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  A dynamic neural network with temporal coding and functional connectivity

Watanabe, M., Aihara, K., & Kondo, S. (1997). A dynamic neural network with temporal coding and functional connectivity. Biological Cybernetics, 78(2), 87-93. doi:10.1007/s004220050416.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-EA68-9 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-EA69-7
Genre: Journal Article

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Watanabe, M1, Author              
Aihara, K, Author
Kondo, S, Author
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1Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              

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 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.

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 Dates: 1997-02
 Publication Status: Published in print
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Title: Biological Cybernetics
Source Genre: Journal
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Pages: - Volume / Issue: 78 (2) Sequence Number: - Start / End Page: 87 - 93 Identifier: -