Microstimulation activates a handful of muscle synergies

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.

Concerto of movement: how expertise shapes the synergistic control of upper limb muscles in complex motor tasks with varying tempo and dynamics

Objective. This research aims to reveal how the synergistic control of upper limb muscles adapts to varying requirements in complex motor tasks and how expertise shapes the motor modules.Approach. We study the muscle synergies of a complex, highly skilled and flexible task-piano playing-and characterize expertise-related muscle-synergy control that permits the experts to effortlessly execute the same task at different tempo and force levels. Surface EMGs (28 muscles) were recorded from adult novice (N= 10) and expert (N= 10) pianists as they played scales and arpeggios at different tempo-force combinations. Muscle synergies were factorized from EMGs.Main results. We found that experts were able to cover both tempo and dynamic ranges using similar synergy selections and achieved better performance, while novices altered synergy selections more to adapt to the changing tempi and keystroke intensities compared with experts. Both groups relied on fine-tuning the muscle weights within specific synergies to accomplish the different task styles, while the experts could tune the muscles in a greater number of synergies, especially when changing the tempo, and switch tempo over a wider range.Significance. Our study sheds light on the control mechanism underpinning expertise-related motor flexibility in highly skilled motor tasks that require decade-long training. Our results have implications on musical and sports training, as well as motor prosthetic design.

Concurrent optogenetic motor mapping of multiple limbs in awake mice reveals cortical organization of coordinated movements

Background

Motor mapping allows for determining the macroscopic organization of motor circuits and corresponding motor movement representations on the cortex. Techniques such as intracortical microstimulation (ICMS) are robust, but can be time consuming and invasive, making them non-ideal for cortex-wide mapping or longitudinal studies. In contrast, optogenetic motor mapping offers a rapid and minimally invasive technique, enabling mapping with high spatiotemporal resolution. However, motor mapping has seen limited use in tracking 3-dimensonal, multi-limb movements in awake animals. This gap has left open questions regarding the underlying organizational principles of motor control of coordinated, ethologically relevant movements involving multiple limbs.

Objective

Our first objective was to develop Multi-limb Optogenetic Motor Mapping (MOMM) to concurrently map motor movement representations of multiple limbs with high fidelity in awake mice. Having established MOMM, our next objective was determine whether maps of coordinated and ethologically relevant motor output were topographically organized on the cortex.

Methods

We combine optogenetic stimulation with a deep learning driven pose-estimation toolbox, DeepLabCut (DLC), and 3-dimentional triangulation to concurrently map motor movements of multiple limbs in awake mice.

Results

MOMM consistently revealed cortical topographies for all mapped features within and across mice. Many motor maps overlapped and were topographically similar. Several motor movement representations extended beyond cytoarchitecturally defined somatomotor cortex. Finer articulations of the forepaw resided within gross motor movement representations of the forelimb. Moreover, many cortical sites exhibited concurrent limb coactivation when photostimulated, prompting the identification of several cortical regions harboring coordinated and ethologically relevant movements.

Conclusions

The cortex appears to be topographically organized by motor programs, which are responsible for coordinated, multi-limbed, and behavioral-like movements.

Inhibitory circuits coordinate leg movements during Drosophila grooming

Limbs execute diverse actions coordinated by the nervous system through multiple motor programs. The basic architecture of motor neurons that activate muscles which articulate joints for antagonistic flexion and extension movements is conserved from flies to vertebrates. While excitatory premotor circuits are expected to establish sets of leg motor neurons that work together, our study uncovered an instructive role for inhibitory circuits. Using electron microscopy data for the Drosophila nerve cord, we categorized ~120 GABAergic inhibitory neurons from the 13A and 13B hemi-lineages into classes based on similarities in morphology and connectivity. By mapping their synaptic partners, we uncovered redundant pathways for inhibiting specific groups of motor neurons, disinhibiting antagonistic counterparts, or inducing alternation between flexion and extension. We tested the function of specific inhibitory neurons through optogenetic activation and silencing, using quantitative leg movement assays for coordination during grooming. Behavior experiments and modeling demonstrate that inhibition can induce rhythmic motion, highlighting the importance of inhibitory circuits in motor control.

Synaptic inputs to motor neurons underlying muscle coactivation for functionally different tasks have different spectral characteristics

The central nervous system (CNS) may produce the same endpoint trajectory or torque profile with different muscle activation patterns. What differentiates these patterns is the presence of cocontraction, which does not contribute to effective torque generation but allows to modulate joints' mechanical stiffness. Although it has been suggested that the generation of force and the modulation of stiffness rely on separate pathways, a characterization of the differences between the synaptic inputs to motor neurons (MNs) underlying these tasks is still missing. In this study, participants coactivated the same pair of upper-limb muscles, i.e., the biceps brachii and the triceps brachii, to perform two functionally different tasks: limb stiffness modulation or endpoint force generation. Spike trains of MNs were identified through decomposition of high-density electromyograms (EMGs) collected from the two muscles. Cross-correlogram showed a higher synchronization between MNs recruited to modulate stiffness, whereas cross-muscle coherence analysis revealed peaks in the β-band, which is commonly ascribed to a cortical origin. These peaks did not appear during the coactivation for force generation, thus suggesting separate cortical inputs for stiffness modulation. Moreover, a within-muscle coherence analysis identified two subsets of MNs that were selectively recruited to generate force or regulate stiffness. This study is the first to highlight different characteristics, and probable different neural origins, of the synaptic inputs driving a pair of muscles under different functional conditions. We suggest that stiffness modulation is driven by cortical inputs that project to a separate set of MNs, supporting the existence of a separate pathway underlying the control of stiffness.NEW & NOTEWORTHY The characterization of the pathways underlying force generation or stiffness modulation are still unknown. In this study, we demonstrated that the common input to motor neurons of antagonist muscles shows a high-frequency component when muscles are coactivated to modulate stiffness but not to generate force. Our results provide novel insights on the neural strategies for the recruitment of multiple muscles by identifying specific spectral characteristics of the synaptic inputs underlying functionally different tasks.

Synergy quality assessment of muscle modules for determining learning performance using a realistic musculoskeletal model

How our central nervous system efficiently controls our complex musculoskeletal system is still debated. The muscle synergy hypothesis is proposed to simplify this complex system by assuming the existence of functional neural modules that coordinate several muscles. Modularity based on muscle synergies can facilitate motor learning without compromising task performance. However, the effectiveness of modularity in motor control remains debated. This ambiguity can, in part, stem from overlooking that the performance of modularity depends on the mechanical aspects of modules of interest, such as the torque the modules exert. To address this issue, this study introduces two criteria to evaluate the quality of module sets based on commonly used performance metrics in motor learning studies: the accuracy of torque production and learning speed. One evaluates the regularity in the direction of mechanical torque the modules exert, while the other evaluates the evenness of its magnitude. For verification of our criteria, we simulated motor learning of torque production tasks in a realistic musculoskeletal system of the upper arm using feed-forward neural networks while changing the control conditions. We found that the proposed criteria successfully explain the tendency of learning performance in various control conditions. These result suggest that regularity in the direction of and evenness in magnitude of mechanical torque of utilized modules are significant factor for determining learning performance. Although the criteria were originally conceived for an error-based learning scheme, the approach to pursue which set of modules is better for motor control can have significant implications in other studies of modularity in general.

Decoding temporal muscle synergy patterns based on brain activity for upper extremity in ADL movements

Muscle synergies have been hypothesized as specific predefined motor primitives that the central nervous system can reduce the complexity of motor control by using them, but how these are expressed in brain activity is ambiguous yet. The main purpose of this paper is to develop synergy-based neural decoding of motor primitives, so for the first time, brain activity and muscle synergy map of the upper extremity was investigated in the activity of daily living movements. To find the relationship between brain activities and muscle synergies, electroencephalogram (EEG) and electromyogram (EMG) signals were acquired simultaneously during activities of daily living. To extract the maximum correlation of neural commands with muscle synergies, application of a combined partial least squares and canonical correlation analysis (PLS-CCA) method was proposed. The Elman neural network was used to decode the relationship between extracted motor commands and muscle synergies. The performance of proposed method was evaluated with tenfold cross-validation and muscle synergy estimation of brain activity with R, VAF, and MSE of 84 ± 2.6%, 70 ± 4.7%, and 0.00011 ± 0.00002 were quantified respectively. Furthermore, the similarity between actual and reconstructed muscle activations was achieved more than 92% for correlation coefficient. To compare with the existing methods, our results showed significantly more accuracy of the model performance. Our results confirm that use of the expression of muscle synergies in brain activity can estimate the neural decoding performance for motor control that can be used to develop neurorehabilitation tools such as neuroprosthesis.

The dorsal stream of visual processing and action-specific domains in parietal and frontal cortex in primates

This review summarizes our findings obtained from over 15 years of research on parietal-frontal networks involved in the dorsal stream of cortical processing. We have presented considerable evidence for the existence of similar, partially independent, parietal-frontal networks involved in specific motor actions in a number of primates. These networks are formed by connections between action-specific domains representing the same complex movement evoked by electrical microstimulation. Functionally matched domains in the posterior parietal (PPC) and frontal (M1-PMC) motor regions are hierarchically related. M1 seems to be a critical link in these networks, since the outputs of M1 are essential to the evoked behavior, whereas PPC and PMC mediate complex movements mostly via their connections with M1. Thus, lesioning or deactivating M1 domains selectively blocks matching PMC and PPC domains, while having limited impact on other domains. When pairs of domains are stimulated together, domains within the same parietal-frontal network (matching domains) are cooperative in evoking movements, while they are mainly competitive with other domains (mismatched domains) within the same set of cortical areas. We propose that the interaction of different functional domains in each cortical region (as well as in striatum) occurs mainly via mutual suppression. Thus, the domains at each level are in competition with each other for mediating one of several possible behavioral outcomes.

Two motor neuron synergies, invariant across ankle joint angles, activate the triceps surae during plantarflexion

Recent studies have suggested that the nervous system generates movements by controlling groups of motor neurons (synergies) that do not always align with muscle anatomy. In this study, we determined whether these synergies are robust across tasks with different mechanical constraints. We identified motor neuron synergies using principal component analysis (PCA) and cross-correlations between smoothed discharge rates of motor neurons. In part 1, we used simulations to validate these methods. The results suggested that PCA can accurately identify the number of common inputs and their distribution across active motor neurons. Moreover, the results confirmed that cross-correlation can separate pairs of motor neurons that receive common inputs from those that do not receive common inputs. In part 2, 16 individuals performed plantarflexion at three ankle angles while we recorded EMG signals from the gastrocnemius lateralis (GL) and medialis (GM) and the soleus (SOL) with grids of surface electrodes. The PCA revealed two motor neuron synergies. These motor neuron synergies were relatively stable, with no significant differences in the distribution of motor neuron weights across ankle angles (P = 0.62). When the cross-correlation was calculated for pairs of motor units tracked across ankle angles, we observed that only 13.0% of pairs of motor units from GL and GM exhibited significant correlations of their smoothed discharge rates across angles, confirming the low level of common inputs between these muscles. Overall, these results highlight the modularity of movement control at the motor neuron level, suggesting a sensible reduction of computational resources for movement control. KEY POINTS: The CNS might generate movements by activating groups of motor neurons (synergies) with common inputs. We show here that two main sources of common inputs drive the motor neurons innervating the triceps surae muscles during isometric ankle plantarflexions. We report that the distribution of these common inputs is globally invariant despite changing the mechanical constraints of the tasks, i.e. the ankle angle. These results suggest the functional relevance of the modular organization of the CNS to control movements.

Exploring Muscle Synergies for Performance Enhancement and Learning in Myoelectric Control Maps

This work proposes two myoelectric control maps based on a DoF-wise synergy algorithm, inspired by human motor control studies. One map, called intuitive, matches control outputs with body movement directions. The second one, named non-intuitive, takes advantage of different synergies contribution to each DoF, without specific correlation to body movement directions. The effectiveness and learning process for the two maps is evaluated through performance metrics in ten able-bodied individuals. The analysis was conducted using a 2-DoFs center-reach-out task and a survey. Results showed equivalent performance and perception for both mappings. However, learning is only visible in subjects that performed better in non-intuitive mapping, that required some familiarization to then exploit its features. Most of the myoelectric control designs use intuitive mappings. Nevertheless, non-intuitive mapping could provide more design flexibility, which can be especially interesting for patients with motor disabilities.

Loss of finger control complexity and intrusion of flexor biases are dissociable in finger individuation impairment after stroke

The ability to control each finger independently is an essential component of human hand dexterity. A common observation of hand function impairment after stroke is the loss of this finger individuation ability, often referred to as enslavement, i.e., the unwanted coactivation of non-intended fingers in individuated finger movements. In the previous literature, this impairment has been attributed to several factors, such as the loss of corticospinal drive, an intrusion of flexor synergy due to upregulations of the subcortical pathways, and/or biomechanical constraints. These factors may or may not be mutually exclusive and are often difficult to tease apart. It has also been suggested, based on a prevailing impression, that the intrusion of flexor synergy appears to be an exaggerated pattern of the involuntary coactivations of task-irrelevant fingers seen in a healthy hand, often referred to as a flexor bias. Most previous studies, however, were based on assessments of enslavement in a single dimension (i.e., finger flexion/extension) that coincide with the flexor bias, making it difficult to tease apart the other aforementioned factors. Here, we set out to closely examine the nature of individuated finger control and finger coactivation patterns in all dimensions. Using a novel measurement device and a 3D finger-individuation paradigm, we aim to tease apart the contributions of lower biomechanical, subcortical constraints, and top-down cortical control to these patterns in both healthy and stroke hands. For the first time, we assessed all five fingers' full capacity for individuation. Our results show that these patterns in the healthy and paretic hands present distinctly different shapes and magnitudes that are not influenced by biomechanical constraints. Those in the healthy hand presented larger angular distances that were dependent on top-down task goals, whereas those in the paretic hand presented larger Euclidean distances that arise from two dissociable factors: a loss of complexity in finger control and the dominance of an intrusion of flexor bias. These results suggest that finger individuation impairment after stroke is due to two dissociable factors: the loss of finger control complexity present in the healthy hand reflecting a top-down neural control strategy and an intrusion of flexor bias likely due to an upregulation of subcortical pathways. Our device and paradigm are demonstrated to be a promising tool to assess all aspects of the dexterous capacity of the hand.

Generating variability from motor primitives during infant locomotor development

Motor variability is a fundamental feature of developing systems allowing motor exploration and learning. In human infants, leg movements involve a small number of basic coordination patterns called locomotor primitives, but whether and when motor variability could emerge from these primitives remains unknown. Here we longitudinally followed 18 infants on 2-3 time points between birth (~4 days old) and walking onset (~14 months old) and recorded the activity of their leg muscles during locomotor or rhythmic movements. Using unsupervised machine learning, we show that the structure of trial-to-trial variability changes during early development. In the neonatal period, infants own a minimal number of motor primitives but generate a maximal motor variability across trials thanks to variable activations of these primitives. A few months later, toddlers generate significantly less variability despite the existence of more primitives due to more regularity within their activation. These results suggest that human neonates initiate motor exploration as soon as birth by variably activating a few basic locomotor primitives that later fraction and become more consistently activated by the motor system.

Hindbrain modules differentially transform activity of single collicular neurons to coordinate movements

Seemingly simple behaviors such as swatting a mosquito or glancing at a signpost involve the precise coordination of multiple body parts. Neural control of coordinated movements is widely thought to entail transforming a desired overall displacement into displacements for each body part. Here we reveal a different logic implemented in the mouse gaze system. Stimulating superior colliculus (SC) elicits head movements with stereotyped displacements but eye movements with stereotyped endpoints. This is achieved by individual SC neurons whose branched axons innervate modules in medulla and pons that drive head movements with stereotyped displacements and eye movements with stereotyped endpoints, respectively. Thus, single neurons specify a mixture of endpoints and displacements for different body parts, not overall displacement, with displacements for different body parts computed at distinct anatomical stages. Our study establishes an approach for unraveling motor hierarchies and identifies a logic for coordinating movements and the resulting pose.

Neuromuscular control: from a biomechanist's perspective

Understanding neural control of movement necessitates a collaborative approach between many disciplines, including biomechanics, neuroscience, and motor control. Biomechanics grounds us to the laws of physics that our musculoskeletal system must obey. Neuroscience reveals the inner workings of our nervous system that functions to control our body. Motor control investigates the coordinated motor behaviours we display when interacting with our environment. The combined efforts across the many disciplines aimed at understanding human movement has resulted in a rich and rapidly growing body of literature overflowing with theories, models, and experimental paradigms. As a result, gathering knowledge and drawing connections between the overlapping but seemingly disparate fields can be an overwhelming endeavour. This review paper evolved as a need for us to learn of the diverse perspectives underlying current understanding of neuromuscular control. The purpose of our review paper is to integrate ideas from biomechanics, neuroscience, and motor control to better understand how we voluntarily control our muscles. As biomechanists, we approach this paper starting from a biomechanical modelling framework. We first define the theoretical solutions (i.e., muscle activity patterns) that an individual could feasibly use to complete a motor task. The theoretical solutions will be compared to experimental findings and reveal that individuals display structured muscle activity patterns that do not span the entire theoretical solution space. Prevalent neuromuscular control theories will be discussed in length, highlighting optimality, probabilistic principles, and neuromechanical constraints, that may guide individuals to families of muscle activity solutions within what is theoretically possible. Our intention is for this paper to serve as a primer for the neuromuscular control scientific community by introducing and integrating many of the ideas common across disciplines today, as well as inspire future work to improve the representation of neural control in biomechanical models.

Chord skill: learning optimized hand postures and bimanual coordination

This reaction time study tested the hypothesis that in the case of finger movements skilled motor control involves the execution of learned hand postures. After delineating hypothetical control mechanisms and their predictions an experiment is described involving 32 participants who practiced 6 chord responses. These responses involved the simultaneous depression of one, two or three keys with either four right-hand fingers or two fingers of both hands. After practicing each of these responses for 240 trials, the participants performed the practiced and also novel chords with the familiar and with the unfamiliar hand configuration of the other practice group. The results suggest that participants learned hand postures rather than spatial or explicit chord representations. Participants practicing with both hands also developed a bimanual coordination skill. Chord execution was most likely slowed by interference between adjacent fingers. This interference seemed eliminated with practice for some chords but not for others. Hence, the results support the notion that skilled control of finger movements is based on learned hand postures that even after practice may be slowed by interference between adjacent fingers.

Muscle synergies for evaluating upper limb in clinical applications: A systematic review

INTRODUCTION

Muscle synergies have been proposed as a strategy employed by the central nervous system to control movements. Muscle synergy analysis is a well-established framework to examine the pathophysiological basis of neurological diseases and has been applied for analysis and assessment in clinical applications in the last decades, even if it has not yet been widely used in clinical diagnosis, rehabilitative treatment and interventions. Even if inconsistencies in the outputs among studies and lack of a normative pipeline including signal processing and synergy analysis limit the progress, common findings and results are identifiable as a basis for future research. Therefore, a literature review that summarizes methods and main findings of previous works on upper limb muscle synergies in clinical environment is needed to i) summarize the main findings so far, ii) highlight the barriers limiting their use in clinical applications, and iii) suggest future research directions needed for facilitating translation of experimental research to clinical scenarios.

METHODS

Articles in which muscle synergies were used to analyze and assess upper limb function in neurological impairments were reviewed. The literature research was conducted in Scopus, PubMed, and Web of Science. Experimental protocols (e.g., the aim of the study, number and type of participants, number and type of muscles, and tasks), methods (e.g., muscle synergy models and synergy extraction methods, signal processing methods), and the main findings of eligible studies were reported and discussed.

RESULTS

383 articles were screened and 51 were selected, which involved a total of 13 diseases and 748 patients and 1155 participants. Each study investigated on average 15 ± 10 patients. Four to forty-one muscles were included in the muscle synergy analysis. Point-to-point reaching was the most used task. The preprocessing of EMG signals and algorithms for synergy extraction varied among studies, and non-negative matrix factorization was the most used method. Five EMG normalization methods and five methods for identifying the optimal number of synergies were used in the selected papers. Most of the studies report that analyses on synergy number, structure, and activations provide novel insights on the physiopathology of motor control that cannot be gained with standard clinical assessments, and suggest that muscle synergies may be useful to personalize therapies and to develop new therapeutic strategies. However, in the selected studies synergies were used only for assessment; different testing procedures were used and, in general, study-specific modifications of muscle synergies were observed; single session or longitudinal studies mainly aimed at assessing stroke (71% of the studies), even though other pathologies were also investigated. Synergy modifications were either study-specific or were not observed, with few analyses available for temporal coefficients. Thus, several barriers prevent wider adoption of muscle synergy analysis including a lack of standardized experimental protocols, signal processing procedures, and synergy extraction methods. A compromise in the design of the studies must be found to combine the systematicity of motor control studies and the feasibility of clinical studies. There are however several potential developments that might promote the use of muscle synergy analysis in clinical practice, including refined assessments based on synergistic approaches not allowed by other methods and the availability of novel models. Finally, neural substrates of muscle synergies are discussed, and possible future research directions are proposed.

CONCLUSIONS

This review provides new perspectives about the challenges and open issues that need to be addressed in future work to achieve a better understanding of motor impairments and rehabilitative therapy using muscle synergies. These include the application of the methods on wider scales, standardization of procedures, inclusion of synergies in the clinical decisional process, assessment of temporal coefficients and temporal-based models, extensive work on the algorithms and understanding of the physio-pathological mechanisms of pathology, as well as the application and adaptation of synergy-based approaches to various rehabilitative scenarios for increasing the available evidence.

The contribution of the basal ganglia and cerebellum to motor learning: A neuro-computational approach

Motor learning involves a widespread brain network including the basal ganglia, cerebellum, motor cortex, and brainstem. Despite its importance, little is known about how this network learns motor tasks and which role different parts of this network take. We designed a systems-level computational model of motor learning, including a cortex-basal ganglia motor loop and the cerebellum that both determine the response of central pattern generators in the brainstem. First, we demonstrate its ability to learn arm movements toward different motor goals. Second, we test the model in a motor adaptation task with cognitive control, where the model replicates human data. We conclude that the cortex-basal ganglia loop learns via a novelty-based motor prediction error to determine concrete actions given a desired outcome, and that the cerebellum minimizes the remaining aiming error.

Use of Surface Electromyography to Estimate End-Point Force in Redundant Systems: Comparison between Linear Approaches

Estimation of the force exerted by muscles from their electromyographic (EMG) activity may be useful to control robotic devices. Approximating end-point forces as a linear combination of the activities of multiple muscles acting on a limb may lead to an inaccurate estimation because of the dependency between the EMG signals, i.e., multi-collinearity. This study compared the EMG-to-force mapping estimation performed with standard multiple linear regression and with three other algorithms designed to reduce different sources of the detrimental effects of multi-collinearity: Ridge Regression, which performs an L2 regularization through a penalty term; linear regression with constraints from foreknown anatomical boundaries, derived from a musculoskeletal model; linear regression of a reduced number of muscular degrees of freedom through the identification of muscle synergies. Two datasets, both collected during the exertion of submaximal isometric forces along multiple directions with the upper limb, were exploited. One included data collected across five sessions and the other during the simultaneous exertion of force and generation of different levels of co-contraction. The accuracy and consistency of the EMG-to-force mappings were assessed to determine the strengths and drawbacks of each algorithm. When applied to multiple sessions, Ridge Regression achieved higher accuracy (R² = 0.70) but estimations based on muscle synergies were more consistent (differences between the pulling vectors of mappings extracted from different sessions: 67%). In contrast, the implementation of anatomical constraints was the best solution, both in terms of consistency (R² = 0.64) and accuracy (74%), in the case of different co-contraction conditions. These results may be used for the selection of the mapping between EMG and force to be implemented in myoelectrically controlled robotic devices.

Decomposition into dynamic features reveals a conserved temporal structure in hand kinematics

The human hand is a unique and highly complex effector. The ability to describe hand kinematics with a small number of features suggests that complex hand movements are composed of combinations of simpler movements. This would greatly simplify the neural control of hand movements. If such movement primitives exist, a dimensionality reduction approach designed to exploit these features should outperform existing methods. We developed a deep neural network to capture the temporal dynamics of movements and demonstrate that the features learned allow accurate representation of functional hand movements using lower-dimensional representations than previously reported. We show that these temporal features are highly conserved across individuals and can interpolate previously unseen movements, indicating that they capture the intrinsic structure of hand movements. These results indicate that functional hand movements are defined by a low-dimensional basis set of movement primitives with important temporal dynamics and that these features are common across individuals.

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Hand movements are comprised of a low-dimensional set of movement primitives

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Primitive movements have an important temporal component

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Spatiotemporal movement primitives are conserved across individuals

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New complex movements can be flexibly reconstructed using these primitives

The relationship between motor pathway damage and flexion-extension patterns of muscle co-excitation during walking

Background

Mass flexion-extension co-excitation patterns during walking are often seen as a consequence of stroke, but there is limited understanding of the specific contributions of different descending motor pathways toward their control. The corticospinal tract is a major descending motor pathway influencing the production of normal sequential muscle coactivation patterns for skilled movements. However, control of walking is also influenced by non-corticospinal pathways such as the corticoreticulospinal pathway that possibly contribute toward mass flexion-extension co-excitation patterns during walking. The current study sought to investigate the associations between damage to corticospinal (CST) and corticoreticular (CRP) motor pathways following stroke and the presence of mass flexion-extension patterns during walking as evaluated using module analysis.

Methods

Seventeen healthy controls and 44 stroke survivors were included in the study. We used non-negative matrix factorization for module analysis of paretic leg electromyographic activity. We typically have observed four modules during walking in healthy individuals. Stroke survivors often have less independently timed modules, for example two-modules presented as mass flexion-extension pattern. We used diffusion tensor imaging-based analysis where streamlines connecting regions of interest between the cortex and brainstem were computed to evaluate CST and CRP integrity. We also used a coarse classification tree analysis to evaluate the relative CST and CRP contribution toward module control.

Results

Interhemispheric CST asymmetry was associated with worse lower extremity Fugl-Meyer score (p = 0.023), propulsion symmetry (p = 0.016), and fewer modules (p = 0.028). Interhemispheric CRP asymmetry was associated with worse lower extremity Fugl-Meyer score (p = 0.009), Dynamic gait index (p = 0.035), Six-minute walk test (p = 0.020), Berg balance scale (p = 0.048), self-selected walking speed (p = 0.041), and propulsion symmetry (p = 0.001). The classification tree model reveled that substantial ipsilesional CRP or CST damage leads to a two-module pattern and poor walking ability with a trend toward increased compensatory contralesional CRP based control.

Conclusion

Both CST and CRP are involved with control of modules during walking and damage to both may lead to greater reliance on the contralesional CRP, which may contribute to a two-module pattern and be associated with worse walking performance.

Similarity of hand muscle synergies elicited by transcranial magnetic stimulation and those found during voluntary movement

Converging evidence in human and animal models suggests that exogenous stimulation of the motor cortex (M1) elicits responses in the hand with similar modular structure to that found during voluntary grasping movements. The aim of this study was to establish the extent to which modularity in muscle responses to transcranial magnetic stimulation (TMS) to M1 resembles modularity in muscle activation during voluntary hand movements involving finger fractionation. Electromyography (EMG) was recorded from eight hand-forearm muscles in eight healthy individuals. Modularity was defined using non-negative matrix factorization to identify low-rank approximations (spatial muscle synergies) of the complex activation patterns of EMG data recorded during high-density TMS mapping of M1 and voluntary formation of gestures in the American Sign Language alphabet. Analysis of synergies revealed greater than chance similarity between those derived from TMS and those derived from voluntary movement. Both data sets included synergies dominated by single intrinsic hand muscles presumably to meet the demand for highly fractionated finger movement. These results suggest that corticospinal connectivity to individual intrinsic hand muscles may be combined with modular multimuscle activation via synergies in the formation of hand postures.NEW & NOTEWORTHY This is the first work to examine the similarity of modularity in hand muscle responses to transcranial magnetic stimulation (TMS) of the motor cortex and that derived from voluntary hand movement. We show that TMS-elicited muscle synergies of the hand, measured at rest, reflect those found in voluntary behavior involving finger fractionation. This work provides a basis for future work using TMS to investigate muscle activation modularity in the human motor system.

Muscle synergy analysis yields an efficient and physiologically relevant method of assessing stroke

The Fugl-Meyer Assessment is widely used to test motor function in stroke survivors. In the Fugl-Meyer Assessment, stroke survivors perform several movement tasks and clinicians subjectively rate the performance of each task item. The individual task items in the Fugl-Meyer Assessment are selected on the basis of clinical experience, and their physiological relevance has not yet been evaluated. In the present study, we aimed to objectively rate the performance of task items by measuring the muscle activity of 41 muscles from the upper body while stroke survivors and healthy participants performed 37 Fugl-Meyer Assessment upper extremity task items. We used muscle synergy analysis to compare muscle activity between subjects and found that 13 muscle synergies in the healthy participants (which we defined as standard synergies) were able to reconstruct all of the muscle activity in the Fugl-Meyer Assessment. Among the standard synergies, synergies involving the upper arms, forearms and fingers were activated to varying degrees during different task items. In contrast, synergies involving posterior trunk muscles were activated during all tasks, which suggests the importance of posterior trunk muscle synergies throughout all sequences. Furthermore, we noted the inactivation of posterior trunk muscle synergies in stroke survivors with severe but not mild impairments, suggesting that lower trunk stability and the underlying activity of posterior trunk muscle synergies may have a strong influence on stroke severity and recovery. By comparing the synergies of stroke survivors with standard synergies, we also revealed that some synergies in stroke survivors corresponded to merged standard synergies; the merging rate increased with the impairment of stroke survivors. Moreover, the degrees of severity-dependent changes in the merging rate (the merging rate–severity relationship) were different among different task items. This relationship was significant for 26 task items only and not for the other 11 task items. Because muscle synergy analysis evaluates coordinated muscle activities, this different dependency suggests that these 26 task items are appropriate for evaluating muscle coordination and the extent of its impairment in stroke survivors. Overall, we conclude that the Fugl-Meyer Assessment reflects physiological function and muscle coordination impairment and suggest that it could be performed using a subset of the 37 task items.

Forearm and Hand Muscles Exhibit High Coactivation and Overlapping of Cortical Motor Representations

Most of the motor mapping procedures using navigated transcranial magnetic stimulation (nTMS) follow the conventional somatotopic organization of the primary motor cortex (M1) by assessing the representation of a particular target muscle, disregarding the possible coactivation of synergistic muscles. In turn, multiple reports describe a functional organization of the M1 with an overlapping among motor representations acting together to execute movements. In this context, the overlap degree among cortical representations of synergistic hand and forearm muscles remains an open question. This study aimed to evaluate the muscle coactivation and representation overlapping common to the grasping movement and its dependence on the stimulation parameters. The nTMS motor maps were obtained from one carpal muscle and two intrinsic hand muscles during rest. We quantified the overlapping motor maps in size (area and volume overlap degree) and topography (similarity and centroid Euclidean distance) parameters. We demonstrated that these muscle representations are highly overlapped and similar in shape. The overlap degrees involving the forearm muscle were significantly higher than only among the intrinsic hand muscles. Moreover, the stimulation intensity had a stronger effect on the size compared to the topography parameters. Our study contributes to a more detailed cortical motor representation towards a synergistic, functional arrangement of M1. Understanding the muscle group coactivation may provide more accurate motor maps when delineating the eloquent brain tissue during pre-surgical planning.

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, non-negative 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.

A network information theoretic framework to characterise muscle synergies in space and time

Objective Current approaches to muscle synergy extraction rely on linear dimensionality reduction algorithms that make specific assumptions on the underlying signals. However, to capture nonlinear time varying, large-scale but also muscle-specific interactions, a more generalised approach is required. Approach Here we developed a novel framework for muscle synergy extraction that relaxes model assumptions by using a combination of information- and network theory and dimensionality reduction. We first quantify informational dynamics between muscles, time-samples or muscle-time pairings using a novel mutual information formulation. We then model these pairwise interactions as multiplex networks and identify modules representing the network architecture. We employ this modularity criterion as the input parameter for dimensionality reduction, which verifiably extracts the identified modules, and also to characterise salient structures within each module. Main results This novel framework captures spatial, temporal and spatiotemporal interactions across two benchmark datasets of reaching movements, producing distinct spatial groupings and both tonic and phasic temporal patterns. Readily interpretable muscle synergies spanning multiple spatial and temporal scales were identified, demonstrating significant task dependence, ability to capture trial-to-trial fluctuations and concordance across participants. Furthermore, our framework identifies submodular structures that represent the distributed networks of co-occurring signal interactions across scales. Significance The capabilities of this framework are illustrated through the concomitant continuity with previous research and novelty of the insights gained. Several previous limitations are circumvented including the extraction of functionally meaningful and multiplexed pairwise muscle couplings under relaxed model assumptions. The extracted synergies provide a holistic view of the movement while important details of task performance are readily interpretable. The identified muscle groupings transcend biomechanical constraints and the temporal patterns reveal characteristics of fundamental motor control mechanisms. We conclude that this framework opens new opportunities for muscle synergy research and can constitute a bridge between existing models and recent network-theoretic endeavours.

Simultaneous control of natural and extra degrees of freedom by isometric force and electromyographic activity in the muscle-to-force null space

OBJECTIVE

Muscle activation patterns in the muscle-to-force null space, i.e., patterns that do not generate task-relevant forces, may provide an opportunity for motor augmentation by allowing to control additional end-effectors simultaneously to natural limbs. Here we tested the feasibility of muscular null space control for augmentation by assessing simultaneous control of natural and extra degrees of freedom.

APPROACH

We instructed eight participants to control translation and rotation of a virtual 3D end-effector by simultaneous generation of isometric force at the hand and null space activity extracted in real-time from the electromyographic signals recorded from 15 shoulder and arm muscles. First, we identified the null space components that each participant could control more naturally by voluntary co-contraction. Then, participants performed several blocks of a reaching and holding task. They displaced an ellipsoidal cursor to reach one of nine targets by generating force, and simultaneously rotated the cursor to match the target orientation by activating null space components. We developed an information-theoretic metric, an index of difficulty defined as the sum of a spatial and a temporal term, to assess individual null space control ability for both reaching and holding.

MAIN RESULTS

On average, participants could reach the targets in most trials already in the first block (72%) and they improved with practice (maximum 93%) but holding performance remained lower (maximum 43%). As there was a high inter-individual variability in performance, we performed a simulation with different spatial and temporal task conditions to estimate those for which each individual participants would have performed best.

SIGNIFICANCE

Muscular null space control is feasible and may be used to control additional virtual or robotics end-effectors. However, decoding of motor commands must be optimized according to individual null space control ability.

Central nervous system physiology

This is the second chapter of the series on the use of clinical neurophysiology for the study of movement disorders. It focusses on methods that can be used to probe neural circuits in brain and spinal cord. These include use of spinal and supraspinal reflexes to probe the integrity of transmission in specific pathways; transcranial methods of brain stimulation such as transcranial magnetic stimulation and transcranial direct current stimulation, which activate or modulate (respectively) the activity of populations of central neurones; EEG methods, both in conjunction with brain stimulation or with behavioural measures that record the activity of populations of central neurones; and pure behavioural measures that allow us to build conceptual models of motor control. The methods are discussed mainly in relation to work on healthy individuals. Later chapters will focus specifically on changes caused by pathology.

Corticospinal populations broadcast complex motor signals to coordinated spinal and striatal circuits

Many models of motor control emphasize the role of sensorimotor cortex in movement, principally through the projections that corticospinal neurons (CSNs) make to the spinal cord. Additionally, CSNs possess expansive supraspinal axon collaterals, the functional organization of which is largely unknown. Using anatomical and electrophysiological circuit-mapping techniques in the mouse, we reveal dorsolateral striatum as the preeminent target of CSN collateral innervation. We found that this innervation is biased so that CSNs targeting different striatal pathways show biased targeting of spinal cord circuits. Contrary to more conventional perspectives, CSNs encode not only individual movements, but also information related to the onset and offset of motor sequences. Furthermore, similar activity patterns are broadcast by CSN populations targeting different striatal circuits. Our results reveal a logic of coordinated connectivity between forebrain and spinal circuits, where separate CSN modules broadcast similarly complex information to downstream circuits, suggesting that differences in postsynaptic connectivity dictate motor specificity.

Clarifying the Biomechanical Concept of Coordination Through Comparison With Coordination in Motor Control

Coordination is a multidisciplinary concept in human movement science, particularly in the field of biomechanics and motor control. However, the term is not used synonymously by researchers and has substantially different meanings depending on the studies. Therefore, it is necessary to clarify the meaning of coordination to avoid confusion. The meaning of coordination in motor control from computational and ecological perspectives has been clarified, and the meanings differed between them. However, in biomechanics, each study has defined the meaning of the term and the meanings are diverse, and no study has attempted to bring together the diversity of the meanings of the term. Therefore, the purpose of this study is to provide a summary of the different meanings of coordination across the theoretical landscape and clarify the meaning of coordination in biomechanics. We showed that in biomechanics, coordination generally means the relation between elements that act toward the achievement of a motor task, which we call biomechanical coordination. We also showed that the term coordination used in computational and ecological perspectives has two different meanings, respectively. Each one had some similarities with biomechanical coordination. The findings of this study lead to an accurate understanding of the concept of coordination, which would help researchers formulate their empirical arguments for coordination in a more transparent manner. It would allow for accurate interpretation of data and theory development. By comprehensively providing multiple perspectives on coordination, this study intends to promote coordination studies in biomechanics.

Intra-Subject and Inter-Subject Movement Variability Quantified with Muscle Synergies in Upper-Limb Reaching Movements

Quantifying movement variability is a crucial aspect for clinical and laboratory investigations in several contexts. However, very few studies have assessed, in detail, the intra-subject variability across movements and the inter-subject variability. Muscle synergies are a valuable method that can be used to assess such variability. In this study, we assess, in detail, intra-subject and inter-subject variability in a scenario based on a comprehensive dataset, including multiple repetitions of multi-directional reaching movements. The results show that muscle synergies are a valuable tool for quantifying variability at the muscle level and reveal that intra-subject variability is lower than inter-subject variability in synergy modules and related temporal coefficients, and both intra-subject and inter-subject similarity are higher than random synergy matching, confirming shared underlying control structures. The study deepens the available knowledge on muscle synergy-based motor function assessment and rehabilitation applications, discussing their applicability to real scenarios.

Emerging of new bioartificial corticospinal motor synergies using a robotic additional thumb

It is likely that when using an artificially augmented hand with six fingers, the natural five plus a robotic one, corticospinal motor synergies controlling grasping actions might be different. However, no direct neurophysiological evidence for this reasonable assumption is available yet. We used transcranial magnetic stimulation of the primary motor cortex to directly address this issue during motor imagery of objects’ grasping actions performed with or without the Soft Sixth Finger (SSF). The SSF is a wearable robotic additional thumb patented for helping patients with hand paresis and inherent loss of thumb opposition abilities. To this aim, we capitalized from the solid notion that neural circuits and mechanisms underlying motor imagery overlap those of physiological voluntary actions. After a few minutes of training, healthy humans wearing the SSF rapidly reshaped the pattern of corticospinal outputs towards forearm and hand muscles governing imagined grasping actions of different objects, suggesting the possibility that the extra finger might rapidly be encoded into the user’s body schema, which is integral part of the frontal-parietal grasping network. Such neural signatures might explain how the motor system of human beings is open to very quickly welcoming emerging augmentative bioartificial corticospinal grasping strategies. Such an ability might represent the functional substrate of a final common pathway the brain might count on towards new interactions with the surrounding objects within the peripersonal space. Findings provide a neurophysiological framework for implementing augmentative robotic tools in humans and for the exploitation of the SSF in conceptually new rehabilitation settings.

Flexible Recruitments of Fundamental Muscle Synergies in the Trunk and Lower Limbs for Highly Variable Movements and Postures

The extent to which muscle synergies represent the neural control of human behavior remains unknown. Here, we tested whether certain sets of muscle synergies that are fundamentally necessary across behaviors exist. We measured the electromyographic activities of 26 muscles, including bilateral trunk and lower limb muscles, during 24 locomotion, dynamic and static stability tasks, and we extracted the muscle synergies using non-negative matrix factorization. Our results show that 13 muscle synergies that may have unique functional roles accounted for almost all 24 tasks by combinations of single and/or merging of synergies. Therefore, our results may support the notion of the low dimensionality in motor outputs, in which the central nervous system flexibly recruits fundamental muscle synergies to execute diverse human behaviors. Further studies are required to validate the neural representation of the fundamental components of muscle synergies.

Linking Individual Movements to a Skilled Repertoire: Fast Modulation of Motor Synergies by Repetition of Stereotyped Movements

Motor skills emerge when practicing individual movements enables the motor system to extract building instructions that facilitate the generation of future diverse movements. Here we asked how practicing stereotyped movements for minutes affects motor synergies that encode human motor skills acquired over years of training. Participants trained a kinematically highly constrained combined index-finger and thumb movement. Before and after training, finger movements were evoked at rest by transcranial magnetic stimulation (TMS). Post-training, the angle between posture vectors describing TMS-evoked movements and the training movements temporarily decreased, suggesting the presence of a short-term memory for the trained movement. Principal component analysis was used to identify joint covariance patterns in TMS-evoked movements. The quality of reconstruction of training or grasping movements from linear combinations of a small subset of these TMS-derived synergies was used as an index of neural efficiency of movement generation. The reconstruction quality increased for the trained movement but remained constant for grasping movements. These findings suggest that the motor system rapidly reorganizes to enhance the coding efficiency of a difficult movement without compromising the coding efficiency of overlearned movements. Practice of individual movements may drive an unsupervised bottom-up process that ultimately shapes synergistic neuronal organization by constant competition of action memories.

The organizational principles of de-differentiated topographic maps in somatosensory cortex

Topographic maps are a fundamental feature of cortex architecture in the mammalian brain. One common theory is that the de-differentiation of topographic maps links to impairments in everyday behavior due to less precise functional map readouts. Here, we tested this theory by characterizing de-differentiated topographic maps in primary somatosensory cortex (SI) of younger and older adults by means of ultra-high resolution functional magnetic resonance imaging together with perceptual finger individuation and hand motor performance. Older adults' SI maps showed similar amplitude and size to younger adults' maps, but presented with less representational similarity between distant fingers. Larger population receptive field sizes in older adults' maps did not correlate with behavior, whereas reduced cortical distances between D2 and D3 related to worse finger individuation but better motor performance. Our data uncover the drawbacks of a simple de-differentiation model of topographic map function, and motivate the introduction of feature-based models of cortical reorganization.

Functional synergy recruitment index as a reliable biomarker of motor function and recovery in chronic stroke patients

Objective. Stroke affects the expression of muscle synergies underlying motor control, most notably in patients with poorer motor function. The majority of studies on muscle synergies have conventionally approached this analysis by assuming alterations in the inner structures of synergies after stroke. Although different synergy-based features based on this assumption have to some extent described pathological mechanisms in post-stroke neuromuscular control, a biomarker that reliably reflects motor function and recovery is still missing.Approach. Based on the theory of muscle synergies, we alternatively hypothesize that functional synergy structures are physically preserved and measure the temporal correlation between the recruitment profiles of healthy modules by paretic and healthy muscles, a feature hereafter reported as the FSRI. We measured clinical scores and extracted the muscle synergies of both ULs of 18 chronic stroke survivors from the electromyographic activity of 8 muscles during bilateral movements before and after 4 weeks of non-invasive BMI controlled robot therapy and physiotherapy. We computed the FSRI as well as features quantifying inter-limb structural differences and evaluated the correlation of these synergy-based measures with clinical scores.Main results. Correlation analysis revealed weak relationships between conventional features describing inter-limb synergy structural differences and motor function. In contrast, FSRI values during specific or combined movement data significantly correlated with UL motor function and recovery scores. Additionally, we observed that BMI-based training with contingent positive proprioceptive feedback led to improved FSRI values during the specific trained finger extension movement.Significance. We demonstrated that FSRI can be used as a reliable physiological biomarker of motor function and recovery in stroke, which can be targeted via BMI-based proprioceptive therapies and adjuvant physiotherapy to boost effective rehabilitation.

The Cortical Motor Areas and the Emergence of Motor Skills: A Neuroanatomical Perspective

What changes in neural architecture account for the emergence and expansion of dexterity in primates? Dexterity, or skill in performing motor tasks, depends on the ability to generate highly fractionated patterns of muscle activity. It also involves the spatiotemporal coordination of activity in proximal and distal muscles across multiple joints. Many motor skills require the generation of complex movement sequences that are only acquired and refined through extensive practice. Improvements in dexterity have enabled primates to manufacture and use tools and humans to engage in skilled motor behaviors such as typing, dance, musical performance, and sports. Our analysis leads to the following synthesis: The neural substrate that endows primates with their enhanced motor capabilities is due, in part, to (a) major organizational changes in the primary motor cortex and (b) the proliferation of output pathways from other areas of the cerebral cortex, especially from the motor areas on the medial wall of the hemisphere.

Approaches to revealing the neural basis of muscle synergies: a review and a critique

The central nervous system (CNS) may produce coordinated motor outputs via the combination of motor modules representable as muscle synergies. Identification of muscle synergies has hitherto relied on applying factorization algorithms to multimuscle electromyographic data (EMGs) recorded during motor behaviors. Recent studies have attempted to validate the neural basis of the muscle synergies identified by independently retrieving the muscle synergies through CNS manipulations and analytic techniques such as spike-triggered averaging of EMGs. Experimental data have demonstrated the pivotal role of the spinal premotor interneurons in the synergies' organization and the presence of motor cortical loci whose stimulations offer access to the synergies, but whether the motor cortex is also involved in organizing the synergies has remained unsettled. We argue that one difficulty inherent in current approaches to probing the synergies' neural basis is that the EMG generative model based on linear combination of synergies and the decomposition algorithms used for synergy identification are not grounded on enough prior knowledge from neurophysiology. Progress may be facilitated by constraining or updating the model and algorithms with knowledge derived directly from CNS manipulations or recordings. An investigative framework based on evaluating the relevance of neurophysiologically constrained models of muscle synergies to natural motor behaviors will allow a more sophisticated understanding of motor modularity, which will help the community move forward from the current debate on the neural versus nonneural origin of muscle synergies.

A randomized controlled trial on the effects induced by robot-assisted and usual-care rehabilitation on upper limb muscle synergies in post-stroke subjects

Muscle synergies are hypothesized to reflect connections among motoneurons in the spinal cord activated by central commands and sensory feedback. Robotic rehabilitation of upper limb in post-stroke subjects has shown promising results in terms of improvement of arm function and motor control achieved by reassembling muscle synergies into a set more similar to that of healthy people. However, in stroke survivors the potentially neurophysiological changes induced by robot-mediated learning versus usual care have not yet been investigated. We quantified upper limb motor deficits and the changes induced by rehabilitation in 32 post-stroke subjects through the movement analysis of two virtual untrained tasks of object placing and pronation. The sample analyzed in this study is part of a larger bi-center study and included all subjects who underwent kinematic analysis and were randomized into robot and usual care groups. Post-stroke subjects who followed robotic rehabilitation showed larger improvements in axial-to-proximal muscle synergies with respect to those who underwent usual care. This was associated to a significant improvement of the proximal kinematics. Both treatments had negative effects in muscle synergies controlling the distal district. This study supports the definition of new rehabilitative treatments for improving the neurophysiological recovery after stroke.

Muscles from the same muscle group do not necessarily share common drive: evidence from the human triceps surae

In this study, we demonstrated that the three muscles composing the human triceps surae share minimal common drive during isometric contractions. Our results suggest that reducing the number of effectively controlled degrees of freedom may not always be the strategy used by the central nervous system to control movements. Independent control of some, but not all, synergist muscles may allow for more flexible control to comply with secondary goals (e.g., joint stabilization).

Striatal bilateral control of skilled forelimb movement

Skilled motor behavior requires bihemispheric coordination, and participation of striatal outputs originating from two neuronal groups identified by distinctive expression of D1 or D2 dopamine receptors. We trained mice to reach for and grasp a single food pellet and determined how the output pathways differently affected forelimb trajectory and task efficiency. We found that inhibition and excitation of D1-expressing spiny projection neurons (D1SPNs) have a similar effect on kinematics results, as if excitation and inhibition disrupt the whole ensemble dynamics and not exclusively one kind of output. In contrast, D2SPNs participate in control of target accuracy. Further, ex vivo electrophysiological comparison of naive mice and mice exposed to the task showed stronger striatal neuronal connectivity for ipsilateral D1 and contralateral D2 neurons in relation to the paw used. In summary, while the output pathways work together to smoothly execute skill movements, practice of the movement itself changes synaptic patterns.

Primary hand motor representation areas in healthy children, preadolescents, adolescents, and adults

The development of the organization of the motor representation areas in children and adolescents is not well-known. This cross-sectional study aimed to provide an understanding for the development of the functional motor areas of the upper extremity muscles by studying healthy right-handed children (6-9 years, n = 10), preadolescents (10-12 years, n = 13), adolescents (15-17 years, n = 12), and adults (22-34 years, n = 12). The optimal representation site and resting motor threshold (rMT) for the abductor pollicis brevis (APB) were assessed in both hemispheres using navigated transcranial magnetic stimulation (nTMS). Motor mapping was performed at 110% of the rMT while recording the EMG of six upper limb muscles in the hand and forearm. The association between the motor map and manual dexterity (box and block test, BBT) was examined. The mapping was well-tolerated and feasible in all but the youngest participant whose rMT exceeded the maximum stimulator output. The centers-of-gravity (CoG) for individual muscles were scattered to the greatest extent in the group of preadolescents and centered and became more focused with age. In preadolescents, the CoGs in the left hemisphere were located more laterally, and they shifted medially with age. The proportion of hand compared to arm representation increased with age (p = 0.001); in the right hemisphere, this was associated with greater fine motor ability. Similarly, there was less overlap between hand and forearm muscles representations in children compared to adults (p<0.001). There was a posterior-anterior shift in the APB hotspot coordinate with age, and the APB coordinate in the left hemisphere exhibited a lateral to medial shift with age from adolescence to adulthood (p = 0.006). Our results contribute to the elucidation of the developmental course in the organization of the motor cortex and its associations with fine motor skills. It was shown that nTMS motor mapping in relaxed muscles is feasible in developmental studies in children older than seven years of age.

Forelimb force direction and magnitude independently controlled by spinal modules in the macaque

Studies in frogs and rodents have shown that to deal with the complexity of controlling all the muscles in the body the brain can activate sets of neurons in the spinal cord with a single signal. Here, we provide confirmation of a similar system of “modular” output in nonhuman primates. Costimulation at two spinal sites resulted in force field directionality that was the linear sum of the fields from each site. However, unlike the frog and rodent, the magnitude of the force vectors was greater than the simple sum (supralinear). Thus, while force direction in primates is controlled by the linear sum of modular output, force amplitude might be adjusted by additional sources shared by those modules.

Modular organization of the spinal motor system is thought to reduce the cognitive complexity of simultaneously controlling the large number of muscles and joints in the human body. Although modular organization has been confirmed in the hindlimb control system of several animal species, it has yet to be established in the forelimb motor system or in primates. Expanding upon experiments originally performed in the frog lumbar spinal cord, we examined whether costimulation of two sites in the macaque monkey cervical spinal cord results in motor activity that is a simple linear sum of the responses evoked by stimulating each site individually. Similar to previous observations in the frog and rodent hindlimb, our analysis revealed that in most cases (77% of all pairs) the directions of the force fields elicited by costimulation were highly similar to those predicted by the simple linear sum of those elicited by stimulating each site individually. A comparable simple summation of electromyography (EMG) output, especially in the proximal muscles, suggested that this linear summation of force field direction was produced by a spinal neural mechanism whereby the forelimb motor output recruited by costimulation was also summed linearly. We further found that the force field magnitudes exhibited supralinear (amplified) summation, which was also observed in the EMG output of distal forelimb muscles, implying a novel feature of primate forelimb control. Overall, our observations support the idea that complex movements in the primate forelimb control system are made possible by flexibly combined spinal motor modules.

From motor planning to execution: a sensorimotor loop perspective

How is an evanescent wish to move translated into a concrete action? This simple question and puzzling miracle remains a focal point of motor systems neuroscience. Where does the difficulty lie? A great deal has been known about biomechanics for quite some time. More recently, there have been significant advances in our understanding of how the spinal system is organized into modules corresponding to spinal synergies, which are fixed patterns of multimuscle recruitment. But much less is known about how the supraspinal system recruits these synergies in the correct spatiotemporal pattern to effectively control movement. We argue that what makes the problem of supraspinal control so difficult is that it emerges as a result of multiple convergent and redundant sensorimotor loops. Because these loops are convergent, multiple modes of information are mixed before being sent to the spinal system; because they are redundant, information is overlapping such that a mechanism must exist to eliminate the redundancy before the signal is sent to the spinal system. Given these complex interactions, simple correlation analyses between movement variables and neural activity are likely to render a confusing and inconsistent picture. Here, we suggest that the perspective of sensorimotor loops might help in achieving a better systems-level understanding. Furthermore, state-of-the-art techniques in neurotechnology, such as optogenetics, appear to be well suited for investigating the problem of motor control at the level of loops.

Quantal biomechanical effects in speech postures of the lips

The unique biomechanical and functional constraints on human speech make it a promising area for research investigating modular control of movement. The present article illustrates how a modular control approach to speech can provide insights relevant to understanding both motor control and observed variation across languages. We specifically explore the robust typological finding that languages produce different degrees of labial constriction using distinct muscle groupings and concomitantly distinct lip postures. Research has suggested that these lip postures exploit biomechanical regions of nonlinearity between neural activation and movement, also known as quantal regions, to allow movement goals to be realized despite variable activation signals. We present two sets of computer simulations showing that these labial postures can be generated under the assumption of modular control and that the corresponding modules are biomechanically robust: first to variation in the activation levels of participating muscles, and second to interference from surrounding muscles. These results provide support for the hypothesis that biomechanical robustness is an important factor in selecting the muscle groupings used for speech movements and provide insight into the neurological control of speech movements and how biomechanical and functional constraints govern the emergence of speech motor modules. We anticipate that future experimental work guided by biomechanical simulation results will provide new insights into the neural organization of speech movements.NEW & NOTEWORTHY This article provides additional evidence that speech motor control is organized in a modular fashion and that biomechanics constrain the kinds of motor modules that may emerge. It also suggests that speech can be a fruitful domain for the study of modularity and that a better understanding of speech motor modules will be useful for speech research. Finally, it suggests that biomechanical modeling can serve as a useful complement to experimental work when studying modularity.

Older adults reduce the complexity and efficiency of neuromuscular control to preserve walking balance

Healthy aging modifies neuromuscular control of dynamic balance. Challenging tasks could amplify such modifications, providing clinical insights. We examined the effects of age and walking condition difficulty on neuromuscular control of walking balance. We analyzed whole-body kinematics and activity of 13 right leg and trunk muscles in 17 young (11 males and 6 females; age 24 ± 3 years) and 14 older adults (3 males and 11 females; age 69 ± 4 years) while walking on a taped line on the floor and a 6-cm wide beam. Spatiotemporal parameters of gait, margin of stability, motor performance, and muscle synergies were estimated. Regardless of age, maintaining walking balance was more difficult on the beam compared to the taped line as evidenced by a shorter distance walked (17.3%), a reduction in step length (5.8%) and speed (10.3%), as well as a 40.0% smaller margin of stability during beam vs. tape walking. The number of muscle synergies was also higher during beam vs. tape walking. Compared to younger adults, older adults had larger margin of stability during beam walking. Older adults also had higher muscle co-activity within each muscle synergy and greater variance accounted for by the first muscle synergy regardless of condition. Such age-effects may be interpreted as a safer, less efficient, and less complex neuromuscular modular control strategy. In conclusion, beam walking increased the difficulty of maintaining walking balance and induced adaptations in modular control. It seems that healthy older adults reduce the complexity and efficiency of neuromuscular control of walking to preserve walking balance.

Unexpected complexity of everyday manual behaviors

How does the brain control an effector as complex and versatile as the hand? One possibility is that neural control is simplified by limiting the space of hand movements. Indeed, hand kinematics can be largely described within 8 to 10 dimensions. This oft replicated finding has been construed as evidence that hand postures are confined to this subspace. A prediction from this hypothesis is that dimensions outside of this subspace reflect noise. To address this question, we track the hand of human participants as they perform two tasks-grasping and signing in American Sign Language. We apply multiple dimension reduction techniques and replicate the finding that most postural variance falls within a reduced subspace. However, we show that dimensions outside of this subspace are highly structured and task dependent, suggesting they too are under volitional control. We propose that hand control occupies a higher dimensional space than previously considered.

Muscle Synergies in Parkinson's Disease

Over the last two decades, experimental studies in humans and other vertebrates have increasingly used muscle synergy analysis as a computational tool to examine the physiological basis of motor control. The theoretical background of muscle synergies is based on the potential ability of the motor system to coordinate muscles groups as a single unit, thus reducing high-dimensional data to low-dimensional elements. Muscle synergy analysis may represent a new framework to examine the pathophysiological basis of specific motor symptoms in Parkinson's disease (PD), including balance and gait disorders that are often unresponsive to treatment. The precise mechanisms contributing to these motor symptoms in PD remain largely unknown. A better understanding of the pathophysiology of balance and gait disorders in PD is necessary to develop new therapeutic strategies. This narrative review discusses muscle synergies in the evaluation of motor symptoms in PD. We first discuss the theoretical background and computational methods for muscle synergy extraction from physiological data. We then critically examine studies assessing muscle synergies in PD during different motor tasks including balance, gait and upper limb movements. Finally, we speculate about the prospects and challenges of muscle synergy analysis in order to promote future research protocols in PD.

Movement Decomposition in the Primary Motor Cortex

A complex action can be described as the composition of a set of elementary movements. While both kinematic and dynamic elements have been proposed to compose complex actions, the structure of movement decomposition and its neural representation remain unknown. Here, we examined movement decomposition by modeling the temporal dynamics of neural populations in the primary motor cortex of macaque monkeys performing forelimb reaching movements. Using a hidden Markov model, we found that global transitions in the neural population activity are associated with a consistent segmentation of the behavioral output into acceleration and deceleration epochs with directional selectivity. Single cells exhibited modulation of firing rates between the kinematic epochs, with abrupt changes in spiking activity timed with the identified transitions. These results reveal distinct encoding of acceleration and deceleration phases at the level of M1, and point to a specific pattern of movement decomposition that arises from the underlying neural activity. A similar approach can be used to probe the structure of movement decomposition in different brain regions, possibly controlling different temporal scales, to reveal the hierarchical structure of movement composition.

Spatially and Temporally Distinct Encoding of Muscle and Kinematic Information in Rostral and Caudal Primary Motor Cortex

The organizing principle of human motor cortex does not follow an anatomical body map, but rather a distributed representational structure in which motor primitives are combined to produce motor outputs. Electrophysiological recordings in primates and human imaging data suggest that M1 encodes kinematic features of movements, such as joint position and velocity. However, M1 exhibits well-documented sensory responses to cutaneous and proprioceptive stimuli, raising questions regarding the origins of kinematic motor representations: are they relevant in top-down motor control, or are they an epiphenomenon of bottom-up sensory feedback during movement? Here we provide evidence for spatially and temporally distinct encoding of kinematic and muscle information in human M1 during the production of a wide variety of naturalistic hand movements. Using a powerful combination of high-field functional magnetic resonance imaging and magnetoencephalography, a spatial and temporal multivariate representational similarity analysis revealed encoding of kinematic information in more caudal regions of M1, over 200 ms before movement onset. In contrast, patterns of muscle activity were encoded in more rostral motor regions much later after movements began. We provide compelling evidence that top-down control of dexterous movement engages kinematic representations in caudal regions of M1 prior to movement production.