A mathematical modeling study of inter-segmental coordination during stick insect walking

The biomechanical conditions for walking in the stick insect require a modeling approach that is based on the control of pairs of antagonistic motoneuron (MN) pools for each leg joint by independent central pattern generators (CPGs). Each CPG controls a pair of antagonistic MN pools. Furthermore, specific sensory feedback signals play an important role in the control of single leg movement and in the generation of inter-leg coordination or the interplay between both tasks. Currently, however, no mathematical model exists that provides a theoretical approach to understanding the generation of coordinated locomotion in such a multi-legged locomotor system. In the present study, I created such a theoretical model for the stick insect walking system, which describes the MN activity of a single forward stepping middle leg and helps to explain the neuronal mechanisms underlying coordinating information transfer between ipsilateral legs. In this model, CPGs that belong to the same leg, as well as those belonging to different legs, are connected by specific sensory feedback pathways that convey information about movements and forces generated during locomotion. The model emphasizes the importance of sensory feedback, which is used by the central nervous system to enhance weak excitatory and inhibitory synaptic connections from front to rear between the three thorax-coxa-joint CPGs. Thereby the sensory feedback activates caudal pattern generation networks and helps to coordinate leg movements by generating in-phase and out-of-phase thoracic MN activity.     

Behaviour-based modelling of hexapod locomotion: linking biology and technical application

Walking in insects and most six-legged robots requires simultaneous control of up to 18 joints. Moreover, the number of joints that are mechanically coupled via body and ground varies from one moment to the next, and external conditions such as friction, compliance and slope of the substrate are often unpredictable. Thus, walking behaviour requires adaptive, context-dependent control of many degrees of freedom. As a consequence, modelling legged locomotion addresses many aspects of any motor behaviour in general. Based on results from behavioural experiments on arthropods, we describe a kinematic model of hexapod walking: the distributed artificial neural network controller walknet. Conceptually, the model addresses three basic problems in legged locomotion. (I) First, coordination of several legs requires coupling between the step cycles of adjacent legs, optimising synergistic propulsion, but ensuring stability through flexible adjustment to external disturbances. A set of behaviourally derived leg coordination rules can account for decentralised generation of different gaits, and allows stable walking of the insect model as well as of a number of legged robots. (II) Second, a wide range of different leg movements must be possible, e.g. to search for foothold, grasp for objects or groom the body surface. We present a simple neural network controller that can simulate targeted swing trajectories, obstacle avoidance reflexes and cyclic searching-movements. (III) Third, control of mechanically coupled joints of the legs in stance is achieved by exploiting the physical interactions between body, legs and substrate. A local positive displacement feedback, acting on individual leg joints, transforms passive displacement of a joint into active movement, generating synergistic assistance reflexes in all mechanically coupled joints.     

A Neuro-Mechanical Model of a Single Leg Joint Highlighting the Basic Physiological Role of Fast and Slow Muscle Fibres of an Insect Muscle System

In legged animals, the muscle system has a dual function: to produce forces and torques necessary to move the limbs in a systematic way, and to maintain the body in a static position. These two functions are performed by the contribution of specialized motor units, i.e. motoneurons driving sets of specialized muscle fibres. With reference to their overall contraction and metabolic properties they are called fast and slow muscle fibres and can be found ubiquitously in skeletal muscles. Both fibre types are active during stepping, but only the slow ones maintain the posture of the body. From these findings, the general hypothesis on a functional segregation between both fibre types and their neuronal control has arisen. Earlier muscle models did not fully take this aspect into account. They either focused on certain aspects of muscular function or were developed to describe specific behaviours only. By contrast, our neuro-mechanical model is more general as it allows functionally to differentiate between static and dynamic aspects of movement control. It does so by including both muscle fibre types and separate motoneuron drives. Our model helps to gain a deeper insight into how the nervous system might combine neuronal control of locomotion and posture. It predicts that (1) positioning the leg at a specific retraction angle in steady state is most likely due to the extent of recruitment of slow muscle fibres and not to the force developed in the individual fibres of the antagonistic muscles; (2) the fast muscle fibres of antagonistic muscles contract alternately during stepping, while co-contraction of the slow muscle fibres takes place during steady state; (3) there are several possible ways of transition between movement and steady state of the leg achieved by varying the time course of recruitment of the fibres in the participating muscles.     

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.     

The investigation of locomotor activity control system in humans under the air-stepping conditions during passive and voluntary leg movements

The degree of activation of the central stepping program during passive leg movement was studied in healthy subjects under unloading conditions; the excitability of spinal motoneurons was studied during passive and voluntary stepping movements. Passive stepping movements with characteristics maximally close to those during voluntary stepping were accomplished by the experimenter. The bursts of muscular activity during voluntary and imposed stepping movements were compared. In addition, the influence on the leg movement of artificially created loading onto the foot was studied. The excitability of spinal motoneurons was estimated by the amplitude of modulation of the m. soleus H reflex. Changes in the H reflex (Hoffmann’s reflex) after fixation of the knee and hip joints were also studied. In most subjects, passive movements were accompanied by bursts of electromyographic (EMG) activity in the hip muscles (sometimes in shank muscles); the timing of the EMG burst during the step cycle coincided with the burst’s timing during voluntary stepping. In many cases, the bursts in EMG activity exceeded the activity of homonymous muscles during voluntary stepping. Simulation of foot loading influenced significantly the distal part of the moving extremity during both voluntary and passive movements, which was expressed in the appearance of movements in the ankle joint and an increase in the phasic EMG activity of the shank muscles. The excitability of motoneurons during passive movements was higher than during voluntary movements. Changes and modulation of the H reflex throughout the step cycle were similar without restriction of joint mobility and without hip joint mobility. Fixation of the knee joint was of great importance. It is supposed that imposed movements activate the same mechanisms of rhythm generation as supraspinal commands during voluntary movements. During passive movements, presynaptic inhibition depends mostly on the afferent influences from the moving leg rather than on the central commands. Under the conditions of “air-stepping,” the afferent influences from the foot pressure receptors are likely to interact actively with the central program of stepping and to determine the final activity pattern irrespective of the movement type (voluntary or passive).     

System identification of muscle–joint interactions of the cat hind limb during locomotion

Neurophysiological experiments in walking cats have shown that a number of neural control mechanisms are involved in regulating the movements of the hind legs during locomotion. It is experimentally hard to isolate individual mechanisms without disrupting the natural walking pattern and we therefore introduce a different approach where we use a model to identify what control is necessary to maintain stability in the musculo-skeletal system. We developed a computer simulation model of the cat hind legs in which the movements of each leg are produced by eight limb muscles whose activations follow a centrally generated pattern with no proprioceptive feedback. All linear transfer functions, from each muscle activation to each joint angle, were identified using the response of the joint angle to an impulse in the muscle activation at 65 postures of the leg covering the entire step cycle. We analyzed the sensitivity and stability of each muscle action on the joint angles by studying the gain and pole plots of these transfer functions. We found that the actions of most of the hindlimb muscles display inherent stability during stepping, even without the involvement of any proprioceptive feedback mechanisms, and that those musculo-skeletal systems are acting in a critically damped manner, enabling them to react quickly without unnecessary oscillations. We also found that during the late swing, the activity of the posterior biceps/semitendinosus (PB/ST) muscles causes the joints to be unstable. In addition, vastus lateralis (VL), tibialis anterior (TA) and sartorius (SAT) muscle-joint systems were found to be unstable during the late stance phase, and we conclude that those muscles require neuronal feedback to maintain stable stepping, especially during late swing and late stance phases. Moreover, we could see a clear distinction in the pole distribution (along the step cycle) for the systems related to the ankle joint from that of the other two joints, hip or knee. A similar pattern, i.e., a pattern in which the poles were scattered over the s-plane with no clear clustering according to the phase of the leg position, could be seen in the systems related to soleus (SOL) and TA muscles which would indicate that these muscles depend on neural control mechanisms, which may involve supraspinal structures, over the whole step cycle.     

Legged insects select the optimal locomotor pattern based on the energetic cost

 The gait transition in legged animals has attracted many researchers, and its relation to metabolic cost and mechanical work has been discussed in recent decades. We assumed that the energetic cost during locomotion is given by the sum of positive mechanical work and the heat energy loss that is proportional to the square of joint torque and examined the optimal locomotor pattern based on the energetic cost in a simple dynamical model of a hexapod by computer simulations. The obtained results well agree with characteristics in the locomotor patterns in legged animals; for example, the leg protraction time, step length, and the metabolic cost of transport are almost constant for many velocities, the leg cycling period decreases with velocity, and the energetic cost of locomotion induced by carrying loads linearly increases with mass loaded. This correspondence of the results of calculation to experimental results suggest that the heat energy loss for torque generation is proportional to the square of the torque during locomotion, and that the locomotor pattern in legged animals is highly optimized based on the energetic cost. Received: 22 December 1998 / Accepted: 14 April 2000     

Convergent evolution and locomotion through complex terrain by insects, vertebrates and robots

Arthropods are the most successful members of the animal kingdom largely because of their ability to move efficiently through a range of environments. Their agility has not been lost on engineers seeking to design agile legged robots. However, one cannot simply copy mechanical and neural control systems from insects into robotic designs. Rather one has to select the properties that are critical for specific behaviors that the engineer wants to capture in a particular robot. Convergent evolution provides an important clue to the properties of legged locomotion that are critical for success. Arthropods and vertebrates evolved legged locomotion independently. Nevertheless, many neural control properties and mechanical schemes are remarkably similar. Here we describe three aspects of legged locomotion that are found in both insects and vertebrates and that provide enhancements to legged robots. They are leg specialization, body flexion and the development of a complex head structure. Although these properties are commonly seen in legged animals, most robotic vehicles have similar legs throughout, rigid bodies and rudimentary sensors on what would be considered the head region. We describe these convergent properties in the context of robots that we developed to capture the agility of insects in moving through complex terrain.     

The investigation of control mechanisms of stepping rhythm in human in the air-stepping conditions during passive and voluntary leg movements

In unloading condition the degree of activation of the central stepping program was investigated during passive leg movements in healthy subjects, as well as the excitability of spinal motoneurons during passive and voluntary stepping movement. Passive stepping movements with characteristics maximally approximated to those during voluntary stepping were accomplished by experimenter. The comparison of the muscle activity bursts during voluntary and imposed movements was made. In addition to that the influence of artificially created loading onto the foot to the leg movement characteristics was analyzed. Spinal motoneuron excitability was estimated by means of evaluation of amplitude modulation of the soleus H-reflex. The changes of H-reflexes under the fixation of knee or hip joints were also studied. In majority of subjects the passive movements were accompanied by bursts of EMG activity of hip muscles (and sometimes of knee muscles), which timing during step cycle was coincided with burst timing of voluntary step cycle. In many cases the bursts of EMG activity during passive movements exceeded activity in homonymous muscles during voluntary stepping. The foot loading imitation exerted essential influence on distal parts of moving extremity during voluntary as well passive movements, that was expressed in the appearance of movements in the ankle joint and accompanied by emergence and increasing of phasic EMG activity of shank muscles. The excitability of motoneurons during passive movements was greater then during voluntary ones. The changes and modulation of H-reflex throughout the step cycle without restriction of joint mobility and during exclusion of hip joint mobility were similar. The knee joint fixation exerted the greater influence. It is supposed that imposed movements activate the same mechanisms of rhythm generation as a supraspinal commands during voluntary movements. In the conditions of passive movements the presynaptic inhibition depend on afferent influences from moving leg in the most degree then on central commands. It seems that afferent inputs from pressure receptors of foot in the condition of "air-stepping" actively interact with central program of stepping and, irrespective of type of the performing movements (voluntary or passive), form the final pattern activity.     

Self-organized control of bipedal locomotion by neural oscillators in unpredictable environment

A new principle of sensorimotor control of legged locomotion in an unpredictable environment is proposed on the basis of neurophysiological knowledge and a theory of nonlinear dynamics. Stable and flexible locomotion is realized as a global limit cycle generated by a global entrainment between the rhythmic activities of a nervous system composed of coupled neural oscillators and the rhythmic movements of a musculo-skeletal system including interaction with its environment. Coordinated movements are generated not by slaving to an explicit representation of the precise trajectories of the movement of each part but by dynamic interactions among the nervous system, the musculo-skeletal system and the environment. The performance of a bipedal model based on the above principle was investigated by computer simulation. Walking movements stable to mechanical perturbations and to environmental changes were obtained. Moreover, the model generated not only the walking movement but also the running movement by changing a single parameter nonspecific to the movement. The transitions between the gait patterns occurred with hysteresis.     

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.     

Biomimetic Design and Optimal Swing of a Hexapod Robot Leg

Biological inspiration has spawned a wealth of solutions to both mechanical design and control schemes in the efforts to develop agile legged machines. This paper presents a compliant leg mechanism for a small six-legged robot, HITCR-ll, based on abstracted anatomy from insect legs. Kinematic structure, relative proportion of leg segment lengths and actuation system were analyzed in consideration of anatomical structure as well as muscle system of insect legs and desired mobility. A spring based passive compliance mechanism inspired by musculoskeletal structures of biological systems was integrated into distal segment of the leg to soften foot impact on touchdown. In addition, an efficient locomotion planner capable of generating natural movements for the legs during swing phase was proposed. The problem of leg swing was formulated as an optimal control procedure that satisfies a series of locomotion task terms while minimizing a biologically-based objective function, which was solved by a Gauss Pseudospectral Method （GPM） based numerical technique. We applied this swing generation algorithm to both a simulation platform and a robot prototype. Results show that the proposed leg structure and swing planner are able to successfully perform effective swing movements on rugged terrains.     

Influence of vibration on the excitability of spinal α-motoneurons under static conditions and during evoked stepping in humans

The excitability of spinal α-motoneurons in healthy humans was investigated with vibrostimulation (20–60 Hz) applied to different groups of muscles both under stationary conditions and during vibration-evoked stepping movements with leg suspension. In 15 subjects, the H-reflex amplitude was compared under the conditions of vibration of the left leg quadriceps femoris (QFM) or biceps femoris (BFM) muscle, as well as under the conditions of vibration of the contralateral, motionless leg QFM muscle in three spatial positions of the body: upright, supine, and lying on the side with the left leg suspended. Under dynamic conditions, the H-reflex value was compared during evoked and voluntary steppings at eight intervals of the step cycle. In all body positions, the vibration of each ipsilateral leg muscle caused a significant H-reflex suppression, this suppression being more prominent under the air-stepping conditions. The vibration of the contralateral leg QFM had weak influence on the H-reflex amplitude. In seven subjects, the vibration of the ipsilateral and contralateral leg muscles generated stepping movements. During vibration-evoked air-stepping, the H-reflex had different amplitudes in different phases of the step cycle. At the same time, the differences between responses under voluntary and involuntary stepping conditions were revealed only in the step cycle phase corresponding to the stance phase. Thus, the different degrees of the H-reflex suppression by vibration in different spatial positions of the body seem to depend on the summary afferent inflows to the spinal cord interneurons involved in the regulation of locomotion and posture. Apparently, an increase in the spinal cord neuronal excitability, which is necessary for activating locomotor automatism under the leg unloading conditions, occurs during evoked air-stepping in the swing phase.     

A modular artificial neural net for controlling a six-legged walking system

 A system that controls the leg movement of an animal or a robot walking over irregular ground has to ensure stable support for the body and at the same time propel it forward. To do so, it has to react adaptively to unpredictable features of the environment. As part of our study of the underlying mechanisms, we present here a model for the control of the leg movement of a 6-legged walking system. The model is based on biological data obtained from the stick insect. It represents a combined treatment of realistic kinematics and biologically motivated, adaptive gait generation. The model extends a previous algorithmic model by substituting simple networks of artificial neurons for the algorithms previously used to control leg state and interleg coordination. Each system controlling an individual leg consists of three subnets. A hierarchically superior net contains two sensory and two ‘premotor’ units; it rhythmically suppresses the output of one or the other of the two subordinate nets. These are continuously active. They might be called the ‘swing module’ and the ‘stance module’ because they are responsible for controlling the swing (return stroke) and the stance (power stroke) movements, respectively. The swing module consists of three motor units and seven sensory units. It can produce appropriate return stroke movements for a broad range of initial and final positions, can cope with mechanical disturbances of the leg movement, and is able to react to an obstacle which hinders the normal performance of the swing movement. The complete model is able to walk at different speeds over irregular surfaces. The control system rapidly reestablishes a stable gait when the movement of the legs is disturbed. Received: 13 July 1994/Accepted in revised form: 15 November 1994     

Jendrassik’s maneuver creates conditions for triggering involuntary stepping

The influence of the Jendrassik maneuver on the generation of the locomotor rhythmicity was studied under conditions of the “suspension” of legs in a horizontal plane. It was shown that during Jendrassik’s maneuver, passive movements of one limb trigger stepping with the participation of both limbs. The Jendrassik’s maneuver also notably facilitates the vibration-induced locomotion. The kinematics of the evoked stepping movements did not differ from the kinematics of the voluntary “air-stepping,” reciprocal electromyographic activity being observed in antagonistic muscles. It seems likely that the generation of cyclic movements during the Jendrassik maneuver occurs due to the activation of the same stepping automatism as in normal stepping. The experimental results suggest that an increase in the level of tonic readiness of the tonogenic CNS structures, which participate in realization of the locomotor program, is a necessary condition for the activation of the spinal mechanisms of the stepping generation.     

Are interlimb interactions disturbed in patients with Parkinson’s disease? A study under unloading conditions

During natural human locomotion, neural connections are activated that are typical of regulation of the quadrupedal walking. The interaction between the neural networks generating rhythmic movements of the upper and lower limbs depends on tonic state of each of these networks regulated by motor signals from the brain. Distortion of these signals in patients with Parkinson’s disease (PD) may lead to disruption of the interlimb interactions. We examined the effect of movements of the limbs of one girdle on the parameters of the motor activity of another limb girdle at their joint cyclic movements under the conditions of arm and leg unloading in 17 patients with PD and 16 healthy subjects. We have shown that, in patients, the effect of voluntary and passive movements of arms, as well as the active movement of the distal parts of arms, on the voluntary movement of legs is weak, while in healthy subjects, the effect of arm movements on the parameters of voluntary stepping is significant. The effect of arm movements on the activation of the involuntary stepping by vibrational stimulation of-legs in patients was absent, while in healthy subjects, the motor activity of arms increased the possibility of involuntary rhythmic movements activation. Differences in the effect of leg movements on the rhythmic movements of arms were found in both patients and healthy subjects. The interlimb interaction appeared after drug administration. However, the effect of the drug was not sufficient for the recovery of normal state of the neural networks in patients. In PD patients, neural networks generating stepping rhythm have an increased tonic activity, which prevents the activation and appearance of involuntary rhythmic movements facilitating the effects of arms on legs.     

Bio-Inspired Controller for a Robot Cheetah with a Neural Mechanism Controlling Leg Muscles

The realization of a high-speed running robot is one of the most challenging problems in developing legged robots.The excellent performance of cheetahs provides inspiration for the control and mechanical design of such robots.This paper presents a three-dimensional model of a cheetah that predicts the locomotory behaviors of a running cheetah.Applying biological knowledge of the neural mechanism,we control the muscle flexion and extension during the stance phase,and control the positions of the joints in the flight phase via a PD controller to minimize complexity.The proposed control strategy is shown to achieve similar locomotion of a real cheetah.The simulation realizes good biological properties,such as the leg retraction,ground reaction force,and spring-like leg behavior.The stable bounding results show the promise of the controller in high-speed locomotion.The model can reach 2.7 m·s- 1 as the highest speed,and can accelerate from 0 to 1.5 m·s -1 in one stride cycle.A mechanical structure based on this simulation is designed to demonstrate the control approach,and the most recently developed hindlimb controlled by the proposed controller is presented in swinging-leg experiments and jump-force experiments.     

Voluntary stepping behavior under single- and dual-task conditions in chronic stroke survivors: A comparison between the involved and uninvolved legs

ObjectiveIf balance is lost, quick step execution can prevent falls. Research has shown that speed of voluntary stepping was able to predict future falls in old adults. The aim of the study was to investigate voluntary stepping behavior, as well as to compare timing and leg push-off force–time relation parameters of involved and uninvolved legs in stroke survivors during single- and dual-task conditions. We also aimed to compare timing and leg push-off force–time relation parameters between stroke survivors and healthy individuals in both task conditions.MethodsTen stroke survivors performed a voluntary step execution test with their involved and uninvolved legs under two conditions: while focusing only on the stepping task and while a separate attention-demanding task was performed simultaneously. Temporal parameters related to the step time were measured including the duration of the step initiation phase, the preparatory phase, the swing phase, and the total step time. In addition, force–time parameters representing the push-off power during stepping were calculated from ground reaction data and compared with 10 healthy controls.ResultsThe involved legs of stroke survivors had a significantly slower stepping time than uninvolved legs due to increased swing phase duration during both single- and dual-task conditions. For dual compared to single task, the stepping time increased significantly due to a significant increase in the duration of step initiation. In general, the force time parameters were significantly different in both legs of stroke survivors as compared to healthy controls, with no significant effect of dual compared with single-task conditions in both groups.ConclusionsThe inability of stroke survivors to swing the involved leg quickly may be the most significant factor contributing to the large number of falls to the paretic side. The results suggest that stroke survivors were unable to rapidly produce muscle force in fast actions. This may be the mechanism of delayed execution of a fast step when balance is lost, thus increasing the likelihood of falls in stroke survivors.     

The influence of vibration on spinal alpha-motoneurons excitability in static conditions and during evoked stepping in human

In healthy human the excitability of spinal alpha-motoneurons under application of vibrostimulation (20-60 Hz) to different leg muscles was investigated both in stationary condition and during stepping movements caused by vibration in the condition of suspended leg. In 15 subjects the amplitude of H-reflex were compared under vibration of rectus femoris (RF) and biceps femoris (BF) muscles of left leg as well during vibration of rectus femoris of contralateral, motionless leg in three spatial positions: upright, supine and on right side of body with suspended left leg. In dynamic conditions the amount of H-reflex was compared during evoked and voluntary stepping at 8 intervals of step cycle. In all body positions the vibration of each ipsilateral leg muscles caused significant suppression of H-reflex, this suppression was more prominent in the air-stepping conditions. The vibration of contralateral leg RF muscle had a weak influence on the amplitude of H-reflex. In 7 subjects the muscle vibration of ipsilateral and contralateral legs generated stepping movements. During evoked "air-stepping" H-reflex had different amplitudes in different phases of step cycle. At the same time the differences between responses under voluntary and non-voluntary stepping were revealed only in stance phase. Thus, different degree of H-reflex suppression by vibration under different body position in space depends on, it seems to be, from summary afferent inflows to spinal cord interneurons, which participate in regulation of posture and locomotion. Seemingly, the increasing of spinal cord neurons excitability occurs under involuntary air-stepping in swing phase, which is necessary for activation of locomotor automatism under unloading leg conditions.     

Distributed mechanical feedback in arthropods and robots simplifies control of rapid running on challenging terrain

Terrestrial arthropods negotiate demanding terrain more effectively than any search-and-rescue robot. Slow, precise stepping using distributed neural feedback is one strategy for dealing with challenging terrain. Alternatively, arthropods could simplify control on demanding surfaces by rapid running that uses kinetic energy to bridge gaps between footholds. We demonstrate that this is achieved using distributed mechanical feedback, resulting from passive contacts along legs positioned by pre-programmed trajectories favorable to their attachment mechanisms. We used wire-mesh experimental surfaces to determine how a decrease in foothold probability affects speed and stability. Spiders and insects attained high running speeds on simulated terrain with 90% of the surface contact area removed. Cockroaches maintained high speeds even with their tarsi ablated, by generating horizontally oriented leg trajectories. Spiders with more vertically directed leg placement used leg spines, which resulted in more effective distributed contact by interlocking with asperities during leg extension, but collapsing during flexion, preventing entanglement. Ghost crabs, which naturally lack leg spines, showed increased mobility on wire mesh after the addition of artificial, collapsible spines. A bioinspired robot, RHex, was redesigned to maximize effective distributed leg contact, by changing leg orientation and adding directional spines. These changes improved RHex's agility on challenging surfaces without adding sensors or changing the control system.