Synchronization of biological neural network systems with stochastic perturbations and time delays

Xianlin Zeng*, Qing Hui, Wassim M. Haddad, Tomohisa Hayakawa, James M. Bailey

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

Abstract

With advances in biochemistry, molecular biology, and neurochemistry there has been impressive progress in the understanding of the molecular properties of anesthetic agents. However, despite these advances, we still do not understand how anesthetic agents affect the properties of neurons that translate into the induction of general anesthesia at the macroscopic level. There is extensive experimental verification that collections of neurons may function as oscillators and the synchronization of oscillators may play a key role in the transmission of information within the central nervous system. This may be particularly relevant to understanding the mechanism of action for general anesthesia. In this paper, we develop a stochastic synaptic drive firing rate model for an excitatory and inhibitory cortical neuronal network in the face of system time delays. In addition, we provide sufficient conditions for global asymptotic mean-square synchronization for this model.

Original languageEnglish
Article number6425969
Pages (from-to)1059-1064
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event51st IEEE Conference on Decision and Control, CDC 2012 - Maui, HI, United States
Duration: 10 Dec 201213 Dec 2012

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