title: Subject-specific muscle synergies in human balance control are consistent across different biomechanical contexts.
abstract: 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.
authors.affiliation: The Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech and Emory University, 313 Ferst Drive, Atlanta, GA 30322-0535, USA.
authors.forename: Gelsy
authors.initials: G
authors.lastname: Torres-Oviedo
authors.forename: Lena H
authors.initials: LH
authors.lastname: Ting
mesh_terms: D000465:Algorithms; D001696:Biomechanical Phenomena / Q000502:physiology; D004576:Electromyography / Q000379:methods; D006801:Humans; D007866:Leg / Q000294:innervation / Q000502:physiology; D008954:Models, Biological; D018482:Muscle, Skeletal / Q000502:physiology*; D004856:Postural Balance / Q000502:physiology*; D011187:Posture / Q000502:physiology*; D011999:Recruitment, Neurophysiological / Q000502:physiology*; D015203:Reproducibility of Results
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