Stochastic resonance in feedforward acupuncture networks

Ying Mei Qin, Jiang Wang, Cong Men, Bin Deng, Xi Le Wei, Hai Tao Yu, Wai Lok Chan

Research output: Journal article publicationJournal articleAcademic researchpeer-review

16 Citations (Scopus)

Abstract

Effects of noises and some other network properties on the weak signal propagation are studied systematically in feedforward acupuncture networks (FFN) based on FitzHugh-Nagumo neuron model. It is found that noises with medium intensity can enhance signal propagation and this effect can be further increased by the feedforward network structure. Resonant properties in the noisy network can also be altered by several network parameters, such as heterogeneity, synapse features, and feedback connections. These results may also provide a novel potential explanation for the propagation of acupuncture signal.
Original languageEnglish
Pages (from-to)3660-3670
Number of pages11
JournalCommunications in Nonlinear Science and Numerical Simulation
Volume19
Issue number10
DOIs
Publication statusPublished - 1 Jan 2014

Keywords

  • Feedforward network
  • FitzHugh-Nagumo neuron
  • Heterogeneity
  • Stochastic resonance

ASJC Scopus subject areas

  • Modelling and Simulation
  • Numerical Analysis
  • Applied Mathematics

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