Interneuron Plasticity in Associative Networks

Abstract

Associative network models with binary synapses are widely studied as a biologically plausible memory mechanism. These models often include a single interneuron, used to set a global threshold for a network of sparsely interconnected principal cells, and the storage capacity improves with the use of a multi-step recall process (Gardner-Medwin, 1976). We demonstrate that the inclusion of non-saturating modifiable Hebbian synaptic weights in the projection from the interneuron to the principal cells drastically improves the performance of the network. These synaptic weights reduce the influence of the principal cells that are active in a disproportionate number of memory events.

Keywords

Associative Memory Synaptic Weight Memory Event Principal Cell Global Threshold 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1997

Authors and Affiliations

  1. 1.Department of Anatomy and Developmental BiologyUniversity College LondonLondonUK

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