Functional muscle synergies constrain force production during postural tasks

McKay, J. Lucas; Ting, Lena H.

doi:10.1016/j.jbiomech.2007.09.012

Cited by 58 publications

(60 citation statements)

References 44 publications

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“…Under this hypothesis, the motivation for a set of muscle synergies is to ensure that joint torques can be produced in all directions (see Methods). Such a hypothesis is related to the ''feasible force sets'' raised in considerations of muscle actions (25,26). For each JT synergy, we found the most similar experimental synergy (see Fig.…”

Section: Overviewmentioning

confidence: 56%

Simplified and effective motor control based on muscle synergies to exploit musculoskeletal dynamics

Berniker

Jarc

Bizzi

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

154

155

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The basic hypothesis of producing a range of behaviors using a small set of motor commands has been proposed in various forms to explain motor behaviors ranging from basic reflexes to complex voluntary movements. Yet many fundamental questions regarding this long-standing hypothesis remain unanswered. Indeed, given the prominent nonlinearities and high dimensionality inherent in the control of biological limbs, the basic feasibility of a lowdimensional controller and an underlying principle for its creation has remained elusive. We propose a principle for the design of such a controller, that it endeavors to control the natural dynamics of the limb, taking into account the nature of the task being performed. Using this principle, we obtained a low-dimensional model of the hindlimb and a set of muscle synergies to command it. We demonstrate that this set of synergies was capable of producing effective control, establishing the viability of this muscle synergy hypothesis. Finally, by combining the low-dimensional model and the muscle synergies we were able to build a relatively simple controller whose overall performance was close to that of the system's full-dimensional nonlinear controller. Taken together, the results of this study establish that a low-dimensional controller is capable of simplifying control without degrading performance.low-dimensional ͉ optimal control ͉ muscle pattern ͉ frog ͉ computational model C ontrolling any movement, whether it be a stereotyped reflex or a sophisticated skill, is highly complex. Fundamentally, every movement requires the detailed specification of a vast number of variables, potentially involving many thousands of motor units distributed throughout the limbs and body. Further, the relationship between these variables and the intended motion of the body is nontrivial, dictated by the intricate nonlinear dynamics of the musculoskeletal system. Elucidating control strategies that can overcome these complexities is a central issue in the neural control of movement.Many investigators have suggested that the central nervous system (CNS) might have developed strategies to simplify the control of movement (1-6). According to one common proposal, the CNS might produce movement through the flexible combination of ''muscle synergies,'' with each such synergy specifying a particular balance of activation across a set of muscles (7-16). By reducing the number of controlled variables, such a lowdimensional control strategy would simplify the production of movement.Although many experiments have found evidence to suggest that many behaviors can be produced through combinations of muscle synergies, several questions concerning this hypothesis remain unresolved. Foremost among these questions is a proof of the concept's viability: can a low-dimensional control scheme based on muscle synergies reproduce the range of observed behaviors with negligible loss of efficacy? Given the nonlinearities and high dimensionality inherent in biological motor control, the answer to this question is not ...

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Section: Overviewmentioning

confidence: 56%

Simplified and effective motor control based on muscle synergies to exploit musculoskeletal dynamics

Berniker

Jarc

Bizzi

et al. 2009

Proc. Natl. Acad. Sci. U.S.A.

154

155

View full text Add to dashboard Cite

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“…The force constraint phenomenon disappears in animals constrained to stand with very narrow stances, and becomes exaggerated at long interpaw distances. This does not appear to be a consequence of mechanical constraints in the hindlimb at difference stance lengths, as the feasible force set maintains its shape at different inter-paw distances (McKay and Ting, 2008), but may reflect mechanical constraints emerging from interaction among the limbs or changes in the neural strategy of standing. Our simulations have not investigated other stance lengths, and it is not clear whether nonlinear simulation would reveal constraints not apparent in the linear analysis of McKay and Ting (McKay and Ting, 2008).…”

Section: Neural Contributions To Force Constraintmentioning

confidence: 94%

“…There are deviations between the simulated and experimental results, including differences in force magnitude and asymmetry in the experimental response direction. The degree to which these reflect interaction among the four limbs and body of the experiments, neural constraints or an active neural strategy McKay and Ting, 2008) remains to be seen.…”

Section: Neural Contributions To Force Constraintmentioning

confidence: 99%

“…Constraining force production may represent a simplifying neural strategy that limits functional neuromuscular redundancy (Macpherson and Fung, 1999;McKay and Ting, 2008). Damage to the central or peripheral nervous systems results in substantial deficits in balance control and force constraint (Deliagina et al, 2007;Macpherson et al, 2007;Macpherson and Fung, 1999).…”

Section: Introductionmentioning

confidence: 99%

“…Using a static musculoskeletal model of the cat hindlimb, we showed that the feasible force set (FFS) in the cat hindlimb is directionally biased not toward the CoM but in the anterior-posterior direction . However, constraining muscle activation to a limited set of experimentally derived muscle synergies does bias the FFS toward the CoM (McKay and Ting, 2008). This suggested that the nervous system can counteract an anatomical bias in force direction and superimpose its own directional constraint during postural responses to perturbation.…”

Section: Introductionmentioning

confidence: 99%

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Directional constraint of endpoint force emerges from hindlimb anatomy

Bunderson

McKay

Ting

et al. 2010

Journal of Experimental Biology

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SUMMARYPostural control requires the coordination of force production at the limb endpoints to apply an appropriate force to the body. Subjected to horizontal plane perturbations, quadruped limbs stereotypically produce force constrained along a line that passes near the center of mass. This phenomenon, referred to as the force constraint strategy, may reflect mechanical constraints on the limb or body, a specific neural control strategy or an interaction among neural controls and mechanical constraints. We used a neuromuscular model of the cat hindlimb to test the hypothesis that the anatomical constraints restrict the mechanical action of individual muscles during stance and constrain the response to perturbations to a line independent of perturbation direction. In a linearized neuromuscular model of the cat hindlimb, muscle lengthening directions were highly conserved across 10,000 different muscle activation patterns, each of which produced an identical, stance-like endpoint force. These lengthening directions were closely aligned with the sagittal plane and reveal an anatomical structure for directionally constrained force responses. Each of the 10,000 activation patterns was predicted to produce stable stance based on Lyapunov stability analysis. In forward simulations of the nonlinear, seven degree of freedom model under the action of 200 random muscle activation patterns, displacement of the endpoint from its equilibrium position produced restoring forces, which were also biased toward the sagittal plane. The single exception was an activation pattern based on minimum muscle stress optimization, which produced destabilizing force responses in some perturbation directions. The sagittal force constraint increased during simulations as the system shifted from an inertial response during the acceleration phase to a viscoelastic response as peak velocity was obtained. These results qualitatively match similar experimental observations and suggest that the force constraint phenomenon may result from the anatomical arrangement of the limb.

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Review and perspective: neuromechanical considerations for predicting muscle activation patterns for movement

Ting

Chvatal

Safavynia

et al. 2012

Numer Methods Biomed Eng

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Muscle coordination may be difficult or impossible to predict accurately based on biomechanical considerations alone due to redundancy in the musculoskeletal system. Because many solutions exist for any given movement, the role of the nervous system in further constraining muscle coordination patterns for movement must be considered in both healthy and impaired motor control. Based on computational neuromechanical analyses of experimental data combined with modeling techniques, we have demonstrated several such neural constraints on the temporal and spatial patterns of muscle activity during both locomotion and postural responses to balance perturbations. We hypothesize that subject-specific as well as trial-by-trial differences in muscle activation can be parameterized and understood by a hierarchical and low-dimensional framework that reflects the neural control of task-level goals. In postural control, we demonstrate that temporal patterns of muscle activity may be governed by feedback control of task-level variables that represent the overall goal-directed motion of the body. These temporal patterns then recruit spatially-fixed patterns of muscle activity called muscle synergies that produce the desired task-level biomechanical functions that require multi-joint coordination. Moreover, these principles apply more generally to movement, and in particular to locomotor tasks in both healthy and impaired individuals. Overall, understanding the goals and organization of the neural control of movement may provide useful reduced dimension parameter sets to address the degrees-of-freedom problem in musculoskeletal movement control. More importantly, however, neuromechanical analyses may lend insight and provide a framework for understanding subject-specific and trial-by-trial differences in movement across both healthy and motor-impaired populations.

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Functional muscle synergies constrain force production during postural tasks

Cited by 58 publications

References 44 publications

Simplified and effective motor control based on muscle synergies to exploit musculoskeletal dynamics

Simplified and effective motor control based on muscle synergies to exploit musculoskeletal dynamics

Directional constraint of endpoint force emerges from hindlimb anatomy

Review and perspective: neuromechanical considerations for predicting muscle activation patterns for movement

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