Nonlinear Dynamics of Neuronal Excitability, Oscillations, and Coincidence Detection.

Nonlinear Dynamics of Neuronal Excitability, Oscillations, and Coincidence Detection.
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DOI:
10.1002/cpa.21469
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发表时间:
2013-09
影响因子:
3
通讯作者:
Huguet G
Huguet G
中科院分区:
数学1区
文献类型:
--
作者:
Rinzel J;Huguet G

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我们回顾了一些广泛研究的神经元系统模型和放电动力学,包括单细胞和网络水平,以及研究它们的动力系统技术。我们特别关注数学神经科学中数十年来吸引数学家关注的两个主题:单细胞兴奋性和爆发。我们回顾了单神经元模型中三种类型的兴奋性和重复放电行为开始的数学框架,及其与 1948 年霍奇金重复放电特性分类的关系。我们使用快/慢分析讨论爆发振荡的数学剖析,并使用单细胞和平均场网络模型演示该方法。最后,我们说明了 III 型兴奋性的特性,在这种情况下,不存在持续或缓慢输入的重复激发。相反,放电只是对刺激发生足够快的变化的反应。我们的案例研究涉及声音定位的神经元计算,听觉脑干中的神经元以亚毫秒时间分辨率执行极其精确的符合检测。
We review some widely studied models and firing dynamics for neuronal systems, both at the single cell and network level, and dynamical systems techniques to study them. In particular, we focus on two topics in mathematical neuroscience that have attracted the attention of mathematicians for decades: single-cell excitability and bursting. We review the mathematical framework for three types of excitability and onset of repetitive firing behavior in single-neuron models and their relation with Hodgkin’s classification in 1948 of repetitive firing properties. We discuss the mathematical dissection of bursting oscillations using fast/slow analysis and demonstrate the approach using single-cell and mean-field network models. Finally, we illustrate the properties of Type III excitability in which case repetitive firing for constant or slow inputs is absent. Rather, firing is in response only to rapid enough changes in the stimulus. Our case study involves neuronal computations for sound localization for which neurons in the auditory brain stem perform extraordinarily precise coincidence detection with submillisecond temporal resolution.
DOI: 10.1085/jgp.43.5.867
发表时间: 1960-05
期刊: The Journal of general physiology
影响因子: --
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