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Cited 6 time in webofscience Cited 6 time in scopus
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Phase dynamics in the biological neural networks SCIE SCOPUS

Title
Phase dynamics in the biological neural networks
Authors
Kim, SLee, SG
Date Issued
2000-12-15
Publisher
ELSEVIER SCIENCE BV
Abstract
The simplified models of neural networks based on biophysical Hodgkin-Huxley neurons are studied with a focus on coherent-phase dynamics. In our approach, each neuron is considered as a nonlinear oscillator, and collective dynamics of a mesoscopic network of neural oscillators are studied using the methods of nonlinear dynamics. We explore the mechanisms for synchrony, clustering and their breakup in the synaptic parameter space and discuss implications to temporal aspects of neural-information processing. (C) 2000 Elsevier Science B.V. All rights reserved.
Keywords
biological neural networks; nonlinear oscillations; synchrony; phase models; CAT VISUAL-CORTEX; LIMIT-CYCLE OSCILLATORS; HODGKIN-HUXLEY NEURONS; COUPLED OSCILLATORS; TIME-DELAY; TEMPORAL SEGMENTATION; SYSTEM; SYNCHRONIZATION; CHAOS; MODEL
URI
https://oasis.postech.ac.kr/handle/2014.oak/19744
DOI
10.1016/S0378-4371(00)00435-0
ISSN
0378-4371
Article Type
Article
Citation
PHYSICA A, vol. 288, no. 1-4, page. 380 - 396, 2000-12-15
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