Neural Excitability and Singular Bifurcations.

IF 2.3 4区 医学 Q1 Neuroscience
Journal of Mathematical Neuroscience Pub Date : 2015-12-01 Epub Date: 2015-08-06 DOI:10.1186/s13408-015-0029-2
Peter De Maesschalck, Martin Wechselberger
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引用次数: 43

Abstract

We discuss the notion of excitability in 2D slow/fast neural models from a geometric singular perturbation theory point of view. We focus on the inherent singular nature of slow/fast neural models and define excitability via singular bifurcations. In particular, we show that type I excitability is associated with a novel singular Bogdanov-Takens/SNIC bifurcation while type II excitability is associated with a singular Andronov-Hopf bifurcation. In both cases, canards play an important role in the understanding of the unfolding of these singular bifurcation structures. We also explain the transition between the two excitability types and highlight all bifurcations involved, thus providing a complete analysis of excitability based on geometric singular perturbation theory.

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神经兴奋性与奇异分岔。
从几何奇异摄动理论的角度讨论了二维慢/快神经模型的兴奋性。我们关注慢/快神经模型固有的奇异性,并通过奇异分叉定义兴奋性。特别地,我们证明了I型兴奋性与一个新的奇异Bogdanov-Takens/SNIC分岔有关,而II型兴奋性与一个奇异Andronov-Hopf分岔有关。在这两种情况下,鸭翼在理解这些奇异分岔结构的展开方面发挥了重要作用。我们还解释了两种可激性类型之间的转换,并强调了所涉及的所有分岔,从而提供了基于几何奇异摄动理论的可激性的完整分析。
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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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