Overlapping cell assemblies from correlators

Article

Huyck, C. 2004. Overlapping cell assemblies from correlators. Neural Computing Letters. 56, pp. 435-439. https://doi.org/10.1016/j.neucom.2003.08.003
TypeArticle
TitleOverlapping cell assemblies from correlators
AuthorsHuyck, C.
Abstract

This paper introduces compensatory learning and shows how it can lead to the formation of Cell Assemblies (CAs) that share neurons. The work starts with standard Hebbian learning then adds a compensatory modifier that forces the total synaptic weight leaving a neuron toward a constant. This enables overlapping CAs because neurons that are in multiple categories have reduced weight stopping Assemblies merging. This provides a biologically plausible learning rule that eases the ability of CAs to overlap. A more complex CA system based on this work, is being developed as part of a current EPSRC grant (EP/D059720/1).

KeywordsNeural networks; Cell assemblies
Research GroupArtificial Intelligence group
PublisherElsevier
JournalNeural Computing Letters
ISSN0925-2312
Publication dates
Print01 Jan 2004
Publication process dates
Deposited21 Aug 2008
Output statusPublished
Publisher's version
Digital Object Identifier (DOI)https://doi.org/10.1016/j.neucom.2003.08.003
Web of Science identifierWOS:000188597300024
LanguageEnglish
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