Improving associative memory in a network of spiking neurons

Russell Hunter, Stuart Cobb, Bruce P. Graham

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

4 Citations (Scopus)


Associative neural network models are a commonly used methodology when investigating the theory of associative memory in the brain. Comparisons between the mammalian hippocampus and neural network models of associative memory have been investigated [7]. Biologically based networks are complex systems built of neurons with a variety of properties. Here we compare and contrast associative memory function in a network of biologically-based spiking neurons [14] with previously published results for a simple artificial neural network model [6]. We investigate biologically plausible implementations of methods for improving recall under biologically realistic conditions, such as a sparsely connected network.

Original languageEnglish
Title of host publicationArtificial Neural Networks - ICANN 2008 - 18th International Conference, Proceedings
EditorsV. Kůrková , R. Neruda, J. Koutník
Place of PublicationBerlin
Number of pages10
EditionPART 2
ISBN (Print)3540875581, 9783540875581
Publication statusPublished - 22 Sept 2008
Event18th International Conference on Artificial Neural Networks, ICANN 2008 - Prague, Czech Republic
Duration: 3 Sept 20086 Sept 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume5164 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference18th International Conference on Artificial Neural Networks, ICANN 2008
Country/TerritoryCzech Republic


  • associative memory
  • inhibition
  • mammalian hippocampus
  • neural networks
  • pattern recall


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