-leg coordination differed most strongly in long-legged Medauroidea.

Serotonin receptors expressed in Drosophila mushroom bodies differentially modulate larval locomotion

Drosophila melanogaster has been successfully used as a simple model to study the cellular and molecular mechanisms underlying behaviors, including the generation of motor programs. Thus, it has been shown that, as in vertebrates, CNS biogenic amines (BA) including serotonin (5HT) participate in motor control in Drosophila. Several evidence show that BA systems innervate an important association area in the insect brain previously associated to the planning and/or execution of motor programs, the Mushroom Bodies (MB). The main objective of this work is to evaluate the contribution of 5HT and its receptors expressed in MB to motor behavior in fly larva. Locomotion was evaluated using an automated tracking system, in Drosophila larvae (3^rd-instar) exposed to drugs that affect the serotonergic neuronal transmission: alpha-methyl-L-dopa, MDMA and fluoxetine. In addition, animals expressing mutations in the 5HT biosynthetic enzymes or in any of the previously identified receptors for this amine (5HT_1AR, 5HT_1BR, 5HT₂R and 5HT₇R) were evaluated in their locomotion. Finally, RNAi directed to the Drosophila 5HT receptor transcripts were expressed in MB and the effect of this manipulation on motor behavior was assessed. Data obtained in the mutants and in animals exposed to the serotonergic drugs, suggest that 5HT systems are important regulators of motor programs in fly larvae. Studies carried out in animals pan-neuronally expressing the RNAi for each of the serotonergic receptors, support this idea and further suggest that CNS 5HT pathways play a role in motor control. Moreover, animals expressing an RNAi for 5HT_1BR, 5HT₂R and 5HT₇R in MB show increased motor behavior, while no effect is observed when the RNAi for 5HT_1AR is expressed in this region. Thus, our data suggest that CNS 5HT systems are involved in motor control, and that 5HT receptors expressed in MB differentially modulate motor programs in fly larvae.

A neuromechanical simulation of insect walking and transition to turning of the cockroach Blaberus discoidalis

A neuromechanical simulation of the cockroach Blaberus discoidalis was developed to explore changes in locomotion when the animal transitions from walking straight to turning. The simulation was based upon the biological data taken from three sources. Neural circuitry was adapted from the extensive literature primarily obtained from the studies of neural connections within thoracic ganglia of stick insect and adapted to cockroach. The 3D joint kinematic data on straight, forward walking for cockroach were taken from a paper that describes these movements in all joints simultaneously as the cockroach walked on an oiled-plate tether (Bender et al. in PloS one 5(10):1-15, 2010b). Joint kinematics for turning were only available for some leg joints (Mu and Ritzmann in J Comp Physiol A Neuroethol Sens Neural Behav Physiol 191(11):1037-54, 2005) and thus had to be obtained using the methods that were applied for straight walking by Bender et al. (PloS one 5(10):1-15, 2010b). Once walking, inside turning, and outside turning were characterized, phase and amplitude changes for each joint of each leg were quantified. Apparent reflex reversals and joint activity changes were used to modify sensory coupling pathways between the CPG at each joint of the simulation. Oiled-plate experiments in simulation produced tarsus trajectories in stance similar to those seen in the animal. Simulations including forces that would be experienced if the insect was walking freely (i.e., weight support and friction) again produced similar results. These data were not considered during the design of the simulation, suggesting that the simulation captures some key underlying the principles of walking, turning, and transitioning in the cockroach. In addition, since the nervous system was modeled with realistic neuron models, biologically plausible reflex reversals are simulated, motivating future neurobiological research.

Biologically-inspired adaptive obstacle negotiation behavior of hexapod robots

Neurobiological studies have shown that insects are able to adapt leg movements and posture for obstacle negotiation in changing environments. Moreover, the distance to an obstacle where an insect begins to climb is found to be a major parameter for successful obstacle negotiation. Inspired by these findings, we present an adaptive neural control mechanism for obstacle negotiation behavior in hexapod robots. It combines locomotion control, backbone joint control, local leg reflexes, and neural learning. While the first three components generate locomotion including walking and climbing, the neural learning mechanism allows the robot to adapt its behavior for obstacle negotiation with respect to changing conditions, e.g., variable obstacle heights and different walking gaits. By successfully learning the association of an early, predictive signal (conditioned stimulus, CS) and a late, reflex signal (unconditioned stimulus, UCS), both provided by ultrasonic sensors at the front of the robot, the robot can autonomously find an appropriate distance from an obstacle to initiate climbing. The adaptive neural control was developed and tested first on a physical robot simulation, and was then successfully transferred to a real hexapod robot, called AMOS II. The results show that the robot can efficiently negotiate obstacles with a height up to 85% of the robot's leg length in simulation and 75% in a real environment.

Spatial coordination of foot contacts in unrestrained climbing insects

Animals that live in a spatially complex environment such as the canopy of a tree, constantly need to find reliable foothold in three-dimensional (3D) space. In multi-legged animals, spatial coordination among legs is thought to improve efficiency of finding foothold by avoiding searching-movements in trailing legs. In stick insects, a "targeting mechanism" has been described that guides foot-placement of hind and middle legs according to the position of their leading ipsilateral leg. So far, this mechanism was shown for standing and tethered walking animals on horizontal surfaces. Here, we investigate the efficiency of this mechanism in spatial limb coordination of unrestrained climbing animals. For this, we recorded whole-body kinematics of freely climbing stick insects and analyzed foot placement in 3D space. We found that touch-down positions of adjacent legs were highly correlated in all three spatial dimensions, revealing 3D coordinate transfer among legs. Furthermore, targeting precision depended on the position of the leading leg. A second objective was to test the importance of sensory information transfer between legs. For this, we ablated a proprioceptive hair field signaling the levation of the leg. After ablation, the operated leg swung higher and performed unexpected searching-movements. Furthermore, targeting of the ipsilateral trailing leg was less precise in antero-posterior and in dorso-ventral directions. Our results reveal that the targeting mechanism is used by unrestrained climbing stick insects in 3D space and that information from the trochanteral hair field is used in ipsilateral spatial coordination among legs.

Insects use two distinct classes of steps during unrestrained locomotion

Background

Adaptive, context-dependent control of locomotion requires modulation of centrally generated rhythmic motor patterns through peripheral control loops and postural reflexes. Thus assuming that the modulation of rhythmic motor patterns accounts for much of the behavioural variability observed in legged locomotion, investigating behavioural variability is a key to the understanding of context-dependent control mechanisms in locomotion. To date, the variability of unrestrained locomotion is poorly understood, and virtually nothing is known about the features that characterise the natural statistics of legged locomotion. In this study, we quantify the natural variability of hexapedal walking and climbing in insects, drawing from a database of several thousand steps recorded over two hours of walking time.

Results

We show that the range of step length used by unrestrained climbing stick insects is large, showing that step length can be changed substantially for adaptive locomotion. Step length distributions were always bimodal, irrespective of leg type and walking condition, suggesting the presence of two distinct classes of steps: short and long steps. Probability density of step length was well-described by a gamma distribution for short steps, and a logistic distribution for long steps. Major coefficients of these distributions remained largely unaffected by walking conditions. Short and long steps differed concerning their spatial occurrence on the walking substrate, their timing within the step sequence, and their prevalent swing direction. Finally, ablation of structures that serve to improve foothold increased the ratio of short to long steps, indicating a corrective function of short steps.

Conclusions

Statistical and functional differences suggest that short and long steps are physiologically distinct classes of leg movements that likely reflect distinct control mechanisms at work.

Walknet, a bio-inspired controller for hexapod walking

Walknet comprises an artificial neural network that allows for the simulation of a considerable amount of behavioral data obtained from walking and standing stick insects. It has been tested by kinematic and dynamic simulations as well as on a number of six-legged robots. Over the years, various different expansions of this network have been provided leading to different versions of Walknet. This review summarizes the most important biological findings described by Walknet and how they can be simulated. Walknet shows how a number of properties observed in insects may emerge from a decentralized architecture. Examples are the continuum of so-called "gaits," coordination of up to 18 leg joints during stance when walking forward or backward over uneven surfaces and negotiation of curves, dealing with leg loss, as well as being able following motion trajectories without explicit precalculation. The different Walknet versions are compared to other approaches describing insect-inspired hexapod walking. Finally, we briefly address the ability of this decentralized reactive controller to form the basis for the simulation of higher-level cognitive faculties exceeding the capabilities of insects.

Instantaneous kinematic phase reflects neuromechanical response to lateral perturbations of running cockroaches

Instantaneous kinematic phase calculation allows the development of reduced-order oscillator models useful in generating hypotheses of neuromechanical control. When perturbed, changes in instantaneous kinematic phase and frequency of rhythmic movements can provide details of movement and evidence for neural feedback to a system-level neural oscillator with a time resolution not possible with traditional approaches. We elicited an escape response in cockroaches (Blaberus discoidalis) that ran onto a movable cart accelerated laterally with respect to the animals' motion causing a perturbation. The specific impulse imposed on animals (0.50 [Formula: see text] 0.04 m s[Formula: see text]; mean, SD) was nearly twice their forward speed (0.25 [Formula: see text] 0.06 m s[Formula: see text]. Instantaneous residual phase computed from kinematic phase remained constant for 110 ms after the onset of perturbation, but then decreased representing a decrease in stride frequency. Results from direct muscle action potential recordings supported kinematic phase results in showing that recovery begins with self-stabilizing mechanical feedback followed by neural feedback to an abstracted neural oscillator or central pattern generator. Trials fell into two classes of forward velocity changes, while exhibiting statistically indistinguishable frequency changes. Animals pulled away from the side with front and hind legs of the tripod in stance recovered heading within 300 ms, whereas animals that only had a middle leg of the tripod resisting the pull did not recover within this period. Animals with eight or more legs might be more robust to lateral perturbations than hexapods.

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

Coordinated walking in vertebrates and multi-legged invertebrates [corrected] such as Drosophila melanogaster requires a complex neural network coupled to sensory feedback. An understanding of this network will benefit from systems such as Drosophila that have the ability to genetically manipulate neural activities. However, the fly's small size makes it challenging to analyze walking in this system. In order to overcome this limitation, we developed an optical method coupled with high-speed imaging that allows the tracking and quantification of gait parameters in freely walking flies with high temporal and spatial resolution. Using this method, we present a comprehensive description of many locomotion parameters, such as gait, tarsal positioning, and intersegmental and left-right coordination for wild type fruit flies. Surprisingly, we find that inactivation of sensory neurons in the fly's legs, to block proprioceptive feedback, led to deficient step precision, but interleg coordination and the ability to execute a tripod gait were unaffected.DOI:http://dx.doi.org/10.7554/eLife.00231.001.

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

Coordinated walking in vertebrates and multi-legged invertebrates such as Drosophila melanogaster requires a complex neural network coupled to sensory feedback. An understanding of this network will benefit from systems such as Drosophila that have the ability to genetically manipulate neural activities. However, the fly's small size makes it challenging to analyze walking in this system. In order to overcome this limitation, we developed an optical method coupled with high-speed imaging that allows the tracking and quantification of gait parameters in freely walking flies with high temporal and spatial resolution. Using this method, we present a comprehensive description of many locomotion parameters, such as gait, tarsal positioning, and intersegmental and left-right coordination for wild type fruit flies. Surprisingly, we find that inactivation of sensory neurons in the fly's legs, to block proprioceptive feedback, led to deficient step precision, but interleg coordination and the ability to execute a tripod gait were unaffected.

DOI:http://dx.doi.org/10.7554/eLife.00231.001

Most animals need to be able to move to survive. Animals without limbs, such as snakes, move by generating by wave-like contractions along their bodies, whereas limbed animals, such as vertebrates and arthropods, walk by coordinating the movements of multi-jointed arms and legs. Locomotion in limbed animals involves bending each joint within each arm or leg in a coordinated manner, while also ensuring that the movements of all the limbs are coordinated with each other. In bipeds such as humans, for example, it is critical that one leg is in the stance phase when the other leg is in the swing phase. The rules that govern the coordination of limbs also depend on the gait, so the rules for walking are not the same as the rules for running.

The nervous systems of bipeds and other animals that walk solve these problems by using complex neural circuits that coordinate the firing of the relevant motor neurons. Two general mechanisms are used to coordinate the firing of motor neurons. In one mechanism, local interneurons within the central nervous system coordinate motor neuron activities: in vertebrates these interneurons are found in the spinal cord. A second mechanism, termed proprioception, relies on sensory neurons that report the load and joint angles from the arms and legs back to the central nervous system, and thereby influence the firing of the motor neurons. Remarkably, both of these mechanisms, and also the types of neurons that comprise motor neuron circuits, are conserved from arthropods to vertebrates.

Mendes et al. describe a new approach that can be used to analyze how the fruit fly, D. melanogaster, walks on surfaces. They use a combination of an optical touch sensor and high-speed video imaging to follow the body of the fly as it walks, and also to record when and where it places each of its six feet on the surface as it moves. Then, using a software package called FlyWalker, they are able to extract a large of number of parameters that can be used to describe locomotion in adult fruit flies with high temporal and spatial resolution. Many of these parameters have never been measured or studied before.

Mendes et al. show that fruit flies do not display the abrupt transitions in gait that are typically observed in vertebrates. However, they do modify their neural circuits depending on their speed: indeed it appears that flies use subtly different neural circuitry for walking at slow, medium and fast speeds. Moreover, when genetic methods are used to block sensory feedback, the fly is still able to walk, albeit with reduced coordination and precision. Further, the data suggest that proprioception is less important when flies walk faster compared to when they walk more slowly. The next step in this research will be to combine this new method for analyzing locomotion in flies with the wide range of genetic tools that are available for the study of Drosophila: this will allow researchers to explore in greater detail the components of the motor neuron circuitry and their role in coordinated walking.

DOI:http://dx.doi.org/10.7554/eLife.00231.002

Neural activity in the central complex of the cockroach brain is linked to turning behaviors

An animal moving through complex terrain must consider sensory cues around it and alter its movements accordingly. In the arthropod brain, the central complex (CC) receives highly preprocessed sensory information and sends outputs to premotor regions, suggesting that it may play a role in the central control of oriented locomotion. We performed tetrode recordings within the CC in cockroaches walking on an air-suspended ball to examine the role of the CC in turning behaviors. When a rod was placed near the cockroach's head, the cockroach touched the rod repeatedly with one or both antennae before locomotion was initiated. Some CC units responded to self-generated antennal contact with the object, but at lower levels compared with externally imposed antennal stimulation. The neural activity of other CC units responded to locomotion. We found that some CC units showed discrete firing fields corresponding to specific locomotion states. We also found that changes in firing rate of some CC units preceded changes in turning speed in one direction but not the other. Furthermore, such biased units were located in the side of the brain ipsilateral to the direction of the turning speed they could predict. Moreover, electrical stimulation of the CC elicited or modified locomotion, and the direction of some evoked locomotion could be predicted by the response property of locomotion-predictive units near the stimulation site. Therefore, our results suggest that, at the population level, asymmetrical activity in the CC precedes and influences turning behavior.

A neuromechanical model for the neuronal basis of curve walking in the stick insect

The coordination of the movement of single and multiple limbs is essential for the generation of locomotion. Movement about single joints and the resulting stepping patterns are usually generated by the activity of antagonistic muscle pairs. In the stick insect, the three major muscle pairs of a leg are the protractor and retractor coxae, the levator and depressor trochanteris, and the flexor and extensor tibiae. The protractor and retractor move the coxa, and thereby the leg, forward and backward. The levator and depressor move the femur up and down. The flexor flexes, and the extensor extends the tibia about the femur-tibia joint. The underlying neuronal mechanisms for a forward stepping middle leg have been thoroughly investigated in experimental and theoretical studies. However, the details of the neuronal and mechanical mechanisms driving a stepping single leg in situations other than forward walking remain largely unknown. Here, we present a neuromechanical model of the coupled three joint control system of the stick insect's middle leg. The model can generate forward, backward, or sideward stepping. Switching between them is achieved by changing only a few central signals controlling the neuromechanical model. In kinematic simulations, we are able to generate curve walking with two different mechanisms. In the first, the inner middle leg is switched from forward to sideward and in the second to backward stepping. Both are observed in the behaving animal, and in the model and animal alike, backward stepping of the inner middle leg produces tighter turns than sideward stepping.

Quadrupedal gaits in hexapod animals - inter-leg coordination in free-walking adult stick insects

The analysis of inter-leg coordination in insect walking is generally a study of six-legged locomotion. For decades, the stick insect Carausius morosus has been instrumental for unravelling the rules and mechanisms that control leg coordination in hexapeds. We analysed inter-leg coordination in C. morosus that freely walked on straight paths on plane surfaces with different slopes. Consecutive 1.7 s sections were assigned inter-leg coordination patterns (which we call gaits) based on footfall patterns. Regular gaits, i.e. wave, tetrapod or tripod gaits, occurred in different proportions depending on surface slopes. Tetrapod gaits were observed most frequently, wave gaits only occurred on 90 deg inclining slopes and tripod gaits occurred most often on 15 deg declining slopes, i.e. in 40% of the sections. Depending on the slope, 36-66% of the sections were assigned irregular gaits. Irregular gaits were mostly due to multiple stepping by the front legs, which is perhaps probing behaviour, not phase coupled to the middle legs' cycles. In irregular gaits, middle leg and hindleg coordination was regular, related to quadrupedal walk and wave gaits. Apparently, front legs uncouple from and couple to the walking system without compromising middle leg and hindleg coordination. In front leg amputees, the remaining legs were strictly coordinated. In hindleg and middle leg amputees, the front legs continued multiple stepping. The coordination of middle leg amputees was maladapted, with front legs and hindlegs performing multiple steps or ipsilateral legs being in simultaneous swing. Thus, afferent information from middle legs might be necessary for a regular hindleg stepping pattern.

Developmental origins and architecture of Drosophila leg motoneurons

Motoneurons are key points of convergence within motor networks, acting as the "output channels" that directly control sets of muscles to maintain posture and generate movement. Here we use genetic mosaic techniques to reveal the origins and architecture of the leg motoneurons of Drosophila. We show that a small number of leg motoneurons are born in the embryo but most are generated during larval life. These postembryonic leg motoneurons are produced by five neuroblasts per hemineuromere, and each lineage generates stereotyped lineage-specific projection patterns. Two of these postembryonic neuroblasts generate solely motoneurons that are the bulk of the leg motoneurons. Within the largest lineage, lineage 15, we see distinct birth-order differences in projection patterns. A comparison of the central projections of leg motoneurons and the muscles they innervate reveals a stereotyped architecture and the existence of a myotopic map. Timeline analysis of axonal outgrowth reveals that leg motoneurons reach their sites of terminal arborization in the leg at the time when their dendrites are elaborating their subtype-specific shapes. Our findings provide a comprehensive description of the origin, development, and architecture of leg motoneurons that will aid future studies exploring the link between the assembly and organization of connectivity within the leg motor system of Drosophila.

Deciding which way to go: how do insects alter movements to negotiate barriers?

Animals must routinely deal with barriers as they move through their natural environment. These challenges require directed changes in leg movements and posture performed in the context of ever changing internal and external conditions. In particular, cockroaches use a combination of tactile and visual information to evaluate objects in their path in order to effectively guide their movements in complex terrain. When encountering a large block, the insect uses its antennae to evaluate the object’s height then rears upward accordingly before climbing. A shelf presents a choice between climbing and tunneling that depends on how the antennae strike the shelf; tapping from above yields climbing, while tapping from below causes tunneling. However, ambient light conditions detected by the ocelli can bias that decision. Similarly, in a T-maze turning is determined by antennal contact but influenced by visual cues. These multi-sensory behaviors led us to look at the central complex as a center for sensori-motor integration within the insect brain. Visual and antennal tactile cues are processed within the central complex and, in tethered preparations, several central complex units changed firing rates in tandem with or prior to altered step frequency or turning, while stimulation through the implanted electrodes evoked these same behavioral changes. To further test for a central complex role in these decisions, we examined behavioral effects of brain lesions. Electrolytic lesions in restricted regions of the central complex generated site specific behavioral deficits. Similar changes were also found in reversible effects of procaine injections in the brain. Finally, we are examining these kinds of decisions made in a large arena that more closely matches the conditions under which cockroaches forage. Overall, our studies suggest that CC circuits may indeed influence the descending commands associated with navigational decisions, thereby making them more context dependent.

A neuromechanical model explaining forward and backward stepping in the stick insect

The mechanism underlying the generation of stepping has been the object of intensive studies. Stepping involves the coordinated movement of different leg joints and is, in the case of insects, produced by antagonistic muscle pairs. In the stick insect, the coordinated actions of three such antagonistic muscle pairs produce leg movements and determine the stepping pattern of the limb. The activity of the muscles is controlled by the nervous system as a whole and more specifically by local neuronal networks for each muscle pair. While many basic properties of these control mechanisms have been uncovered, some important details of their interactions in various physiological conditions have so far remained unknown. In this study, we present a neuromechanical model of the coupled protractor-retractor and levator-depressor neuromuscular systems and use it to elucidate details of their coordinated actions during forward and backward walking. The switch from protraction to retraction is evoked at a critical angle of the femur during downward movement. This angle represents a sensory input that integrates load, motion, and ground contact. Using the model, we can make detailed suggestions as to how rhythmic stepping might be generated by the central pattern generators of the local neuronal networks, how this activity might be transmitted to the corresponding motoneurons, and how the latter might control the activity of the related muscles. The entirety of these processes yields the coordinated interaction between neuronal and mechanical parts of the system. Moreover, we put forward a mechanism by which motoneuron activity could be modified by a premotor network and suggest that this mechanism might serve as a basis for fast adaptive behavior, like switches between forward and backward stepping, which occur, for example, during curve walking, and especially sharp turning, of insects.

Proprioceptive feedback reinforces centrally generated stepping patterns in the cockroach

The relative importance of sensory input for the production of centrally generated motor patterns is crucial to our understanding of how animals coordinate their body segments to locomote. In legged locomotion, where terrain heterogeneity may require stride-by-stride changes in leg placement, evidence suggests that sensory information is essential for the timing of leg movement. In a previous study we showed that in cockroaches, renowned for rapid and stable running, a coordinated pattern can be elicited from the motor centres driving the different legs in the absence of sensory feedback. In the present paper, we assess the role of movement-related sensory inputs in modifying this central pattern. We studied the effect of spontaneous steps as well as imposed transient and periodic movements of a single intact leg, and demonstrate that, depending on the movement properties, the resulting proprioceptive feedback can significantly modify phase relationships among segmental oscillators of other legs. Our analysis suggests that feedback from front legs is weaker but more phasically precise than from hind legs, selectively transferring movement-related information in a manner that strengthens the inherent rhythmic pattern and modulates local perturbations.

Active tactile exploration for adaptive locomotion in the stick insect

Insects carry a pair of actively movable feelers that supply the animal with a range of multimodal information. The antennae of the stick insect Carausius morosus are straight and of nearly the same length as the legs, making them ideal probes for near-range exploration. Indeed, stick insects, like many other insects, use antennal contact information for the adaptive control of locomotion, for example, in climbing. Moreover, the active exploratory movement pattern of the antennae is context-dependent. The first objective of the present study is to reveal the significance of antennal contact information for the efficient initiation of climbing. This is done by means of kinematic analysis of freely walking animals as they undergo a tactually elicited transition from walking to climbing. The main findings are that fast, tactually elicited re-targeting movements may occur during an ongoing swing movement, and that the height of the last antennal contact prior to leg contact largely predicts the height of the first leg contact. The second objective is to understand the context-dependent adaptation of the antennal movement pattern in response to tactile contact. We show that the cycle frequency of both antennal joints increases after obstacle contact. Furthermore, inter-joint coupling switches distinctly upon tactile contact, revealing a simple mechanism for context-dependent adaptation.

Small is beautiful: models of small neuronal networks

Modeling has contributed a great deal to our understanding of how individual neurons and neuronal networks function. In this review, we focus on models of the small neuronal networks of invertebrates, especially rhythmically active CPG networks. Models have elucidated many aspects of these networks, from identifying key interacting membrane properties to pointing out gaps in our understanding, for example missing neurons. Even the complex CPGs of vertebrates, such as those that underlie respiration, have been reduced to small network models to great effect. Modeling of these networks spans from simplified models, which are amenable to mathematical analyses, to very complicated biophysical models. Some researchers have now adopted a population approach, where they generate and analyze many related models that differ in a few to several judiciously chosen free parameters; often these parameters show variability across animals and thus justify the approach. Models of small neuronal networks will continue to expand and refine our understanding of how neuronal networks in all animals program motor output, process sensory information and learn.