使用Poisson–Nernst–Planck处理和传导速度估计对神经元跳跃性传导的时空建模

Q3 Engineering
Rahul Gulati, Shiva Rudraraju
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引用次数: 1

摘要

动作电位沿轴突和树突的传播是在大脑和神经系统其他部分观察到的电活动的基础。长期以来,这种动作电位活动的理论和数值建模一直是电化学神经元建模的一个关键焦点领域,多年来,人们提出了不同复杂度的电网模型。具体而言,考虑到沿着有髓鞘轴突存在Ranvier节点,动作电位传播的单索模型已经很流行。在这些模型的基础上,考虑到髓鞘下方的二次导电通路,提出了双电缆模型。这种基于电缆理论的治疗方法,包括经典的霍奇金-赫胥黎模型、单电缆模型和双电缆模型,在文献中得到了广泛的研究。但这些都有内在的局限性,因为它们缺乏对神经元电化学时空演变的表征。相反,基于泊松-能斯特-普朗克(PNP)的电扩散框架解释了潜在的时空离子浓度动力学,是一种更通用、更全面的处理方法。在这项工作中,演示了PNP模型的高保真度实现。该电扩散模型显示出类似于基于电缆理论的电网模型的结果,此外,还捕捉到了潜在离子输运的丰富时空演化。这项工作的新颖之处在于将PNP模型扩展到具有多个Ranvier节点的轴突几何形状,其与基于电缆理论的模型的相关性,以及电扩散模型的多种变体——不含髓鞘的PNP、含髓鞘的PN,以及带髓鞘和轴突周围间隙的PNP。此外,我们应用这一时空模型,使用三种模型变体对大鼠轴突中的传导速度进行了数值估计。具体来说,研究了由于髓鞘和轴突周围空间的存在而引起的空间跳跃传导。意义陈述:在这项工作中,我们提出了一种基于PDE的综合治疗方法,用于模拟神经元动作电位的产生和传播,并提供了第一个用于计算估计动作电位传导速度的框架。该电扩散模型基于泊松-能斯特-普朗克(PNP)公式,其结果与基于电缆理论的电网模型相似,此外,还捕捉到了潜在离子输运的丰富时空演化。这项工作的新颖之处在于将PNP模型扩展到具有多个Ranvier节点的轴突几何结构,其与基于电缆理论的模型的相关性,以及电扩散模型的多种变体-不含髓鞘的PNP、含髓鞘的PN以及含髓鞘和轴周间隙的PNP。此外,我们应用这一时空模型,使用三种模型变体对大鼠轴突中的传导速度进行了数值估计。具体来说,研究了由于髓鞘和轴突周围空间的存在而引起的空间跳跃传导。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Spatio-temporal modeling of saltatory conduction in neurons using Poisson–Nernst–Planck treatment and estimation of conduction velocity

Action potential propagation along the axons and across the dendrites is the foundation of the electrical activity observed in the brain and the rest of the nervous system. Theoretical and numerical modeling of this action potential activity has long been a key focus area of electro-chemical neuronal modeling, and over the years, electrical network models of varying complexity have been proposed. Specifically, considering the presence of nodes of Ranvier along the myelinated axon, single-cable models of the propagation of action potential have been popular. Building on these models, and considering a secondary electrical conduction pathway below the myelin sheath, the double-cable model has been proposed. Such cable theory based treatments, including the classical Hodgkin–Huxley model, single-cable model, and double-cable model have been extensively studied in the literature. But these have inherent limitations in their lack of a representation of the spatio-temporal evolution of the neuronal electro-chemistry. In contrast, a Poisson–Nernst–Planck (PNP) based electro-diffusive framework accounts for the underlying spatio-temporal ionic concentration dynamics and is a more general and comprehensive treatment. In this work, a high-fidelity implementation of the PNP model is demonstrated. This electro-diffusive model is shown to produce results similar to the cable theory based electrical network models, and in addition, the rich spatio-temporal evolution of the underlying ionic transport is captured. Novel to this work is the extension of PNP model to axonal geometries with multiple nodes of Ranvier, its correlation with cable theory based models, and multiple variants of the electro-diffusive model — PNP without myelin, PNP with myelin, and PNP with the myelin sheath and peri-axonal space. Further, we apply this spatio-temporal model to numerically estimate conduction velocity in a rat axon using the three model variants. Specifically, spatial saltatory conduction due to the presence of myelin sheath and the peri-axonal space is investigated.

Statement of Significance: In this work, we present a comprehensive PDE based treatment for modeling neuronal action potential generation and propagation and provide a first-of-its-kind framework for computationally estimating action potential conduction velocities. This electro-diffusive model, based on a Poisson-Nernst-Planck (PNP) formulation, is shown to produce results similar to the cable theory based electrical network models, and in addition, the rich spatio-temporal evolution of the underlying ionic transport is captured. Novel to this work is the extension of PNP model to axonal geometries with multiple nodes of Ranvier, its correlation with cable theory based models, and multiple variants of the electro-diffusive model - PNP without myelin, PNP with myelin, and PNP with the myelin sheath and periaxonal space. Further, we apply this spatio-temporal model to numerically estimate conduction velocity in a rat axon using the three model variants. Specifically, spatial saltatory conduction due to the presence of myelin sheath and the peri-axonal space is investigated.

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来源期刊
Brain multiphysics
Brain multiphysics Physics and Astronomy (General), Modelling and Simulation, Neuroscience (General), Biomedical Engineering
CiteScore
4.80
自引率
0.00%
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0
审稿时长
68 days
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