PMID: 3755622Jan 1, 1986Paper

Associative recognition and storage in a model network of physiological neurons

Biological cybernetics
J Buhmann, K Schulten

Abstract

We consider a neural network model in which the single neurons are chosen to closely resemble known physiological properties. The neurons are assumed to be linked by synapses which change their strength according to Hebbian rules on a short time scale (100 ms). The dynamics of the network--the time evolution of the cell potentials and the synapses--is investigated by computer simulation. As in more abstract network models (Cooper 1973; Hopfield 1982; Kohonen 1984) it is found that the local dynamics of the cell potentials and the synaptic strengths result in global cooperative properties of the network and enable the network to process an incoming flux of information and to learn and store patterns associatively. A trained net can associate missing details of a pattern, can correct wrong details and can suppress noise in a pattern. The network can further abstract the prototype from a series of patterns with variations. A suitable coupling constant connecting the dynamics of the cell potentials with the synaptic strengths is derived by a mean field approximation. This coupling constant controls the neural sensitivity and thereby avoids both extremes of the network state, the state of permanent inactivity and the state of epilep...Continue Reading

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Citations

Mar 15, 1991·Physical Review. a·W C SchieveG M Davis
Jun 20, 2006·Journal of Integrative Neuroscience·Roman R Poznanski, Jorge J Riera
Jan 1, 1992·Biological cybernetics·W Gerstner, J L van Hemmen
Jan 1, 1993·Biological cybernetics·A B KirillovD J Woodward
Nov 5, 2004·Journal of Neurophysiology·Jeremy D Cohen, Manuel A Castro-Alamancos
Dec 8, 2017·PloS One·Oliver L C Rourke, Daniel A Butts
Jan 1, 1987·Biological cybernetics·S Shinomoto
Jan 1, 1987·Biological cybernetics·J Buhmann, K Schulten
Jan 1, 1995·Physical Review. E, Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics·W Gerstner

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