Conference Paper (published)

Improving Associative Memory in a Network of Spiking Neurons

Details

Citation

Hunter R, Cobb SR & Graham B (2008) Improving Associative Memory in a Network of Spiking Neurons. In: Kurkova V, Neruda R & Koutnik J (eds.) Artificial Neural Networks - ICANN 2008: 18th International Conference, Prague, Czech Republic, September 3-6, 2008, Proceedings, Part II. Lecture Notes in Computer Science, 5164. 18th International Conference on Artificial Neural Networks –ICANN 2008, Prague, Czech Republic, 03.09.2008-06.09.2008. Berlin, Germany: Springer-Verlag, pp. 636-645. http://www.springerlink.com/content/b98q662816538526/; https://doi.org/10.1007/978-3-540-87559-8_66

Abstract
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. 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 with previously published results for a simple artificial neural network model. We investigate biologically plausible implementations of methods for improving recall under biologically realistic conditions, such as a sparsely connected network.

Keywords
Associative memory; Mammalian hippocampus; Neural networks; Pattern recall; Inhibition

StatusPublished
Title of seriesLecture Notes in Computer Science
Number in series5164
Publication date31/12/2008
Publication date online03/09/2008
Related URLshttp://www.informatik.uni-trier.de/…icann2008-1.html
PublisherSpringer-Verlag
Publisher URLhttp://www.springerlink.com/content/b98q662816538526/
Place of publicationBerlin, Germany
ISSN of series0302-9743
ISBN978-3-540-87558-1
Conference18th International Conference on Artificial Neural Networks –ICANN 2008
Conference locationPrague, Czech Republic
Dates

People (1)

Professor Bruce Graham

Professor Bruce Graham

Emeritus Professor, Computing Science