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Stochastic optimization of a biologically plausible spino-neuromuscular system model

A comparison with human subjects

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An Erratum to this article was published on 17 June 2010

Abstract

Simulations and modeling techniques are becoming increasingly important in understanding the behavior of biological systems. Detailed models help researchers answer questions in diverse areas such as the behavior of bacteria and viruses and aiding in the diagnosis and treatment of injuries and diseases. However, to yield meaningful biological behavior, biological simulations often include hundreds of parameters that correspond to biological components and characteristics. This paper demonstrates the effectiveness of genetic algorithms (GA) and particle swarm optimizer (PSO) based techniques in training biologically plausible behavior in a neuromuscular simulation of a biceps/triceps pair. The results are compared to human subjects during flexion/extension movements to show that these algorithms are effective in training biologically plausible behaviors on both neural and gross anatomical levels. Specific behaviors of interest that emerge include tonic tensions in both muscles during resting periods, biceps/triceps coactivation patterns, and recruitment-like behaviors. These are all fundamental characteristics of biological motor control and emerge without direct selection for these behaviors. This is the first time that all of these characteristic behaviors emerge in a model of this detail without direct selective pressure.

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Notes

  1. In this paper, the terms ‘biceps’ and ‘triceps’ will be used to denote those skeletal muscles whose official names are ‘biceps brachii’ and ‘triceps brachii,’ respectively. These terms are used for convenience because these are the prominent muscles of the upper arm. In actuality, the biceps brachii does not attach to the humorous as indicated in Fig. 1.

  2. In this paper, each group consisting of one contractile element, one damping element, one serial elastic component will be called a “motor unit” where an entire “muscle” consists of six motor units. Biologically, a motor unit also includes the innervating α-MN.

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Acknowledgments

We thank Dr. Mark DeSantis of the University of Idaho’s Department of Biological Sciences for his helpful discussions and suggestions.

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Authors and Affiliations

  1. Department of Computer Science, University of Idaho, Moscow, ID, USA

    Stanley Gotshall & Terence Soule

  2. Department of Health, Physical Education, Recreation, and Dance, University of Idaho, Moscow, ID, USA

    Kathy Browder

  3. Department of Mechanical Engineering, University of Idaho, Moscow, ID, USA

    Jessica Sampson

  4. Department of Electrical and Computer Engineering, University of Idaho, Moscow, ID, USA

    Richard Wells

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  1. Stanley Gotshall
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  2. Kathy Browder
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  3. Jessica Sampson
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  4. Terence Soule
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Correspondence to Stanley Gotshall.

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An erratum to this article can be found online at http://dx.doi.org/10.1007/s10710-010-9108-z.

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Gotshall, S., Browder, K., Sampson, J. et al. Stochastic optimization of a biologically plausible spino-neuromuscular system model. Genet Program Evolvable Mach 8, 355–380 (2007). https://doi.org/10.1007/s10710-007-9044-8

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  • DOI: https://doi.org/10.1007/s10710-007-9044-8

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