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可兴奋细胞模型中周期性和混沌爆发的产生。

Generation of periodic and chaotic bursting in an excitable cell model.

作者信息

Fan Y S, Chay T R

机构信息

Department of Biological Sciences, Faculty of Arts and Sciences, University of Pittsburgh, PA 15260.

出版信息

Biol Cybern. 1994;71(5):417-31. doi: 10.1007/BF00198918.

Abstract

There are interesting oscillatory phenomena associated with excitable cells that require theoretical insight. Some of these phenomena are: the threshold low amplitude oscillations before bursting in neuronal cells, the damped burst observed in muscle cells, the period-adding bifurcations without chaos in pancreatic beta-cells, chaotic bursting and beating in neurons, and inverse period-doubling bifurcation in heart cells. The three variable model formulated by Chay provides a mathematical description of how excitable cells generate bursting action potentials. This model contains a slow dynamic variable which forms a basis for the underlying wave, a fast dynamic variable which causes spiking, and the membrane potential which is a dependent variable. In this paper, we use the Chay model to explain these oscillatory phenomena. The Poincaré return map approach is used to construct bifurcation diagrams with the 'slow' conductance (i.e., gK, C) as the bifurcation parameter. These diagrams show that the system makes a transition from repetitive spiking to chaotic bursting as parameter gK, C is varied. Depending on the time kinetic constant of the fast variable (lambda n), however, the transition between burstings via period-adding bifurcation can occur even without chaos. Damped bursting is present in the Chay model over a certain range of gK, C and lambda n. In addition, a threshold sinusoidal oscillation was observed at certain values of gK, C before triggering action potentials. Probably this explains why the neuronal cells exhibit low-amplitude oscillations before bursting.

摘要

可兴奋细胞存在一些有趣的振荡现象,这需要理论上的深入理解。其中一些现象包括:神经元细胞爆发前的阈值低幅振荡、肌肉细胞中观察到的阻尼爆发、胰腺β细胞中无混沌的周期增加分岔、神经元中的混沌爆发和搏动,以及心脏细胞中的逆倍周期分岔。Chay提出的三变量模型提供了一个关于可兴奋细胞如何产生爆发性动作电位的数学描述。该模型包含一个形成基础波的慢动态变量、一个导致尖峰的快动态变量以及作为因变量的膜电位。在本文中,我们使用Chay模型来解释这些振荡现象。庞加莱返回映射方法用于以“慢”电导(即gK、C)作为分岔参数构建分岔图。这些图表明,随着参数gK、C的变化,系统从重复尖峰转变为混沌爆发。然而,根据快变量(lambda n)的时间动力学常数,即使没有混沌,也可能通过周期增加分岔在爆发之间发生转变。在Chay模型中,在gK、C和lambda n的一定范围内存在阻尼爆发。此外,在触发动作电位之前,在gK、C的某些值处观察到阈值正弦振荡。这可能解释了为什么神经元细胞在爆发前表现出低幅振荡。

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