论文标题
峰值霍奇金 - 赫克斯利神经元网络中的爆炸性,连续和沮丧的同步转变:拓扑和突触相互作用的作用
Explosive, continuous and frustrated synchronization transition in spiking Hodgkin-Huxley neuronal networks: the role of topology and synaptic interaction
论文作者
论文摘要
同步是相互作用振荡剂中重要的集体现象。大脑的许多功能特征与神经元的同步有关。近年来,可能发生的同步转变的类型(爆炸性与连续)一直是强烈关注的重点,主要是在相振荡器模型的背景下,集体行为与天然频率的平均值无关。但是,生物动机神经模型的同步性能取决于点火频率。在这项研究中,我们报告了一项系统的研究研究,该研究是对尖峰霍奇金 - 赫克斯利神经元中通过电或化学突触相互作用的伽玛同步。我们使用各种网络模型来定义连接矩阵。我们发现,γ波段中的基本机制和类型与β波段不同。在γ波段中,网络规则性抑制过渡,而随机性促进了连续的过渡。基础拓扑中的异质性不会导致过渡顺序的任何变化,但是,突触数量和神经元频率之间的相关性将导致具有电突触的异源网络中的爆炸性同步。此外,在聚类和随机性(如皮质中)之间建模良好平衡的小世界网络会导致与电突触的爆炸性同步,但在化学突触的情况下是平稳的转变。我们还发现,等级模块化网络(例如Connectome)导致沮丧的过渡。我们根据网络的各种特性来解释我们的结果,特别关注聚类和远程突触之间的竞争。
Synchronization is an important collective phenomenon in interacting oscillatory agents. Many functional features of the brain are related to synchronization of neurons. The type of synchronization transition that may occur (explosive vs. continuous) has been the focus of intense attention in recent years, mostly in the context of phase oscillator models for which collective behavior is independent of the mean-value of natural frequency. However, synchronization properties of biologically-motivated neural models depend on the firing frequencies. In this study we report a systematic study of gamma-band synchronization in spiking Hodgkin-Huxley neurons which interact via electrical or chemical synapses. We use various network models in order to define the connectivity matrix. We find that the underlying mechanisms and types of synchronization transitions in gamma-band differs from beta-band. In gamma-band, network regularity suppresses transition while randomness promotes a continuous transition. Heterogeneity in the underlying topology does not lead to any change in the order of transition, however, correlation between number of synapses and frequency of a neuron will lead to explosive synchronization in heterogenous networks with electrical synapses. Furthermore, small-world networks modeling a fine balance between clustering and randomness (as in the cortex), lead to explosive synchronization with electrical synapses, but a smooth transition in the case of chemical synapses. We also find that hierarchical modular networks, such as the connectome, lead to frustrated transitions. We explain our results based on various properties of the network, paying particular attention to the competition between clustering and long-range synapses.