Pattern generation for walking and searching movements of a stick insect leg. I. Coordination of motor activity

Thorax-Segment- and Leg-Segment-Specific Motor Control for Adaptive Behavior

We have just started to understand the mechanisms underlying flexibility of motor programs among segmental neural networks that control each individual leg during walking in vertebrates and invertebrates. Here, we investigated the mechanisms underlying curve walking in the stick insect Carausius morosus during optomotor-induced turning. We wanted to know, whether the previously reported body-side specific changes in a two-front leg turning animal are also observed in the other thoracic leg segments. The motor activity of the three major leg joints showed three types of responses: 1) a context-dependent increase or decrease in motor neuron (MN) activity of the antagonistic MN pools of the thorax-coxa (ThC)-joint during inside and outside turns; 2) an activation of 1 MN pool with simultaneous cessation of the other, independent of the turning direction in the coxa-trochanteral (CTr)-joint; 3) a modification in the activity of both FTi-joint MN pools which depended on the turning direction in one, but not in the other thorax segment. By pharmacological activation of the meso- or metathoracic central pattern generating networks (CPG), we show that turning-related modifications in motor output involve changes to local CPG activity. The rhythmic activity in the MN pools of the ThC and CTr-joints was modified similarly to what was observed under control conditions in saline. Our results indicate that changes in meso- and metathoracic motor activity during curve walking are leg-joint- and thorax-segment-specific, can depend on the turning direction, and are mediated through changes in local CPG activity.

Investigating the role of low level reinforcement reflex loops in insect locomotion

Insects are highly capable walkers, but many questions remain regarding how the insect nervous system controls locomotion. One particular question is how information is communicated between the 'lower level' ventral nerve cord (VNC) and the 'higher level' head ganglia to facilitate control. In this work, we seek to explore this question by investigating how systems traditionally described as 'positive feedback' may initiate and maintain stepping in the VNC with limited information exchanged between lower and higher level centers. We focus on the 'reflex reversal' of the stick insect femur-tibia joint between a resistance reflex (RR) and an active reaction in response to joint flexion, as well as the activation of populations of descending dorsal median unpaired (desDUM) neurons from limb strain as our primary reflex loops. We present the development of a neuromechanical model of the stick insect (Carausius morosus) femur-tibia (FTi) and coxa-trochanter joint control networks 'in-the-loop' with a physical robotic limb. The control network generates motor commands for the robotic limb, whose motion and forces generate sensory feedback for the network. We based our network architecture on the anatomy of the non-spiking interneuron joint control network that controls the FTi joint, extrapolated network connectivity based on known muscle responses, and previously developed mechanisms to produce 'sideways stepping'. Previous studies hypothesized that RR is enacted by selective inhibition of sensory afferents from the femoral chordotonal organ, but no study has tested this hypothesis with a model of an intact limb. We found that inhibiting the network's flexion position and velocity afferents generated a reflex reversal in the robot limb's FTi joint. We also explored the intact network's ability to sustain steady locomotion on our test limb. Our results suggested that the reflex reversal and limb strain reinforcement mechanisms are both necessary but individually insufficient to produce and maintain rhythmic stepping in the limb, which can be initiated or halted by brief, transient descending signals. Removing portions of this feedback loop or creating a large enough disruption can halt stepping independent of the higher-level centers. We conclude by discussing why the nervous system might control motor output in this manner, as well as how to apply these findings to generalized nervous system understanding and improved robotic control.

Distributed control of motor circuits for backward walking in Drosophila

How do descending inputs from the brain control leg motor circuits to change how an animal walks? Conceptually, descending neurons are thought to function either as command-type neurons, in which a single type of descending neuron exerts a high-level control to elicit a coordinated change in motor output, or through a population coding mechanism, whereby a group of neurons, each with local effects, act in combination to elicit a global motor response. The Drosophila Moonwalker Descending Neurons (MDNs), which alter leg motor circuit dynamics so that the fly walks backwards, exemplify the command-type mechanism. Here, we identify several dozen MDN target neurons within the leg motor circuits, and show that two of them mediate distinct and highly-specific changes in leg muscle activity during backward walking: LBL40 neurons provide the hindleg power stroke during stance phase; LUL130 neurons lift the legs at the end of stance to initiate swing. Through these two effector neurons, MDN directly controls both the stance and swing phases of the backward stepping cycle. These findings suggest that command-type descending neurons can also operate through the distributed control of local motor circuits.

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.

Robust dynamical invariants in sequential neural activity

By studying different sources of temporal variability in central pattern generator (CPG) circuits, we unveil fundamental aspects of the instantaneous balance between flexibility and robustness in sequential dynamics -a property that characterizes many systems that display neural rhythms. Our analysis of the triphasic rhythm of the pyloric CPG (Carcinus maenas) shows strong robustness of transient dynamics in keeping not only the activation sequences but also specific cycle-by-cycle temporal relationships in the form of strong linear correlations between pivotal time intervals, i.e. dynamical invariants. The level of variability and coordination was characterized using intrinsic time references and intervals in long recordings of both regular and irregular rhythms. Out of the many possible combinations of time intervals studied, only two cycle-by-cycle dynamical invariants were identified, existing even outside steady states. While executing a neural sequence, dynamical invariants reflect constraints to optimize functionality by shaping the actual intervals in which activity emerges to build the sequence. Our results indicate that such boundaries to the adaptability arise from the interaction between the rich dynamics of neurons and connections. We suggest that invariant temporal sequence relationships could be present in other networks, including those shaping sequences of functional brain rhythms, and underlie rhythm programming and functionality.

Swing Velocity Profiles of Small Limbs Can Arise from Transient Passive Torques of the Antagonist Muscle Alone

In large limbs, changing motor neuron activity typically controls within-movement velocity. For example, sequential agonist-antagonist-agonist motor neuron firing typically underlies the slowing often present at the end of human reaches. In physiological movements of large limbs, antagonistic muscle passive torque is generally negligible. In small limbs, alternatively, passive torques can determine limb rest position, generate restoring movements to it, and decrease agonist-generated movement amplitude and velocity maxima. These observations suggest that, in small limbs, passive forces might also control velocity changes within movements. We investigated this issue in stick insect middle leg femur-tibia (FT) joint. During swing, the FT joint extensor muscle actively shortens and the flexor muscle passively lengthens. As in human reaching, after its initial acceleration, FT joint velocity continuously decreases. We measured flexor passive forces during imposed stretches spanning the ranges of FT joint angles, angular velocities, and movement amplitudes present in leg swings. The viscoelastic "transient" passive force that occurs during and soon after stretch depended on all three variables and could be tens of times larger than the "steady-state" passive force commonly measured long after stretch end. We combined these data, the flexor and extensor moment arms, and an existing extensor model to simulate FT joint swing. To measure only passive (flexor) muscle-dependent effects, we used constant extensor activations in these simulations. In simulations using data from ten flexor muscles, flexor passive torque could always produce swings with, after swing initiation, continuously decreasing velocities. Antagonist muscle passive torques alone can thus control within-movement velocity.

Calcium imaging of CPG-evoked activity in efferent neurons of the stick insect

The stick insect is a well-established experimental animal to study the neural basis of walking. Here, we introduce a preparation that allows combining calcium imaging in efferent neurons with electrophysiological recordings of motor neuron activity in the stick insect thoracic nerve cord. The intracellular free calcium concentration in middle leg retractor coxae motor neurons and modulatory octopaminergic DUM neurons was monitored after backfilling lateral nerve nl5 that contains the axons of these neurons with the calcium indicator Oregon Green BAPTA-1. Rhythmic spike activity in retractor and protractor motor neurons was evoked by pharmacological activation of central pattern generating neuronal networks and recorded extracellularly from lateral nerves. A primary goal of this study was to investigate whether changes in the intracellular free calcium concentration observed in motor neurons during oscillatory activity depend on action potentials. We show that rhythmic spike activity in leg motor neurons induced either pharmacologically or by tactile stimulation of the animal is accompanied by a synchronous modulation in the intracellular free calcium concentration. Calcium oscillations in motor neurons do not appear to depend on calcium influx through voltage-sensitive calcium channels that are gated by action potentials because Calcium oscillations persist after pharmacologically blocking action potentials in the motor neurons. Calcium oscillations were also apparent in the modulatory DUM neurons innervating the same leg muscle. However, the timing of calcium oscillations varied not only between DUM neurons and motor neurons, but also among different DUM neurons. Therefore, we conclude that the motor neurons and the different DUM neurons receive independent central drive.

Leg-local neural mechanisms for searching and learning enhance robotic locomotion

Adapting motor output based on environmental forces is critical for successful locomotion in the real world. Arthropods use at least two neural mechanisms to adjust muscle activation while walking based on detected forces. Mechanism 1 uses negative feedback of leg depressor force to ensure that each stance leg supports an appropriate amount of the body's weight. Mechanism 2 encourages searching for ground contact if the leg supports no body weight. We expand the neural controller for MantisBot, a robot based upon a praying mantis, to include these mechanisms by incorporating leg-local memory and command neurons, as observed in arthropods. We present results from MantisBot transitioning between searching and stepping, mimicking data from animals as reported in the literature.

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.

Design process and tools for dynamic neuromechanical models and robot controllers

We present a serial design process with associated tools to select parameter values for a posture and locomotion controller for simulation of a robot. The controller is constructed from dynamic neuron and synapse models and simulated with the open-source neuromechanical simulator AnimatLab 2. Each joint has a central pattern generator (CPG), whose neurons possess persistent sodium channels. The CPG rhythmically inhibits motor neurons that control the servomotor's velocity. Sensory information coordinates the joints in the leg into a cohesive stepping motion. The parameter value design process is intended to run on a desktop computer, and has three steps. First, our tool FEEDBACKDESIGN uses classical control methods to find neural and synaptic parameter values that stably and robustly control servomotor output. This method is fast, testing over 100 parameter value variations per minute. Next, our tool CPGDESIGN generates bifurcation diagrams and phase response curves for the CPG model. This reveals neural and synaptic parameter values that produce robust oscillation cycles, whose phase can be rapidly entrained to sensory feedback. It also designs the synaptic conductance of inter-joint pathways. Finally, to understand sensitivity to parameters and how descending commands affect a leg's stepping motion, our tool SIMSCAN runs batches of neuromechanical simulations with specified parameter values, which is useful for searching the parameter space of a complicated simulation. These design tools are demonstrated on a simulation of a robot, but may be applied to neuromechanical animal models or physical robots as well.

Neuroethological Concepts and their Transfer to Walking Machines

A systems approach to animal motor behavior reveals concepts that can be useful for the pragmatic design of walking machines. This is because the relation of animal behavior to its underlying nervous control algorithms bears many parallels to the relation of machine function to electronic control. Here, three major neuroethological concepts of motor behavior are described in terms of a conceptual framework based on artificial neural networks (ANN). Central patterns of activity and postural reflexes are both interpreted as a result of feedback loops, with the distinction of loops via an internal model from loops via the physical environment (body, external world). This view allows continuous transitions between predictive (centrally driven) and reactive (reflex driven) motor systems. Motor primitives, behavioral modules that are elicited by distinct commands, are also considered. ANNs capture these three major concepts in terms of a formal description, in which the interactions and mutual interdependences of the various output parameters are comprised by the weight matrix of the net. Based upon behavioral observations of insect walking, we further demonstrate how a decentralized network of separate modules, each one described by an ANN, can account for adaptive behavior. Complex coordination patterns of several manipulators are controlled by imposing simple interaction rules between limbs, and by exploiting the interaction of the body with its physical environment. Finally, we discuss the technical use of leg-like active tactile sensors for obstacle detection, and we show how specific design of such active sensors may increase efficiency of walking on rough terrain. Applied to active sensors, an example of parallel, self-organizing forward models on the basis of extended Kohonen maps is presented to emphasize the potential of adaptive forward models in motor control.

Insect-computer hybrid legged robot with user-adjustable speed, step length and walking gait

We have constructed an insect-computer hybrid legged robot using a living beetle (Mecynorrhina torquata; Coleoptera). The protraction/retraction and levation/depression motions in both forelegs of the beetle were elicited by electrically stimulating eight corresponding leg muscles via eight pairs of implanted electrodes. To perform a defined walking gait (e.g., gallop), different muscles were individually stimulated in a predefined sequence using a microcontroller. Different walking gaits were performed by reordering the applied stimulation signals (i.e., applying different sequences). By varying the duration of the stimulation sequences, we successfully controlled the step frequency and hence the beetle's walking speed. To the best of our knowledge, this paper presents the first demonstration of living insect locomotion control with a user-adjustable walking gait, step length and walking speed.

Force feedback reinforces muscle synergies in insect legs

The nervous system solves complex biomechanical problems by activating muscles in modular, synergist groups. We have studied how force feedback in substrate grip is integrated with effects of sense organs that monitor support and propulsion in insects. Campaniform sensilla are mechanoreceptors that encode forces as cuticular strains. We tested the hypothesis that integration of force feedback from receptors of different leg segments during grip occurs through activation of specific muscle synergies. We characterized the effects of campaniform sensilla of the feet (tarsi) and proximal segments (trochanter and femur) on activities of leg muscles in stick insects and cockroaches. In both species, mechanical stimulation of tarsal sensilla activated the leg muscle that generates substrate grip (retractor unguis), as well as proximal leg muscles that produce inward pull (tibial flexor) and support/propulsion (trochanteral depressor). Stimulation of campaniform sensilla on proximal leg segments activated the same synergistic group of muscles. In stick insects, the effects of proximal receptors on distal leg muscles changed and were greatly enhanced when animals made active searching movements. In insects, the task-specific reinforcement of muscle synergies can ensure that substrate adhesion is rapidly established after substrate contact to provide a stable point for force generation.

Imaging fictive locomotor patterns in larval Drosophila

We have established a preparation in larval Drosophila to monitor fictive locomotion simultaneously across abdominal and thoracic segments of the isolated CNS with genetically encoded Ca²⁺ indicators. The Ca²⁺ signals closely followed spiking activity measured electrophysiologically in nerve roots. Three motor patterns are analyzed. Two comprise waves of Ca²⁺ signals that progress along the longitudinal body axis in a posterior-to-anterior or anterior-to-posterior direction. These waves had statistically indistinguishable intersegmental phase delays compared with segmental contractions during forward and backward crawling behavior, despite being ∼10 times slower. During these waves, motor neurons of the dorsal longitudinal and transverse muscles were active in the same order as the muscle groups are recruited during crawling behavior. A third fictive motor pattern exhibits a left-right asymmetry across segments and bears similarities with turning behavior in intact larvae, occurring equally frequently and involving asymmetry in the same segments. Ablation of the segments in which forward and backward waves of Ca²⁺ signals were normally initiated did not eliminate production of Ca²⁺ waves. When the brain and subesophageal ganglion (SOG) were removed, the remaining ganglia retained the ability to produce both forward and backward waves of motor activity, although the speed and frequency of waves changed. Bilateral asymmetry of activity was reduced when the brain was removed and abolished when the SOG was removed. This work paves the way to studying the neural and genetic underpinnings of segmentally coordinated motor pattern generation in Drosophila with imaging techniques.

A leg-local neural mechanism mediates the decision to search in stick insects

In many animals, individual legs can either function independently, as in behaviors such as scratching or searching, or be used in coordinated patterns with other legs, as in walking or climbing. While the control of walking has been extensively investigated, the mechanisms mediating the behavioral choice to activate individual legs independently are poorly understood. We examined this issue in stick insects, in which each leg can independently produce a rhythmic searching motor pattern if it doesn't find a foothold [1-4]. We show here that one non-spiking interneuron, I4, controls searching behavior in individual legs. One I4 is present in each hemi-segment of the three thoracic ganglia [5, 6]. Search-inducing sensory input depolarizes I4. I4 activity was necessary and sufficient to initiate and maintain searching movements. When substrate contact was provided, I4 depolarization no longer induced searching. I4 therefore both integrates search-inducing sensory input and is gated out by other sensory input (substrate contact). Searching thus occurs only when it is behaviorally appropriate. I4 depolarization never elicited stepping. These data show that individual, locally activated neurons can mediate the behavioral choice to use individual legs independently. This mechanism may be particularly important in insects' front legs, which can function independently like vertebrate arms and hands [7]. Similar local command mechanisms that selectively activate the pattern generators controlling repeated functional units such as legs or body segments may be present in other systems.

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.

The role of leg touchdown for the control of locomotor activity in the walking stick insect

Much is known on how select sensory feedback contributes to the activation of different motoneuron pools in the locomotor control system of stick insects. However, even though activation of the stance phase muscles depressor trochanteris, retractor unguis, flexor tibiae and retractor coxae is correlated with the touchdown of the leg, the potential sensory basis of this correlation or its connection to burst intensity remains unknown. In our experiments, we are using a trap door setup to investigate how ground contact contributes to stance phase muscle activation and burst intensity in different stick insect species, and which afferent input is involved in the respective changes. While the magnitude of activation is changed in all of the above stance phase muscles, only the timing of the flexor tibiae muscle is changed if the animal unexpectedly steps into a hole. Individual and combined ablation of different force sensors on the leg demonstrated influence from femoral campaniform sensilla on flexor muscle timing, causing a significant increase in the latencies during control and air steps. Our results show that specific load feedback signals determine the timing of flexor tibiae activation at the swing-to-stance transition in stepping stick insects, but that additional feedback may also be involved in flexor muscle activation during stick insect locomotion. With respect to timing, all other investigated stance phase muscles appear to be under sensory control other than that elicited through touchdown.

Positive force feedback in development of substrate grip in the stick insect tarsus

The mechanics of substrate adhesion has recently been intensively studied in insects but less is known about the sensorimotor control of substrate engagement. We characterized the responses and motor effects of tarsal campaniform sensilla in stick insects to understand how sensory signals of force could contribute to substrate grip. The tarsi consist of a chain of segments linked by highly flexible articulations. Morphological studies showed that one to four campaniform sensilla are located on the distal end of each segment. Activities of the receptors were recorded neurographically and sensilla were identified by stimulation and ablation of their cuticular caps. Responses were characterized to bending forces and axial loads, muscle contractions and to forces applied to the retractor apodeme (tendon). The tarsal sensilla effectively encoded both the rate and amplitude of loads and muscle forces, but only when movement was resisted. Mechanical stimulation of the receptors produced activation of motor neurons in the retractor unguis and tibial flexor muscles. These findings indicate that campaniform sensilla can provide information about the effectiveness of the leg muscles in generating substrate adherence. They can also produce positive force feedback that could contribute to the development of substrate grip and stabilization of the tarsal chain.

WITHDRAWN: Positive force feedback in development of substrate grip in the stick insect tarsus

The Publisher regrets that this article is an accidental duplication of an article that has already been published, http://dx.doi.org/10.1016/j.asd.2014.06.002. The duplicate article has therefore been withdrawn.

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.

A neuro-mechanical model explaining the physiological role of fast and slow muscle fibres at stop and start of stepping of an insect leg

Stop and start of stepping are two basic actions of the musculo-skeletal system of a leg. Although they are basic phenomena, they require the coordinated activities of the leg muscles. However, little is known of the details of how these activities are generated by the interactions between the local neuronal networks controlling the fast and slow muscle fibres at the individual leg joints. In the present work, we aim at uncovering some of those details using a suitable neuro-mechanical model. It is an extension of the model in the accompanying paper and now includes all three antagonistic muscle pairs of the main joints of an insect leg, together with their dedicated neuronal control, as well as common inhibitory motoneurons and the residual stiffness of the slow muscles. This model enabled us to study putative processes of intra-leg coordination during stop and start of stepping. We also made use of the effects of sensory signals encoding the position and velocity of the leg joints. Where experimental observations are available, the corresponding simulation results are in good agreement with them. Our model makes detailed predictions as to the coordination processes of the individual muscle systems both at stop and start of stepping. In particular, it reveals a possible role of the slow muscle fibres at stop in accelerating the convergence of the leg to its steady-state position. These findings lend our model physiological relevance and can therefore be used to elucidate details of the stop and start of stepping in insects, and perhaps in other animals, too.

Directional specificity and encoding of muscle forces and loads by stick insect tibial campaniform sensilla, including receptors with round cuticular caps

In many systems, loads are detected as the resistance to muscle contractions. We studied responses to loads and muscle forces in stick insect tibial campaniform sensilla, including a subgroup of receptors (Group 6B) with unusual round cuticular caps in oval-shaped collars. Loads were applied in different directions and muscle contractions were emulated by applying forces to the tibial flexor muscle tendon (apodeme). All sensilla 1) were maximally sensitive to loads applied in the plane of joint movement and 2) encoded muscle forces but did not discharge to unresisted movements. Identification of 6B sensilla by stimulation of cuticular caps demonstrated that receptor responses were correlated with their morphology. Sensilla with small cuticular collars produced small extracellular potentials, had low thresholds and strong tonic sensitivities that saturated at moderate levels. These receptors could effectively signal sustained loads. The largest spikes, derived from sensilla with large cuticular collars, had strong dynamic sensitivities and signaled a wide range of muscle forces and loads. Tibial sensilla are apparently tuned to produce no responses to inertial forces, as occur in the swing phase of walking. This conclusion is supported by tests in which animals 'stepped' on a compliant surface and sensory discharges only occurred in stance.

Animal-to-animal variability in the phasing of the crustacean cardiac motor pattern: an experimental and computational analysis

The cardiac ganglion (CG) of Homarus americanus is a central pattern generator that consists of two oscillatory groups of neurons: "small cells" (SCs) and "large cells" (LCs). We have shown that SCs and LCs begin their bursts nearly simultaneously but end their bursts at variable phases. This variability contrasts with many other central pattern generator systems in which phase is well maintained. To determine both the consequences of this variability and how CG phasing is controlled, we modeled the CG as a pair of Morris-Lecar oscillators coupled by electrical and excitatory synapses and constructed a database of 15,000 simulated networks using random parameter sets. These simulations, like our experimental results, displayed variable phase relationships, with the bursts beginning together but ending at variable phases. The model suggests that the variable phasing of the pattern has important implications for the functional role of the excitatory synapses. In networks in which the two oscillators had similar duty cycles, the excitatory coupling functioned to increase cycle frequency. In networks with disparate duty cycles, it functioned to decrease network frequency. Overall, we suggest that the phasing of the CG may vary without compromising appropriate motor output and that this variability may critically determine how the network behaves in response to manipulations.

Neural control and adaptive neural forward models for insect-like, energy-efficient, and adaptable locomotion of walking machines

Living creatures, like walking animals, have found fascinating solutions for the problem of locomotion control. Their movements show the impression of elegance including versatile, energy-efficient, and adaptable locomotion. During the last few decades, roboticists have tried to imitate such natural properties with artificial legged locomotion systems by using different approaches including machine learning algorithms, classical engineering control techniques, and biologically-inspired control mechanisms. However, their levels of performance are still far from the natural ones. By contrast, animal locomotion mechanisms seem to largely depend not only on central mechanisms (central pattern generators, CPGs) and sensory feedback (afferent-based control) but also on internal forward models (efference copies). They are used to a different degree in different animals. Generally, CPGs organize basic rhythmic motions which are shaped by sensory feedback while internal models are used for sensory prediction and state estimations. According to this concept, we present here adaptive neural locomotion control consisting of a CPG mechanism with neuromodulation and local leg control mechanisms based on sensory feedback and adaptive neural forward models with efference copies. This neural closed-loop controller enables a walking machine to perform a multitude of different walking patterns including insect-like leg movements and gaits as well as energy-efficient locomotion. In addition, the forward models allow the machine to autonomously adapt its locomotion to deal with a change of terrain, losing of ground contact during stance phase, stepping on or hitting an obstacle during swing phase, leg damage, and even to promote cockroach-like climbing behavior. Thus, the results presented here show that the employed embodied neural closed-loop system can be a powerful way for developing robust and adaptable machines.

Passive resting state and history of antagonist muscle activity shape active extensions in an insect limb

Limb movements can be driven by muscle contractions, external forces, or intrinsic passive forces. For lightweight limbs like those of insects or small vertebrates, passive forces can be large enough to overcome the effects of gravity and may even generate limb movements in the absence of active muscle contractions. Understanding the sources and actions of such forces is therefore important in understanding motor control. We describe passive properties of the femur-tibia joint of the locust hind leg. The resting angle is determined primarily by passive properties of the relatively large extensor tibiae muscle and is influenced by the history of activation of the fast extensor tibiae motor neuron. The resting angle is therefore better described as a history-dependent resting state. We selectively stimulated different flexor tibiae motor neurons to generate a range of isometric contractions of the flexor tibiae muscle and then stimulated the fast extensor tibiae motor neuron to elicit active tibial extensions. Residual forces in the flexor muscle have only a small effect on subsequent active extensions, but the effect is larger for distal than for proximal flexor motor neurons and varies with the strength of flexor activation. We conclude that passive properties of a lightweight limb make substantial and complex contributions to the resting state of the limb that must be taken into account in the patterning of neuronal control signals driving its active movements. Low variability in the effects of the passive forces may permit the nervous system to accurately predict their contributions to behavior.

Dominance of local sensory signals over inter-segmental effects in a motor system: experiments

Legged locomotion requires that information local to one leg, and inter-segmental signals coming from the other legs are processed appropriately to establish a coordinated walking pattern.However, very little is known about the relative importance of local and inter-segmental signals when they converge upon the central pattern generators (CPGs) of different leg joints.We investigated this question on the CPG of the middle leg coxa–trochanter (CTr)-joint of the stick insect which is responsible for lifting and lowering the leg.We used a semi-intact preparation with an intact front leg stepping on a treadmill, and simultaneously stimulated load sensors of the middle leg.We found that middle leg load signals induce bursts in the middle leg depressor motoneurons(MNs). The same local load signals could also elicit rhythmic activity in the CPG of the middle leg CTr-joint when the stimulation of middle leg load sensors coincided with front leg stepping. However, the influence of front leg stepping was generally weak such that front leg stepping alone was only rarely accompanied by switching between middle leg levator and depressor MN activity. We therefore conclude that the impact of the local sensory signals on the levator–depressor motor system is stronger than the inter-segmental influence through front leg stepping.

From neuron to behavior: dynamic equation-based prediction of biological processes in motor control

This article presents the use of continuous dynamic models in the form of differential equations to describe and predict temporal changes in biological processes and discusses several of its important advantages over discontinuous bistable ones, exemplified on the stick insect walking system. In this system, coordinated locomotion is produced by concerted joint dynamics and interactions on different dynamical scales, which is therefore difficult to understand. Modeling using differential equations possesses, in general, the potential for the inclusion of biological detail, the suitability for simulation, and most importantly, parameter manipulation to make predictions about the system behavior. We will show in this review article how, in case of the stick insect walking system, continuous dynamical system models can help to understand coordinated locomotion.

Deriving neural network controllers from neuro-biological data: implementation of a single-leg stick insect controller

This article presents modular recurrent neural network controllers for single legs of a biomimetic six-legged robot equipped with standard DC motors. Following arguments of Ekeberg et al. (Arthropod Struct Dev 33:287-300, 2004), completely decentralized and sensori-driven neuro-controllers were derived from neuro-biological data of stick-insects. Parameters of the controllers were either hand-tuned or optimized by an evolutionary algorithm. Employing identical controller structures, qualitatively similar behaviors were achieved for robot and for stick insect simulations. For a wide range of perturbing conditions, as for instance changing ground height or up- and downhill walking, swing as well as stance control were shown to be robust. Behavioral adaptations, like varying locomotion speeds, could be achieved by changes in neural parameters as well as by a mechanical coupling to the environment. To a large extent the simulated walking behavior matched biological data. For example, this was the case for body support force profiles and swing trajectories under varying ground heights. The results suggest that the single-leg controllers are suitable as modules for hexapod controllers, and they might therefore bridge morphological- and behavioral-based approaches to stick insect locomotion control.

Activity Patterns and Timing of Muscle Activity in the Forward Walking and Backward Walking Stick Insect Carausius morosus

Understanding how animals control locomotion in different behaviors requires understanding both the kinematics of leg movements and the neural activity underlying these movements. Stick insect leg kinematics differ in forward and backward walking. Describing leg muscle activity in these behaviors is a first step toward understanding the neuronal basis for these differences. We report here the phasing of EMG activities and latencies of first spikes relative to precise electrical measurements of middle leg tarsus touchdown and liftoff of three pairs ( protractor/retractor coxae, levator/depressor trochanteris, extensor/flexor tibiae) of stick insect middle leg antagonistic muscles that play central roles in generating leg movements during forward and backward straight walking. Forward walking stance phase muscle (depressor, flexor, and retractor) activities were tightly coupled to touchdown, beginning on average 93 ms prior to and 9 and 35 ms after touchdown, respectively. Forward walking swing phase muscle (levator, extensor, and protractor) activities were less tightly coupled to liftoff, beginning on average 100, 67, and 37 ms before liftoff, respectively. In backward walking the protractor/retractor muscles reversed their phasing compared with forward walking, with the retractor being active during swing and the protractor during stance. Comparison of intact animal and reduced two- and one-middle-leg preparations during forward straight walking showed only small alterations in overall EMG activity but changes in first spike latencies in most muscles. Changing body height, most likely due to changes in leg joint loading, altered the intensity, but not the timing, of depressor muscle activity.

Coding characteristics of spiking local interneurons during imposed limb movements in the locust

The performance of adaptive behavior relies on continuous sensory feedback to produce relevant modifications to central motor patterns. The femoral chordotonal organ (FeCO) of the legs of the desert locust monitors the movements of the tibia about the femoro-tibial joint. A ventral midline population of spiking local interneurons in the metathoracic ganglia integrates inputs from the FeCO. We used a Wiener kernel cross-correlation method combined with a Gaussian white noise stimulation of the FeCO to completely characterize and model the output dynamics of the ventral midline population of interneurons. A wide range of responses were observed, and interneurons could be classified into three broad groups that received excitatory and inhibitory or principally inhibitory or excitatory synaptic inputs from the FeCO. Interneurons that received mixed inputs also had the greatest linear responses but primarily responded to extension of the tibia and were mostly sensitive to stimulus velocity. Interneurons that received principally inhibitory inputs were sensitive to extension and to joint position. A small group of interneurons received purely excitatory synaptic inputs and were also sensitive to tibial extension. In addition to capturing the linear and nonlinear dynamics of this population of interneurons, first- and second-order Wiener kernels revealed that the dynamics of the interneurons in the population were graded and formed a spectrum of responses whereby the activity of many cells appeared to be required to adequately describe a particular stimulus characteristic, typical of population coding.

Premotor Interneurons in the Local Control of Stepping Motor Output for the Stick Insect Single Middle Leg

In insect walking systems, nonspiking interneurons (NSIs) play an important role in the control of posture and movement. As such NSIs are known to contribute to state-dependent modifications in processing of proprioceptive signals from the legs. For example, NSIs process a flexion of the femur-tibia (FTi) joint signaled by the femoral chordotonal organ (fCO) such that the stance phase motor output is reinforced in the active locomotor system. This phenomenon representing a reflex reversal is the first part of the “active reaction” (AR) and was hypothesized to functionally represent a major control feature by which sensory feedback supports stance generation. As NSIs are known to contribute to the AR, the question arises, whether they serve similar functions during stepping and whether the AR is generally part of the control system for walking. We studied these issues in vivo, in a single leg preparation of Carausius morosus with the leg kinematics being confined to changes in one plane, along the coxa-trochanteral and the FTi-joint. Following kinematic analysis, identified NSIs (E1-E8, I1, I2, and I4) were recorded intracellularly during single leg stepping at different velocities. We detected clear similarities between the activity pattern of NSIs during single leg stepping and their responses to fCO-stimulation during the generation of the AR. This strongly supports the notion that the motor output generated during the AR reflects part of the control regime for stepping. Furthermore, our experiments revealed that alterations in stepping velocity result from modifications in the activity of the premotor NSIs involved in stance phase generation.

Control of stepping velocity in the stick insect Carausius morosus

We performed electrophysiological and behavioral experiments in single-leg preparations and intact animals of the stick insect Carausius morosus to understand mechanisms underlying the control of walking speed. At the level of the single leg, we found no significant correlation between stepping velocity and spike frequency of motor neurons (MNs) other than the previously shown modification in flexor (stance) MN activity. However, pauses between stance and swing motoneuron activity at the transition from stance to swing phase and stepping velocity are correlated. Pauses become shorter with increasing speed and completely disappear during fast stepping sequences. By means of extra- and intracellular recordings in single-leg stick insect preparations we found no systematic relationship between the velocity of a stepping front leg and the motoneuronal activity in the ipsi- or contralateral mesothoracic protractor and retractor, as well as flexor and extensor MNs. The observations on the lack of coordination of stepping velocity between legs in single-leg preparations were confirmed in behavioral experiments with intact stick insects tethered above a slippery surface, thereby effectively removing mechanical coupling through the ground. In this situation, there were again no systematic correlations between the stepping velocities of different legs, despite the finding that an increase in stepping velocity in a single front leg is correlated with a general increase in nerve activity in all connectives between the subesophageal and all thoracic ganglia. However, when the tethered animal increased walking speed due to a short tactile stimulus, provoking an escape-like response, stepping velocities of ipsilateral legs were found to be correlated for several steps. These results indicate that there is no permanent coordination of stepping velocities between legs, but that such coordination can be activated under certain circumstances.

Activity of neuromodulatory neurones during stepping of a single insect leg

Octopamine plays a major role in insect motor control and is released from dorsal unpaired median (DUM) neurones, a group of cells located on the dorsal midline of each ganglion. We were interested whether and how these neurones are activated during walking and chose the semi-intact walking preparation of stick insects that offers to investigate single leg-stepping movements. DUM neurones were characterized in the thoracic nerve cord by backfilling lateral nerves. These backfills revealed a population of 6-8 efferent DUM cells per thoracic segment. Mesothoracic DUM cells were subsequently recorded during middle leg stepping and characterized by intracellular staining. Seven out of eight identified individual different types of DUM neurones were efferent. Seven types except the DUMna nl2 were tonically depolarized during middle leg stepping and additional phasic depolarizations in membrane potential linked to the stance phase of the middle leg were observed. These DUM neurones were all multimodal and received depolarizing synaptic drive when the abdomen, antennae or different parts of the leg were mechanically stimulated. We never observed hyperpolarising synaptic inputs to DUM neurones. Only one type of DUM neurone, DUMna, exhibited spontaneous rhythmic activity and was unaffected by different stimuli or walking movements.

Organizing network action for locomotion: insights from studying insect walking

The operational basis for the generation of a functional motor output during walking is formed by the interaction between central pattern generating networks, local feedback from sensory neurons about movements and forces generated in the locomotor organs and coordinating signals from neighboring segments or appendages. This review primarily addresses the current knowledge about network organization underlying the control of an insect walking leg and recent advances in understanding the ways by which modifications in the motor output for walking are generated. Here we focus especially on modifications of the walking motor pattern that are associated with changing walking speed and walking direction. We will place the current knowledge and new results into the broad context gained from other locomotor behaviors and organisms.

Intersegmental coordination: influence of a single walking leg on the neighboring segments in the stick insect walking system

A key element of walking is the coordinated interplay of multiple limbs to achieve a stable locomotor pattern that is adapted to the environment. We investigated intersegmental coordination of walking in the stick insect, Carausius morosus by examining the influence a single stepping leg has on the motoneural activity of the other hemiganglia, and whether this influence changes with the walking direction. We used a reduced single leg walking preparation with only one intact front, middle, or hind leg. The intact leg performed stepping movements on a treadmill, thus providing intersegmental signals about its stepping to the other hemiganglia. The activity of coxal motoneurons was simultaneously recorded extracellularly in all other segments. Stepping sequences of any given single leg in either walking direction were accompanied by an increase in coxal motoneuron (MN) activity of all other segments, which was mostly modulated and slightly in phase with stance of the walking leg. In addition, forward stepping of the front leg and, to a lesser extent, backward stepping of the hind leg elicited alternating activity in mesothoracic coxal MNs. Forward and backward stepping of the middle leg did not elicit alternating activity in coxal MNs in any other hemiganglia, indicating that the influence of middle leg stepping is qualitatively different from that of forward front and backward hind leg stepping. Our results indicate that in an insect walking system individual segments differ with respect to their intersegmental influences and thus cannot be treated as similar within the chain of segmental walking pattern generators. Consequences for the current concepts on intersegmental coordination are discussed.

Control of stepping velocity in a single insect leg during walking

In the single middle leg preparation of the stick insect walking on a treadmill, the activity of flexor and extensor tibiae motor neurons and muscles, which are responsible for the movement of the tibia in stance and swing phases, respectively, was investigated with respect to changes in stepping velocity. Changes in stepping velocity were correlated with cycle period. There was a close correlation of flexor motor neuron activity (stance phase) with stepping velocity, but the duration and activation of extensor motor neurons (swing phase) was not altered. The depolarization of flexor motor neurons showed two components. At all step velocities, a stereotypic initial depolarization was generated at the beginning of stance phase activity. A subsequent larger depolarization and activation was tightly linked to belt velocity, i.e. it occurred earlier and with larger amplitude during fast steps compared with slow steps. Alterations in a tonic background excitation appear not to play a role in controlling the motor neuron activity for changes in stepping velocity. Our results indicate that in the single insect leg during walking, mechanisms for altering stepping velocity become effective only during an already ongoing stance phase motor output. We discuss the putative mechanisms involved.

Tethered stick insect walking: A modified slippery surface setup with optomotor stimulation and electrical monitoring of tarsal contact

A modified and improved setup based on Epstein and Graham [Epstein S, Graham D. Behaviour and motor output of stick insects walking on a slippery surface. I. Forward walking. J Exp Biol 1983;105: 215-29] to study straight and curve walking in the stick insect was developed and applications for its use are described. The animal is fixed on a balsa stick and walks freely on a slippery surface created with a thin film of a glycerin/water solution on a black, Ni-coated, polished brass plate. The glycerine/water ratio controls the viscosity of the lubricant and thereby the forces necessary to move the legs of the stick insect. A small amount of NaCl is added to ensure electric conductivity. Walking is induced through an optomotor stimulus given by two stripe-projectors producing rotatory and translatory stimuli to influence walking direction. The walking pattern is monitored in two ways: (1) tarsal contact with the slippery surface is measured electrically using a lock-in-amplifier. The tarsal contact signal allows correlation with the activity in different muscles of the stick insect leg recorded with EMG electrodes; (2) leg kinematics in the horizontal plane is monitored using synchronized high speed video. This setup allows us to determine the coupling of activity in different leg muscles to either swing or stance phase during straight and curve walking in the intact animal or the reduced single-leg preparation with a high time resolution.

Natural neural output that produces highly variable locomotory movements

We recorded fast extensor tibiae motor neuron activity during single-legged treadmill walking in the stick insect, Carausius morosus. We used this activity to stimulate the extensor muscle motor nerve, observed the resulting extensor muscle contractions under isotonic conditions, and quantified these contractions with a variety of measures. Extensor contractions induced in this manner were highly variable, with contraction measures having SDs of 12 to 51%, and ranges of 82 to 275%, when expressed as percentages of the means, an unexpectedly wide range for a locomotory pattern. Searches for correlations among the contraction measures showed that, in general, this high variability is not reduced by contraction measure covariation. Comparing responses (to identical input) across animals showed that extensor muscles from different animals generally significantly differed from one another. However, correlation analyses on these data suggested that these differences do not indicate that multiple extensor muscle subtypes exist. Extensor muscles instead appear to belong to a single class, albeit one with high animal to animal variability. These data thus provide another well-quantified example (along with Aplysia feeding) of a repetitive but highly variable motor pattern (in contrast to the high rhythmicity and stereotypy present in most other well-quantified repetitive motor patterns). We suggest this high variability could be an adaptive combination of locomotion, active sensing, and crypsis arising from the relatively low demand for locomotion in Carausius behavior, the highly fragmented environment the animal inhabits, and its need to avoid predatory attention.

Kinematics and motor activity during tethered walking and turning in the cockroach, Blaberus discoidalis

When insects turn from walking straight, their legs have to follow different motor patterns. In order to examine such pattern change precisely, we stimulated single antenna of an insect, thereby initiating its turning behavior, tethered over a lightly oiled glass plate. The resulting behavior included asymmetrical movements of prothoracic and mesothoracic legs. The mesothoracic leg on the inside of the turn (in the apparent direction of turning) extended the coxa-trochanter and femur-tibia joints during swing rather than during stance as in walking, while the outside mesothoracic leg kept a slow walking pattern. Electromyograms in mesothoracic legs revealed consistent changes in the motor neuron activity controlling extension of the coxa-trochanter and femur-tibia joints. In tethered walking, depressor trochanter activity consistently preceded slow extensor tibia activity. This pattern was reversed in the inside mesothoracic leg during turning. Also for turning, extensor and depressor motor neurons of the inside legs were activated in swing phase instead of stance. Turning was also examined in free ranging animals. Although more variable, some trials resembled the pattern generated by tethered animals. The distinct inter-joint and inter-leg coordination between tethered turning and walking, therefore, provides a good model to further study the neural control of changing locomotion patterns.

Sensory control and organization of neural networks mediating coordination of multisegmental organs for locomotion

It is well established that locomotor patterns result from the interaction between central pattern generating networks in the nervous system, local feedback from sensory neurons about movements and forces generated in the locomotor organs, and coordinating signals from neighboring segments or appendages. This review addresses the issue of how the movements of multi-segmented locomotor organs are coordinated and provides an overview of recent advances in understanding sensory control and the internal organization of central pattern generating networks that operate multi-segmented locomotor organs, such as a walking leg. Findings from the stick insect and the cat are compared and discussed in relation to new findings on the lamprey swimming network. These findings support the notion that common schemes of sensory feedback are used for generating walking and that central neural networks controlling multi-segmented locomotor organs generally encompass multiple central pattern generating networks that correspond with the segmental structure of the locomotor organ.

Intersegmental coordination of walking movements in stick insects

Locomotion requires the coordination of movements across body segments, which in walking animals is expressed as gaits. We studied the underlying neural mechanisms of this coordination in a semi-intact walking preparation of the stick insect Carausius morosus. During walking of a single front leg on a treadmill, leg motoneuron (MN) activity tonically increased and became rhythmically modulated in the ipsilateral deafferented and deefferented mesothoracic (middle leg) ganglion. The pattern of modulation was correlated with the front leg cycle and specific for a given MN pool, although it was not consistent with functional leg movements for all MN pools. In an isolated preparation of a pair of ganglia, where one ganglion was made rhythmically active by application of pilocarpine, we found no evidence for coupling between segmental central pattern generators (CPGs) that could account for the modulation of MN activity observed in the semi-intact walking preparation. However, a third preparation provided evidence that signals from the front leg's femoral chordotonal organ (fCO) influenced activity of ipsilateral MNs in the adjacent mesothoracic ganglion. These intersegmental signals could be partially responsible for the observed MN activity modulation during front leg walking. While afferent signals from a single walking front leg modulate the activity of MNs in the adjacent segment, additional afferent signals, local or from contralateral or posterior legs, might be necessary to produce the functional motor pattern observed in freely walking animals.

Synaptic depression in conjunction with A-current channels promote phase constancy in a rhythmic network

In many central pattern generators, pairs of neurons maintain an approximately fixed phase despite large changes in the frequency. The mechanisms underlying phase maintenance are not clear. Previous theoretical work suggested that inhibitory synapses that show short-term depression could play a critical role in this respect. In this work we examine how the interaction between synaptic depression and the kinetics of a transient potassium (A-like) current could be advantageous for phase constancy in a rhythmic network. To demonstrate the mechanism in the context of a realistic central pattern generator, we constructed a detailed model of the crustacean pyloric circuit. The frequency of the rhythm was modified by changing the level of a ligand-activated current in one of the pyloric neurons. We examined how the time difference of firing activities between two selected neurons in this circuit is affected by synaptic depression, A-current, and a combination of the two. We tuned the parameters of the model such that with synaptic depression alone, or A-current alone, phase was not maintained between these two neurons. However, when these two components came together, they acted synergistically to maintain the phase across a wide range of cycle periods. This suggests that synaptic depression may be necessary to allow an A-current to delay a postsynaptic neuron in a frequency-dependent manner, such that phase invariance is ensured.

Dynamic simulation of insect walking

Insect walking relies on a complex interaction between the environment, body segments, muscles and the nervous system. For the stick insect in particular, previous investigations have highlighted the role of specific sensory signals in the timing of activity of central neural networks driving the individual leg joints. The objective of the current study was to relate specific sensory and neuronal mechanisms, known from experiments on reduced preparations, to the generation of the natural sequence of events forming the step cycle in a single leg. We have done this by simulating a dynamic 3D-biomechanical model of the stick insect coupled to a reduced model of the neural control system, incorporating only the mechanisms under study. The neural system sends muscle activation levels to the biomechanical system, which in turn provides correctly timed propriosensory signals back to the neural model. The first simulations were designed to test if the currently known mechanisms would be sufficient to explain the coordinated activation of the different leg muscles in the middle leg. Two experimental situations were mimicked: restricted stepping where only the coxa-trochanteral joint and the femur-tibia joint were free to move, and the unrestricted single leg movements on a friction-free surface. The first of these experimental situations is in fact similar to the preparation used in gathering much of the detailed knowledge on sensory and neuronal mechanisms. The simulations show that the mechanisms included can indeed account for the entire step cycle in both situations. The second aim was to test to what extent the same sensory and neuronal mechanisms would be adequate also for controlling the front and hind legs, despite the large differences in both leg morphology and kinematic patterns. The simulations show that front leg stepping can be generated by basically the same mechanisms while the hind leg control requires some reorganization. The simulations suggest that the influence from the femoral chordotonal organs on the network controlling levation-depression may have a reversed effect in the hind legs as compared to the middle and front legs. This, and other predictions from the model will have to be confirmed by additional experiments.

Load sensing and control of posture and locomotion

This article reviews recent findings on how forces are detected by sense organs of insect legs and how this information is integrated in control of posture and walking. These experiments have focused upon campaniform sensilla, receptors that detect forces as strains in the exoskeleton, and include studies of sensory discharges in freely moving animals and intracellular characterization of connectivity of afferent inputs in the central nervous system. These findings provide insights into how campaniform sensilla can contribute to the adjustment of motor outputs to changes in load. In this review we discuss (1) anatomy of the receptors and their activities in freely moving insects, (2) mechanisms by which inputs are incorporated into motor outputs and (3) the integration of sensory signals of diverse modalities. The discharges of some groups of receptors can encode body load when standing. Responses are also correlated with muscle-generated forces during specific times in walking. These activities can enhance motor outputs through reflexes and can affect the timing of motoneuron firing through inputs to pattern generating interneurons. Flexibility in the system is also provided by interactions of afferent inputs at several levels. These mechanisms can contribute to the adaptability of insect locomotion to diverse terrains and environments.

Signals From Load Sensors Underlie Interjoint Coordination During Stepping Movements of the Stick Insect Leg

During stance and swing phase of a walking stick insect, the retractor coxae (RetCx) and protractor coxae (ProCx) motoneurons and muscles supplying the thorax-coxa (TC)-joint generate backward and forward movements of the leg. Their activity is tightly coupled to the movement of the more distal leg segments, i.e., femur, tibia, and tarsus. We used the single middle leg preparation to study how this coupling is generated. With only the distal leg segments of the middle leg being free to move, motoneuronal activity of the de-afferented and -efferented TC-joint is similarly coupled to leg stepping. RetCx motoneurons are active during stance and ProCx motoneurons during swing. We studied whether sensory signals are involved in this coordination of TC-joint motoneuronal activity. Ablation of the load measuring campaniform sensilla (CS) revealed that they substantially contribute to the coupling of TC-joint motoneuronal activity to leg stepping. Individually ablating trochanteral and femoral CS revealed the trochanteral CS to be necessary for establishing the coupling between leg stepping and coxal motoneuron activity. When the locomotor system was active and generated alternating bursts of activity in ProCx and RetCx motoneurons, stimulation of the CS by rearward bending of the femur in otherwise de-afferented mesothoracic ganglion terminated ongoing ProCx motoneuronal activity and initiated RetCx motoneuronal activity. We show that cuticular strain signals from the trochanteral CS play a major role in shaping TC-joint motoneuronal activity during walking and contribute to their coordination with the stepping pattern of the distal leg joints. We present a model for the sensory control of timing of motoneuronal activity in walking movements of the single middle leg.