Control of structural redundancy from the head to trunk in the human upright standing revealed using a data-driven approach.

The human being dynamically and highly controls the head-trunk with redundant mechanical structures to maintain a stable upright standing position that is inherently unstable. The posture control strategies are also affected by the differences in the conditions of sensory inputs. However, it is unclear how the head-trunk segmental properties are altered to respond to situations that require appropriate changes in standing posture control strategies. We used a data-driven approach to conduct a multipoint measurement of head-trunk sway control in a quiet standing position with differences in the conditions of sensory inputs. Healthy young subjects with 22 accelerometers attached to their backs were evaluated for head-trunk vibration during quiet standing under two conditions: one with open eyes and one with closed eyes. The synchronization of the acceleration and the instantaneous phase was then calculated. The results showed that the synchronization of acceleration and instantaneous phase varied depending on the visual condition, and there were some continuous coherent patterns in each condition. Findings were that the structural redundancy of the head-trunk, which is multi-segmental and has a high mass ratio in the whole body, must be adjusted adaptively according to the conditions to stabilize upright standing in human-specific bipeds.

Contribution of Afferent Feedback to Adaptive Hindlimb Walking in Cats: A Neuromusculoskeletal Modeling Study.

Mammalian locomotion is generated by central pattern generators (CPGs) in the spinal cord, which produce alternating flexor and extensor activities controlling the locomotor movements of each limb. Afferent feedback signals from the limbs are integrated by the CPGs to provide adaptive control of locomotion. Responses of CPG-generated neural activity to afferent feedback stimulation have been previously studied during fictive locomotion in immobilized cats. Yet, locomotion in awake, behaving animals involves dynamic interactions between central neuronal circuits, afferent feedback, musculoskeletal system, and environment. To study these complex interactions, we developed a model simulating interactions between a half-center CPG and the musculoskeletal system of a cat hindlimb. Then, we analyzed the role of afferent feedback in the locomotor adaptation from a dynamic viewpoint using the methods of dynamical systems theory and nullcline analysis. Our model reproduced limb movements during regular cat walking as well as adaptive changes of these movements when the foot steps into a hole. The model generates important insights into the mechanism for adaptive locomotion resulting from dynamic interactions between the CPG-based neural circuits, the musculoskeletal system, and the environment.

Quantitative evaluation of posture control in rats with inferior olive lesions.

Impairment of inferior olivary neurons (IONs) affects whole-body movements and results in abnormal gait and posture. Because IONs are activated by unpredicted motion rather than regular body movements, the postural dysfunction caused by ION lesions is expected to involve factors other than simple loss of feedback control. In this study, we measured the postural movements of rats with pharmacological ION lesions (IO rats) trained to stand on their hindlimbs. The coordination of body segments as well as the distribution and frequency characteristics of center of mass (COM) motion were analyzed. We determined that the lesion altered the peak properties of the power spectrum density of the COM, whereas changes in coordination and COM distribution were minor. To investigate how the observed properties reflected changes in the control system, we constructed a mathematical model of the standing rats and quantitatively identified the control system. We found an increase in linear proportional control and a decrease in differential and nonlinear control in IO rats compared with intact rats. The dystonia-like changes in body stiffness explain the nature of the linear proportional and differential control, and a disorder in the internal model is one possible cause of the decrease in nonlinear control.

Fast and Slow Adaptations of Interlimb Coordination via Reflex and Learning During Split-Belt Treadmill Walking of a Quadruped Robot.

Interlimb coordination plays an important role in adaptive locomotion of humans and animals. This has been investigated using a split-belt treadmill, which imposes different speeds on the two sides of the body. Two types of adaptation have been identified, namely fast and slow adaptations. Fast adaptation induces asymmetric interlimb coordination soon after a change of the treadmill speed condition from same speed for both belts to different speeds. In contrast, slow adaptation slowly reduces the asymmetry after fast adaptation. It has been suggested that these adaptations are primarily achieved by the spinal reflex and cerebellar learning. However, these adaptation mechanisms remain unclear due to the complicated dynamics of locomotion. In our previous work, we developed a locomotion control system for a biped robot based on the spinal reflex and cerebellar learning. We reproduced the fast and slow adaptations observed in humans during split-belt treadmill walking of the biped robot and clarified the adaptation mechanisms from a dynamic viewpoint by focusing on the changes in the relative positions between the center of mass and foot stance induced by reflex and learning. In this study, we modified the control system for application to a quadruped robot. We demonstrate that even though the basic gait pattern of our robot is different from that of general quadrupeds (due to limitations of the robot experiment), fast and slow adaptations that are similar to those of quadrupeds appear during split-belt treadmill walking of the quadruped robot. Furthermore, we clarify these adaptation mechanisms from a dynamic viewpoint, as done in our previous work. These results will increase the understanding of how fast and slow adaptations are generated in quadrupedal locomotion on a split-belt treadmill through body dynamics and sensorimotor integration via the spinal reflex and cerebellar learning and help the development of control strategies for adaptive locomotion of quadruped robots.

Dynamic localization of αB-crystallin at the microtubule cytoskeleton network in beating heart cells.

αB-crystallin is highly expressed in the heart and slow skeletal muscle; however, the roles of αB-crystallin in the muscle are obscure. Previously, we showed that αB-crystallin localizes at the sarcomere Z-bands, corresponding to the focal adhesions of cultured cells. In myoblast cells, αB-crystallin completely colocalizes with microtubules and maintains cell shape and adhesion. In this study, we show that in beating cardiomyocytes α-tubulin and αB-crystallin colocalize at the I- and Z-bands of the myocardium, where it may function as a molecular chaperone for tubulin/microtubules. Fluorescence recovery after photobleaching (FRAP) analysis revealed that the striated patterns of GFP-αB-crystallin fluorescence recovered quickly at 37°C. FRAP mobility assay also showed αB-crystallin to be associated with nocodazole-treated free tubulin dimers but not with taxol-treated microtubules. The interaction of αB-crystallin and free tubulin was further confirmed by immunoprecipitation and microtubule sedimentation assay in the presence of 1-100 µM calcium, which destabilizes microtubules. Förster resonance energy transfer analysis showed that αB-crystallin and tubulin were at 1-10 nm apart from each other in the presence of colchicine. These results suggested that αB-crystallin may play an essential role in microtubule dynamics by maintaining free tubulin in striated muscles, such as the soleus or cardiac muscles.

Self-reorganization of neuronal activation patterns in the cortex under brain-machine interface and neural operant conditioning.

In this review, we describe recent experimental observations and model simulations in the research subject of brain-machine interface (BMI). Studies of BMIs have applied decoding models to extract functional characteristics of the recorded neurons, and some of these have more focused on adaptation based on neural operant conditioning. Under a closed loop feedback with the environment through BMIs, neuronal activities are forced to interact directly with the environment. These studies have shown that the neuron ensembles self-reorganized their activity patterns and completed a transition to adaptive state within a short time scale. Based on these observations, we discuss how the brain could identify the target neurons directly interacting with the environment and determine in which direction the activities of those neurons should be changed for adaptation. For adaptation over a short time scale, the changes of neuron ensemble activities seem to be restricted by the intrinsic correlation structure of the neuronal network (intrinsic manifold). On the other hand, for adaptation over a long time scale, modifications to the synaptic connections enable the neuronal network to generate a novel activation pattern required by BMI (extension of the intrinsic manifold). Understanding of the intrinsic constraints in adaptive changes of neuronal activities will provide the basic principles of learning mechanisms in the brain and methodological clues for better performance in engineering and clinical applications of BMI.

Contribution of Phase Resetting to Adaptive Rhythm Control in Human Walking Based on the Phase Response Curves of a Neuromusculoskeletal Model.

Humans walk adaptively in varying environments by manipulating their complicated and redundant musculoskeletal system. Although the central pattern generators in the spinal cord are largely responsible for adaptive walking through sensory-motor coordination, it remains unclear what neural mechanisms determine walking adaptability. It has been reported that locomotor rhythm and phase are regulated by the production of phase shift and rhythm resetting (phase resetting) for periodic motor commands in response to sensory feedback and perturbation. While the phase resetting has been suggested to make a large contribution to adaptive walking, it has only been investigated based on fictive locomotion in decerebrate cats, and thus it remains unclear if human motor control has such a rhythm regulation mechanism during walking. In our previous work, we incorporated a phase resetting mechanism into a motor control model and demonstrated that it improves the stability and robustness of walking through forward dynamic simulations of a human musculoskeletal model. However, this did not necessarily verify that phase resetting plays a role in human motor control. In our other previous work, we used kinematic measurements of human walking to identify the phase response curve (PRC), which explains phase-dependent responses of a limit cycle oscillator to a perturbation. This revealed how human walking rhythm is regulated by perturbations. In this study, we integrated these two approaches using a physical model and identification of the PRC to examine the hypothesis that phase resetting plays a role in the control of walking rhythm in humans. More specifically, we calculated the PRC using our neuromusculoskeletal model in the same way as our previous human experiment. In particular, we compared the PRCs calculated from two different models with and without phase resetting while referring to the PRC for humans. As a result, although the PRC for the model without phase resetting did not show any characteristic shape, the PRC for the model with phase resetting showed a characteristic phase-dependent shape with trends similar to those of the PRC for humans. These results support our hypothesis and will improve our understanding of adaptive rhythm control in human walking.

Phase-Dependent Response to Afferent Stimulation During Fictive Locomotion: A Computational Modeling Study.

Central pattern generators (CPGs) in the spinal cord generate rhythmic neural activity and control locomotion in vertebrates. These CPGs operate under the control of sensory feedback that affects the generated locomotor pattern and adapt it to the animal's biomechanics and environment. Studies of the effects of afferent stimulation on fictive locomotion in immobilized cats have shown that brief stimulation of peripheral nerves can reset the ongoing locomotor rhythm. Depending on the phase of stimulation and the stimulated nerve, the applied stimulation can either shorten or prolong the current locomotor phase and the locomotor cycle. Here, we used a mathematical model of a half-center CPG to investigate the phase-dependent effects of brief stimulation applied to CPG on the CPG-generated locomotor oscillations. The CPG in the model consisted of two half-centers mutually inhibiting each other. The rhythmic activity in each half-center was based on a slowly inactivating, persistent sodium current. Brief stimulation was applied to CPG half-centers in different phases of the locomotor cycle to produce phase-dependent changes in CPG activity. The model reproduced several results from experiments on the effect of afferent stimulation of fictive locomotion in cats. The mechanisms of locomotor rhythm resetting under different conditions were analyzed using dynamic systems theory methods.

Locomotor kinematics and EMG activity during quadrupedal versus bipedal gait in the Japanese macaque.

Several qualitative features distinguish bipedal from quadrupedal locomotion in mammals. In this study we show quantitative differences between quadrupedal and bipedal gait in the Japanese monkey in terms of gait patterns, trunk/hindlimb kinematics, and electromyographic (EMG) activity, obtained from 3 macaques during treadmill walking. We predicted that as a consequence of an almost upright body axis, bipedal gait would show properties consistent with temporal and spatial optimization countering higher trunk/hindlimb loads and a less stable center of mass (CoM). A comparatively larger step width, an ~9% longer duty cycle, and ~20% increased relative duration of the double-support phase were all in line with such a strategy. Bipedal joint kinematics showed the strongest differences in proximal, and least in distal, hindlimb joint excursions compared with quadrupedal gait. Hindlimb joint coordination (cyclograms) revealed more periods of single-joint rotations during bipedal gait and predominance of proximal joints during single support. The CoM described a symmetrical, quasi-sinusoidal left/right path during bipedal gait, with an alternating shift toward the weight-supporting limb during stance. Trunk/hindlimb EMG activity was nonuniformally increased during bipedal gait, most prominently in proximal antigravity muscles during stance (up to 10-fold). Non-antigravity hindlimb EMG showed altered temporal profiles during liftoff or touchdown. Muscle coactivation was more, but muscle synergies less, frequent during bipedal gait. Together, these results show that behavioral and EMG properties of bipedal vs. quadrupedal gait are quantitatively distinct and suggest that the neural control of bipedal primate locomotion underwent specific adaptations to generate these particular behavioral features to counteract increased load and instability. NEW & NOTEWORTHY Bipedal locomotion imposes particular biomechanical constraints on motor control. In a within-species comparative study, we investigated joint kinematics and electromyographic characteristics of bipedal vs. quadrupedal treadmill locomotion in Japanese macaques. Because these features represent (to a large extent) emergent properties of the underlying neural control, they provide a comparative, behavioral, and neurophysiological framework for understanding the neural system dedicated to bipedal locomotion in this nonhuman primate, which constitutes a critical animal model for human bipedalism.

Neuromusculoskeletal model that walks and runs across a speed range with a few motor control parameter changes based on the muscle synergy hypothesis.

Humans walk and run, as well as change their gait speed, through the control of their complicated and redundant musculoskeletal system. These gaits exhibit different locomotor behaviors, such as a double-stance phase in walking and flight phase in running. The complex and redundant nature of the musculoskeletal system and the wide variation in locomotion characteristics lead us to imagine that the motor control strategies for these gaits, which remain unclear, are extremely complex and differ from one another. It has been previously proposed that muscle activations may be generated by linearly combining a small set of basic pulses produced by central pattern generators (muscle synergy hypothesis). This control scheme is simple and thought to be shared between walking and running at different speeds. Demonstrating that this control scheme can generate walking and running and change the speed is critical, as bipedal locomotion is dynamically challenging. Here, we provide such a demonstration by using a motor control model with 69 parameters developed based on the muscle synergy hypothesis. Specifically, we show that it produces both walking and running of a human musculoskeletal model by changing only seven key motor control parameters. Furthermore, we show that the model can walk and run at different speeds by changing only the same seven parameters based on the desired speed. These findings will improve our understanding of human motor control in locomotion and provide guiding principles for the control design of wearable exoskeletons and prostheses.

Gait Generation and Its Energy Efficiency Based on Rat Neuromusculoskeletal Model.

Changing gait is crucial for adaptive and smooth animal locomotion. Although it remains unclear what makes animals decide on a specific gait, energy efficiency is an important factor. It has been reported that the relationship of oxygen consumption with speed is U-shaped for each horse gait and that different gaits have different speeds at which oxygen consumption is minimized. This allows the horse to produce energy-efficient locomotion in a wide speed range by changing gait. However, the underlying mechanisms causing oxygen consumption to be U-shaped and the speeds for the minimum consumption to be different between different gaits are unclear. In the present study, we used a neuromusculoskeletal model of the rat to examine the mechanism from a dynamic viewpoint. Specifically, we constructed the musculoskeletal part of the model based on empirical anatomical data on rats and the motor control model based on the physiological concepts of the spinal central pattern generator and muscle synergy. We also incorporated the posture and speed regulation models at the levels of the brainstem and cerebellum. Our model achieved walking through forward dynamic simulation, and the simulated joint kinematics and muscle activities were compared with animal data. Our model also achieved trotting by changing only the phase difference of the muscle-synergy-based motor commands between the forelimb and hindlimb. Furthermore, the speed of each gait varied by changing only the extension phase duration and amplitude of the muscle synergy-based motor commands and the reference values for the regulation models. The relationship between cost of transport (CoT) and speed was U-shaped for both the generated walking and trotting, and the speeds for the minimum CoT were different for the two gaits, as observed in the oxygen consumption of horses. We found that the resonance property and the posture and speed regulations contributed to the CoT shape and difference in speeds for the minimum CoT. We further discussed the energy efficiency of gait based on the simulation results.

Adaptive hindlimb split-belt treadmill walking in rats by controlling basic muscle activation patterns via phase resetting.

To investigate the adaptive locomotion mechanism in animals, a split-belt treadmill has been used, which has two parallel belts to produce left-right symmetric and asymmetric environments for walking. Spinal cats walking on the treadmill have suggested the contribution of the spinal cord and associated peripheral nervous system to the adaptive locomotion. Physiological studies have shown that phase resetting of locomotor commands involving a phase shift occurs depending on the types of sensory nerves and stimulation timing, and that muscle activation patterns during walking are represented by a linear combination of a few numbers of basic temporal patterns despite the complexity of the activation patterns. Our working hypothesis was that resetting the onset timings of basic temporal patterns based on the sensory information from the leg, especially extension of hip flexors, contributes to adaptive locomotion on the split-belt treadmill. Our hypothesis was examined by conducting forward dynamic simulations using a neuromusculoskeletal model of a rat walking on a split-belt treadmill with its hindlimbs and by comparing the simulated motions with the measured motions of rats.

Alteration of gait parameters in a mouse model of surgically induced knee osteoarthritis.

PURPOSE: Joint pain is the most common symptom of osteoarthritis (OA); however, its mechanism remains unclarified. The present study investigated hindlimb motion during locomotion on the treadmill using a three-dimensional (3D) motion analysis system with high-speed cameras to evaluate whether this method can be used as an indication of joint pain in a mouse model of surgically induced OA. METHODS: We resected the medial meniscus and medial collateral ligament in 8-week old C57BL/6 male mice and performed locomotion recording 6 months post-operatively. Additionally, we performed the same recording after oral administration of the selective cyclooxygenase-2 inhibitor to determine whether alteration of the parameters were associated with joint pain. RESULTS: OA development, characterized by cartilage degeneration and osteophyte formation, was markedly enhanced in the OA group. There was no significant difference between the sham and OA groups in basic gait parameters, including stance duration, swing duration and gait cycle. However, when we divided the gait cycle into four phases and calculated the joint ranges of motion in each phase, the range of motion of the knee joint during the stepping-in phase and the swing duration were significantly decreased in the OA group. These significant differences between the sham and OA groups were diminished by the oral administration of a selective cyclooxygenase-2 inhibitor to the OA group. CONCLUSION: The present method may be useful to evaluate joint pain in experimental mice and contribute to elucidating the molecular mechanisms of pain in the OA knee joint in combination with genetically modified mice.

Postural control during quiet bipedal standing in rats.

The control of bipedal posture in humans is subject to non-ideal conditions such as delayed sensation and heartbeat noise. However, the controller achieves a high level of functionality by utilizing body dynamics dexterously. In order to elucidate the neural mechanism responsible for postural control, the present study made use of an experimental setup involving rats because they have more accessible neural structures. The experimental design requires rats to stand bipedally in order to obtain a water reward placed in a water supplier above them. Their motions can be measured in detail using a motion capture system and a force plate. Rats have the ability to stand bipedally for long durations (over 200 s), allowing for the construction of an experimental environment in which the steady standing motion of rats could be measured. The characteristics of the measured motion were evaluated based on aspects of the rats' intersegmental coordination and power spectrum density (PSD). These characteristics were compared with those of the human bipedal posture. The intersegmental coordination of the standing rats included two components that were similar to that of standing humans: center of mass and trunk motion. The rats' PSD showed a peak at approximately 1.8 Hz and the pattern of the PSD under the peak frequency was similar to that of the human PSD. However, the frequencies were five times higher in rats than in humans. Based on the analysis of the rats' bipedal standing motion, there were some common characteristics between rat and human standing motions. Thus, using standing rats is expected to be a powerful tool to reveal the neural basis of postural control.

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

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

Adaptation mechanism of interlimb coordination in human split-belt treadmill walking through learning of foot contact timing: a robotics study.

Human walking behaviour adaptation strategies have previously been examined using split-belt treadmills, which have two parallel independently controlled belts. In such human split-belt treadmill walking, two types of adaptations have been identified: early and late. Early-type adaptations appear as rapid changes in interlimb and intralimb coordination activities when the belt speeds of the treadmill change between tied (same speed for both belts) and split-belt (different speeds for each belt) configurations. By contrast, late-type adaptations occur after the early-type adaptations as a gradual change and only involve interlimb coordination. Furthermore, interlimb coordination shows after-effects that are related to these adaptations. It has been suggested that these adaptations are governed primarily by the spinal cord and cerebellum, but the underlying mechanism remains unclear. Because various physiological findings suggest that foot contact timing is crucial to adaptive locomotion, this paper reports on the development of a two-layered control model for walking composed of spinal and cerebellar models, and on its use as the focus of our control model. The spinal model generates rhythmic motor commands using an oscillator network based on a central pattern generator and modulates the commands formulated in immediate response to foot contact, while the cerebellar model modifies motor commands through learning based on error information related to differences between the predicted and actual foot contact timings of each leg. We investigated adaptive behaviour and its mechanism by split-belt treadmill walking experiments using both computer simulations and an experimental bipedal robot. Our results showed that the robot exhibited rapid changes in interlimb and intralimb coordination that were similar to the early-type adaptations observed in humans. In addition, despite the lack of direct interlimb coordination control, gradual changes and after-effects in the interlimb coordination appeared in a manner that was similar to the late-type adaptations and after-effects observed in humans. The adaptation results of the robot were then evaluated in comparison with human split-belt treadmill walking, and the adaptation mechanism was clarified from a dynamic viewpoint.

Measuring body sway of bipedally standing rat and quantitative evaluation of its postural control.

Human generates very slow (<1 Hz) body sway during standing, and the behavior of this sway is known to be changed characteristically depending on the neural ataxia. In order to investigate the sway mechanism and mechanism of neural ataxia through this sway behavior, the present research proposes an experimental environment of rats under bipedal standing. By the experiment, we succeeded the measurement of six intact rats standing for over 200 seconds without postural supports. Moreover, by comparing measured center of pressure (COP) and that of system model with nonlinear PID control model which is proposed as human standing model, control parameters of rats were numerically evaluated. Evaluated control parameters of rats were close to those of human, i.e., control strategy was considered to be comparable between rats and human.

Investigation of adaptive split-belt treadmill walking by the hindlimbs of rats.

In this study, we investigated the adaptive behavior during hindlimb locomotion of rats on a split-belt treadmill. We measured and analyzed the movement of intact rats walking by the hindlimbs on the splitbelt treadmill with two conditions: symmetric and asymmetric belt speed. In addition, we conducted the dynamic simulation of a neuromusculoskeletal model of rat's hindlimb walking on a split-belt treadmill. We investigated the immediate modulations of the duty factors and relative phase between the right and left limbs depending on the conditions of the treadmill. The results of the simulation were qualitatively similar to those of the measurement experiment. Furthermore, these results were qualitatively similar to the measurement data of the humans and cats in the previous studies. This suggests that our model have the essential aspects to produce the adaptive split-belt treadmill walking in dynamics viewpoints.

Hysteresis in the metachronal-tripod gait transition of insects: a modeling study.

Locomotion in biological systems involves various gaits, and hysteresis appears when the gaits change in accordance with the locomotion speed. That is, the gaits vary at different locomotion speeds depending on the direction of speed change. Although hysteresis is a typical characteristic of nonlinear dynamic systems, the underlying mechanism for the hysteresis in gait transitions remains largely unclear. In this study, we construct a neuromechanical model of an insect and investigate the dynamic characteristics of its gait and gait transition. The simulation results show that our insect model produces metachronal and tripod gaits depending on the locomotion speed through dynamic interactions among the body mechanical system, the nervous system, and the environment in a self-organized manner. They also show that it undergoes the metachronal-tripod gait transition with hysteresis by changing the locomotion speed. We examined the hysteresis mechanism in the metachronal-tripod gait transition of insects from a dynamic viewpoint.

A stability-based mechanism for hysteresis in the walk-trot transition in quadruped locomotion.

Quadrupeds vary their gaits in accordance with their locomotion speed. Such gait transitions exhibit hysteresis. However, the underlying mechanism for this hysteresis remains largely unclear. It has been suggested that gaits correspond to attractors in their dynamics and that gait transitions are non-equilibrium phase transitions that are accompanied by a loss in stability. In the present study, we used a robotic platform to investigate the dynamic stability of gaits and to clarify the hysteresis mechanism in the walk-trot transition of quadrupeds. Specifically, we used a quadruped robot as the body mechanical model and an oscillator network for the nervous system model to emulate dynamic locomotion of a quadruped. Experiments using this robot revealed that dynamic interactions among the robot mechanical system, the oscillator network, and the environment generate walk and trot gaits depending on the locomotion speed. In addition, a walk-trot transition that exhibited hysteresis was observed when the locomotion speed was changed. We evaluated the gait changes of the robot by measuring the locomotion of dogs. Furthermore, we investigated the stability structure during the gait transition of the robot by constructing a potential function from the return map of the relative phase of the legs and clarified the physical characteristics inherent to the gait transition in terms of the dynamics.