The Study of Generalized Synchronization between Two Identical Neurons Based on the Laplace Transform Method
Source abstract
Abstract
In this paper, a new method is proposed based on the auxiliary system approach to investigate generalized synchronization between two identical neurons with unidirectional coupling. Different from other studies, the synchronization error system between the response and auxiliary systems is converted into a set of Volterra integral equations according to the Laplace transform method and convolution theorem. By using the successive approximation method in the theory of integral equations, an analytical criterion for the detection of generalized synchronization between two identical neurons is obtained. It is found that there is a time difference between two signals of neurons when the generalized synchronization between them is achieved. Furthermore, the value of the time difference has no relation to the generalized synchronization condition but depends on the coupling function between two neurons. The study in this paper shows that one can construct a coupling function between two identical neurons using the current signal of the drive system to predict its future signal or make its past signal reappear.
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Research context
OpenAlex topics: stochastic dynamics and bifurcation · Nonlinear Dynamics and Pattern Formation · Neural dynamics and brain function
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Affiliations
School of Environment and Architecture, University of Shanghai for Science and Technology, Shanghai 200093, China
Funding
National Natural Science Foundation of China
References (28)
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