Identification of muscle synergies associated with gait transition in humans

Hagio, Shota; Fukuda, Mitsutoshi; Kouzaki, Motoki

doi:10.3389/fnhum.2015.00048

Cited by 77 publications

(89 citation statements)

References 43 publications

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“…This can be interpreted as a reorganisation of muscular coordination patterns, which occurs at ID 5.1 in parallel to the phase transition in dynamical regime seen in behaviour. These changes in time-dependent activation profiles during a transition in movement are comparable to what was recently found by Hagio et al 27. and by Ivanenko and colleagues2829 who studied muscle synergies during gait transitions.…”

Section: Discussionsupporting

confidence: 89%

Functional coordination of muscles underlying changes in behavioural dynamics

Vernooij

Rao

Perdikis

et al. 2016

Sci Rep

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The dynamical systems approach addresses Bernstein’s degrees of freedom problem by assuming that the neuro-musculo-skeletal system transiently assembles and dismantles its components into functional units (or synergies) to meet task demands. Strikingly, little is known from a dynamical point of view about the functioning of the muscular sub-system in this process. To investigate the interaction between the dynamical organisation at muscular and behavioural levels, we searched for specific signatures of a phase transition in muscular coordination when a transition is displayed at the behavioural level. Our results provide evidence that, during Fitts’ task when behaviour switches to a different dynamical regime, muscular activation displays typical signatures of a phase transition; a reorganisation in muscular coordination patterns accompanied by a peak in the variability of muscle activation. This suggests that consistent changes occur in coordination processes across the different levels of description (i.e., behaviour and muscles). Specifically, in Fitts’ task, target size acts as a control parameter that induces a destabilisation and a reorganisation of coordination patterns at different levels of the neuro-musculo-skeletal system.

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Section: Discussionsupporting

confidence: 89%

Functional coordination of muscles underlying changes in behavioural dynamics

Vernooij

Rao

Perdikis

et al. 2016

Sci Rep

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“…In other words, five muscular synergies are sufficient to describe muscular coordination in Fitts' task, thereby suggesting a significant dimensional reduction of the muscular system independent of the ID. This result is consistent with those observed in previous studies examining different tasks (e.g., walking: Cappellini et al, 2006; reaching: d'Avella et al, 2008; gait transitions: Hagio et al, 2015; cycling: De Marchis et al, 2013). However, here we showed that (i) a change in the behavioral dynamics resulting from increasing accuracy constraints is associated with muscular reorganization, based on PCA analyses of the temporal activation patterns, and (ii) the repertoire of muscular activation patterns is modified and reduced over aging.…”

Section: Discussionsupporting

confidence: 92%

“…The reorganization, again, indicates that older adults start their reorganization at a lower ID than young adults do (old adults at ID 4.2, and young adults at ID 5.1). The appearance of alterations in temporal activation profiles only has been shown during phase transitions in gait (Ivanenko et al, 2004; Cappellini et al, 2006; Hagio et al, 2015). It can therefore be suggested that a phase transition in behavioral dynamics is initiated by a reorganization of the muscular system by means of altered phasing of muscular coordination patterns.…”

Section: Discussionmentioning

confidence: 99%

The Effect of Aging on Muscular Dynamics Underlying Movement Patterns Changes

Vernooij

Rao

Berton

et al. 2016

Front. Aging Neurosci.

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Introduction: Aging leads to alterations not only within the complex subsystems of the neuro-musculo-skeletal system, but also in the coupling between them. Here, we studied how aging affects functional reorganizations that occur both within and between the behavioral and muscular levels, which must be coordinated to produce goal-directed movements. Using unimanual reciprocal Fitts' task, we examined the behavioral and muscular dynamics of older adults (74.4 ± 3.7 years) and compared them to those found for younger adults (23.2 ± 2.0 years).Methods: To achieve this objective, we manipulated the target size to trigger a phase transition in the behavioral regime and searched for concomitant signatures of a phase transition in the muscular coordination. Here, muscular coordination was derived by using the method of muscular synergy extraction. With this technique, we obtained functional muscular patterns through non-negative matrix factorization of the muscular signals followed by clustering the resulting synergies.Results: Older adults showed a phase transition in behavioral regime, although, in contrast to young participants, their kinematic profiles did not show a discontinuity. In parallel, muscular coordination displayed two typical signatures of a phase transition, that is, increased variability of coordination patterns and a reorganization of muscular synergies. Both signatures confirmed the existence of muscular reorganization in older adults, which is coupled with change in dynamical regime at behavioral level. However, relative to young adults, transition occurred at lower index of difficulty (ID) in older participants and the reorganization of muscular patterns lasted longer (over multiple IDs).Discussion: This implies that consistent changes occur in coordination processes across behavior and muscle. Furthermore, the repertoire of muscular patterns was reduced and somewhat modified for older adults, relative to young participants. This suggests that aging is not only related to changes in individual muscles (e.g., caused by dynapenia) but also in their coordination.

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“…Previous empirical findings have demonstrated that complex activation of a large number of muscles could be adequately captured by the combination of a few modularly coordinated muscle activation patterns, the so-called muscle synergies [2][3][4][5][6]. Muscle synergies have been estimated based on the linear decomposition of muscle activation patterns in various tasks [6][7][8][9][10]. Moreover, several findings have shown that similar muscle synergies were extracted across behaviours with different biomechanical demands, indicating that muscle synergies underlying a complex motor repertoire were shared across different motor tasks [11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

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

Hagio

Kouzaki

2018

J. R. Soc. Interface.

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

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Identification of muscle synergies associated with gait transition in humans

Cited by 77 publications

References 43 publications

Functional coordination of muscles underlying changes in behavioural dynamics

Functional coordination of muscles underlying changes in behavioural dynamics

The Effect of Aging on Muscular Dynamics Underlying Movement Patterns Changes

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

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