Weak electric fields detectability in a noisy neural network

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• 作者：Jia Zhao ; Bin Deng ; Yingmei Qin ; Cong Men ; Jiang Wang ; Xile Wei…
• 关键词：Detectability ; Stochastic resonance ; Izhikevich neuron model ; Weak electric field
• 刊名：Cognitive Neurodynamics
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：11
• 期：1
• 页码：81-90
• 全文大小：
• 刊物主题：Biomedicine, general; Neurosciences; Computer Science, general; Artificial Intelligence (incl. Robotics); Biochemistry, general; Cognitive Psychology;
• 出版者：Springer Netherlands
• ISSN：1871-4099
• 卷排序：11

文摘

We investigate the detectability of weak electric field in a noisy neural network based on Izhikevich neuron model systematically. The neural network is composed of excitatory and inhibitory neurons with similar ratio as that in the mammalian neocortex, and the axonal conduction delays between neurons are also considered. It is found that the noise intensity can modulate the detectability of weak electric field. Stochastic resonance (SR) phenomenon induced by white noise is observed when the weak electric field is added to the network. It is interesting that SR almost disappeared when the connections between neurons are cancelled, suggesting the amplification effects of the neural coupling on the synchronization of neuronal spiking. Furthermore, the network parameters, such as the connection probability, the synaptic coupling strength, the scale of neuron population and the neuron heterogeneity, can also affect the detectability of the weak electric field. Finally, the model sensitivity is studied in detail, and results show that the neural network model has an optimal region for the detectability of weak electric field signal.