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• W4288077830 abstract "ABSTRACT Understanding how the central nervous system coordinates diverse motor outputs has been a topic of extensive investigation. While it is generally accepted that a small set of synergies underlies many common activities, such as walking, whether synergies are equally robust across a broader array of gait patterns or can be flexibly modified remains unclear. Here, we evaluated the extent to which synergies changed as nondisabled adults (n = 14) explored gait patterns using custom biofeedback. Secondarily, we used Bayesian Additive Regression Trees to identify factors which were predictive of synergy modulation. Participants performed 41.1 ± 8.0 gait patterns using biofeedback, during which synergy recruitment changed depending on the type and magnitude of gait pattern modification. Specifically, a consistent set of synergies was recruited to accommodate small deviations from baseline, but additional synergies emerged for larger gait changes. Synergy complexity was similarly modulated; complexity decreased for 82.6% of the attempted gait patterns, however, distal gait mechanics were highly predictive of these changes. In particular, greater ankle dorsiflexion moments and knee flexion through stance, as well as greater knee extension moments at initial contact corresponded to a reduction in synergy complexity. Taken together, these results suggest that the central nervous system preferentially adopts a low-dimensional, largely invariant control strategy, but can modify that strategy to produce diverse gait patterns. Beyond improving understanding of how synergies are recruited during gait, study outcomes may also help identify parameters that can be targeted with interventions to alter synergies and improve motor control following neurological injury." @default.
• W4288077830 created "2022-07-28" @default.
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• W4288077830 date "2022-07-27" @default.
• W4288077830 modified "2023-10-16" @default.
• W4288077830 title "Muscle synergies are flexibly recruited during gait pattern exploration using motor control-based biofeedback" @default.
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• W4288077830 doi "https://doi.org/10.1101/2022.07.25.501482" @default.
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