Suppr超能文献

通过电压门控缝隙连接通道相互连接的神经元网络中的兴奋回响。

Reverberation of excitation in neuronal networks interconnected through voltage-gated gap junction channels.

作者信息

Maciunas Kestutis, Snipas Mindaugas, Paulauskas Nerijus, Bukauskas Feliksas F

机构信息

Institute of Cardiology, Lithuanian University of Health Sciences, 50009 Kaunas, Lithuania.

Institute of Cardiology, Lithuanian University of Health Sciences, 50009 Kaunas, Lithuania Department of Mathematical Modelling, Kaunas University of Technology, 51368 Kaunas, Lithuania.

出版信息

J Gen Physiol. 2016 Mar;147(3):273-88. doi: 10.1085/jgp.201511488. Epub 2016 Feb 15.

Abstract

We combined Hodgkin-Huxley equations and gating models of gap junction (GJ) channels to simulate the spread of excitation in two-dimensional networks composed of neurons interconnected by voltage-gated GJs. Each GJ channel contains two fast and slow gates, each exhibiting current-voltage (I-V) rectification and gating properties that depend on transjunctional voltage (Vj). The data obtained show how junctional conductance (gj), which is necessary for synchronization of the neuronal network, depends on its size and the intrinsic firing rate of neurons. A phase shift between action potentials (APs) of neighboring neurons creates bipolar, short-lasting Vj spikes of approximately ± 100 mV that induce Vj gating, leading to a small decay of gj, which can accumulate into larger decays during bursting activity of neurons. We show that I-V rectification of GJs in local regions of the two-dimensional network of neurons can lead to unidirectional AP transfer and consequently to reverberation of excitation. This reverberation can be initiated by a single electrical pulse and terminated by a low-amplitude pulse applied in a specific window of reverberation cycle. Thus, the model accounts for the influence of dynamically modulatable electrical synapses in shaping the function of a neuronal network and the formation of reverberation, which, as proposed earlier, may be important for the development of short-term memory and its consolidation into long-term memory.

摘要

我们将霍奇金-赫胥黎方程与缝隙连接(GJ)通道的门控模型相结合,以模拟由通过电压门控GJ相互连接的神经元组成的二维网络中兴奋的传播。每个GJ通道包含两个快速和慢速门,每个门都表现出电流-电压(I-V)整流和取决于跨结电压(Vj)的门控特性。获得的数据显示了神经元网络同步所必需的结电导(gj)如何取决于其大小和神经元的固有放电率。相邻神经元动作电位(AP)之间的相位偏移会产生约±100 mV的双极、短暂Vj尖峰,从而诱导Vj门控,导致gj出现小幅度衰减,在神经元爆发活动期间,这种衰减可能会累积成更大的衰减。我们表明,二维神经元网络局部区域中GJ的I-V整流可导致AP单向传递,进而导致兴奋的回响。这种回响可由单个电脉冲引发,并可通过在回响周期的特定窗口施加低幅度脉冲来终止。因此,该模型解释了动态可调制电突触在塑造神经元网络功能和回响形成中的影响,正如之前所提出的,这可能对短期记忆的发展及其巩固为长期记忆很重要。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验