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Studying the interactions in a mammalian nerve fiber: a functional modeling approach

机译:研究哺乳动物神经纤维中的相互作用:一种功能建模方法

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Modern therapeutic interventions are increasingly favoring electrical stimulation to treat neurophysiological disorders. These therapies are associated with suboptimal efficacy since most neurostimulation devices operate in an open-loop manner (i.e., stimulation settings like frequency, amplitude are preprogrammed). A closed-loop system can dynamically adjust stimulation parameters and may provide efficient therapies. Computational models used to design these systems vary in complexity which can adversely affect their real-time performance. In this study, we compare two models of varying degrees of complexity. We constructed two computational models of a myelinated nerve fiber (functional versus mechanistic) each receiving two inputs: the underlying physiological activity at one end of the fiber, and the external stimulus applied to the middle of the fiber. We then defined relay reliability as the percentage of physiological action potentials that make it to the other end of the nerve fiber. We applied the two inputs to the fiber at various frequencies and analyze reliability. We found that the functional model and the mechanistic model have similar reliability properties, but the functional model significantly decreases the computational complexity and simulation run time. This modeling effort is the first step towards understanding and designing closed loop, real-time neurostimulation devices.
机译:现代治疗干预越来越倾向于电刺激来治疗神经生理疾病。由于大多数神经刺激装置以开环方式操作(即,对诸如频率,幅度的刺激设置进行了预编程),因此这些疗法与次佳的疗效相关。闭环系统可以动态调整刺激参数,并可以提供有效的治疗方法。用于设计这些系统的计算模型的复杂度各不相同,这可能会对它们的实时性能产生不利影响。在这项研究中,我们比较了复杂程度不同的两个模型。我们构建了有髓神经纤维(功能性与机械性)的两个计算模型,每个都收到两个输入:纤维一端的潜在生理活动,以及施加在纤维中间的外部刺激。然后,我们将中继可靠性定义为使其到达神经纤维另一端的生理动作电位的百分比。我们将两个输入以不同的频率应用于光纤,并分析了可靠性。我们发现功能模型和机械模型具有相似的可靠性属性,但是功能模型显着降低了计算复杂度和仿真运行时间。这种建模工作是了解和设计闭环实时神经刺激设备的第一步。

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