Analytic Modeling of Neural Tissue: I. A Spherical Bidomain.

IF 2.3 4区 医学 Q1 Neuroscience Journal of Mathematical Neuroscience Pub Date : 2016-12-01 Epub Date: 2016-09-09 DOI:10.1186/s13408-016-0041-1
Benjamin L Schwartz, Munish Chauhan, Rosalind J Sadleir
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引用次数: 3

Abstract

Presented here is a model of neural tissue in a conductive medium stimulated by externally injected currents. The tissue is described as a conductively isotropic bidomain, i.e. comprised of intra and extracellular regions that occupy the same space, as well as the membrane that divides them, and the injection currents are described as a pair of source and sink points. The problem is solved in three spatial dimensions and defined in spherical coordinates [Formula: see text]. The system of coupled partial differential equations is solved by recasting the problem to be in terms of the membrane and a monodomain, interpreted as a weighted average of the intra and extracellular domains. The membrane and monodomain are defined by the scalar Helmholtz and Laplace equations, respectively, which are both separable in spherical coordinates. Product solutions are thus assumed and given through certain transcendental functions. From these electrical potentials, analytic expressions for current density are derived and from those fields the magnetic flux density is calculated. Numerical examples are considered wherein the interstitial conductivity is varied, as well as the limiting case of the problem simplifying to two dimensions due to azimuthal independence. Finally, future modeling work is discussed.

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神经组织的解析建模:I.球面双域。
这里展示的是一个在导电介质中受外部注入电流刺激的神经组织模型。该组织被描述为导电各向同性双域,即由占据相同空间的细胞内和细胞外区域以及分隔它们的膜组成,注射电流被描述为一对源点和汇点。该问题在三维空间中求解,并在球坐标中定义[公式:见文本]。耦合偏微分方程系统通过将问题重新转换为膜和单域来解决,解释为细胞内和细胞外区域的加权平均值。膜和单畴分别由标量亥姆霍兹方程和拉普拉斯方程定义,它们在球坐标系中都是可分离的。因此,乘积解被假定并通过某些超越函数给出。根据这些电势,导出了电流密度的解析表达式,并根据这些场计算了磁通密度。考虑了间隙电导率变化的数值例子,以及由于方位无关性而简化为二维问题的极限情况。最后,对今后的建模工作进行了展望。
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来源期刊
Journal of Mathematical Neuroscience
Journal of Mathematical Neuroscience Neuroscience-Neuroscience (miscellaneous)
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0.00%
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审稿时长
13 weeks
期刊介绍: The Journal of Mathematical Neuroscience (JMN) publishes research articles on the mathematical modeling and analysis of all areas of neuroscience, i.e., the study of the nervous system and its dysfunctions. The focus is on using mathematics as the primary tool for elucidating the fundamental mechanisms responsible for experimentally observed behaviours in neuroscience at all relevant scales, from the molecular world to that of cognition. The aim is to publish work that uses advanced mathematical techniques to illuminate these questions. It publishes full length original papers, rapid communications and review articles. Papers that combine theoretical results supported by convincing numerical experiments are especially encouraged. Papers that introduce and help develop those new pieces of mathematical theory which are likely to be relevant to future studies of the nervous system in general and the human brain in particular are also welcome.
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