The estimation of neurotransmitter release probability in feedforward neuronal network based on adaptive synchronization

Ming Xue, Jiang Wang, Chenhui Jia, Haitao Yu, Bin Deng, Xile Wei, Yanqiu Che

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

In this paper, we proposed a new approach to estimate unknown parameters and topology of a neuronal network based on the adaptive synchronization control scheme. A virtual neuronal network is constructed as an observer to track the membrane potential of the corresponding neurons in the original network. When they achieve synchronization, the unknown parameters and topology of the original network are obtained. The method is applied to estimate the real-time status of the connection in the feedforward network and the neurotransmitter release probability of unreliable synapses is obtained by statistic computation. Numerical simulations are also performed to demonstrate the effectiveness of the proposed adaptive controller. The obtained results may have important implications in system identification in neural science.

Original languageEnglish (US)
Article number013109
JournalChaos
Volume23
Issue number1
DOIs
StatePublished - Mar 18 2013

All Science Journal Classification (ASJC) codes

  • Statistical and Nonlinear Physics
  • Mathematical Physics
  • Physics and Astronomy(all)
  • Applied Mathematics

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