Synchronized action of synaptically coupled chaotic model neurons
Synchronized action of synaptically coupled chaotic model neurons
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DOI：
10.1162/neco.1996.8.8.1567
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发表时间：
1996-11-15
影响因子：
2.9
通讯作者：
Selverston, AI
中科院分区：
文献类型：
--
作者：
Abarbanel, HDI;Huerta, R;Selverston, AI
对单个神经元的细胞内电活动记录的实验观察表明，时间行为往往是混乱的。我们讨论了我们自己对龙虾口胃中枢模式发生器细胞的观察和早期对其他细胞的观察。在这篇论文中，我们研究了混沌神经元的模型，建立在Hindmarsh和Rose关于神经元爆发、尖峰活动的模型之上。这些简化的神经元模型的关键特征是存在耦合的慢速和快速子系统。我们使用与分析实验数据相同的工具来分析模型神经元。我们以电张力和电化学方式将两个模型神经元以抑制性和兴奋性方式耦合起来。在每种情况下，我们都证明了模型神经元可以根据耦合的强度在相位和非相位中同步。对于正常的突触耦合，我们在一个神经元的动作和另一个神经元的反应之间有一个时间延迟。我们还分析了同步如何依赖于此延迟。对于电偶联神经元和神经元之间的抑制偶联来说，同步行为的丰富谱是可能的。在同步神经元中，通常可以看到耦合神经元的混沌运动。激发耦合产生的本质上是周期性的电压轨迹，这也是同步的。我们使用同步的两个“距离”度量来显示和讨论这些同步行为。
Experimental observations of the intracellular recorded electrical activity in individual neurons show that the temporal behavior is often chaotic We discuss both our own observations on a cell from the stomatogastric central pattern generator of lobster and earlier observations in other cells.In this paper we work with models of chaotic neurons, building on models by Hindmarsh and Rose for bursting, spiking activity in neurons. The key feature of these simplified models of neurons is the presence of coupled slow and fast subsystems. We analyze the model neurons using the same tools employed in the analysis of our experimental data.We couple two model neurons both electrotonically and electrochemically in inhibitory and excitatory fashions. In each of these cases, we demonstrate that the model neurons can synchronize in phase and out of phase depending on the strength of the coupling. For normal synaptic coupling, we have a time delay between the action of one neuron and the response of the other. We also analyze how the synchronization depends on this delay. A rich spectrum of synchronized behaviors is possible for electrically coupled neurons and for inhibitory coupling between neurons. In synchronous neurons one typically sees chaotic motion of the coupled neurons. Excitatory coupling produces essentially periodic voltage trajectories, which are also synchronized. We display and discuss these synchronized behaviors using two ''distance'' measures of the synchronization.