Hull Michael J, Soffe Stephen R, Willshaw David J, Roberts Alan
Institute for Adaptive and Neural Computation, University of Edinburgh, Edinburgh, United Kingdom; School of Biological Sciences, University of Bristol, Bristol, United Kingdom.
School of Biological Sciences, University of Bristol, Bristol, United Kingdom.
PLoS Comput Biol. 2015 May 8;11(5):e1004240. doi: 10.1371/journal.pcbi.1004240. eCollection 2015 May.
Gap junctions between fine unmyelinated axons can electrically couple groups of brain neurons to synchronise firing and contribute to rhythmic activity. To explore the distribution and significance of electrical coupling, we modelled a well analysed, small population of brainstem neurons which drive swimming in young frog tadpoles. A passive network of 30 multicompartmental neurons with unmyelinated axons was used to infer that: axon-axon gap junctions close to the soma gave the best match to experimentally measured coupling coefficients; axon diameter had a strong influence on coupling; most neurons were coupled indirectly via the axons of other neurons. When active channels were added, gap junctions could make action potential propagation along the thin axons unreliable. Increased sodium and decreased potassium channel densities in the initial axon segment improved action potential propagation. Modelling suggested that the single spike firing to step current injection observed in whole-cell recordings is not a cellular property but a dynamic consequence of shunting resulting from electrical coupling. Without electrical coupling, firing of the population during depolarising current was unsynchronised; with coupling, the population showed synchronous recruitment and rhythmic firing. When activated instead by increasing levels of modelled sensory pathway input, the population without electrical coupling was recruited incrementally to unpatterned activity. However, when coupled, the population was recruited all-or-none at threshold into a rhythmic swimming pattern: the tadpole "decided" to swim. Modelling emphasises uncertainties about fine unmyelinated axon physiology but, when informed by biological data, makes general predictions about gap junctions: locations close to the soma; relatively small numbers; many indirect connections between neurons; cause of action potential propagation failure in fine axons; misleading alteration of intrinsic firing properties. Modelling also indicates that electrical coupling within a population can synchronize recruitment of neurons and their pacemaker firing during rhythmic activity.
细无髓鞘轴突之间的缝隙连接可使脑神经元群电耦合,从而使放电同步并促进节律性活动。为了探究电耦合的分布及意义,我们对一小群驱动幼蛙蝌蚪游泳的脑干神经元进行了建模分析,该神经元群已得到充分研究。我们使用了一个由30个具有无髓鞘轴突的多房室神经元组成的被动网络来推断:靠近胞体的轴突 - 轴突缝隙连接与实验测量的耦合系数最匹配;轴突直径对耦合有很大影响;大多数神经元通过其他神经元的轴突间接耦合。当添加活性通道时,缝隙连接会使动作电位沿细轴突的传播变得不可靠。增加初始轴突段的钠通道密度并降低钾通道密度可改善动作电位的传播。建模表明,在全细胞记录中观察到的对阶跃电流注入的单个尖峰放电不是细胞特性,而是电耦合导致的分流的动态结果。没有电耦合时,去极化电流期间群体的放电是不同步的;有耦合时,群体显示出同步募集和节律性放电。当通过增加模拟感觉通路输入水平来激活时,没有电耦合的群体逐渐被募集到无模式活动中。然而,当耦合时,群体在阈值时全或无地被募集到节律性游泳模式中:蝌蚪“决定”游泳。建模强调了细无髓鞘轴突生理学的不确定性,但在生物学数据的指导下,对缝隙连接做出了一般性预测:靠近胞体的位置;数量相对较少;神经元之间有许多间接连接;细轴突中动作电位传播失败的原因;内在放电特性的误导性改变。建模还表明,群体内的电耦合可使神经元在节律性活动期间的募集及其起搏器放电同步。