This brief review addresses two major aspects of the neural control of multi-element systems. First, theprinciple of abundance suggests that the central nervous system unites elements into synergies (co-variation ofelemental variables across trials quantified within the framework of the uncontrolled manifold hypothesis) that stabilizeimportant performance variables. Second, a novel method, analytical inverse optimization, has been introduced tocompute cost functions that define averaged across trials involvement of individual elements over a range of values oftask-specific performance variables. The two aspects reflect two features of motor coordination: (1) using variablesolutions that allow performing secondary tasks and stabilizing performance variables; and (2) selecting combinationsof elemental variables that follow an optimization principle. We suggest that the conflict between the two approaches (asingle solution vs. families of solutions) is apparent, not real. Natural motor variability may be due to using the samecost function across slightly different initial states; on the other hand, there may be variability in the cost function itselfleading to variable solutions that are all optimal with respect to slightly different cost functions. The analysis of motorsynergies has revealed specific changes associated with atypical development, healthy aging, neurological disorders, andpractice. These have allowed formulating hypotheses on the neurophysiological mechanisms involved in the synergiccontrol of actions.
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