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Noise-induced Resonance in Hodgkin-Huxley Model

Author: GuanWenZuo
Tutor: WangJiang
School: Tianjin University
Course: Detection Technology and Automation
Keywords: Hodgkin-Huxley model noise Coherence Resonance Stochastic Resonance Vibrational Resonance
CLC: O321
Type: Master's thesis
Year: 2009
Downloads: 39
Quote: 1
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Abstract


Neural systems are complicated networks connected by a large number of neurons through gap junctions and synapse. The information transmission in neural network is realized by the firing and propagation of action potential. The combinations of action potentials of coupled neurons carry plenty of information. Noise plays an important role in both the information integration for a single neuron and information transmission in neural populations. So we can gain a deep understanding of the mechanism of information coding and transmission by analyzing the effects of noise on neurons.This thesis made a bifurcation analysis on Hodgkin-Huxley model and got its bifurcation point. Sinusoidal input of different amplitudes and frequencies was added near its saddle-node bifurcation point. In this way, we got the frequency that is sensitive to the system and analyzed the different patterns of firing in the different parameter spaces of input signal of the system.Coherence resonance analysis was made on Hodgkin-Huxley model by adding Gaussian White Noise and Ornstein-Uhlenbeck Noise to it respectively. This thesis, for the first time, points out the difference of the above-mentioned two noises for the coherence resonance phenomenon in neural systems.This thesis discussed the stochastic resonance and vibrational resonance for a single Hodgkin-Huxley model, and concluded that for neural systems, noise and high frequency can substitute each other. This thesis also got the appropriate coupling strength and noise intensity in stochastic resonance for excitatory chemical coupled neurons and discrete Laplacian operator connected neuron arrays.Based on the original research in this thesis, we got the mechanism of noise on neural systems. It also shed new light on the information transmission and processing in neural networks.

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CLC: > Mathematical sciences and chemical > Mechanics > Vibration theory > Linear vibration
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