Phase dynamics in the biological neural networks
SCIE
SCOPUS
- Title
- Phase dynamics in the biological neural networks
- Authors
- Kim, S; Lee, 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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- There are no files associated with this item.
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