Deep brain stimulation and motor synergies in Parkinson's disease

urrent motor control theories postulate the existence of motor synergies, consisting of neural ensembles in the central nervous system (CNS), capable of coordinating multiple causal variables (e.g. single motor unit activation, joint torques, etc.) into task-specific functional groups, towards the goal of stabilizing the effects on salient performance variables (e.g., resultant force during grasping). Among different computational methods that experimentally analyze human motor synergies, the uncontrolled manifold (UCM) theory assumes that the CNS leaves some redundant causal variables to vary uncontrolled in a “permission range”, so that the overall variance of the performance variable remains acceptable. Accordingly, by acting through motor synergies (exact combinations of these causal variables), the CNS stabilizes either the value or time profile of the specific performance variable, minimizing the computational effort (Latash, 2016).