Whether the nervous system relies on modularity to simplify acquisition and control of complex motor skills remains controversial. To date, evidence for modularity has been indirect, based on statistical regularities in the motor commands captured by muscle synergies. Here we provide direct evidence by testing the prediction that in a truly modular controller it must be harder to adapt to perturbations that are incompatible with the modules. We investigated a reaching task in which human subjects used myoelectric control to move a mass in a virtual environment. In this environment we could perturb the normal muscle-to-force mapping, as in a complex surgical rearrangement of the tendons, by altering the mapping between recorded muscle activity and simulated force applied on the mass. After identifying muscle synergies, we performed two types of virtual surgeries. After compatible virtual surgeries, a full range of movements could still be achieved recombining the synergies, whereas after incompatible virtual surgeries, new or modified synergies would be required. Adaptation rates after the two types of surgery were compared. If synergies were only a parsimonious description of the regularities in the muscle patterns generated by a nonmodular controller, we would expect adaptation rates to be similar, as both types of surgeries could be compensated with similar changes in the muscle patterns. In contrast, as predicted by modularity, we found strikingly faster adaptation after compatible surgeries than after incompatible ones. These results indicate that muscle synergies are key elements of a modular architecture underlying motor control and adaptation.
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