Abstract
Muscle synergies have been proposed as a way for the central nervous system (CNS) to simplify the generation of motor commands and they have been shown to explain a large fraction of the variation in the muscle patterns across a variety of conditions. However, whether human subjects are able to control forces and movements effectively with a small set of synergies has not been tested directly. Here we show that muscle synergies can be used to generate target forces in multiple directions with the same accuracy achieved using individual muscles. We recorded electromyographic (EMG) activity from 13 arm muscles and isometric hand forces during a force reaching task in a virtual environment. From these data we estimated the force associated to each muscle by linear regression and we identified muscle synergies by non-negative matrix factorization. We compared trajectories of a virtual mass displaced by the force estimated using the entire set of recorded EMGs to trajectories obtained using 4–5 muscle synergies. While trajectories were similar, when feedback was provided according to force estimated from recorded EMGs (EMG-control) on average trajectories generated with the synergies were less accurate. However, when feedback was provided according to recorded force (force-control) we did not find significant differences in initial angle error and endpoint error. We then tested whether synergies could be used as effectively as individual muscles to control cursor movement in the force reaching task by providing feedback according to force estimated from the projection of the recorded EMGs into synergy space (synergy-control). Human subjects were able to perform the task immediately after switching from force-control to EMG-control and synergy-control and we found no differences between initial movement direction errors and endpoint errors in all control modes. These results indicate that muscle synergies provide an effective strategy for motor coordination.
Highlights
How the central nervous system (CNS) coordinates a large number of muscles to control forces and movements is a long standing issue in neuroscience
As in many previous studies, we found that a small number of muscle synergies explained a large fraction of the variation of the muscle patterns recorded during different task conditions
We focused on the question whether a small number of muscle synergies can accurately generate the forces involved in the task and, whether muscle synergies can be used to perform the task effectively
Summary
How the CNS coordinates a large number of muscles to control forces and movements is a long standing issue in neuroscience. A small number of muscle synergies, identified by multidimensional factorization techniques such as non-negative matrix factorization (NMF) (Lee and Seung, 1999), independent component analysis (ICA) (Bell and Sejnowski, 1995), and other iterative algorithms (d’Avella and Tresch, 2002; Tresch et al, 2006; Omlor and Giese, 2011), have been shown to explain a large fraction of the variation in the muscle patterns in a variety of vertebrate species (Tresch et al, 1999; Saltiel et al, 2001; d’Avella et al, 2003; Hart and Giszter, 2004; Ivanenko et al, 2004; Cheung et al, 2005; Ting and Macpherson, 2005), across different behaviors and experimental conditions (d’Avella and Bizzi, 2005; Cappellini et al, 2006; d’Avella et al, 2006, 2008, 2011; Ivanenko et al, 2007; Torres-Oviedo and Ting, 2007; Overduin et al, 2008; Torres-Oviedo and Ting, 2010; Dominici et al, 2011; Hug et al, 2011; Chvatal and Ting, 2012; Frere and Hug, 2012; Roh et al, 2012; Chvatal and Ting, 2013; d’Andola et al, 2013; Gentner et al, 2013) These observations provide support to the existence of muscle synergies as neural control strategy employed by the CNS for motor coordination. In order to validate muscle synergies as a neural control strategy their functional consequences need to be investigated
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