'Muscle synergies for modular and adaptive human motor control'

Learning Centre UG09
Life and Environmental Sciences, Research
Tuesday 26th November 2013 (15:00-16:00)
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For more information please contact Contact: Dr Ulrik Beierholm (u.beierholm@bham.ac.uk).

Part of the School Seminar Series

Speaker: Dr Andrea d'Avella, Santa Lucia Foundation, Rome, Italy

Host: Orna Rosenthal, Special CN-CR seminar

Abstract: A fundamental challenge in neuroscience is understanding how the central nervous system (CNS) acquires and controls complex motor skills that require coordinating a large number of degrees-of-freedom. A long standing hypothesis is that the CNS relies on a modular architecture to simplify motor control and skill learning. Evidence for modularity has come from the observation of regularities in the spatiotemporal organization of the muscle activation patterns recorded in different species, behaviors, and conditions. For example, a large fraction of the variation in the muscle patterns recorded in humans subjects during reaching and catching is captured by the linear combination of a small number of muscle synergies, coordinated activations of groups of muscles. These results suggest that muscle synergies are basic modules providing a low-dimensional representation of the motor commands that exploits the inherent structure of the musculoskeletal system and of the motor tasks. However, whether muscle synergies are only a parsimonious description of the regularities of the control policies’ output rather than a key feature of their neural organization is still debated. A novel experimental approach in which human subjects use myoelectric control to move a mass in a virtual environment has now provided direct evidence for modularity. By altering the mapping between recorded muscle activity and simulated force applied on the mass, as in a complex surgical rearrangement of the tendons, it has been possible to test the prediction that in a truly modular controller it must be harder to adapt to perturbations that are incompatible with the modules. After identifying muscle synergies, two types of virtual surgeries were performed. 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 were required. As predicted by modularity, adaptation after compatible surgeries was found to be faster than after incompatible ones. These results indicate that muscle synergies are basic structural elements of a modular and adaptive control architecture.