There is no theoretical or empirical evidence to suggest how the central nervous system (CNS) controls a variety of muscles associated with gait transition between walking and running. Here, we examined the motor control during a gait transition based on muscle synergies, which modularly organize functionally similar muscles. To this end, the subjects walked or ran on a treadmill and performed a gait transition spontaneously as the treadmill speed increased or decreased (a changing speed condition) or voluntarily following an experimenter’s instruction at constant treadmill speed (a constant speed condition). Surface electromyograms (EMGs) were recorded from 11 lower limb muscles bilaterally. We then extracted the muscle weightings of synergies and their activation coefficients from the EMG data using non-negative matrix factorization. As a result, the gait transition was controlled by approximately 9 muscle synergies, which were common during a walking and running, and their activation profiles were changed before and after a gait transition. Near a gait transition, the peak activation phases of the synergies, which were composed of plantar flexor muscles, were shifted to an earlier phase at the walk-to-run transition, and vice versa. The shifts were gradual in the changing speed condition, but an abrupt change was observed in the constant speed condition. These results suggest that the CNS low-dimensionally regulate the activation profiles of the specific synergies based on afferent information (spontaneous gait transition) or by changing only the descending neural input to the muscle synergies (voluntary gait transition) to achieve a gait transition.
To simplify redundant motor control, the central nervous system (CNS) may modularly organize and recruit groups of muscles as "muscle synergies." However, smooth and efficient movements are expected to require not only low-dimensional organization, but also flexibility in the recruitment or combination of synergies, depending on force-generating capability of individual muscles. In this study, we examined how the CNS controls activations of muscle synergies as changing joint angles. Subjects performed multidirectional isometric force generations around right ankle and extracted the muscle synergies using nonnegative matrix factorization across various knee and hip joint angles. As a result, muscle synergies were selectively recruited with merging or decomposition as changing the joint angles. Moreover, the activation profiles, including activation levels and the direction indicating the peak, of muscle synergies across force directions depended on the joint angles. Therefore, we suggested that the CNS selects appropriate muscle synergies and controls their activation patterns based on the force-generating capability of muscles with merging or decomposing descending neural inputs.
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