dynamic synergy center for optimal wellness

In time-dependent formulations, muscle synergy constitutes the coordinated activations of groups of muscles with fixed time-varying profiles ( D'Avella et al., 2006). Muscle synergy is defined by using several modules formulated by either time-dependent or time-independent parameters. The notion of muscle synergy is introduced to simplify the computational mechanism between the CNS and muscle control ( Popovic and Popovic, 2001 Cirstea et al., 2003 D'Avella et al., 2003 Krishnamoorthy et al., 2003 Sohn and Hallett, 2004 Tresch and Jarc, 2009 Clark et al., 2010 Safavynia et al., 2011 Cheung et al., 2012). In this paper, we discuss this scenario and demonstrate through experiments that the CNS can create an optimal set of efficient behaviors through behavior training. In such a scenario, the redundancy of the musculoskeletal system contributes toward creating a suitable set depending on the environment. Choosing the behavior from a smaller set would allow the CNS to control the behavior with less redundancy. One possible mechanism for choosing a proper behavior from the numerous options is that through behavior training, the CNS narrows down the redundancy of the options to a smaller set. Many researches have attempted to clarify the computational mechanism employed by the CNS for behavior selection by introducing the optimal parameters of behavior control ( Flash and Hogan, 1985 Uno et al., 1989 Alexander, 1997), the principles of biological controllers ( Tanaka and Kimura, 2008 Shimoda and Kimura, 2010 Shimoda et al., 2013) and other methods, but this problem remains an open research topic. Owing to redundancy in the human musculoskeletal system, the CNS can choose the most efficient movements from an infinite number of behavior options ( Bernstein, 1967 Sporns and Edelman, 1993). Human behaviors are a result of complex neural dynamics between the central nervous system (CNS), proprioceptors, and muscles. These results suggest that the CNS has the ability to create optimal sets of efficient behaviors by optimizing the size of the synergy space at the appropriate region through interacting with the environment.

The results on automatic posture response experiments show that SSI and SCI are positively correlated with the balance skill of the participants, and they are tunable by behavior training. Two indices were introduced in this study, one is the synergy stability index (SSI) that indicates the region of the synergy space, the other is the synergy coordination index (SCI) that indicates the size of the synergy space. In this study, we investigated the mechanism the CNS may use to define the appropriate region and size of the synergy space when performing skilled behavior. The synergy space defines the suitable combinations of muscles, and time-dependent variables vary in lower-dimensional space to control behaviors. The notion of muscle synergy, which was introduced to divide muscle activations into a lower-dimensional synergy space and time-dependent variables, is a suitable tool relevant to the discussion of this issue. One effective method of choosing muscle combinations is to create a set containing the muscle combinations of only efficient behaviors, and then to choose combinations from that set.

The computational mechanism of choosing muscle combinations, however, remains a long-standing challenge. This flexibility in muscle combinations allows for efficient behaviors to be generated in daily life. Muscle redundancy allows the central nervous system (CNS) to choose a suitable combination of muscles from a number of options.

2Department of Mechanical Engineering, Division of Artificial Systems Science, Chiba University, Chiba, Japan.

1Intelligent Behavior Control Unit, Brain Science Institute, BSI-TOYOTA Collaboration Center of RIKEN, Nagoya, Japan.Fady Alnajjar 1* Tytus Wojtara 2 Hidenori Kimura 1 Shingo Shimoda 1

Dynamic synergy center for optimal wellness