Vibrational resonance in a randomly connected neural network

被引:21
|
作者
Qin, Yingmei [1 ]
Han, Chunxiao [1 ]
Che, Yanqiu [1 ]
Zhao, Jia [2 ,3 ,4 ]
机构
[1] Tianjin Univ Technol & Educ, Sch Automat & Elect Engn, Tianjin Key Lab Informat Sensing & Intelligent Co, Tianjin, Peoples R China
[2] Southwest Univ, Minist Educ, Key Lab Cognit & Personal, Chongqing, Peoples R China
[3] Southwest Univ, Fac Psychol, Chongqing, Peoples R China
[4] Chongqing Collaborat Innovat Ctr Brain Sci, Chongqing, Peoples R China
基金
中国国家自然科学基金;
关键词
Vibrational resonance; Neural network; Izhikevich neuron model; Weak electric field; DIRECT-CURRENT STIMULATION; STOCHASTIC RESONANCE; ELECTRIC-FIELDS; EXCITABLE SYSTEMS; NEURONAL NETWORKS; NOISE; PROPAGATION; SPIKING; SIGNAL; OSCILLATIONS;
D O I
10.1007/s11571-018-9492-2
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
A randomly connected network is constructed with similar characteristics (e.g., the ratio of excitatory and inhibitory neurons, the connection probability between neurons, and the axonal conduction delays) as that in the mammalian neocortex and the effects of high-frequency electrical field on the response of the network to a subthreshold low-frequency electrical field are studied in detail. It is found that both the amplitude and frequency of the high-frequency electrical field can modulate the response of the network to the low-frequency electric field. Moreover, vibrational resonance (VR) phenomenon induced by the two types of electrical fields can also be influenced by the network parameters, such as the neuron population, the connection probability between neurons and the synaptic strength. It is interesting that VR is found to be related with the ratio of excitatory neurons that are under high-frequency electrical stimuli. In summary, it is suggested that the interaction of excitatory and inhibitory currents is also an important factor that can influence the performance of VR in neural networks.
引用
收藏
页码:509 / 518
页数:10
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