Muscle Synergies Characterizing Human Postural Responses

2007 ◽  
Vol 98 (4) ◽  
pp. 2144-2156 ◽  
Author(s):  
Gelsy Torres-Oviedo ◽  
Lena H. Ting
Keyword(s):  
Postural Control ◽  
Muscle Activation ◽  
Muscle Synergies ◽  
Support Surface ◽  
Muscle Coordination ◽  
Natural Behavior ◽  
Activation Patterns ◽  
Muscle Activation Patterns ◽  
Postural Responses ◽  
Automatic Postural Responses

Postural control is a natural behavior that requires the spatial and temporal coordination of multiple muscles. Complex muscle activation patterns characterizing postural responses suggest the need for independent muscle control. However, our previous work shows that postural responses in cats can be robustly reproduced by the activation of a few muscle synergies. We now investigate whether a similar neural strategy is used for human postural control. We hypothesized that a few muscle synergies could account for the intertrial variability in automatic postural responses from different perturbation directions, as well as different postural strategies. Postural responses to multidirectional support-surface translations in 16 muscles of the lower back and leg were analyzed in nine healthy subjects. Six or fewer muscle synergies were required to reproduce the postural responses of each subject. The composition and temporal activation of several muscle synergies identified across all subjects were consistent with the previously identified “ankle” and “hip” strategies in human postural responses. Moreover, intertrial variability in muscle activation patterns was successfully reproduced by modulating the activity of the various muscle synergies. This suggests that trial-to-trial variations in the activation of individual muscles are correlated and, moreover, represent variations in the amplitude of descending neural commands that activate individual muscle synergies. Finally, composition and temporal activation of most of the muscle synergies were similar across subjects. These results suggest that muscle synergies represent a general neural strategy underlying muscle coordination in postural tasks.

Muscle Synergy Organization Is Robust Across a Variety of Postural Perturbations

2006 ◽  
Vol 96 (3) ◽  
pp. 1530-1546 ◽  
Author(s):  
Gelsy Torres-Oviedo ◽  
Jane M. Macpherson ◽  
Lena H. Ting
Keyword(s):  
Muscle Activation ◽  
Balance Control ◽  
Muscle Synergy ◽  
Muscle Synergies ◽  
Support Surface ◽  
Experimental Conditions ◽  
Activation Patterns ◽  
Muscle Activation Patterns ◽  
Postural Responses ◽  
Force Vectors

We recently showed that four muscle synergies can reproduce multiple muscle activation patterns in cats during postural responses to support surface translations. We now test the robustness of functional muscle synergies, which specify muscle groupings and the active force vectors produced during postural responses under several biomechanically distinct conditions. We aimed to determine whether such synergies represent a generalized control strategy for postural control or if they are merely specific to each postural task. Postural responses to multidirectional translations at different fore-hind paw distances and to multidirectional rotations at the preferred stance distance were analyzed. Five synergies were required to adequately reconstruct responses to translation at the preferred stance distance—four were similar to our previous analysis of translation, whereas the fifth accounted for the newly added background activity during quiet stance. These five control synergies could account for >80% total variability or r2 > 0.6 of the electromyographic and force tuning curves for all other experimental conditions. Forces were successfully reconstructed but only when they were referenced to a coordinate system that rotated with the limb axis as stance distance changed. Finally, most of the functional muscle synergies were similar across all of the six cats in terms of muscle synergy number, synergy activation patterns, and synergy force vectors. The robustness of synergy organization across perturbation types, postures, and animals suggests that muscle synergies controlling task-variables are a general construct used by the CNS for balance control.

scholarly journals Subject-Specific Muscle Synergies in Human Balance Control Are Consistent Across Different Biomechanical Contexts

2010 ◽  
Vol 103 (6) ◽  
pp. 3084-3098 ◽  
Author(s):  
Gelsy Torres-Oviedo ◽  
Lena H. Ting
Keyword(s):  
Muscle Activation ◽  
Balance Control ◽  
Nonnegative Matrix ◽  
The Body ◽  
Muscle Synergy ◽  
Muscle Synergies ◽  
Support Surface ◽  
Activation Patterns ◽  
Muscle Activation Patterns ◽  
Specific Muscle

The musculoskeletal redundancy of the body provides multiple solutions for performing motor tasks. We have proposed that the nervous system solves this unconstrained problem through the recruitment of motor modules or functional muscle synergies that map motor intention to action. Consistent with this hypothesis, we showed that trial-by-trial variations in muscle activation for multidirectional balance control in humans were constrained by a small set of muscle synergies. However, apparent muscle synergy structures could arise from characteristic patterns of sensory input resulting from perturbations or from low-dimensional optimal motor solutions. Here we studied electromyographic (EMG) responses for balance control across a range of biomechanical contexts, which alter not only the sensory inflow generated by postural perturbations, but also the muscle activation patterns used to restore balance. Support-surface translations in 12 directions were delivered to subjects standing in six different postural configurations: one-leg, narrow, wide, very wide, crouched, and normal stance. Muscle synergies were extracted from each condition using nonnegative matrix factorization. In addition, muscle synergies from the normal stance condition were used to reconstruct muscle activation patterns across all stance conditions. A consistent set of muscle synergies were recruited by each subject across conditions. When balance demands were extremely different from the normal stance (e.g., one-legged or crouched stance), task-specific muscle synergies were recruited in addition to the preexisting ones, rather generating de novo muscle synergies. Taken together, our results suggest that muscle synergies represent consistent motor modules that map intention to action, regardless of the biomechanical context of the task.

A Feedback Model Reproduces Muscle Activity During Human Postural Responses to Support-Surface Translations

2008 ◽  
Vol 99 (2) ◽  
pp. 1032-1038 ◽  
Author(s):  
Torrence D. J. Welch ◽  
Lena H. Ting
Keyword(s):  
Postural Control ◽  
Muscle Activity ◽  
Muscle Activation ◽  
Control Process ◽  
Temporal Patterns ◽  
Human Dimensions ◽  
Support Surface ◽  
Level Control ◽  
Muscle Activation Patterns ◽  
Postural Responses

Although feedback models have been used to simulate body motions in human postural control, it is not known whether muscle activation patterns generated by the nervous system during postural responses can also be explained by a feedback control process. We investigated whether a simple feedback law could explain temporal patterns of muscle activation in response to support-surface translations in human subjects. Previously, we used a single-link inverted-pendulum model with a delayed feedback controller to reproduce temporal patterns of muscle activity during postural responses in cats. We scaled this model to human dimensions and determined whether it could reproduce human muscle activity during forward and backward support-surface perturbations. Through optimization, we found three feedback gains (on pendulum acceleration, velocity, and displacement) and a common time delay that allowed the model to best match measured electromyographic (EMG) signals. For each muscle and each subject, the entire time courses of EMG signals during postural responses were well reconstructed in muscles throughout the lower body and resembled the solution derived from an optimal control model. In ankle muscles, >75% of the EMG variability was accounted for by model reconstructions. Surprisingly, >67% of the EMG variability was also accounted for in knee, hip, and pelvis muscles, even though motion at these joints was minimal. Although not explicitly required by our optimization, pendulum kinematics were well matched to subject center-of-mass (CoM) kinematics. Together, these results suggest that a common set of feedback signals related to task-level control of CoM motion is used in the temporal formation of muscle activity during postural control.

A Limited Set of Muscle Synergies for Force Control During a Postural Task

2005 ◽  
Vol 93 (1) ◽  
pp. 609-613 ◽  
Author(s):  
Lena H. Ting ◽  
Jane M. Macpherson
Keyword(s):  
Degrees Of Freedom ◽  
Neural Control ◽  
Muscle Activation ◽  
Balance Control ◽  
Computational Techniques ◽  
Muscle Synergies ◽  
Support Surface ◽  
Muscle Activation Patterns ◽  
Automatic Postural Response ◽  
Postural Responses

Recently developed computational techniques have been used to reduce muscle activation patterns of high complexity to a simple synergy organization and to bring new insights to the long-standing degrees of freedom problem in motor control. We used a nonnegative factorization approach to identify muscle synergies during postural responses in the cat and to examine the functional significance of such synergies for natural behaviors. We hypothesized that the simplification of neural control afforded by muscle synergies must be matched by a similar reduction in degrees of freedom at the biomechanical level. Electromyographic data were recorded from 8–15 hindlimb muscles of cats exposed to 16 directions of support surface translation. Results showed that as few as four synergies could account for >95% of the automatic postural response across all muscles and all directions. Each synergy was activated for a specific set of perturbation directions, and moreover, each was correlated with a unique vector of endpoint force under the limb. We suggest that, within the context of active balance control, postural synergies reflect a neural command signal that specifies endpoint force of a limb.

scholarly journals Lower complexity of motor primitives ensures robust control of high-speed human locomotion

2020 ◽  
Author(s):  
Alessandro Santuz ◽  
Antonis Ekizos ◽  
Yoko Kunimasa ◽  
Kota Kijima ◽  
Masaki Ishikawa ◽  
...  
Keyword(s):  
High Speed ◽  
Muscle Activation ◽  
Human Locomotion ◽  
Muscle Synergies ◽  
Activation Patterns ◽  
Motor Primitives ◽  
Muscle Activation Patterns ◽  
Relative Contribution ◽  
Muscle Activations ◽  
Low Dimensional

AbstractWalking and running are mechanically and energetically different locomotion modes. For selecting one or another, speed is a parameter of paramount importance. Yet, both are likely controlled by similar low-dimensional neuronal networks that reflect in patterned muscle activations called muscle synergies. Here, we investigated how humans synergistically activate muscles during locomotion at different submaximal and maximal speeds. We analysed the duration and complexity (or irregularity) over time of motor primitives, the temporal components of muscle synergies. We found that the challenge imposed by controlling high-speed locomotion forces the central nervous system to produce muscle activation patterns that are wider and less complex relative to the duration of the gait cycle. The motor modules, or time-independent coefficients, were redistributed as locomotion speed changed. These outcomes show that robust locomotion control at challenging speeds is achieved by modulating the relative contribution of muscle activations and producing less complex and wider control signals, whereas slow speeds allow for more irregular control.

scholarly journals Alterations in upper limb muscle synergy structure in chronic stroke survivors

2013 ◽  
Vol 109 (3) ◽  
pp. 768-781 ◽  
Author(s):  
Jinsook Roh ◽  
William Z. Rymer ◽  
Eric J. Perreault ◽  
Seng Bum Yoo ◽  
Randall F. Beer
Keyword(s):  
Muscle Activation ◽  
Isometric Force ◽  
Muscle Synergy ◽  
Muscle Synergies ◽  
Stroke Survivors ◽  
Activation Patterns ◽  
Force Matching ◽  
Muscle Activation Patterns ◽  
Anterior Deltoid ◽  
Arm Function

Previous studies in neurologically intact subjects have shown that motor coordination can be described by task-dependent combinations of a few muscle synergies, defined here as a fixed pattern of activation across a set of muscles. Arm function in severely impaired stroke survivors is characterized by stereotypical postural and movement patterns involving the shoulder and elbow. Accordingly, we hypothesized that muscle synergy composition is altered in severely impaired stroke survivors. Using an isometric force matching protocol, we examined the spatial activation patterns of elbow and shoulder muscles in the affected arm of 10 stroke survivors (Fugl-Meyer <25/66) and in both arms of six age-matched controls. Underlying muscle synergies were identified using non-negative matrix factorization. In both groups, muscle activation patterns could be reconstructed by combinations of a few muscle synergies (typically 4). We did not find abnormal coupling of shoulder and elbow muscles within individual muscle synergies. In stroke survivors, as in controls, two of the synergies were comprised of isolated activation of the elbow flexors and extensors. However, muscle synergies involving proximal muscles exhibited consistent alterations following stroke. Unlike controls, the anterior deltoid was coactivated with medial and posterior deltoids within the shoulder abductor/extensor synergy and the shoulder adductor/flexor synergy in stroke was dominated by activation of pectoralis major, with limited anterior deltoid activation. Recruitment of the altered shoulder muscle synergies was strongly associated with abnormal task performance. Overall, our results suggest that an impaired control of the individual deltoid heads may contribute to poststroke deficits in arm function.

scholarly journals Matrix Factorization Algorithms for the Identification of Muscle Synergies: Evaluation on Simulated and Experimental Data Sets

2006 ◽  
Vol 95 (4) ◽  
pp. 2199-2212 ◽  
Author(s):  
Matthew C. Tresch ◽  
Vincent C. K. Cheung ◽  
Andrea d'Avella
Keyword(s):  
Matrix Factorization ◽  
Muscle Activation ◽  
Nonnegative Matrix Factorization ◽  
Nonnegative Matrix ◽  
Muscle Synergies ◽  
Data Sets ◽  
Data Set ◽  
Activation Patterns ◽  
Muscle Activation Patterns ◽  
Factorization Algorithms

Several recent studies have used matrix factorization algorithms to assess the hypothesis that behaviors might be produced through the combination of a small number of muscle synergies. Although generally agreeing in their basic conclusions, these studies have used a range of different algorithms, making their interpretation and integration difficult. We therefore compared the performance of these different algorithms on both simulated and experimental data sets. We focused on the ability of these algorithms to identify the set of synergies underlying a data set. All data sets consisted of nonnegative values, reflecting the nonnegative data of muscle activation patterns. We found that the performance of principal component analysis (PCA) was generally lower than that of the other algorithms in identifying muscle synergies. Factor analysis (FA) with varimax rotation was better than PCA, and was generally at the same levels as independent component analysis (ICA) and nonnegative matrix factorization (NMF). ICA performed very well on data sets corrupted by constant variance Gaussian noise, but was impaired on data sets with signal-dependent noise and when synergy activation coefficients were correlated. Nonnegative matrix factorization (NMF) performed similarly to ICA and FA on data sets with signal-dependent noise and was generally robust across data sets. The best algorithms were ICA applied to the subspace defined by PCA (ICAPCA) and a version of probabilistic ICA with nonnegativity constraints (pICA). We also evaluated some commonly used criteria to identify the number of synergies underlying a data set, finding that only likelihood ratios based on factor analysis identified the correct number of synergies for data sets with signal-dependent noise in some cases. We then proposed an ad hoc procedure, finding that it was able to identify the correct number in a larger number of cases. Finally, we applied these methods to an experimentally obtained data set. The best performing algorithms (FA, ICA, NMF, ICAPCA, pICA) identified synergies very similar to one another. Based on these results, we discuss guidelines for using factorization algorithms to analyze muscle activation patterns. More generally, the ability of several algorithms to identify the correct muscle synergies and activation coefficients in simulated data, combined with their consistency when applied to physiological data sets, suggests that the muscle synergies found by a particular algorithm are not an artifact of that algorithm, but reflect basic aspects of the organization of muscle activation patterns underlying behaviors.

scholarly journals Sex-specific tuning of modular muscle activation patterns for locomotion in young and older adults

2021 ◽  
Author(s):  
Alessandro Santuz ◽  
Lars Janshen ◽  
Leon Bruell ◽  
Victor Munoz-Martel ◽  
Juri Taborri ◽  
...  
Keyword(s):  
Older Adults ◽  
Motor Control ◽  
Muscle Activation ◽  
Human Locomotion ◽  
Older Age ◽  
Modular Organization ◽  
Muscle Synergies ◽  
Activation Patterns ◽  
Motor Primitives ◽  
Muscle Activation Patterns

There is increasing evidence that including sex as a biological variable is of crucial importance to promote rigorous, repeatable and reproducible science. In spite of this, the body of literature that accounts for the sex of participants in human locomotion studies is small and often produces controversial results. Here, we investigated the modular organization of muscle activation patterns for human locomotion using the concept of muscle synergies with a double purpose: i) uncover possible sex-specific characteristics of motor control and ii) assess whether these are maintained in older age. We recorded electromyographic activities from 13 ipsilateral muscles of the lower limb in young and older adults of both sexes walking (young and old) and running (young) on a treadmill. The data set obtained from the 215 participants was elaborated through non-negative matrix factorization to extract the time-independent (i.e., motor modules) and time-dependent (i.e., motor primitives) coefficients of muscle synergies. We found sparse sex-specific modulations of motor control. Motor modules showed a different contribution of hip extensors, knee extensors and foot dorsiflexors in various synergies. Motor primitives were wider (i.e., lasted longer) in males in the propulsion synergy for walking (but only in young and not in older adults) and in the weight acceptance synergy for running. Moreover, the complexity of motor primitives was similar in younger adults of both sexes, but lower in older females as compared to older males. In essence, our results revealed the existence of small but defined sex-specific differences in the way humans control locomotion and that these strategies are not entirely maintained in older age.

scholarly journals The effect of hyper-pronated foot on postural control and ankle muscle activity during running and cutting movement

2020 ◽  
Vol 14 (4) ◽  
pp. 216-220
Author(s):  
Zahed Mantashloo ◽  
Heydar Sadeghi ◽  
Mehdi Khaleghi Tazji ◽  
Vanessa Rice ◽  
Elizabeth J Bradshaw
Keyword(s):  
Postural Control ◽  
Muscle Activity ◽  
Muscle Activation ◽  
Cross Sectional Study ◽  
The Body ◽  
Lateral Direction ◽  
Cross Sectional ◽  
Activation Patterns ◽  
Muscle Activation Patterns ◽  
Ankle Muscle

Objective: The aim of this study was to examine the effect of hyper pronated foot on postural control and ankle muscle activity during running and cutting movement (v-cut). Methods: In this Cross-Sectional study, 42 young physically active (exercising three times per week regularly) males participated in this study, including 21 with hyper-pronated feet and 21 with normal feet. Each participant completed a running and cutting task. Body postural control was measured using a force platform (1000Hz) which was synchronized with surface electromyography of selected ankle muscles. MATLAB software was used to process and analyze the data. One-away ANOVA was used to identify any differences between groups. Results: Differing muscle activation patterns in the surrounding ankle musculature (tibialis anterior, peroneus longus) through to reduced postural stability in the medial-lateral direction and increased vertical ground reaction forces were observed between groups. Conclusion: According to the obtained results it seems that subtalar hyper-pronation can be regarded as a factor affecting the biomechanics of cutting by changing activation patterns of the muscles surrounding the ankle, and reducing postural control of the body in medial-lateral direction, but not in anterior-posterior direction.

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