论文标题
神经异质性对尖峰神经网络动态的影响
Effects of Neural Heterogeneity on Spiking Neural Network Dynamics
论文作者
论文摘要
大脑由相互作用的神经元的复杂网络组成，这些神经元在其生理和尖峰特征中表达相当多的异质性。神经异质性如何影响宏观神经动力学，它如何促进神经动力学功能？在这封信中，我们通过研究异质Izhikevich神经元网络的宏观动态来解决这些问题。我们得出这些网络的平均场方程，并研究了Izhikevich神经元的尖峰阈值中的异质性如何影响新兴的宏观动力学。我们的结果表明，抑制群体的异质性水平控制着耦合兴奋性和抑制性神经元系统的共振和磁滞性能。因此，神经异质性可以用作控制介观脑回路动态曲目的一种手段。
The brain is composed of complex networks of interacting neurons that express considerable heterogeneity in their physiology and spiking characteristics. How does neural heterogeneity affect macroscopic neural dynamics and how does it contribute to neurodynamic functions? In this letter, we address these questions by studying the macroscopic dynamics of networks of heterogeneous Izhikevich neurons. We derive mean-field equations for these networks and examine how heterogeneity in the spiking thresholds of Izhikevich neurons affects the emergent macroscopic dynamics. Our results suggest that the level of heterogeneity of inhibitory populations controls resonance and hysteresis properties of systems of coupled excitatory and inhibitory neurons. Neural heterogeneity may thus serve as a means to control the dynamic repertoire of mesoscopic brain circuits.
