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一种检测动力系统中虚假分岔的方法:应用于神经场模型。

A method for detecting false bifurcations in dynamical systems: application to neural-field models.

作者信息

Rodrigues Serafim, Barton David, Marten Frank, Kibuuka Moses, Alarcon Gonzalo, Richardson Mark P, Terry John R

机构信息

Department of Engineering Mathematics, University of Bristol, Bristol, UK.

出版信息

Biol Cybern. 2010 Feb;102(2):145-54. doi: 10.1007/s00422-009-0357-y. Epub 2009 Dec 24.

Abstract

In this article, we present a method for tracking changes in curvature of limit cycle solutions that arise due to inflection points. In keeping with previous literature, we term these changes false bifurcations, as they appear to be bifurcations when considering a Poincaré section that is tangent to the solution, but in actual fact the deformation of the solution occurs smoothly as a parameter is varied. These types of solutions arise commonly in electroencephalogram models of absence seizures and correspond to the formation of spikes in these models. Tracking these transitions in parameter space allows regions to be defined corresponding to different types of spike and wave dynamics, that may be of use in clinical neuroscience as a means to classify different subtypes of the more general syndrome.

摘要

在本文中,我们提出了一种追踪由于拐点而产生的极限环解曲率变化的方法。与先前的文献一致,我们将这些变化称为虚假分岔,因为当考虑与解相切的庞加莱截面时,它们看起来像是分岔,但实际上,随着参数的变化,解的变形是平滑发生的。这类解在失神发作的脑电图模型中很常见,并且对应于这些模型中尖峰的形成。在参数空间中追踪这些转变可以定义与不同类型的尖峰和波动态相对应的区域,这在临床神经科学中可能有用,作为对更一般综合征的不同亚型进行分类的一种手段。

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