Motor actions are associated with setting two types of variables by a controller, those that ultimately define average performance patterns and those that define associated synergies. These analysis results suggest that neural systems use muscle group combinations to solve motor control redundancy problems (muscle synergy hypothesis) and manipulate those basic patterns to. Here, we provide such a demonstration by using a motor control model with 69 parameters developed based on the muscle synergy hypothesis. This is particularly important in medical fields and especially in rehabilitation. In general, the results revealed that the noise and NoC affected the outputs of muscle synergy analysis, especially for noise. A limited number of muscles (eight muscles in this study) are enough to depict the variability of synergy structure. The principle of minimal final action is formulated as the guiding principle within the referent configuration hypothesis. The muscle synergies hypothesis suggests different strategies of the CNS to perform tasks with and without neurological conditions. The results suggest that, in the future muscle synergy analysis, it is not that more muscles are better. Merging these concepts into a single coherent scheme requires focusing on control variables rather than performance variables. A three-synergy model was chosen, because the fourth synergy explained less than 5 of variance across sets. Despite some minor differences in the timing of activation of some muscles in muscle synergy components, our hypothesis was globally verified.
The article offers a way to unite three recent developments in the field of motor control and coordination: (1) The notion of synergies is introduced based on the principle of motor abundance (2) The uncontrolled manifold hypothesis is described as offering a computational framework to identify and quantify synergies and (3) The equilibrium-point hypothesis is described for a single muscle, single joint, and multijoint systems. The muscle synergy hypothesis enables a large reduction in the number of model parameters due to the assumption of a low-dimensional structure at the motor-neuron activation level, which will accelerate modeling studies and increase their importance for understanding motor control strategies. We hypothesized that muscle synergies would be reliable both intra- and inter-day.
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