The Forces Generated by Agonist Muscles during Isometric Contractions Arise from Motor Unit Synergies.

The purpose of our study was to identify the low-dimensional latent components, defined hereafter as motor unit modes, underlying the discharge rates of the motor units in two knee extensors (vastus medialis and lateralis, eight men) and two hand muscles (first dorsal interossei and thenars, seven men and one woman) during submaximal isometric contractions. Factor analysis identified two independent motor unit modes that captured most of the covariance of the motor unit discharge rates. We found divergent distributions of the motor unit modes for the hand and vastii muscles. On average, 75% of the motor units for the thenar muscles and first dorsal interosseus were strongly correlated with the module for the muscle in which they resided. In contrast, we found a continuous distribution of motor unit modes spanning the two vastii muscle modules. The proportion of the muscle-specific motor unit modes was 60% for vastus medialis and 45% for vastus lateralis. The other motor units were either correlated with both muscle modules (shared inputs) or belonged to the module for the other muscle (15% for vastus lateralis). Moreover, coherence of the discharge rates between motor unit pools was explained by the presence of shared synaptic inputs. In simulations with 480 integrate-and-fire neurons, we demonstrate that factor analysis identifies the motor unit modes with high levels of accuracy. Our results indicate that correlated discharge rates of motor units that comprise motor unit modes arise from at least two independent sources of common input among the motor neurons innervating synergistic muscles.SIGNIFICANCE STATEMENT It has been suggested that the nervous system controls synergistic muscles by projecting common synaptic inputs to the engaged motor neurons. In our study, we reduced the dimensionality of the output produced by pools of synergistic motor neurons innervating the hand and thigh muscles during isometric contractions. We found two neural modules, each representing a different common input, that were each specific for one of the muscles. In the vastii muscles, we found a continuous distribution of motor unit modes spanning the two synergistic muscles. Some of the motor units from the homonymous vastii muscle were controlled by the dominant neural module of the other synergistic muscle. In contrast, we found two distinct neural modules for the hand muscles.

Muscle synergies for multidirectional isometric force generation during maintenance of upright standing posture.

Muscle synergies are defined as coordinated recruitment of groups of muscles with specific activation balances and time profiles aimed at generating task-specific motor commands. While muscle synergies in postural control have been investigated primarily in reactive balance conditions, the neuromechanical contribution of muscle synergies during voluntary control of upright standing is still unclear. In this study, muscle synergies were investigated during the generation of isometric force at the trunk during the maintenance of standing posture. Participants were asked to maintain the steady-state upright standing posture while pulling forces of different magnitudes were applied at the level at the waist in eight horizontal directions. Muscle synergies were extracted by nonnegative matrix factorization from sixteen lower limb and trunk muscles. An average of 5-6 muscle synergies were sufficient to account for a wide variety of EMG waveforms associated with changes in the magnitude and direction of pulling forces. A cluster analysis partitioned the muscle synergies of the participants into a large group of clusters according to their similarity, indicating the use of a subjective combination of muscles to generate a multidirectional force vector in standing. Furthermore, we found a participant-specific distribution in the values of cosine directional tuning parameters of synergy amplitude coefficients, suggesting the existence of individual neuromechanical strategies to stabilize the whole-body posture. Our findings provide a starting point for the development of novel diagnostic tools to assess muscle coordination in postural control and lay the foundation for potential applications of muscle synergies in rehabilitation.

Investigating the impact of external load on muscle synergies during bipedal squats.

PURPOSE: A broad functional movement repertoire is crucial for engaging in physical activity and reducing the risk of injury, both of which are central aspects of lifelong health. As a fundamental exercise in both recreational and rehabilitative training regimes, the bipedal squat (SQBp) incorporates many everyday movement patterns. Crucially, SQBp can only be considered functional if the practitioner can meet the coordinative demands. Many factors affect coordinative aspects of an exercise, most notably external load. Since compound movements are assumed to be organized in a synergistic manner, we employed muscle synergy analysis to examine differences in muscle synergy properties between various external load levels during SQBp. METHODS: Ten healthy male recreational athletes were enrolled in the present study. Each participant performed three sets of ten SQBp on a smith machine at three submaximal load levels (50%, 62.5%, and 75% of 3 repetition maximum) across three non-consecutive days. Muscle activity was recorded from 12 prime movers of SQBp by way of electromyography (EMG). Muscle synergies were analyzed in terms of temporal activation patterns, i.e., waveform, as well as the relative input of each muscle into individual synergies, i.e., weight contribution. RESULTS: Waveforms of muscle synergies did not differ between loads. Weight contributions showed significant differences between load levels, albeit only for the gastrocnemius muscle in a single synergy. CONCLUSION: Taken together, our results imply mostly stable spatiotemporal composition of muscle activity during SQBp, underlining the importance of technical competence during compound movement performance in athletic and rehabilitative settings.

Transferring Sensor-Based Assessments to Clinical Practice: The Case of Muscle Synergies.

Sensor-based assessments in medical practice and rehabilitation include the measurement of physiological signals such as EEG, EMG, ECG, heart rate, and NIRS, and the recording of movement kinematics and interaction forces. Such measurements are commonly employed in clinics with the aim of assessing patients' pathologies, but so far some of them have found full exploitation mainly for research purposes. In fact, even though the data they allow to gather may shed light on physiopathology and mechanisms underlying motor recovery in rehabilitation, their practical use in the clinical environment is mainly devoted to research studies, with a very reduced impact on clinical practice. This is especially the case for muscle synergies, a well-known method for the evaluation of motor control in neuroscience based on multichannel EMG recordings. In this paper, considering neuromotor rehabilitation as one of the most important scenarios for exploiting novel methods to assess motor control, the main challenges and future perspectives for the standard clinical adoption of muscle synergy analysis are reported and critically discussed.

Correlation networks of spinal motor neurons that innervate lower limb muscles during a multi-joint isometric task.

Movements are reportedly controlled through the combination of synergies that generate specific motor outputs by imposing an activation pattern on a group of muscles. To date, the smallest unit of analysis of these synergies has been the muscle through the measurement of its activation. However, the muscle is not the lowest neural level of movement control. In this human study (n = 10), we used a purely data-driven method grounded on graph theory to extract networks of motor neurons based on their correlated activity during an isometric multi-joint task. Specifically, high-density surface electromyography recordings from six lower limb muscles were decomposed into motor neurons spiking activity. We analysed these activities by identifying their common low-frequency components, from which networks of correlated activity to the motor neurons were derived and interpreted as networks of common synaptic inputs. The vast majority of the identified motor neurons shared common inputs with other motor neuron(s). In addition, groups of motor neurons were partly decoupled from their innervated muscle, such that motor neurons innervating the same muscle did not necessarily receive common inputs. Conversely, some motor neurons from different muscles-including distant muscles-received common inputs. The study supports the theory that movements are produced through the control of small numbers of groups of motor neurons via common inputs and that there is a partial mismatch between these groups of motor neurons and muscle anatomy. We provide a new neural framework for a deeper understanding of the structure of common inputs to motor neurons. KEY POINTS: A central and unresolved question is how spinal motor neurons are controlled to generate movement. We decoded the spiking activities of dozens of spinal motor neurons innervating six muscles during a multi-joint task, and we used a purely data-driven method grounded on graph theory to extract networks of motor neurons based on their correlated activity (considered as common input). The vast majority of the identified motor neurons shared common inputs with other motor neuron(s). Groups of motor neurons were partly decoupled from their innervated muscle, such that motor neurons innervating the same muscle did not necessarily receive common inputs. Conversely, some motor neurons from different muscles, including distant muscles, received common inputs. The study supports the theory that movement is produced through the control of groups of motor neurons via common inputs and that there is a partial mismatch between these groups of motor neurons and muscle anatomy.

Evolution of muscle coordination and mechanical output following four weeks of arm cranking submaximal training.

Muscle synergies is extensively studied to understand how the neuromusculoskeletal system deals with abundancy. The synergies represent covariant muscles that acts as building blocks for movement production. Nevertheless, little is known on how those synergies evolve following training, learning and expertise. This study reports the influence a 4-weeks submaximal training of arm-cranking on novice participants' muscle synergies. METHODS: 12 participants performed 8 sessions of submaximal training for 4 weeks. One session consisted in two 30-second-maximal power tests followed by six 2-minutes-bouts at 30% of maximal recorded power. Cranking torque and EMG of 11 muscles were recorded during the entire protocol. After EMG normalization, muscle synergies were extracted using NNMF. Similarity was computed using cross-correlation and cosine similarities and statistical evolution across training was tested using repeated measured ANOVA. RESULTS: While maximal power increased across training days nor torque management, EMG or muscle synergies were significantly affected by submaximal training. Nevertheless, results suggest slights modifications of muscle synergies across day despite to non-significant differences. DISCUSSION: Despite the strong complexity of the upper limbs anatomy, our results showed that training didn't induce significant changes in movement realization (mechanical and coordination level). A low-dimensional organization of muscle synergies is selected from the first day and kept through the following training days, despite slight but non-significant modifications.This study supports the hypothesis that motor control for movement production could be simplify using low-dimensional building blocks (muscle synergies). Such building blocks allow stability in movement execution and are slightly adjusted to fit movement requirements with training.

Motor control complexity can be dynamically simplified during gait pattern exploration using motor control-based biofeedback.

Understanding how the central nervous system coordinates diverse motor outputs has been a topic of extensive investigation. Although it is generally accepted that a small set of synergies underlies many common activities, such as walking, whether synergies are equally robust across a broader array of gait patterns or can be flexibly modified remains unclear. Here, we evaluated the extent to which synergies changed as nondisabled adults (n = 14) explored gait patterns using custom biofeedback. Secondarily, we used Bayesian additive regression trees to identify factors that were associated with synergy modulation. Participants explored 41.1 ± 8.0 gait patterns using biofeedback, during which synergy recruitment changed depending on the type and magnitude of gait pattern modification. Specifically, a consistent set of synergies was recruited to accommodate small deviations from baseline, but additional synergies emerged for larger gait changes. Synergy complexity was similarly modulated; complexity decreased for 82.6% of the attempted gait patterns, but distal gait mechanics were strongly associated with these changes. In particular, greater ankle dorsiflexion moments and knee flexion through stance, as well as greater knee extension moments at initial contact, corresponded to a reduction in synergy complexity. Taken together, these results suggest that the central nervous system preferentially adopts a low-dimensional, largely invariant control strategy but can modify that strategy to produce diverse gait patterns. Beyond improving understanding of how synergies are recruited during gait, study outcomes may also help identify parameters that can be targeted with interventions to alter synergies and improve motor control after neurological injury.NEW & NOTEWORTHY We used a motor control-based biofeedback system and machine learning to characterize the extent to which nondisabled adults can modulate synergies during gait pattern exploration. Results revealed that a small library of synergies underlies an array of gait patterns but that recruitment from this library changes as a function of the imposed biomechanical constraints. Our findings enhance understanding of the neural control of gait and may inform biofeedback strategies to improve synergy recruitment after neurological injury.

Persistent changes in motor adaptation strategies after perturbations that require exploration of novel muscle activation patterns.

Motor skill learning requires the acquisition of novel muscle patterns and a new control policy-a process that requires time. In contrast, motor adaptation often requires only the adjustment of existing muscle patterns-a fast process. By altering the mapping of muscle activations onto cursor movements in a myoelectrically controlled virtual environment, we are able to create perturbations that require either the recombination of existing muscle synergies (compatible virtual surgery) or the learning of novel muscle patterns (incompatible virtual surgery). We investigated whether adaptation to a compatible surgery is affected by prior exposure to an incompatible surgery, i.e., a motor skill learning task. We found that adaptation to a compatible surgery was characterized by a decrease in the quality of muscle pattern reconstructions using the original synergies and an increase in reaction times only after exposure to an incompatible surgery. In contrast, prior exposure to a compatible surgery did not affect the learning process required to overcome an incompatible surgery. The fact that exposure to an incompatible surgery had a profound effect on the muscle patterns during the adaptation to a subsequent compatible surgery and not vice versa suggests that null space exploration, possibly combined with an explicit exploration strategy, is engaged during exposure to an incompatible surgery and remains enhanced during a new adaptation episode. We conclude that motor skill learning, requiring novel muscle activation patterns, leads to changes in the exploration strategy employed during a subsequent perturbation.NEW & NOTEWORTHY Motor skill learning requires the acquisition of novel muscle patterns, whereas motor adaptation requires adjusting existing ones. We wondered whether training a new motor skill affects motor adaptation strategies. We show that learning an incompatible perturbation, a complex skill requiring new muscle synergies, affects the muscle patterns observed during adaption to a compatible perturbation, which requires adjusting the existing synergies. Our results suggest that motor skill learning results in persistent changes in the exploration strategy.

Muscle synergies are associated with intermuscular coherence and cortico-synergy coherence in an isometric upper limb task.

To elucidate the underlying physiological mechanisms of muscle synergies, we investigated long-range functional connectivity by cortico-muscular (CMC), intermuscular (IMC) and cortico-synergy (CSC) coherence. Fourteen healthy participants executed an isometric upper limb task in synergy-tuned directions. Cortical activity was recorded using 32-channel electroencephalography (EEG) and muscle activity using 16-channel electromyography (EMG). Using non-negative matrix factorisation (NMF), we calculated muscle synergies from two different tasks. A preliminary multidirectional task was used to identify synergy-preferred directions (PDs). A subsequent coherence task, consisting of generating forces isometrically in the synergy PDs, was used to assess the functional connectivity properties of synergies. Overall, we were able to identify four different synergies from the multidirectional task. A significant alpha band IMC was consistently present in all extracted synergies. Moreover, IMC alpha band was higher between muscles with higher weights within a synergy. Interestingly, CSC alpha band was also significantly higher across muscles with higher weights within a synergy. In contrast, no significant CMC was found between the motor cortex area and synergy muscles. The presence of a shared input onto synergistic muscles within a synergy supports the idea of neurally derived muscle synergies that build human movement. Our findings suggest cortical modulation of some of the synergies and the consequential existence of shared input between muscles within cortically modulated synergies.

Inter-muscular coordination during running on grass, concrete and treadmill.

Running is an exercise that can be performed in different environments that imposes distinct foot-floor interactions. For instance, running on grass may help reducing instantaneous vertical impact loading, while compromising natural speed. Inter-muscular coordination during running is an important factor to understand motor performance, but little is known regarding the impact of running surface hardness on inter-muscular coordination. Therefore, we investigated whether inter-muscular coordination during running is influenced by running surface. Surface electromyography (EMG) from 12 lower limb muscles were recorded from young male individuals (n = 9) while running on grass, concrete, and on a treadmill. Motor modules consisting of weighting coefficients and activation signals were extracted from the multi-muscle EMG datasets representing 50 consecutive running cycles using non-negative matrix factorization. We found that four motor modules were sufficient to represent the EMG from all running surfaces. The inter-subject similarity across muscle weightings was the lowest for running on grass (r = 0.76 ± 0.11) compared to concrete (r = 0.81 ± 0.07) and treadmill (r = 0.78 ± 0.05), but no differences in weighting coefficients were found when analyzing the number of significantly active muscles and residual muscle weightings (p > 0.05). Statistical parametric mapping showed no temporal differences between activation signals across running surfaces (p > 0.05). However, the activation duration (% time above 15% peak activation) was significantly shorter for treadmill running compared to grass and concrete (p < 0.05). These results suggest predominantly similar neuromuscular strategies to control multiple muscles across different running surfaces. However, individual adjustments in inter-muscular coordination are required when coping with softer surfaces or the treadmill's moving belt.

Epidural stimulation restores muscle synergies by modulating neural drives in participants with sensorimotor complete spinal cord injuries.

Multiple studies have corroborated the restoration of volitional motor control after motor-complete spinal cord injury (SCI) through the use of epidural spinal cord stimulation (eSCS), but rigorous quantitative descriptions of muscle coordination have been lacking. Six participants with chronic, motor and sensory complete SCI underwent a brain motor control assessment (BMCA) consisting of a set of structured motor tasks with and without eSCS. We investigated how muscle activity complexity and muscle synergies changed with and without stimulation. We performed this analysis to better characterize the impact of stimulation on neuromuscular control. We also recorded data from nine healthy participants as controls. Competition exists between the task origin and neural origin hypotheses underlying muscle synergies. The ability to restore motor control with eSCS in participants with motor and sensory complete SCI allows us to test whether changes in muscle synergies reflect a neural basis in the same task. Muscle activity complexity was computed with Higuchi Fractal Dimensional (HFD) analysis, and muscle synergies were estimated using non-negative matrix factorization (NNMF) in six participants with American Spinal Injury Association (ASIA) Impairment Score (AIS) A. We found that the complexity of muscle activity was immediately reduced by eSCS in the SCI participants. We also found that over the follow-up sessions, the muscle synergy structure of the SCI participants became more defined, and the number of synergies decreased over time, indicating improved coordination between muscle groups. Lastly, we found that the muscle synergies were restored with eSCS, supporting the neural hypothesis of muscle synergies. We conclude that eSCS restores muscle movements and muscle synergies that are distinct from those of healthy, able-bodied controls.

Muscle synergy patterns as altered coordination strategies in individuals with chronic low back pain: a cross-sectional study.

BACKGROUND: Chronic low back pain (CLBP) is a highly prevalent disease with poorly understood underlying mechanisms. In particular, altered trunk muscle coordination in response to specific trunk tasks remains largely unknown. METHODS: We investigated the muscle synergies during 11 trunk movement and stability tasks in 15 healthy individuals (8 females and 7 males, aged 21. 3 (20.1-22.8) ± 0.6 years) and in 15 CLBP participants (8 females and 7 males, aged 20. 9 (20.2-22.6) ± 0.7 years) by recording the surface electromyographic activities of 12 back and abdominal muscles (six muscles unilaterally). Non-negative matrix factorization was performed to extract the muscle synergies. RESULTS: We found six trunk muscle synergies and temporal patterns in both groups. The high similarity of the trunk synergies and temporal patterns in the groups suggests that both groups share the common feature of the trunk coordination strategy. We also found that trunk synergies related to the lumbar erector spinae showed lower variability in the CLBP group. This may reflect the impaired back muscles that reshape the trunk synergies in the fixed structure of CLBP. Furthermore, the higher variability of trunk synergies in the other muscle regions such as in the latissimus dorsi and oblique externus, which were activated in trunk stability tasks in the CLBP group, represented more individual motor strategies when the trunk tasks were highly demanding. CONCLUSION: Our work provides the first demonstration that individual modular organization is fine-tuned while preserving the overall structures of trunk synergies and temporal patterns in the presence of persistent CLBP.

Synergistic Organization of Neural Inputs from Spinal Motor Neurons to Extrinsic and Intrinsic Hand Muscles.

Our current understanding of synergistic muscle control is based on the analysis of muscle activities. Modules (synergies) in muscle coordination are extracted from electromyographic (EMG) signal envelopes. Each envelope indirectly reflects the neural drive received by a muscle; therefore, it carries information on the overall activity of the innervating motor neurons. However, it is not known whether the output of spinal motor neurons, whose number is orders of magnitude greater than the muscles they innervate, is organized in a low-dimensional fashion when performing complex tasks. Here, we hypothesized that motor neuron activities exhibit a synergistic organization in complex tasks and therefore that the common input to motor neurons results in a large dimensionality reduction in motor neuron outputs. To test this hypothesis, we factorized the output spike trains of motor neurons innervating 14 intrinsic and extrinsic hand muscles and analyzed the dimensionality of control when healthy individuals exerted isometric forces using seven grip types. We identified four motor neuron synergies, accounting for >70% of the variance of the activity of 54.1 ± 12.9 motor neurons, and we identified four functionally similar muscle synergies. However, motor neuron synergies better discriminated individual finger forces than muscle synergies and were more consistent with the expected role of muscles actuating each finger. Moreover, in a few cases, motor neurons innervating the same muscle were active in separate synergies. Our findings suggest a highly divergent net neural inputs to spinal motor neurons from spinal and supraspinal structures, contributing to the dimensionality reduction captured by muscle synergies.SIGNIFICANCE STATEMENT We addressed whether the output of spinal motor neurons innervating multiple hand muscles could be accounted for by a modular organization, i.e., synergies, previously described to account for the coordination of multiple muscles. We found that motor neuron synergies presented similar dimensionality (implying a >10-fold reduction in dimensionality) and structure as muscle synergies. Nonetheless, the synergistic behavior of subsets of motor neurons within a muscle was also observed. These results advance our understanding of how neuromuscular control arises from mapping descending inputs to muscle activation signals. We provide, for the first time, insights into the organization of neural inputs to spinal motor neurons which, to date, has been inferred through analysis of muscle synergies.

The Spinal Control of Backward Locomotion.

Animal locomotion requires changing direction, from forward to backward. Here, we tested the hypothesis that sensorimotor circuits within the spinal cord generate backward locomotion and adjust it to task demands. We collected kinematic and electromyography (EMG) data during forward and backward locomotion at different treadmill speeds before and after complete spinal transection in six adult cats (three males and three females). After spinal transection, five/six cats performed backward locomotion, which required tonic somatosensory input in the form of perineal stimulation. One spinal cat performed forward locomotion but not backward locomotion while two others stepped backward but not forward. Spatiotemporal adjustments to increasing speed were similar in intact and spinal cats during backward locomotion and strategies were similar to forward locomotion, with shorter cycle and stance durations and longer stride lengths. Patterns of muscle activations, including muscle synergies, were similar for forward and backward locomotion in spinal cats. Indeed, we identified five muscle synergies that were similar during forward and backward locomotion. Lastly, spinal cats also stepped backward on a split-belt treadmill, with the left and right hindlimbs stepping at different speeds. Therefore, our results show that spinal sensorimotor circuits generate backward locomotion but require additional excitability compared with forward locomotion. Similar strategies for speed modulation and similar patterns of muscle activations and muscle synergies during forward and backward locomotion are consistent with a shared spinal locomotor network, with sensory feedback from the limbs controlling the direction.SIGNIFICANCE STATEMENT Animal locomotion requires changing direction, including forward, sideways and backward. This paper shows that the center controlling locomotion within the spinal cord can produce a backward pattern when instructed by sensory signals from the limbs. However, the spinal locomotor network requires greater excitability to produce backward locomotion compared with forward locomotion. The paper also shows that the spinal network controlling locomotion in the forward direction also controls locomotion in the backward direction.

The brain integrates proprioceptive information to ensure robust locomotion.

Robust locomotion relies on information from proprioceptors: sensory organs that communicate the position of body parts to the spinal cord and brain. Proprioceptive circuits in the spinal cord are known to coarsely regulate locomotion in the presence of perturbations. Yet, the regulatory importance of the brain in maintaining robust locomotion remains less clear. Here, through mouse genetic studies and in vivo electrophysiology, we examined the role of the brain in integrating proprioceptive information during perturbed locomotion. The systemic removal of proprioceptors left the mice in a constantly perturbed state, similar to that observed during mechanically perturbed locomotion in wild-type mice and characterised by longer and less accurate synergistic activation patterns. By contrast, after surgically interrupting the ascending proprioceptive projection to the brain through the dorsal column of the spinal cord, wild-type mice showed normal walking behaviour, yet lost the ability to respond to external perturbations. Our findings provide direct evidence of a pivotal role for ascending proprioceptive information in achieving robust, safe locomotion. KEY POINTS: Whether brain integration of proprioceptive feedback is crucial for coping with perturbed locomotion is not clear. We showed a crucial role of the brain for responding to external perturbations and ensure robust locomotion. We used mouse genetics to remove proprioceptors and a spinal lesion model to interrupt the flow of proprioceptive information to the brain through the dorsal column in wild-type animals. Using a custom-built treadmill, we administered sudden and random mechanical perturbations to mice during walking. External perturbations affected locomotion in wild-type mice similar to the absence of proprioceptors in genetically modified mice. Proprioceptive feedback from muscle spindles and Golgi tendon organs contributed to locomotor robustness. Wild-type mice lost the ability to respond to external perturbations after interruption of the ascending proprioceptive projection to the brainstem.

Evidence for basic units of upper limb muscle synergies underlying a variety of complex human manipulations.

Manipulations require complex upper limb movements in which the central nervous system (CNS) must deal with many degrees of freedom. Evidence suggests that the CNS utilizes motor primitives called muscle synergies to simplify the production of movements. However, the exact neural mechanism underlying muscle synergies to control a wide array of manipulations is not fully understood. Here, we tested whether there are basic units of muscle synergies that can explain a diverse range of manipulations. We measured the electromyographic activities of 20 muscles across the shoulder, elbow, and wrist and fingers during 24 manipulation tasks. As a result, nonnegative matrix factorization identified nine basic units of muscle synergies derived from the upper limb muscles that are shared across all tasks. The high similarity between muscle synergies of each of the 24 tasks and various combinations of nine basic unit muscle synergies in a single and/or merging state provides evidence that the CNS flexibly selects and modifies the degree of contribution of the nine basic units of muscle synergies to overcome different mechanical demands of tasks.NEW & NOTEWORTHY We expanded upon experiments that investigated motor modularity in upper limb movements in humans. The identification of modular features, including distinct functional muscle weightings, during highly variable manipulation tasks supports a hypothetical neural mechanism in which the CNS combines preexisting basic patterns of muscle synergies rather than framing new patterns to deal with behavioral diversity in the upper limb.

Task space exploration improves adaptation after incompatible virtual surgeries.

Humans have a remarkable capacity to learn new motor skills, a process that requires novel muscle activity patterns. Muscle synergies may simplify the generation of muscle patterns through the selection of a small number of synergy combinations. Learning of new motor skills may then be achieved by acquiring novel muscle synergies. In a previous study, we used myoelectric control to construct virtual surgeries that altered the mapping from muscle activity to cursor movements. After compatible virtual surgeries, which could be compensated by recombining subject-specific muscle synergies, participants adapted quickly. In contrast, after incompatible virtual surgeries, which could not be compensated by recombining existing synergies, participants explored new muscle patterns but failed to adapt. Here, we tested whether task space exploration can promote learning of novel muscle synergies required to overcome an incompatible surgery. Participants performed the same reaching task as in our previous study but with more time to complete each trial, thus allowing for exploration. We found an improvement in trial success after incompatible virtual surgeries. Remarkably, improvements in movement direction accuracy after incompatible surgeries occurred faster for corrective movements than for the initial movement, suggesting that learning of new synergies is more effective when used for feedback control. Moreover, reaction time was significantly higher after incompatible than compatible virtual surgeries, suggesting an increased use of an explicit adaptive strategy to overcome incompatible surgeries. Taken together, these results indicate that exploration is important for skill learning and suggest that human participants, with sufficient time, can learn new muscle synergies.NEW & NOTEWORTHY Motor skill learning requires the acquisition of novel muscle patterns, a slow adaptive process. Here we show that learning to control a cursor after an incompatible virtual surgery, a complex skill requiring new muscle synergies, is possible when enough time for task space exploration is provided. Our results suggest that learning new synergies is related to the exceptional human capacity to acquire a wide variety of novel motor skills with practice.

Influence of task complexity on movement planning and release after stroke: insights from startReact.

The capacity to plan movement following stroke is diminished when reaching from a standing position. Two mechanisms have been proposed: increased task complexity compared to simpler tasks and inhibition between the pathways controlling whole-body posture and upper extremity reaching. The objective of this study was to determine if task complexity alone can alter planning and release (or involuntary execution) capacity when whole-body postural adjustment is not required. Data were collected from 10 stroke survivors and 8 age-matched controls. Ballistic elbow extension movements were performed with and without voluntary shoulder abduction, adding complexity by anti-gravity arm support that enhanced the expression of abnormal muscle synergies linking elbow and shoulder after stroke. Our primary finding was in support of our hypothesis that startReact (involuntary release of planned movement by a startling stimulus) would be intact but that the increased task complexity would decrease the capacity to plan and release movement. StartReact was intact for both tasks with and without shoulder abduction. Despite the intact startReact response across both conditions following stroke, the incidence of startReact was decreased during the shoulder abduction task similar to prior studies showing a decrease during tasks of higher complexity. Our results suggest that individuals with stroke have a diminished capacity to plan and release movement as task complexity increases. This study highlights the unique potential for startReact to be used as a clinical tool to probe the capacity to plan and release movement following stroke and how that capacity is affected by the complexity of the task being performed. Such a tool may be useful for assessing functional impairments and tracking changes during the rehabilitation process.

Motor primitives are determined in early development and are then robustly conserved into adulthood.

Motor patterns in legged vertebrates show modularity in both young and adult animals, comprising motor synergies or primitives. Are such spinal modules observed in young mammals conserved into adulthood or altered? Conceivably, early circuit modules alter radically through experience and descending pathways' activity. We analyze lumbar motor patterns of intact adult rats and the same rats after spinal transection and compare these with adult rats spinal transected 5 days postnatally, before most motor experience, using only rats that never developed hind limb weight bearing. We use independent component analysis (ICA) to extract synergies from electromyography (EMG). ICA information-based methods identify both weakly active and strongly active synergies. We compare all spatial synergies and their activation/drive strengths as proxies of spinal modules and their underlying circuits. Remarkably, we find that spatial primitives/synergies of adult injured and neonatal injured rats differed insignificantly, despite different developmental histories. However, intact rats possess some synergies that differ significantly, although modestly, in spatial structure. Rats injured as adults were more similar in modularity to rats that had neonatal spinal transection than to themselves before injury. We surmise that spinal circuit modules for spatial synergy patterns may be determined early, before postnatal day 5 (P5), and remain largely unaltered by subsequent development or weight-bearing experience. An alternative explanation but equally important is that, after complete spinal transection, both neonatal and mature adult spinal cords rapidly converge to common synergy sets. This fundamental or convergent synergy circuitry, fully determined by P5, is revealed after spinal cord transection.

The Number and Structure of Muscle Synergies Depend on the Number of Recorded Muscles: A Pilot Simulation Study with OpenSim.

The muscle synergy approach is used to evaluate motor control and to quantitatively determine the number and structure of the modules underlying movement. In experimental studies regarding the upper limb, typically 8 to 16 EMG probes are used depending on the application, although the number of muscles involved in motor generation is higher. Therefore, the number of motor modules may be underestimated and the structure altered with the standard spatial synergy model based on the non-negative matrix factorization (NMF). In this study, we compared the number and structure of muscle synergies when considering 12 muscles (an "average" condition that represents previous studies) and 32 muscles of the upper limb, also including multiple muscle heads and deep muscles. First, we estimated the muscle activations with an upper-limb model in OpenSim using data from multi-directional reaching movements acquired in experimental sessions; then, spatial synergies were extracted from EMG activations from 12 muscles and from 32 muscles and their structures were compared. Finally, we compared muscle synergies obtained from OpenSim and from real experimental EMG signals to assess the reliability of the results. Interestingly, we found that on average, an additional synergy is needed to reconstruct the same R2 level with 32 muscles with respect to 12 muscles; synergies have a very similar structure, although muscles with comparable physiological functions were added to the synergies extracted with 12 muscles. The additional synergies, instead, captured patterns that could not be identified with only 12 muscles. We concluded that current studies may slightly underestimate the number of controlled synergies, even though the main structure of synergies is not modified when adding more muscles. We also show that EMG activations estimated with OpenSim are in partial (but not complete) agreement with experimental recordings. These findings may have significative implications for motor control and clinical studies.