![]() ![]() How does the CNS “choose” among the infinity of solutions of a given motor task (i.e., Bernstein problem) ( Bernstein, 1967)? How are motor intentions translated into muscle activations? How can biological systems learn and plan movements so rapidly? A prominent hypothesis suggests that motor circuitries are organized in a modular fashion, so that muscle activations can be realized by flexibly combining such modules. The complexity of the musculoskeletal apparatus as well as its dynamical properties allow biological systems to perform a wide variety of motor tasks ( Bizzi et al., 1992) on the other hand, such a complexity has to be mastered by efficient strategies implemented in the central nervous system (CNS). One of the fundamental questions in motor control concerns the mechanisms that underlie muscle contractions during the execution of movements. We suggest that synergy extraction methods should explicitly take into account task execution variables, thus moving from a perspective purely based on input-space to one grounded on task-space as well. This requirement is not always explicitly considered in experimental neuroscience, as muscle synergies are often estimated solely by analyzing recorded muscle activities. Moreover, it clarifies the importance of assessing the functional role of muscle synergies: although these basic modules are defined at the level of muscle activations (input-space), they should result in the effective accomplishment of the desired task. The comparison between these two lines of research, in particular their different goals and approaches, is instrumental to explain the computational implications of the hypothesized modular organization. We provide an overview of the methods that have been employed to test the validity of this scheme, and we show how the concept of muscle synergy has been generalized for the control of artificial agents. In particular, we refer to the hypothesis that the central nervous system (CNS) generates desired muscle contractions by combining a small number of predefined modules, called muscle synergies. In this paper we review the works related to muscle synergies that have been carried-out in neuroscience and control engineering. 6UR CIAMS, EA 4532 – Motor Control and Perception Team, Université Paris-Sud 11, Orsay, France.5Center for Nueorscience and Cognitive Systems Istituto Italiano di Tecnologia, Rovereto (TN), Italy.4Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, UK.3Communication, Computer and System Sciences Department, University of Genoa, Genoa, Italy.2RBCS, Italian Institute of Technology, Genoa.1Artificial Intelligence Laboratory, Department of Informatics, University of Zurich, Zurich, Switzerland.Cristiano Alessandro 1* Ioannis Delis 2,3,4 Francesco Nori 2 Stefano Panzeri 4,5 Bastien Berret 6 ![]()
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