Phase dynamics in the biological neural networks

Seunghwan Kim and Sang Gui Lee

Physica A: Statistical Mechanics and its Applications, 2000, vol. 288, issue 1, 380-396

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.

Keywords: Biological neural networks; Nonlinear oscillations; Synchrony; Phase models (search for similar items in EconPapers)
Date: 2000
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:288:y:2000:i:1:p:380-396

DOI: 10.1016/S0378-4371(00)00435-0

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