Synchronization and Rhythm Transition in a Complex Neuronal Network

被引:12
作者
Wang, Yuan [1 ]
Shi, Xia [2 ]
Cheng, Bo [1 ]
Chen, Junliang [1 ]
机构
[1] Beijing Univ Posts & Telecommun, State Key Lab Networking & Switching Technol, Beijing 100876, Peoples R China
[2] Beijing Univ Posts & Telecommun, Sch Sci, Beijing 100876, Peoples R China
基金
美国国家科学基金会;
关键词
Neurons; Synchronization; Rhythm; Biological neural networks; Computational modeling; Mathematical model; Biological system modeling; Small-world network; Neuronal network; Brain rhythm; Excitatory-Inhibitory network; Izhikevich neuron model; TIMING-DEPENDENT PLASTICITY; NEURAL-NETWORKS; BURST SYNCHRONIZATION; OSCILLATIONS; DYNAMICS; MODELS;
D O I
10.1109/ACCESS.2020.2997879
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Synchronization and rhythm transition in an excitatory-inhibitory balanced cortical neuronal network are investigated in this paper. A small-world neuronal network is performed to be the cortical region of cerebral cortex, which is composed of different types of Izhikevich neurons. The combination of regular spiking (RS) cells, chattering (CH) cells, or mixed RS and CH cells are imitated as excitatory neurons, whereas fast spiking (FS) cells mimic inhibitory neurons. We mainly focus on the effect of different types of neurons on synchronization and rhythm transition of the neuronal network. The simulation results illustrate that it is easier for the neuronal network with CH excitatory neurons to achieve synchronization, and it is also more susceptible to the parameters than the network with RS neurons. Together with the weight of the synaptic connection, the structure of the small-world network is also explored to identify its influence on the synchronization and the rhythm transition. Moreover, we found that the synchronization performance could be improved by increasing the degree of influence among neurons. Importantly, the synchronization states are associated with the rhythm transitions. Especially, the consistency of synchronization of the neuronal network and band rhythm is illustrated. In addition, our results could have an important significance on further understanding brain rhythms and synchrony in neuroscience.
引用
收藏
页码:102436 / 102448
页数:13
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