Improving recall in an associative neural network of spiking neurons

Russell Hunter, Stuart Cobb, Bruce P. Graham

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

1 Citation (Scopus)

Abstract

The mammalian hippocampus has often been compared to neural networks of associative memory [6]. Previous investigation of associative memory in the brain using associative neural networks have lacked biological complexity. Using a network of biologically plausible spiking neurons we examine associative memory function against results for a simple artificial neural net [5]. We investigate implementations of methods for improving recall under biologically realistic conditions.

Original languageEnglish
Title of host publicationDynamic Brain - from Neural Spikes to Behaviors - 12th International Summer School on Neural Networks, Revised Lectures
EditorsM. Marinaro, S. Scarpetta, Y. Yamaguchi
Place of PublicationBerlin
PublisherSpringer
Pages137-141
Number of pages5
ISBN (Print)3540888527, 9783540888529
DOIs
Publication statusPublished - 1 Dec 2008
Event12th International Summer School on Neural Networks - Erice, Italy
Duration: 5 Dec 200712 Dec 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5286 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference12th International Summer School on Neural Networks
CountryItaly
CityErice
Period5/12/0712/12/07

Keywords

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

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  • Cite this

    Hunter, R., Cobb, S., & Graham, B. P. (2008). Improving recall in an associative neural network of spiking neurons. In M. Marinaro, S. Scarpetta, & Y. Yamaguchi (Eds.), Dynamic Brain - from Neural Spikes to Behaviors - 12th International Summer School on Neural Networks, Revised Lectures (pp. 137-141). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5286 LNCS). Berlin: Springer. https://doi.org/10.1007/978-3-540-88853-6_12