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Existence and stability of limit cycles in a macroscopic neuronal population model

机译:宏观神经元种群模型中极限环的存在和稳定性

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摘要

We present rigorous results concerning the existence and stability of limit cycles in a macroscopic model of neuronal activity. The specific model we consider is developed from the Ki set methodology, popularized by Walter Freeman. In particular we focus on a specific reduction of the KII sets, denoted RKII sets. We analyse the unfolding of supercritical Hopf bifurcations via consideration of the normal forms and centre manifold reductions. Subsequently we analyse the global stability of limit cycles on a region of parameter space and this is achieved by applying a new methodology termed Global Analysis of Piecewise Linear Systems. The analysis presented may also be used to consider coupled systems of this type. A number of macroscopic mean-field approaches to modelling human EEG may be considered as coupled RKII networks. Hence developing a theoretical understanding of the onset of oscillations in models of this type has important implications in clinical neuroscience, as limit cycle oscillations have been demonstrated to be critical in the onset of certain types of epilepsy. (c) 2007 Elsevier B.V. All rights reserved.
机译:我们提出了关于神经活动宏观模型中极限环的存在和稳定性的严格结果。我们考虑的特定模型是根据Walter Freeman推广的Ki set方法开发的。特别是,我们专注于KII集的具体减少,称为RKII集。我们通过考虑正常形式和中心流形减少来分析超临界霍夫夫分叉的展开。随后,我们分析了参数空间区域上极限环的全局稳定性,这是通过应用一种称为分段线性系统全局分析的新方法来实现的。提出的分析也可以用于考虑这种类型的耦合系统。可以将许多建模人脑电图的宏观平均场方法视为耦合RKII网络。因此,在这种类型的模型中发展对振荡发作的理论理解对临床神经科学具有重要意义,因为已经证明极限循环振荡对于某些类型的癫痫发作至关重要。 (c)2007 Elsevier B.V.保留所有权利。

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