A Self-Organizing Pulse-Coupled Network of Sub-Threshold Oscillating Spiking Neurons

Kai KINOSHITA  Hiroyuki TORIKAI  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E94-A   No.1   pp.300-314
Publication Date: 2011/01/01
Online ISSN: 1745-1337
DOI: 10.1587/transfun.E94.A.300
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Nonlinear Problems
Keyword: 
spiking neuron model,  synchronization,  pulse-coupled neural network,  self-organization,  

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Summary: 
In this paper, an artificial sub-threshold oscillating spiking neuron is presented and its response phenomena to an input spike-train are analyzed. In addition, a dynamic parameter update rule of the neuron for achieving synchronizations to the input spike-train having various spike frequencies is presented. Using an analytical two-dimensional return map, local stability of the parameter update rule is analyzed. Furthermore, a pulse-coupled network of the neurons is presented and its basic self-organizing function is analyzed. Fundamental comparisons are also presented.