Abstract
We accept two axioms: (1) the central nervous system is a physical/physiological object, not a computational one, and (2) the neural control of natural voluntary movements is organized in a hierarchical way. At the top level of the hierarchy, referent values for a few salient, task-specific variables are reflected in a set of neural signals (possibly, subthreshold depolarization levels of neuronal pools). Further, as a result of a sequence of few-to-many mappings, these signals result in sets of activation thresholds of the alpha-motoneuronal pools for the many muscles involved in the planned movement. This scheme naturally results in synergies stabilizing the values (time profiles) of task-specific, salient variables. In this context, “synergies” are defined as covaried across repetitive trials adjustments within a redundant set of elemental variables that ensure stability of a performance variable to which they all contribute. Several consequences of this scheme have received experimental support in recent studies. In particular, a novel phenomenon of feed-forward motor control, anticipatory synergy adjustments, has been discovered. Another nontrivial prediction of this scheme is that transient perturbations are expected to lead to equifinality at the level of task–relevant variables, but not necessarily at the level of elemental variables. Results of two recent experiments have confirmed this prediction for multi-joint positional tasks and multi-digit force production tasks. These results provide direct support for the ideas of control with referent configurations organized into a hierarchical system.
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Preparation of this paper was in part supported by NIH grants NS-035032 and AR-048563.
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Latash, M. (2014). Motor Control: On the Way to Physics of Living Systems. In: Levin, M. (eds) Progress in Motor Control. Advances in Experimental Medicine and Biology, vol 826. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-1338-1_1
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