Modeling focal epileptic activity in the Wilson-cowan model with depolarization block.

IF 2.3 4区 医学 Q1 Neuroscience
Journal of Mathematical Neuroscience Pub Date : 2015-03-27 eCollection Date: 2015-01-01 DOI:10.1186/s13408-015-0019-4
Hil G E Meijer, Tahra L Eissa, Bert Kiewiet, Jeremy F Neuman, Catherine A Schevon, Ronald G Emerson, Robert R Goodman, Guy M McKhann, Charles J Marcuccilli, Andrew K Tryba, Jack D Cowan, Stephan A van Gils, Wim van Drongelen
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引用次数: 45

Abstract

Unlabelled: Measurements of neuronal signals during human seizure activity and evoked epileptic activity in experimental models suggest that, in these pathological states, the individual nerve cells experience an activity driven depolarization block, i.e. they saturate. We examined the effect of such a saturation in the Wilson-Cowan formalism by adapting the nonlinear activation function; we substituted the commonly applied sigmoid for a Gaussian function. We discuss experimental recordings during a seizure that support this substitution. Next we perform a bifurcation analysis on the Wilson-Cowan model with a Gaussian activation function. The main effect is an additional stable equilibrium with high excitatory and low inhibitory activity. Analysis of coupled local networks then shows that such high activity can stay localized or spread. Specifically, in a spatial continuum we show a wavefront with inhibition leading followed by excitatory activity. We relate our model simulations to observations of spreading activity during seizures.

Electronic supplementary material: The online version of this article (doi:10.1186/s13408-015-0019-4) contains supplementary material 1.

Abstract Image

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威尔逊-考恩模型的局灶性癫痫活动去极化阻滞模型。
未标记:对实验模型中人类癫痫发作活动和诱发癫痫活动期间的神经元信号的测量表明,在这些病理状态下,单个神经细胞经历了活动驱动的去极化阻滞,即它们饱和。我们通过采用非线性激活函数检验了Wilson-Cowan形式中这种饱和的影响;我们用常用的s型函数代替高斯函数。我们讨论癫痫发作期间的实验记录,支持这种替代。接下来,我们用高斯激活函数对Wilson-Cowan模型进行分岔分析。主要作用是高兴奋性和低抑制活性的额外稳定平衡。对耦合局部网络的分析表明,这种高活动性可以保持局部或传播。具体地说,在一个空间连续体中,我们显示了一个波前,先是抑制,然后是兴奋性活动。我们将我们的模型模拟与癫痫发作期间扩散活动的观察联系起来。电子补充资料:本文的在线版本(doi:10.1186/s13408-015-0019-4)包含补充资料1。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Journal of Mathematical Neuroscience
Journal of Mathematical Neuroscience Neuroscience-Neuroscience (miscellaneous)
自引率
0.00%
发文量
0
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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