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从复合动作电位中测定神经纤维直径分布:一种连续方法。

Determination of Nerve Fiber Diameter Distribution From Compound Action Potential: A Continuous Approach.

出版信息

IEEE Trans Neural Syst Rehabil Eng. 2018 Jan;26(1):77-83. doi: 10.1109/TNSRE.2017.2771823.

Abstract

When a signal is initiated in the nerve, it is transmitted along each nerve fiber via an action potential (called single fiber action potential (SFAP)) which travels with a velocity that is related with the diameter of the fiber. The additive superposition of SFAPs constitutes the compound action potential (CAP) of the nerve. The fiber diameter distribution (FDD) in the nerve can be computed from the CAP data by solving an inverse problem. This is usually achieved by dividing the fibers into a finite number of diameter groups and solve a corresponding linear system to optimize FDD. However, number of fibers in a nerve can be measured sometimes in thousands and it is possible to assume a continuous distribution for the fiber diameters which leads to a gradient optimization problem. In this paper, we have evaluated this continuous approach to the solution of the inverse problem. We have utilized an analytical function for SFAP and an assumed a polynomial form for FDD. The inverse problem involves the optimization of polynomial coefficients to obtain the best estimate for the FDD. We have observed that an eighth order polynomial for FDD can capture both unimodal and bimodal fiber distributions present in vivo, even in case of noisy CAP data. The assumed FDD distribution regularizes the ill-conditioned inverse problem and produces good results.

摘要

当神经中的信号被启动时,它会通过动作电位(称为单纤维动作电位 (SFAP))沿每个神经纤维传输,其传播速度与纤维的直径有关。SFAP 的累加构成了神经的复合动作电位 (CAP)。可以通过求解逆问题从 CAP 数据中计算出神经中的纤维直径分布 (FDD)。这通常是通过将纤维划分为有限数量的直径组并求解相应的线性系统来优化 FDD 来实现的。然而,有时可以在神经中测量数千根纤维,并且可以假设纤维直径的连续分布,从而导致梯度优化问题。在本文中,我们评估了这种连续方法对逆问题的求解。我们使用了 SFAP 的解析函数,并假设了 FDD 的多项式形式。逆问题涉及优化多项式系数以获得 FDD 的最佳估计。我们观察到,对于 FDD 的八阶多项式可以捕获体内存在的单峰和双峰纤维分布,即使在 CAP 数据存在噪声的情况下也是如此。所假设的 FDD 分布正则化了病态的逆问题,并产生了良好的结果。

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