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具有突触和间隙连接耦合的二次积分和放电神经元环形网络中的活动模式。

Activity patterns in ring networks of quadratic integrate-and-fire neurons with synaptic and gap junction coupling.

机构信息

<a href="https://ror.org/03bnmw459">University of Potsdam</a>, Institute of Physics and Astronomy, Karl-Liebknecht-Str. 24/25, 14476 Potsdam, Germany.

School of Mathematical and Computational Sciences, <a href="https://ror.org/052czxv31">Massey University</a>, Private Bag 102-904 NSMC, Auckland, New Zealand.

出版信息

Phys Rev E. 2024 Sep;110(3-1):034411. doi: 10.1103/PhysRevE.110.034411.

Abstract

We consider a ring network of quadratic integrate-and-fire neurons with nonlocal synaptic and gap junction coupling. The corresponding neural field model supports solutions such as standing and traveling waves, and also lurching waves. We show that many of these solutions satisfy self-consistency equations which can be used to follow them as parameters are varied. We perform numerical bifurcation analysis of the neural field model, concentrating on the effects of varying gap junction coupling strength. Our methods are generally applicable to a wide variety of networks of quadratic integrate-and-fire neurons.

摘要

我们考虑了一个具有非局部突触和间隙连接耦合的二次积分和点火神经元的环形网络。相应的神经场模型支持驻波和行波等解,也支持颠簸波。我们表明,这些解中的许多满足自洽方程,可以用于随着参数的变化来跟踪它们。我们对神经场模型进行了数值分岔分析,集中研究了改变间隙连接耦合强度的影响。我们的方法通常适用于各种二次积分和点火神经元网络。

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