Cognitive Neurodynamics

, Volume 11, Issue 1, pp 81–90 | Cite as

Weak electric fields detectability in a noisy neural network

  • Jia Zhao
  • Bin DengEmail author
  • Yingmei Qin
  • Cong Men
  • Jiang Wang
  • Xile Wei
  • Jianbing Sun
Research Article


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.


Detectability Stochastic resonance Izhikevich neuron model Weak electric field 



This work is supported by the National Natural Science Foundation of China (Grant Nos. 61401312 and 61671320).


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Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Jia Zhao
    • 1
  • Bin Deng
    • 2
    Email author
  • Yingmei Qin
    • 3
  • Cong Men
    • 2
  • Jiang Wang
    • 2
  • Xile Wei
    • 2
  • Jianbing Sun
    • 2
  1. 1.Key Laboratory of Cognition and Personality (Ministry of Education) and School of PsychologySouthwest UniversityChongqingChina
  2. 2.School of Electrical Engineering and AutomationTianjin UniversityTianjinChina
  3. 3.Tianjin Key Laboratory of Information Sensing and Inteligent ControlTianjin University of Technology and EducationTianjinChina

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