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Response functions for electrically coupled neuronal network: a method of local point matching and its applications

机译:电耦合神经网络的响应函数:局部点匹配方法及其应用

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摘要

Neuronal networks connected by electrical synapses, also referred to as gap junctions, are present throughout the entire central nervous system. Many instances of gap-junctional coupling are formed between dendritic arbours of individual cells, and these dendro-dendritic gap junctions are known to play an important role in mediating various brain rhythms in both normal and pathological states. The dynamics of such neuronal networks modelled by passive or quasi-active (resonant) membranes can be described by the Green’s function which provides the fundamental input-output relationships of the entire network. One of the methods for calculating this response function is the so-called ‘sum-over-trips’ framework which enables the construction of the Green’s function for an arbitrary network as a convergent infinite series solution. Here we propose an alternative and computationally efficient approach for constructing the Green’s functions on dendro-dendritic gap junction-coupled neuronal networks which avoids any infinite terms in the solutions. Instead, the Green’s function is constructed from the solution of a system of linear algebraic equations. We apply this new method to a number of systems including a simple single cell model and two-cell neuronal networks. We also demonstrate that the application of this novel approach allows one to reduce a model with complex dendritic formations to an equivalent model with a much simpler morphological structure.
机译:通过电突触连接的神经元网络,也称为间隙连接,存在于整个中枢神经系统中。单个细胞的树突状树突之间形成了许多缝隙-连接偶联的情况,并且已知这些树突-树突状缝隙连接在介导正常和病理状态下的各种脑节律中起重要作用。格林函数可以描述由被动或准主动(共振)膜建模的这种神经元网络的动力学,格林函数提供了整个网络的基本输入输出关系。计算此响应函数的方法之一是所谓的“行程总和”框架,该框架可将任意网络的格林函数构造为收敛的无限级数解。在这里,我们提出了一种替代的,计算效率高的方法,用于在树突-树突间隙连接耦合神经元网络上构造格林函数,从而避免了解决方案中的任何无限项。相反,格林函数是根据线性代数方程组的解来构造的。我们将此新方法应用于许多系统,包括简单的单细胞模型和两细胞神经元网络。我们还证明,这种新颖方法的应用使人们可以将具有复杂树突状结构的模型还原为具有更简单的形态结构的等效模型。

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