Motor learning in multijoint virtual arm movements with novel kinematics.

Humans move their hands toward precise positions, a skill supported by the coordination of multiple joint movements, even in the presence of inherent redundancy. However, it remains unclear how the central nervous system learns the relationship between redundant joint movements and hand positions when starting from scratch. To address this question, a virtual-arm reaching task was performed in which participants were required to move a cursor corresponding to the hand of a virtual arm to a target. The joint angles of the virtual arm were determined by the heights of the participants' fingers. The results demonstrated that the participants moved the cursor to the target straighter and faster in the late phase than they did in the initial phase of learning. This improvement was accompanied by a reduction in the amount of angular changes in the virtual limb joint, predominantly characterized by an increased reliance on the virtual shoulder joint as opposed to the virtual wrist joint. These findings suggest that the central nervous system selects a combination of multijoint movements that minimize motor effort while learning novel upper-limb kinematics.

Generalization in de novo learning of virtual upper limb movements is influenced by motor exploration.

The acquisition of new motor skills from scratch, also known as de novo learning, is an essential aspect of motor development. In de novo learning, the ability to generalize skills acquired under one condition to others is crucial because of the inherently limited range of motor experiences available for learning. However, the presence of generalization in de novo learning and its influencing factors remain unclear. This study aimed to elucidate the generalization of de novo motor learning by examining the motor exploration process, which is the accumulation of motor experiences. To this end, we manipulated the exploration process during practice by changing the target shape using either a small circular target or a bar-shaped target. Our findings demonstrated that the amount of learning during practice was generalized across different conditions. Furthermore, the extent of generalization is influenced by movement variability in the control space, which is irrelevant to the task, rather than the target shapes themselves. These results confirmed the occurrence of generalization in de novo learning and suggest that the exploration process within the control space plays a significant role in facilitating this generalization.

Anticipatory postural control in adaptation of goal-directed lower extremity movements.

Skilled football players can adapt their kicking movements depending on external environments. Predictive postural control movements, known as anticipatory postural adjustments (APAs), are needed preceding kicking movements to precisely control them while maintaining a standing posture only with the support leg. We aimed to clarify APAs of the support leg in the process of adaptation of goal-directed movements with the lower limb. Participants replicated ball-kicking movements such that they reached a cursor, representing a kicking-foot position towards a forward target while standing with the support leg. APAs were observed as the centre of pressure of the support leg shifted approximately 300 ms in advance of the onset of movement of the kicking foot. When the cursor trajectory of the kicking foot was visually rotated during the task, the kicking-foot movement was gradually modified to reach the target, indicating adaptation to the novel visuomotor environment. Interestingly, APAs in the mediolateral direction were also altered following the change in kicking-foot movements. Additionally, the APAs modified more slowly than the kicking-foot movements. These results suggest that flexible changes in predictive postural control might support the adaptation of goal-directed movements of the lower limb.

Visuomotor Adaptation of Lower Extremity Movements During Virtual Ball-Kicking Task.

Sophisticated soccer players can skillfully manipulate a ball with their feet depending on the external environment. This ability of goal-directed control in the lower limbs has not been fully elucidated, although upper limb movements have been studied extensively using motor adaptation tasks. The purpose of this study was to clarify how the goal-directed movements of the lower limbs is acquired by conducting an experiment of visuomotor adaptation in ball-kicking movements. In this study, healthy young participants with and without experience playing soccer or futsal performed ball-kicking movements. They were instructed to move a cursor representing the right foot position and shoot a virtual ball to a target on a display in front of them. During the learning trials, the trajectories of the virtual ball were rotated by 15° either clockwise or counterclockwise relative to the actual ball direction. As a result, participants adapted their lower limb movements to novel visuomotor perturbation regardless of the soccer playing experience, and changed their whole trajectories not just the kicking position during adaptation. These results indicate that the goal-directed lower limb movements can be adapted to the novel environment. Moreover, it was suggested that fundamental structure of visuomotor adaptation is common between goal-directed movements in the upper and lower limbs.

Muscle synergies of multidirectional postural control in astronauts on Earth after a long-term stay in space.

Movements of the human biological system have adapted to the physical environment under the 1-g gravitational force on Earth. However, the effects of microgravity in space on the underlying functional neuromuscular control behaviors remain poorly understood. Here, we aimed to elucidate the effects of prolonged exposure to a microgravity environment on the functional coordination of multiple muscle activities. The activities of 16 lower limb muscles of 5 astronauts who stayed in space for at least 3 mo were recorded while they maintained multidirectional postural control during bipedal standing. The coordinated activation patterns of groups of muscles, i.e., muscle synergies, were estimated from the muscle activation datasets using a factorization algorithm. The experiments were repeated a total of five times for each astronaut, once before and four times after spaceflight. The compositions of muscle synergies were altered, with a constant number of synergies, after long-term exposure to microgravity, and the extent of the changes was correlated with the increased velocity of postural sway. Furthermore, the muscle synergies extracted 3 mo after the return were similar in their activation profile but not in their muscle composition compared with those extracted in the preflight condition. These results suggest that the modularity in the neuromuscular system became reorganized to adapt to the microgravity environment and then possibly reoptimized to the new sensorimotor environment after the astronauts were reexposed to a gravitational force. It is expected that muscle synergies can be used as physiological markers of the status of astronauts with gravity-dependent change.NEW & NOTEWORTHY The human neuromuscular system has adapted to the gravitational environment on Earth. Here, we demonstrated that prolonged exposure to a microgravity environment in space changes the functional coordination of multiple muscle activities regarding multidirectional standing postural control. Furthermore, the amount of change led to a greater regulatory balancing activity needed for postural control immediately after returning to Earth and differences in muscular coordination before space flight and 3 mo after the return to Earth.

Modulation of spatial and temporal modules in lower limb muscle activations during walking with simulated reduced gravity.

Gravity plays a crucial role in shaping patterned locomotor output to maintain dynamic stability during locomotion. The present study aimed to clarify the gravity-dependent regulation of modules that organize multiple muscle activities during walking in humans. Participants walked on a treadmill at seven speeds (1-6 km h-1 and a subject- and gravity-specific speed determined by the Froude number (Fr) corresponding to 0.25) while their body weight was partially supported by a lift to simulate walking with five levels of gravity conditions from 0.07 to 1 g. Modules, i.e., muscle-weighting vectors (spatial modules) and phase-dependent activation coefficients (temporal modules), were extracted from 12 lower-limb electromyographic (EMG) activities in each gravity (Fr ~ 0.25) using nonnegative matrix factorization. Additionally, a tensor decomposition model was fit to the EMG data to quantify variables depending on the gravity conditions and walking speed with prescribed spatial and temporal modules. The results demonstrated that muscle activity could be explained by four modules from 1 to 0.16 g and three modules at 0.07 g, and the modules were shared for both spatial and temporal components among the gravity conditions. The task-dependent variables of the modules acting on the supporting phase linearly decreased with decreasing gravity, whereas that of the module contributing to activation prior to foot contact showed nonlinear U-shaped modulation. Moreover, the profiles of the gravity-dependent modulation changed as a function of walking speed. In conclusion, reduced gravity walking was achieved by regulating the contribution of prescribed spatial and temporal coordination in muscle activities.

Visuomotor Transformation for the Lead Leg Affects Trail Leg Trajectories During Visually Guided Crossing Over a Virtual Obstacle in Humans.

When walking around a room or outside, we often need to negotiate external physical objects, such as walking up stairs or stepping over an obstacle. In previous studies on obstacle avoidance, lead and trail legs in humans have been considered to be controlled independently on the basis of visual input regarding obstacle properties. However, this perspective has not been sufficient because the influence of visuomotor transformation in the lead leg on the trail leg has not been fully elucidated due to technical limitations in the experimental tasks of stepping over physical obstacles. In this study, we investigated how visuomotor transformation in the lead leg affected movement trajectories in the trail leg using a visually guided task of crossing over a virtual obstacle. Trials for stepping over a physical obstacle were established followed by visually guided tasks in which cursors corresponding to the subject's lead and trail limb toe positions were displayed on a head-mounted display apparatus. Subjects were instructed to manipulate the cursors so that they precisely crossover a virtual obstacle. In the middle of the trials, the vertical displacement of the cursor only in the lead leg was reduced relative to the actual toe movement during one or two consecutive trials. This visuomotor perturbation resulted in higher elevation not only in the lead limb toe position but also in the trail limb toe trajectories, and then the toe heights returned to the baseline in washout trials, indicating that the visuomotor transformation for obstacle avoidance in the lead leg affects the trail leg trajectory. Taken together, neural resources of limb-specific motor memories for obstacle crossing movements in the lead and trail legs can be shared based on visual input regarding obstacle properties.

Modularity speeds up motor learning by overcoming mechanical bias in musculoskeletal geometry.

We can easily learn and perform a variety of movements that fundamentally require complex neuromuscular control. Many empirical findings have demonstrated that a wide range of complex muscle activation patterns could be well captured by the combination of a few functional modules, the so-called muscle synergies. Modularity represented by muscle synergies would simplify the control of a redundant neuromuscular system. However, how the reduction of neuromuscular redundancy through a modular controller contributes to sensorimotor learning remains unclear. To clarify such roles, we constructed a simple neural network model of the motor control system that included three intermediate layers representing neurons in the primary motor cortex, spinal interneurons organized into modules and motoneurons controlling upper-arm muscles. After a model learning period to generate the desired shoulder and/or elbow joint torques, we compared the adaptation to a novel rotational perturbation between modular and non-modular models. A series of simulations demonstrated that the modules reduced the effect of the bias in the distribution of muscle pulling directions, as well as in the distribution of torques associated with individual cortical neurons, which led to a more rapid adaptation to multi-directional force generation. These results suggest that modularity is crucial not only for reducing musculoskeletal redundancy but also for overcoming mechanical bias due to the musculoskeletal geometry allowing for faster adaptation to certain external environments.

Speed-Dependent Modulation of Muscle Activity Based on Muscle Synergies during Treadmill Walking.

The regulation of walking speed is easily achieved. However, the central nervous system (CNS) must coordinate numerous muscles in order to achieve a smooth and continuous control of walking speed. To control walking speed appropriately, the CNS may need to utilize a simplified system for the control of numerous muscles. Previous studies have revealed that the CNS may control walking via muscle synergies that simplify the control of muscles by modularly organizing several muscles. We hypothesized that the CNS controls the walking speed by flexibly modulating activation of muscle synergies within one gait cycle. Then, we investigated how the activation of muscle synergies depend on walking speeds using the center of activity (CoA) that indicates the center of the distribution of activation timing within one gait cycle. Ten healthy men walked on a treadmill at 14 different walking speeds. We measured the surface electromyograms (EMGs) and kinematic data. Muscle synergies were extracted using non-negative matrix factorization. Then, we calculated the CoA of each muscle synergy. We observed that the CoA of each specific synergy would shift as the walking speed changed. The CoA that was mainly activated during the heel contact phase (C1) and the activation that contributed to the double support phase (C3) shifted to the earlier phase as the walking speed increased, whereas the CoA that produced swing initiation motion (C4) and the activation that related to the late-swing phase (C5) shifted to the later phase. This shifting of the CoA indicates that the CNS controls intensive activation of muscle synergies during the regulation of walking speed. In addition, shifting the CoA might be associated with changes in kinematics or kinetics depending on the walking speed. We concluded that the CNS flexibly controls the activation of muscle synergies in regulation of walking speed.

Lower Local Dynamic Stability and Invariable Orbital Stability in the Activation of Muscle Synergies in Response to Accelerated Walking Speeds.

In order to achieve flexible and smooth walking, we must accomplish subtasks (e. g., loading response, forward propulsion or swing initiation) within a gait cycle. To evaluate subtasks within a gait cycle, the analysis of muscle synergies may be effective. In the case of walking, extracted sets of muscle synergies characterize muscle patterns that relate to the subtasks within a gait cycle. Although previous studies have reported that the muscle synergies of individuals with disorders reflect impairments, a way to investigate the instability in the activations of muscle synergies themselves has not been proposed. Thus, we investigated the local dynamic stability and orbital stability of activations of muscle synergies across various walking speeds using maximum Lyapunov exponents and maximum Floquet multipliers. We revealed that the local dynamic stability in the activations decreased with accelerated walking speeds. Contrary to the local dynamic stability, the orbital stability of the activations was almost constant across walking speeds. In addition, the increasing rates of maximum Lyapunov exponents were different among the muscle synergies. Therefore, the local dynamic stability in the activations might depend on the requirement of motor output related to the subtasks within a gait cycle. We concluded that the local dynamic stability in the activation of muscle synergies decrease as walking speed accelerates. On the other hand, the orbital stability is sustained across broad walking speeds.

Action Direction of Muscle Synergies in Voluntary Multi-Directional Postural Control.

A muscle synergy is a coordinative structure of muscles that has been proposed as a strategy to reduce the number of variables that the central nervous system (CNS) has to address in motor tasks. In this article, the mechanical contribution of muscle synergies and coordinative structures of muscles in voluntary multi-directional postural control were investigated. The task for healthy, young subjects was to shift and align their center of pressure (COP) to targets dispersed in 12 different directions in the horizontal plane by leaning their bodies for 10 s. Electromyograms (EMGs) of 18 muscles and COPs were recorded in the experiment. Muscle synergies were extracted using non-negative matrix factorization (NMF), and the structure of coordinative modules to keep the posture leaning toward various directions was disclosed. Then the directional properties, such as the mechanical role (i.e., action directions, we use ADs as abbreviation below), of muscle synergies and muscles were estimated using an electromyogram-weighted averaging (EWA) method, which is based on a cross-correlation between the fluctuations in the activation of muscle synergies and the COP. The results revealed that the ADs of muscle synergies were almost uniformly distributed in the task space in most of the subjects, which indicates that mechanical characteristics reduce the redundancy in postural control. In terms of the composition of muscle synergies and the ADs of individual muscles, we confirmed that muscle synergies in multi-directional postural control comprised a combination of several muscles, including various ADs, that generate torque at different joints.

Comparison of muscle synergies for running between different foot strike patterns.

It is well known that humans run with a fore-foot strike (FFS), a mid-foot strike (MFS) or a rear-foot strike (RFS). A modular neural control mechanism of human walking and running has been discussed in terms of muscle synergies. However, the neural control mechanisms for different foot strike patterns during running have been overlooked even though kinetic and kinematic differences between different foot strike patterns have been reported. Thus, we examined the differences in the neural control mechanisms of human running between FFS and RFS by comparing the muscle synergies extracted from each foot strike pattern during running. Muscle synergies were extracted using non-negative matrix factorization with electromyogram activity recorded bilaterally from 12 limb and trunk muscles in ten male subjects during FFS and RFS running at different speeds (5-15 km/h). Six muscle synergies were extracted from all conditions, and each synergy had a specific function and a single main peak of activity in a cycle. The six muscle synergies were similar between FFS and RFS as well as across subjects and speeds. However, some muscle weightings showed significant differences between FFS and RFS, especially the weightings of the tibialis anterior of the landing leg in synergies activated just before touchdown. The activation patterns of the synergies were also different for each foot strike pattern in terms of the timing, duration, and magnitude of the main peak of activity. These results suggest that the central nervous system controls running by sending a sequence of signals to six muscle synergies. Furthermore, a change in the foot strike pattern is accomplished by modulating the timing, duration and magnitude of the muscle synergy activity and by selectively activating other muscle synergies or subsets of the muscle synergies.

Action Direction of Muscle Synergies in Three-Dimensional Force Space.

Redundancy in the musculoskeletal system was supposed to be simplified by muscle synergies, which modularly organize muscles. To clarify the underlying mechanisms of motor control using muscle synergies, it is important to examine the spatiotemporal contribution of muscle synergies in the task space. In this study, we quantified the mechanical contribution of muscle synergies as considering spatiotemporal correlation between the activation of muscle synergies and endpoint force fluctuations. Subjects performed isometric force generation in the three-dimensional force space. The muscle-weighting vectors of muscle synergies and their activation traces across different trials were extracted from electromyogram data using decomposing technique. We then estimated mechanical contribution of muscle synergies across each trial based on cross-correlation analysis. The contributing vectors were averaged for all trials, and the averaging was defined as action direction (AD) of muscle synergies. As a result, we extracted approximately five muscle synergies. The ADs of muscle synergies mainly depended on the anatomical functions of their weighting muscles. Furthermore, the AD of each muscle indicated the synchronous activation of muscles, which composed of the same muscle synergy. These results provide the spatiotemporal characteristics of muscle synergies as neural basis.

Recruitment of muscle synergies is associated with endpoint force fluctuations during multi-directional isometric contractions.

It has long been assumed that the human central nervous system uses flexible combinations of several muscle synergies to effortlessly and efficiently control redundant movements. However, whether muscle synergies exist in the neural circuit remains controversial, and it is critical to examine the association between the recruitment pattern of synergies and motor output. In this study, we examined the relationship between the activation of muscle synergies and endpoint force fluctuations in the presence of signal-dependent noise. Subjects performed multi-directional isometric force generations around the right ankle on the sagittal plane. We then extracted muscle synergies from measured electromyogram (EMG) data using nonnegative matrix factorization. As a result, the sum of the activation of muscle synergies was correlated with the endpoint force variability from the desired directions. Furthermore, we determined that the activation trace of each synergy reflected the endpoint force fluctuations using cross-correlation analysis. Therefore, these results suggest that muscle synergies statistically calculated from EMG data should be related to the motor output.

Identification of muscle synergies associated with gait transition in humans.

There is no theoretical or empirical evidence to suggest how the central nervous system (CNS) controls a variety of muscles associated with gait transition between walking and running. Here, we examined the motor control during a gait transition based on muscle synergies, which modularly organize functionally similar muscles. To this end, the subjects walked or ran on a treadmill and performed a gait transition spontaneously as the treadmill speed increased or decreased (a changing speed condition) or voluntarily following an experimenter's instruction at constant treadmill speed (a constant speed condition). Surface electromyograms (EMGs) were recorded from 11 lower limb muscles bilaterally. We then extracted the muscle weightings of synergies and their activation coefficients from the EMG data using non-negative matrix factorization. As a result, the gait transition was controlled by approximately 9 muscle synergies, which were common during a walking and running, and their activation profiles were changed before and after a gait transition. Near a gait transition, the peak activation phases of the synergies, which were composed of plantar flexor muscles, were shifted to an earlier phase at the walk-to-run transition, and vice versa. The shifts were gradual in the changing speed condition, but an abrupt change was observed in the constant speed condition. These results suggest that the CNS low-dimensionally regulate the activation profiles of the specific synergies based on afferent information (spontaneous gait transition) or by changing only the descending neural input to the muscle synergies (voluntary gait transition) to achieve a gait transition.

The flexible recruitment of muscle synergies depends on the required force-generating capability.

To simplify redundant motor control, the central nervous system (CNS) may modularly organize and recruit groups of muscles as "muscle synergies." However, smooth and efficient movements are expected to require not only low-dimensional organization, but also flexibility in the recruitment or combination of synergies, depending on force-generating capability of individual muscles. In this study, we examined how the CNS controls activations of muscle synergies as changing joint angles. Subjects performed multidirectional isometric force generations around right ankle and extracted the muscle synergies using nonnegative matrix factorization across various knee and hip joint angles. As a result, muscle synergies were selectively recruited with merging or decomposition as changing the joint angles. Moreover, the activation profiles, including activation levels and the direction indicating the peak, of muscle synergies across force directions depended on the joint angles. Therefore, we suggested that the CNS selects appropriate muscle synergies and controls their activation patterns based on the force-generating capability of muscles with merging or decomposing descending neural inputs.

Synergistic co-activation in multi-directional postural control in humans.

To examine the muscle synergies of multi-directional postural control, we calculated the target-directed variance fraction (η) and net action direction of each muscle using the electromyogram-weighted averaging (EWA) method. Subjects stood barefoot on a force platform and maintained their posture by producing a center of pressure (COP) in twelve target directions. Surface electromyograms were recorded from 6 right-sided muscles: tibialis anterior (TA), soleus (SOL), lateral gastrocnemius (LG), medial gastrocnemius (MG), fibularis longus (FL), and gluteus medius (GM). η was calculated from COP with duration of 20-s, during which the COP was relatively constant. The EWA method was applied to the EMG and the two COP components to estimate the net action direction of each muscle. The results showed that η values in all directions did not cross the 0.8 threshold. This suggests that human postural control is achieved by synergistic co-activation. The EWA revealed that the net action directions of TA, SOL, LG, MG, and GM were 277.6°, 71.1°, 87.7°, 94.0°, and 2.2°, respectively. This suggests that postural maintenance by muscle synergy can be attributed to the relevant muscles having various action directions. These results demonstrate that muscle synergies can be investigated using COP fluctuations.

Index finger position fluctuations reflect multi-muscle coordination.

We hypothesized that movement fluctuations in the index finger reflect the integrated result of the coordination of multiple muscles because index finger movements are determined by the cooperation of multiple muscles spanning the metacarpophalangeal (MCP) joint. To evaluate this hypothesis, the aim of the present study was to examine the fluctuations of the index finger in abduction-adduction and extension-flexion directions during a position-holding task using two laser displacement sensors. Eleven healthy men maintained their index finger position while supporting a load at 5% of the maximal voluntary contraction force. To maintain the position of the index finger, displacement of the index finger in the abduction-adduction and extension-flexion directions was measured from a distance with two laser displacement sensors that were positioned to the lateral side of and above the index finger. The index finger movements fluctuated around the target position in not only the abduction-adduction direction but also the extension-flexion direction. The path length of finger displacement and the standard deviation of finger acceleration were significantly greater in the extension-flexion direction than in the abduction-adduction direction. These results suggest that the index finger movements quantified by two laser displacement sensors reflect the coordination of multiple muscles spanning the MCP joint.

Region specificity of rectus femoris muscle for force vectors in vivo.

To examine the region specificity within the rectus femoris (RF) for knee extension and hip flexion force directions, three force components around the ankle were measured during intramuscular electrical stimulation applied to six parts of the RF: a proximal and medial part, a proximal and lateral part, a middle and medial part, a middle and lateral part, a distal and medial part, and a distal and lateral part. As a result, the exerted force directions in all of the subjects were variable in all regions, and the proximal region of the RF was the dominant contributor to the hip flexion moment. In addition, the force in the lateral region of the RF, rather than that in the medial region, denoted the lateral direction. These results suggest that divergent regions of muscle fibers within the RF are responsible for different functions in determining the force direction.