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一种用于对形态细节神经元周围大规模细胞外电扩散进行建模的基尔霍夫-能斯特-泊松-纳里卡姆方程框架。

A Kirchhoff-Nernst-Planck framework for modeling large scale extracellular electrodiffusion surrounding morphologically detailed neurons.

机构信息

Center for Integrative Neuroplasticity, University of Oslo, Oslo, Norway.

Department of Physics, University of Oslo, Oslo, Norway.

出版信息

PLoS Comput Biol. 2018 Oct 4;14(10):e1006510. doi: 10.1371/journal.pcbi.1006510. eCollection 2018 Oct.

Abstract

Many pathological conditions, such as seizures, stroke, and spreading depression, are associated with substantial changes in ion concentrations in the extracellular space (ECS) of the brain. An understanding of the mechanisms that govern ECS concentration dynamics may be a prerequisite for understanding such pathologies. To estimate the transport of ions due to electrodiffusive effects, one must keep track of both the ion concentrations and the electric potential simultaneously in the relevant regions of the brain. Although this is currently unfeasible experimentally, it is in principle achievable with computational models based on biophysical principles and constraints. Previous computational models of extracellular ion-concentration dynamics have required extensive computing power, and therefore have been limited to either phenomena on very small spatiotemporal scales (micrometers and milliseconds), or simplified and idealized 1-dimensional (1-D) transport processes on a larger scale. Here, we present the 3-D Kirchhoff-Nernst-Planck (KNP) framework, tailored to explore electrodiffusive effects on large spatiotemporal scales. By assuming electroneutrality, the KNP-framework circumvents charge-relaxation processes on the spatiotemporal scales of nanometers and nanoseconds, and makes it feasible to run simulations on the spatiotemporal scales of millimeters and seconds on a standard desktop computer. In the present work, we use the 3-D KNP framework to simulate the dynamics of ion concentrations and the electrical potential surrounding a morphologically detailed pyramidal cell. In addition to elucidating the single neuron contribution to electrodiffusive effects in the ECS, the simulation demonstrates the efficiency of the 3-D KNP framework. We envision that future applications of the framework to more complex and biologically realistic systems will be useful in exploring pathological conditions associated with large concentration variations in the ECS.

摘要

许多病理状况,如癫痫发作、中风和扩散性抑郁,都与大脑细胞外空间(ECS)中离子浓度的显著变化有关。了解控制 ECS 浓度动态的机制可能是理解这些病理状况的前提。为了估计由于电扩散效应引起的离子传输,必须同时跟踪大脑相关区域中的离子浓度和电势。虽然这在实验上目前是不可行的,但它在原则上是可以通过基于生物物理原理和约束的计算模型来实现的。以前的细胞外离子浓度动态的计算模型需要大量的计算能力,因此仅限于非常小的时空尺度(微米和毫秒)上的现象,或者在较大的尺度上简化和理想化的一维(1-D)传输过程。在这里,我们提出了 3-D Kirchhoff-Nernst-Planck (KNP) 框架,旨在探索大时空尺度上的电扩散效应。通过假设电中性,KNP 框架回避了纳米和纳秒时空尺度上的电荷弛豫过程,使得在标准台式计算机上在毫米和秒的时空尺度上运行模拟成为可能。在目前的工作中,我们使用 3-D KNP 框架来模拟围绕形态详细的锥体神经元的离子浓度和电势的动态。除了阐明单个神经元对 ECS 中电扩散效应的贡献外,模拟还展示了 3-D KNP 框架的效率。我们设想,该框架未来在更复杂和更具生物学真实性的系统中的应用,将有助于探索与 ECS 中浓度变化较大相关的病理状况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b25/6191143/ec07b6bcff53/pcbi.1006510.g001.jpg

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