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用于癫痫动力学建模的相空间方法。

Phase space approach for modeling of epileptic dynamics.

作者信息

Wang Yujiang, Goodfellow Marc, Taylor Peter Neal, Baier Gerold

机构信息

Doctoral Training Centre Integrative Systems Biology, Manchester Interdisciplinary Biocentre, 131 Princess Street, Manchester M1 7DN, United Kingdom.

出版信息

Phys Rev E Stat Nonlin Soft Matter Phys. 2012 Jun;85(6 Pt 1):061918. doi: 10.1103/PhysRevE.85.061918. Epub 2012 Jun 22.

Abstract

Epileptic electroencephalography recordings can be described in terms of four prototypic wave forms: fast sinusoidal oscillations, large slow waves, fast spiking, and spike waves. On the macroscopic level, these wave forms have been modeled by different mechanistic models which share canonical features. Here we derive a minimal model of excitatory and inhibitory processes with features common to all previous models. We can infer that at least three interacting processes are required to support the prototypic epileptic dynamics. Based on a separation of time scales we analyze the model in terms of interacting manifolds in phase space. This allows qualitative reverse engineering of all epileptic wave forms and transitions between them. We propose this method as a complement to traditional approaches to modeling epileptiform rhythms.

摘要

癫痫脑电图记录可以用四种典型波形来描述

快速正弦振荡、大慢波、快速棘波和棘慢波。在宏观层面上,这些波形已由具有共同特征的不同机制模型进行建模。在此,我们推导了一个兴奋性和抑制性过程的最小模型,该模型具有所有先前模型共有的特征。我们可以推断,至少需要三个相互作用的过程来支持典型的癫痫动力学。基于时间尺度的分离,我们在相空间中根据相互作用流形来分析该模型。这使得对所有癫痫波形及其之间的转换进行定性逆向工程成为可能。我们提出这种方法作为对癫痫样节律建模的传统方法的补充。

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