PMID: 9525035Apr 3, 1998Paper

A dynamic neural network with temporal coding and functional connectivity

Biological cybernetics
M WatanabeS Kondo

Abstract

A neural network model capable of altering its pattern classifying properties by program input is proposed. Here the "program input" is another source of input besides the pattern input. Unlike most neural network models, this model runs as a deterministic point process of spikes in continuous time; connections among neurons have finite delays, which are set randomly according to a normal distribution. Furthermore, this model utilizes functional connectivity which is dynamic connectivity among neurons peculiar to temporal-coding neural networks with short neuronal decay time constants. Computer simulation of the proposed network has been performed, and the results are considered in light of experimental results shown recently for correlated firings of neurons.

Citations

Dec 14, 1999·Neuroscience and Biobehavioral Reviews·Y Sakurai
Jun 20, 2001·Neural Networks : the Official Journal of the International Neural Network Society·M WatanabeK Aihara
Nov 23, 2001·Neural Networks : the Official Journal of the International Neural Network Society·Y Sakai
Mar 10, 2004·Neural Computation·Naoki Masuda, Kazuyuki Aihara
Oct 16, 2004·IEEE Transactions on Neural Networks·Masataka Watanabe, Kazuyuki Aihara
Dec 12, 2001·Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics·N Masuda, K Aihara
Nov 3, 2001·Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics·Y Li, A Guo

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