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自适应指数积分发放神经元网络中的峰电位爆发嵌合态

Spike-burst chimera states in an adaptive exponential integrate-and-fire neuronal network.

作者信息

Santos Moises S, Protachevicz Paulo R, Iarosz Kelly C, Caldas Iberê L, Viana Ricardo L, Borges Fernando S, Ren Hai-Peng, Szezech José D, Batista Antonio M, Grebogi Celso

机构信息

Department of Physics, Federal University of Paraná, 80060-000 Curitiba, PR, Brazil.

Graduate in Science Program-Physics, State University of Ponta Grossa, 84030-900 Ponta Grossa, PR, Brazil.

出版信息

Chaos. 2019 Apr;29(4):043106. doi: 10.1063/1.5087129.

DOI:10.1063/1.5087129
PMID:31042937
Abstract

Chimera states are spatiotemporal patterns in which coherence and incoherence coexist. We observe the coexistence of synchronous (coherent) and desynchronous (incoherent) domains in a neuronal network. The network is composed of coupled adaptive exponential integrate-and-fire neurons that are connected by means of chemical synapses. In our neuronal network, the chimera states exhibit spatial structures both with spike and burst activities. Furthermore, those desynchronized domains not only have either spike or burst activity, but we show that the structures switch between spikes and bursts as the time evolves. Moreover, we verify the existence of multicluster chimera states.

摘要

嵌合态是指相干性和非相干性共存的时空模式。我们观察到在神经网络中同步(相干)域和去同步(非相干)域共存。该网络由通过化学突触连接的耦合自适应指数积分发放神经元组成。在我们的神经网络中,嵌合态表现出具有尖峰和爆发活动的空间结构。此外,那些去同步域不仅具有尖峰或爆发活动,而且我们表明随着时间的推移,这些结构在尖峰和爆发之间切换。此外,我们验证了多簇嵌合态的存在。

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