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Normalized Index of Synergy for Evaluating the Coordination of Motor Commands.

Togo S, Imamizu H - PLoS ONE (2015)

Bottom Line: We hypothesized that a large part of the change in the coordination of motor outputs through learning was because of changes in motor commands.In a motor learning task, subjects tracked a target trajectory of the total torque.We conclude that the normalized index of synergy can be used to evaluate the coordination of motor commands independently from the properties of the musculoskeletal system.

View Article: PubMed Central - PubMed

Affiliation: Cognitive Mechanisms Laboratories, Advanced Telecommunications Research Institute International, Kyoto, Japan; Japan Society for the Promotion of Science, Tokyo, Japan.

ABSTRACT
Humans perform various motor tasks by coordinating the redundant motor elements in their bodies. The coordination of motor outputs is produced by motor commands, as well properties of the musculoskeletal system. The aim of this study was to dissociate the coordination of motor commands from motor outputs. First, we conducted simulation experiments where the total elbow torque was generated by a model of a simple human right and left elbow with redundant muscles. The results demonstrated that muscle tension with signal-dependent noise formed a coordinated structure of trial-to-trial variability of muscle tension. Therefore, the removal of signal-dependent noise effects was required to evaluate the coordination of motor commands. We proposed a method to evaluate the coordination of motor commands, which removed signal-dependent noise from the measured variability of muscle tension. We used uncontrolled manifold analysis to calculate a normalized index of synergy. Simulation experiments confirmed that the proposed method could appropriately represent the coordinated structure of the variability of motor commands. We also conducted experiments in which subjects performed the same task as in the simulation experiments. The normalized index of synergy revealed that the subjects coordinated their motor commands to achieve the task. Finally, the normalized index of synergy was applied to a motor learning task to determine the utility of the proposed method. We hypothesized that a large part of the change in the coordination of motor outputs through learning was because of changes in motor commands. In a motor learning task, subjects tracked a target trajectory of the total torque. The change in the coordination of muscle tension through learning was dominated by that of motor commands, which supported the hypothesis. We conclude that the normalized index of synergy can be used to evaluate the coordination of motor commands independently from the properties of the musculoskeletal system.

No MeSH data available.


Related in: MedlinePlus

Method for evaluating the coordination of motor commands.(a) The musculoskeletal system considered in this study. The CNS sends motor commands to each muscle. The muscle generates muscle tension with signal-dependent noise. The muscle tensions form the joint torque. (b) Transformation from the coordination of muscle tensions to that of motor commands. Using a coefficient of variation of each muscle, the variability of muscle tensions across trials is transformed so that it is distributed according to a signal-independent mixture of Gaussian distributions. Then, the UCM analysis is applied to quantitatively evaluate the coordination of motor commands.
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pone.0140836.g002: Method for evaluating the coordination of motor commands.(a) The musculoskeletal system considered in this study. The CNS sends motor commands to each muscle. The muscle generates muscle tension with signal-dependent noise. The muscle tensions form the joint torque. (b) Transformation from the coordination of muscle tensions to that of motor commands. Using a coefficient of variation of each muscle, the variability of muscle tensions across trials is transformed so that it is distributed according to a signal-independent mixture of Gaussian distributions. Then, the UCM analysis is applied to quantitatively evaluate the coordination of motor commands.

Mentions: In this study, we consider a simple musculoskeletal system as shown in Fig 2A. The central nervous system (CNS) sends motor command ei to each muscle. Because each muscle has SDN properties, the muscle tension of the i-th muscle Ti is defined as follows:Ti=ei+eiαiN(0,1),(1)where αi denotes the coefficient of variation of the i-th muscle and N(0,1) indicates a Gaussian distribution with mean 0 and standard deviation 1. Then, an isometric joint torque τ is produced by a muscle tension T as follows:τ=A⋅T,(2)where A denotes a transformation matrix. We considered an isometric condition; thus, the transformation matrix A s constant.


Normalized Index of Synergy for Evaluating the Coordination of Motor Commands.

Togo S, Imamizu H - PLoS ONE (2015)

Method for evaluating the coordination of motor commands.(a) The musculoskeletal system considered in this study. The CNS sends motor commands to each muscle. The muscle generates muscle tension with signal-dependent noise. The muscle tensions form the joint torque. (b) Transformation from the coordination of muscle tensions to that of motor commands. Using a coefficient of variation of each muscle, the variability of muscle tensions across trials is transformed so that it is distributed according to a signal-independent mixture of Gaussian distributions. Then, the UCM analysis is applied to quantitatively evaluate the coordination of motor commands.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4608756&req=5

pone.0140836.g002: Method for evaluating the coordination of motor commands.(a) The musculoskeletal system considered in this study. The CNS sends motor commands to each muscle. The muscle generates muscle tension with signal-dependent noise. The muscle tensions form the joint torque. (b) Transformation from the coordination of muscle tensions to that of motor commands. Using a coefficient of variation of each muscle, the variability of muscle tensions across trials is transformed so that it is distributed according to a signal-independent mixture of Gaussian distributions. Then, the UCM analysis is applied to quantitatively evaluate the coordination of motor commands.
Mentions: In this study, we consider a simple musculoskeletal system as shown in Fig 2A. The central nervous system (CNS) sends motor command ei to each muscle. Because each muscle has SDN properties, the muscle tension of the i-th muscle Ti is defined as follows:Ti=ei+eiαiN(0,1),(1)where αi denotes the coefficient of variation of the i-th muscle and N(0,1) indicates a Gaussian distribution with mean 0 and standard deviation 1. Then, an isometric joint torque τ is produced by a muscle tension T as follows:τ=A⋅T,(2)where A denotes a transformation matrix. We considered an isometric condition; thus, the transformation matrix A s constant.

Bottom Line: We hypothesized that a large part of the change in the coordination of motor outputs through learning was because of changes in motor commands.In a motor learning task, subjects tracked a target trajectory of the total torque.We conclude that the normalized index of synergy can be used to evaluate the coordination of motor commands independently from the properties of the musculoskeletal system.

View Article: PubMed Central - PubMed

Affiliation: Cognitive Mechanisms Laboratories, Advanced Telecommunications Research Institute International, Kyoto, Japan; Japan Society for the Promotion of Science, Tokyo, Japan.

ABSTRACT
Humans perform various motor tasks by coordinating the redundant motor elements in their bodies. The coordination of motor outputs is produced by motor commands, as well properties of the musculoskeletal system. The aim of this study was to dissociate the coordination of motor commands from motor outputs. First, we conducted simulation experiments where the total elbow torque was generated by a model of a simple human right and left elbow with redundant muscles. The results demonstrated that muscle tension with signal-dependent noise formed a coordinated structure of trial-to-trial variability of muscle tension. Therefore, the removal of signal-dependent noise effects was required to evaluate the coordination of motor commands. We proposed a method to evaluate the coordination of motor commands, which removed signal-dependent noise from the measured variability of muscle tension. We used uncontrolled manifold analysis to calculate a normalized index of synergy. Simulation experiments confirmed that the proposed method could appropriately represent the coordinated structure of the variability of motor commands. We also conducted experiments in which subjects performed the same task as in the simulation experiments. The normalized index of synergy revealed that the subjects coordinated their motor commands to achieve the task. Finally, the normalized index of synergy was applied to a motor learning task to determine the utility of the proposed method. We hypothesized that a large part of the change in the coordination of motor outputs through learning was because of changes in motor commands. In a motor learning task, subjects tracked a target trajectory of the total torque. The change in the coordination of muscle tension through learning was dominated by that of motor commands, which supported the hypothesis. We conclude that the normalized index of synergy can be used to evaluate the coordination of motor commands independently from the properties of the musculoskeletal system.

No MeSH data available.


Related in: MedlinePlus