Learning Synaptic Clusters for Nonlinear Dendritic Processing

Authors:
Michael W. Spratling;Gillian M. Hayes
Affiliations:
Department of Artificial Intelligence, University of Edinburgh, 5 Forrest Hill, Edinburgh, EH1 2QL, U.K. mikes@dai.ed.ac.uk;Department of Artificial Intelligence, University of Edinburgh, 5 Forrest Hill, Edinburgh, EH1 2QL, U.K. mikes@dai.ed.ac.uk
Venue:
Neural Processing Letters
Year:
2000

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Abstract

Nonlinear dendritic processing appears to be a feature of biological neuronsand would also be of use in many applications of artificial neuralnetworks. This paper presents a model of an initially standard linearnode which uses unsupervised learning to find clusters of inputs withinwhich inactivity at one synapse can occlude the activity at the othersynapses.