The effects of external electrical field on a neural network with synaptic plasticity and conduction delays

被引：0

作者：

Zhao, Jia ^{[1
]}

Deng, Bin ^{[1
]}

Wei, Xile ^{[1
]}

Wang, Jiang ^{[1
]}

Men, Cong ^{[1
]}

Qin, Yingmei ^{[1
]}

Sun, Jianbing ^{[1
]}

机构：

[1] Tianjin Univ, Sch Elect Engn & Automat, Tianjin 300072, Peoples R China

来源：

PROCEEDINGS OF THE 2012 24TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC) | 2012年

关键词：

Spike-timing-dependent plasticity (STDP); Weak direct current stimuli; Rhythmic activity; TIMING-DEPENDENT PLASTICITY; DIRECT-CURRENT STIMULATION; LEARNING RULE; DYNAMICS; MODEL; EXCITABILITY; OSCILLATIONS;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Effects of external DC stimuli to the evolution of a neural network model are studied. It's found that the external DC stimuli can enhance the neural network's average firing rate, induces the neural network to get to a balanced state that exhibits rhythmic activity with high rate. The activity of the neural network can be affected by the synaptic connection strength, the conduction delays, the external stimuli and so on. These parameters can serve as factors in modulating the evolution of the neural network with different firing activities. Furthermore, these results may also relate to the mechanism of memory and learning process.

引用

页码：2449 / 2454

页数：6

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