Control of Fast-Reaching Movements by Muscle Synergy Combinations

By Andrea d'Avella, Alessandro Portone, Laure Fernandez, Francesco Lacquaniti. Journal of Neuroscience, 2006

715 citations recorded by the source corpus.

How the CNS selects the appropriate muscle patterns to achieve a behavioral goal is an open question. To gain insight into this process, we characterized the spatiotemporal organization of the muscle patterns for fast-reaching movements. We recorded electromyographic activity from up to 19 shoulder and arm muscles during point-to-point movements between a central location and 8 peripheral targets in each of 2 vertical planes. We used an optimization algorithm to identify a set of time-varying muscle synergies, i.e., the coordinated activations of groups of muscles with specific time-varying profiles. For each one of nine subjects, we extracted four or five synergies whose combinations, after scaling in amplitude and shifting in time each synergy independently for each movement condition, explained 73–82% of the data variation. We then tested whether these synergies could reconstruct the muscle patterns for point-to-point movements with different loads or forearm postures and for reversal and via-point movements. We found that reconstruction accuracy remained high, indicating generalization across these conditions. Finally, the synergy amplitude coefficients were directionally tuned according to a cosine function with a preferred direction that showed a smaller variability with changes of load, posture, and endpoint than the preferred direction of individual muscles. Thus the complex spatiotemporal characteristics of the muscles patterns for reaching were captured by the combinations of a small number of components, suggesting that the mechanisms involved in the generation of the muscle patterns exploit this low dimensionality to simplify control.

Subfields: Biomedical Engineering, Cognitive Neuroscience, Physical Therapy, Sports Therapy and Rehabilitation

View Paper: https://www.semanticscholar.org/paper/b707760f99fee06076586f022184414525ef3aa9

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Citations in the corpus

Neuromechanics of muscle synergies for posture and movement. (2007, background): “Studies of motor systems ranging from those of invertebrates to those of humans suggest that the nervous system uses flexible combinations of just a few muscle synergies – the elements from which complex muscle activation patterns are constructed – to produce a wide range of motor behaviors [1,2,3 ,”
Extracting Simultaneous and Proportional Neural Control Information for Multiple-DOF Prostheses From the Surface Electromyographic Signal (2009, methodology): “imal studies) or distantly separated surface electrodes (for human studies) [18], where crosstalk is negligible [26].”
Patterned control of human locomotion (2012, background): “…(Bizzi et al. 2008) to nociceptive wiping responses (Giszter et al. 2010), whole body postural responses (Ting & MacKay, 2007), arm reaching (d’Avella et al. 2006), hand manipulation (Soechting & Flanders, 2008), and in several other animal species in addition to humans (Gillner, 1985;…”
Principles of sensorimotor learning (2011, background): “The overall motor output will be the sum of all primitives, weighted by the level of the activation of each module 77 .”
Intrinsically Motivated Learning of Real-World Sensorimotor Skills with Developmental Constraints (2013, background): “, 1995), synergies for reaching with the hand (d’Avella et al., 2006), closing the fingers in a coordinated manner such as used in grasping (Weiss and Flanders, 2004), or of course skills such as breathing or swallowing (Dick et al.”
Common muscle synergies for balance and walking (2013, background): “COMPUTATIONAL NEUROSCIENCE ORIGINAL RESEARCH ARTICLE published: 02 May 2013 doi: 10.3389/fncom.2013.00048 Common muscle synergies for balance and walking”