Hot coffee: associative memory with bump attractor cell assemblies of spiking neurons

Article

Huyck, C. and Vergani, A. 2020. Hot coffee: associative memory with bump attractor cell assemblies of spiking neurons. Journal of Computational Neuroscience. 48 (3), pp. 299-316. https://doi.org/10.1007/s10827-020-00758-1
TypeArticle
TitleHot coffee: associative memory with bump attractor cell assemblies of spiking neurons
AuthorsHuyck, C. and Vergani, A.
Abstract

Networks of spiking neurons can have persistently firing stable bump attractors to represent continuous spaces (like temperature). This can be done with a topology with local excitatory synapses and local surround inhibitory synapses. Activating large ranges in the attractor can lead to multiple bumps, that show repeller and attractor dynamics; however, these bumps can be merged by overcoming the repeller dynamics. A simple associative memory can include these bump attractors, allowing the use of continuous variables in these memories, and these associations can be learned by Hebbian rules. These simulations are related to biological networks, showing that this is a step toward a more complete neural cognitive associative memory.

KeywordsAssociative memory; Bump attractor; Cell assemblies; Hebbian learning; Spiking neurons
Research GroupArtificial Intelligence group
PublisherSpringer International Publishing
JournalJournal of Computational Neuroscience
ISSN0929-5313
Electronic1573-6873
Publication dates
Online27 Jul 2020
Print01 Aug 2020
Publication process dates
Deposited13 Jul 2020
Accepted09 Jul 2020
Output statusPublished
Accepted author manuscript
Copyright Statement

This is a post-peer-review, pre-copyedit version of an article published in Journal of Computational Neuroscience. The final authenticated version is available online at: http://dx.doi.org/10.1007/s10827-020-00758-1

Digital Object Identifier (DOI)https://doi.org/10.1007/s10827-020-00758-1
Web of Science identifierWOS:000552602600001
LanguageEnglish
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