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首页> 外文期刊>Journal of Computational Neuroscience >Relating reflex gain modulation in posture control to underlying neural network properties using a neuromusculoskeletal model
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Relating reflex gain modulation in posture control to underlying neural network properties using a neuromusculoskeletal model

机译：使用神经肌肉骨骼模型将姿势控制中的反射增益调制与基础神经网络属性相关

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摘要

During posture control, reflexive feedback allows humans to efficiently compensate for unpredictable mechanical disturbances. Although reflexes are involuntary, humans can adapt their reflexive settings to the characteristics of the disturbances. Reflex modulation is commonly studied by determining reflex gains: a set of parameters that quantify the contributions of la, Ib and Ⅱ afferents to mechanical joint behavior. Many mechanisms, like presynaptic inhibition and fusimotor drive, can account for reflex gain modulations. The goal of this study was to investigate the effects of underlying neural and sensory mechanisms on mechanical joint behavior. A neuromusculoskeletal model was built, in which a pair of muscles actuated a limb, while being controlled by a model of 2,298 spiking neurons in six pairs of spinal populations. Identical to experiments, the endpoint of the limb was disturbed with force perturbations. System identification was used to quantify the control behavior with reflex gains. A sensitivity analysis was then performed on the neuromusculoskeletal model, determining the influence of the neural, sensory and synaptic parameters on the joint dynamics. The results showed that the lumped reflex gains positively correlate to their most direct neural substrates: the velocity gain with la afferent velocity feedback, the positional gain with muscle stretch over II afferents and the force feedback gain with Ib afferent feedback. However, position feedback and force feedback gains show strong interactions with other neural and sensory properties. These results give important insights in the effects of neural properties on joint dynamics and in the identifiability of reflex gains in experiments.
机译：在姿势控制期间，反射反馈使人类可以有效地补偿不可预测的机械干扰。尽管反射是非自愿的，但人类可以使自己的反射设置适应干扰的特征。反射调制通常通过确定反射增益来研究：一组参数可量化la，Ib和Ⅱ传入对机械关节行为的贡献。突触前抑制和融合运动驱动等许多机制都可以解释反射增益调制。这项研究的目的是调查潜在的神经和感觉机制对机械关节行为的影响。建立了一个神经肌肉骨骼模型，其中一对肌肉驱动肢体，同时由六对脊椎种群中的2298个尖刺神经元模型控制。与实验相同，肢体的端点受到力的扰动。系统识别用于量化具有反射增益的控制行为。然后对神经肌肉骨骼模型进行敏感性分析，确定神经，感觉和突触参数对关节动力学的影响。结果表明，集总反射增益与其最直接的神经基质呈正相关：传入速度反馈时的速度增益，肌肉在II传入者上伸展时的位置增益以及Ib传入者反馈的力反馈增益。但是，位置反馈和力反馈增益显示出与其他神经和感觉特性的强烈交互作用。这些结果为神经特性对关节动力学的影响以及实验中反射增益的可识别性提供了重要的见识。

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  • 来源
    《Journal of Computational Neuroscience》 |2011年第3期|p.555-565|共11页
  • 作者

    Jasper Schuurmans; Frans C. T. van der Helm; Alfred C. Schouten;

  • 作者单位

    Department of Biomechanical Engineering,Delft University of Technology, Mekelweg 2,2628 CD Delft, The Netherlands;

    Department of Biomechanical Engineering,Delft University of Technology, Mekelweg 2,2628 CD Delft, The Netherlands,Laboratory of Biomechanical Engineering, MIRA Institute for Biomedical Technology and Technical Medicine,University of Twente, P.O. Box 217,7500 AE Enschede, The Netherlands;

    Department of Biomechanical Engineering,Delft University of Technology, Mekelweg 2,2628 CD Delft, The Netherlands,Laboratory of Biomechanical Engineering, MIRA Institute for Biomedical Technology and Technical Medicine,University of Twente, P.O. Box 217,7500 AE Enschede, The Netherlands;

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  • 正文语种 eng
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  • 关键词

    reflexes; afferent feedback; reflex gains; sensitivity anajysis; system identification;

    机译：反思;令人反感的反馈;反射增益;敏感性分析系统识别;

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