University of Hertfordshire

By the same authors

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Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer
Pages136-142
Number of pages7
Volume7223 LNCS
ISBN (Electronic)978-3-642-28792-3
ISBN (Print)978-3-642-28791-6
DOIs
Publication statusPublished - 2012
EventIPCAT 2012 - Cambridge, United Kingdom
Duration: 31 Mar 2012 → …

Conference

ConferenceIPCAT 2012
CountryUnited Kingdom
CityCambridge
Period31/03/12 → …

Abstract

In real neuronal networks it is known that neurons are either excitatory or inhibitory. However, it is not known whether all synapses within the subpopulations are plastic. It is interesting to investigate the implications these constraints may have on functionality. Here we investigate highly simplified models of associative memory with a variety of allowed synaptic plasticity regimes. We show that the allowed synaptic plasticity does indeed have a large effect on the performance of the network and that some regimes are much better than others.

Projects

ID: 1005857