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Can co-activation reduce kinematic variability? A simulation study

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Abstract

Impedance modulation has been suggested as a means to suppress the effects of internal ‘noise’ on movement kinematics. We investigated this hypothesis in a neuro-musculo-skeletal model. A prerequisite is that the muscle model produces realistic force variability. We found that standard Hill-type models do not predict realistic force variability in response to variability in stimulation. In contrast, a combined motor-unit pool model and a pool of parallel Hill-type motor units did produce realistic force variability as a function of target force, largely independent of how the force was transduced to the tendon. To test the main hypothesis, two versions of the latter model were simulated as an antagonistic muscle pair, controlling the position of a frictionless hinge joint, with a distal segment having realistic inertia relative to the muscle strength. Increasing the impedance through co-activation resulted in less kinematic variability, except for the lowest levels of co-activation. Model behavior in this region was affected by the noise amplitude and the inertial properties of the model. Our simulations support the idea that muscular co-activation is in principle an effective strategy to meet accuracy demands.

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References

  • Adam A, DeLuca CJ, Erim Z (1998) Hand dominance and motor unit firing behavior. J Neurophysiol 80(3):1373–1382

    PubMed  CAS  Google Scholar 

  • Burdet E, Osu R, Franklin DW, Milner TE, Kawato M (2001) The central nervous system stabilizes unstable dynamics by learning optimal impedance. Nature 414(6862):446–449

    Article  PubMed  CAS  Google Scholar 

  • Christou EA, Grossman M, Carlton LG (2002) Modeling variability of force during isometric contractions of the quadriceps femoris. J Mot Behav 34(1):67–81

    Article  PubMed  Google Scholar 

  • Franklin DW, Burdet E, Osu R, Kawato M, Milner TE (2003) Functional significance of stiffness in adaptation of multijoint arm movements to stable and unstable dynamics. Exp Brain Res 151(2):145–157

    Article  PubMed  Google Scholar 

  • Fuglevand AJ, Winter DA, Patla AE (1993) Models of recruitment and rate coding organization in motor-unit pools. JNeurophysiol 70(6):2470–2488

    CAS  Google Scholar 

  • Gribble PL, Mullin LI, Cothros N, Mattar A (2003) A role for cocontraction in arm movement accuracy. J Neurophysiol 89(5):2396–2405

    Article  PubMed  Google Scholar 

  • Hamilton AF, Wolpert DM (2002) Controlling the statistics of action: obstacle avoidance. J Neurophysiol 87(5):2434–2440

    PubMed  Google Scholar 

  • Harris CM, Wolpert DM (1998) Signal-dependent noise determines motor planning. Nature 394(6695):780–784

    Article  PubMed  CAS  Google Scholar 

  • Jones KE, De AF, Hamilton C, Wolpert DM (2002) Sources of signal-dependent noise during isometric force production. J Neurophysiol 88(3):1533–1544

    PubMed  Google Scholar 

  • Laidlaw DH, Bilodeau M, Enoka RM (2000) Steadiness is reduced and motor unit discharge is more variable in old adults. Muscle Nerve 23(4):600–612

    Article  PubMed  CAS  Google Scholar 

  • Laursen B, Jensen BR, Sjogaard G (1998) Effect of speed and precision demands on human shoulder muscle electromyography during a repetitive task. Eur J Appl Physiol Occup Physiol 78(6):544–548

    Article  PubMed  CAS  Google Scholar 

  • Matthews PB (1996) Relationship of firing intervals of human motor units to the trajectory of post-spike after-hyperpolarization and synaptic noise. J Physiol 492(Pt2):597–628

    PubMed  CAS  Google Scholar 

  • Mazzaro N, Grey MJ, Sinkjaer T (2005) Contribution of afferent feedback to the soleus muscle activity during human locomotion. J Neurophysiol 93(1):167–177

    Article  PubMed  Google Scholar 

  • McAuley JH, Rothwell JC, Marsden CD (1997) Frequency peaks of tremor, muscle vibration and electromyographic activity at 10 hz, 20 hz and 40 hz during human finger muscle contraction may reflect rhythmicities of central neural firing. Exp Brain Res 114(3):525–541

    Article  PubMed  CAS  Google Scholar 

  • Moritz CT, Barry BK, Pascoe MA, Enoka RM (2005) Discharge rate variability influences the variation in force fluctuations across the working range of a hand muscle. JNeurophysiol 93(5):2449–2459

    Article  Google Scholar 

  • Osu R, Gomi H (1999) Multijoint muscle regulation mechanisms examined by measured human arm stiffness and emg signals. J Neurophysiol 81(4):1458–1468

    PubMed  CAS  Google Scholar 

  • Osu R, Kamimura N, Iwasaki H, Nakano E, Harris CM, Wada Y, Kawato M (2004) Optimal impedance control for task achievement in the presence of signal-dependent noise. JNeurophysiol 92(2):1199–1215

    Article  Google Scholar 

  • Pandy MG, Zajac FE, Sim E, Levine WS (1990) An optimal control model for maximum-height human jumping. J Biomech 23(12):1185–1198

    Article  PubMed  CAS  Google Scholar 

  • Perreault EJ, Kirsch RF, Acosta AM (1999) Multiple-input, multiple-output system identification for characterization of limb stiffness dynamics. Biol Cybern 80(5):327–337

    Article  PubMed  CAS  Google Scholar 

  • Ridderikhoff A, Peper CL, Carson RG, Beek PJ (2004) Effector dynamics of rhythmic wrist activity and its implications for (modeling) bimanual coordination. Hum Mov Sci 23(3-4):285–313

    Article  PubMed  Google Scholar 

  • Scholz JP, Schöner G, Latash ML (2000) Identifying the control structure of multijoint coordination during pistol shooting. Exp Brain Res 135(3):382–404

    Article  PubMed  CAS  Google Scholar 

  • Shiller DM, Laboissiere R, Ostry DJ (2002) Relationship between jaw stiffness and kinematic variability in speech. J Neurophysiol 88(5):2329–2340

    Article  PubMed  Google Scholar 

  • Slifkin AB, Newell KM (1999) Noise, information transmission, and force variability. J Exp Psychol Hum Percept Perform 25(3):837–851

    Article  PubMed  CAS  Google Scholar 

  • Taylor AM, Christou EA, Enoka RM (2003) Multiple features of motor-unit activity influence force fluctuations during isometric contractions. J Neurophysiol 90(2):1350–1361

    Article  PubMed  Google Scholar 

  • Todorov E, Jordan MI (2002) Optimal feedback control as a theory of motor coordination. Nat Neurosci 5(11):1226–1235

    Article  PubMed  CAS  Google Scholar 

  • Tseng YW, Scholz JP, Schöner G, Hotchkiss L (2003) Effect of accuracy constraint on joint coordination during pointing movements. Exp Brain Res 149(3):276–288

    PubMed  Google Scholar 

  • Vander Burg JCE, Casius LJR, Kingma I, VanDieén JH, VanSoest AJ (2005) Factors underlying the perturbation resistance of the trunk in the first part of a lifting movement. Biol Cybern 93(1):54–62

    Article  CAS  Google Scholar 

  • VanGalen GP, DeJong W (1995) Fitts’ law as the outcome of a dynamic noise filtering model of motor control. Hum Mov Sci 12:539–571

    Google Scholar 

  • VanSoest AJ, Bobbert MF (1993) The contribution of muscle properties in the control of explosive movements. Biol Cybern 69(3):195– 204

    Article  PubMed  Google Scholar 

  • Visser B, DeLooze M, DeGraaff M, VanDieén J (2004) Effects of precision demands and mental pressure on muscle activation and hand forces in computer mouse tasks. Ergonomics 47(2):202–217

    Article  PubMed  Google Scholar 

  • Wagner H, Blickhan R (2003) Stabilizing function of antagonistic neuromusculoskeletal systems: an analytical investigation. Biol Cybern 89(1):71–79

    PubMed  Google Scholar 

  • Welter TG, Bobbert MF (2002) Initial arm muscle activation in a planar ballistic arm movement with varying external force directions: a simulation study. Motor Control 6(3):217–229

    PubMed  Google Scholar 

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Correspondence to Jaap H. van Dieën.

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Selen, L.P.J., Beek, P.J. & Dieën, J.H.v. Can co-activation reduce kinematic variability? A simulation study. Biol Cybern 93, 373–381 (2005). https://doi.org/10.1007/s00422-005-0015-y

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  • DOI: https://doi.org/10.1007/s00422-005-0015-y

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