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
Type | Article |
---|---|
Title | Hot coffee: associative memory with bump attractor cell assemblies of spiking neurons |
Authors | Huyck, 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. |
Keywords | Associative memory; Bump attractor; Cell assemblies; Hebbian learning; Spiking neurons |
Research Group | Artificial Intelligence group |
Publisher | Springer International Publishing |
Journal | Journal of Computational Neuroscience |
ISSN | 0929-5313 |
Electronic | 1573-6873 |
Publication dates | |
Online | 27 Jul 2020 |
01 Aug 2020 | |
Publication process dates | |
Deposited | 13 Jul 2020 |
Accepted | 09 Jul 2020 |
Output status | Published |
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 identifier | WOS:000552602600001 |
Language | English |
https://repository.mdx.ac.uk/item/89025
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