Study for nonlocally coupled excitable cells exposed by noise using computer simulation = 잡음에 노출된 비국소적으로 연결된 흥분 세포들의 컴퓨터 시늉을 이용한 연구

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The response of nonlinear systems to noise is very interesting research topic. Especially, stochastic resonance (SR) has attracted large attention during the last two decades. The basic result of SR shows that the response of a nonlinear system is optimized at a certain finite level, neither very weak nor very strong, of noise. Here, optimized response means that a system detects very weak signal aid by optimal noise and can show most coherent motion aid by optimal noise. The SR phenomena have emerged in many fields, from physical to biological systems. In particular, SR has been studied very extensively due to an application in information process of neuroscience. In this thesis, we investigate the response of neural network to noise for two neuron models with numerical method. Previous studies have been conducted on regular or fully random network mainly. But it is well known that biological neural network present a clear clustering in their neurons but have small distances between each pair of neurons. This kind of network is known as small-world network. Therefore, throughout this work, we employ Watts-Strogatz small-world network as a connection topology. Firstly, we investigate the coherence resonance (CR) of Hodgkin-Huxley neurons. It is found that increasing the randomness p of the network topology leads to an enhancement of temporal coherence and of spatial synchronization. Especially, it is found that (1) spatial synchronization increase as characteristic path length L shortens and (2) firing frequency increases as clustering coefficient C decreases. We introduce constant-clustering network. In such a network, synchronization increases as L shortens, but firing frequency remains constantly. This result leads to more confidence of above relations. Secondly, we study the effect of spatially correlated noise on CR in neural network of Fitz Hugh-Nagumo neurons, where the noise correlation decays exponentially with distance between neurons. For intermediat...
Advisors
Moon, Hie-Taeresearcher문희태researcher
Description
한국과학기술원 : 물리학과,
Publisher
한국과학기술원
Issue Date
2006
Identifier
254159/325007  / 020015026
Language
eng
Description

학위논문(박사) - 한국과학기술원 : 물리학과, 2006.2, [ ix, 59 p. ]

Keywords

noise; Neuron; small-world network; 좁은세상 연결망; 잡음; 신경세포

URI
http://hdl.handle.net/10203/47379
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=254159&flag=dissertation
Appears in Collection
PH-Theses_Ph.D.(박사논문)
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