Associative memory with biologically-inspired cell assemblies
Conference paper
Ji, Y., Gamez, D. and Huyck, C. 2024. Associative memory with biologically-inspired cell assemblies. Samsonovich, A.V. and Liu, T. (ed.) 2023 Annual International Conference on Brain-Inspired Cognitive Architectures for Artificial Intelligence, the 14th Annual Meeting of the BICA Society (BICA*AI 2023). Ningbo, China 13 - 15 Oct 2023 Springer. pp. 422-428 https://doi.org/10.1007/978-3-031-50381-8_43
Type | Conference paper |
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Title | Associative memory with biologically-inspired cell assemblies |
Authors | Ji, Y., Gamez, D. and Huyck, C. |
Abstract | Associative memory is a central cognitive task. However, the actual biological architecture that supports this memory is not currently known, so simulating with biologically plausible neurons and topologies is an ideal mechanism to improve understanding of associative memory. Simulations of spiking networks that per-form associative memory tasks lay the groundwork for utilizing biological neurons in cognitive tasks. Specifically, this paper explores simulations of spiking networks that perform associative memory tasks using Hebbian cell assemblies of neurons to represent nodes and synapses to represent associations. The first tasks use binary cell assemblies to perform two well-known cognitive tasks. Then the paper examines different topologies of excitatory neurons for basic assemblies and their performance as short-term memory. Lastly, larger assemblies are associated in 2/3 sets, where two active elements can retrieve the third. Future research is proposed to explore the potential use of these assemblies and associations in cognitive tasks. By investigating biologically and cognitively plausible topologies, learning, and neurons, simulations will lead to an improved under-standing of neuro-cognition, and potentially to systems that surpass the brittleness and domain specificity of current AI systems. |
Keywords | Cell Assemblies; Neurocognitive Model; Stroop Task; Associative Memory; Spiking Network |
Sustainable Development Goals | 16 Peace, justice and strong institutions |
Middlesex University Theme | Health & Wellbeing |
Research Group | Artificial Intelligence group |
Conference | 2023 Annual International Conference on Brain-Inspired Cognitive Architectures for Artificial Intelligence, the 14th Annual Meeting of the BICA Society (BICA*AI 2023) |
Page range | 422-428 |
Proceedings Title | Biologically Inspired Cognitive Architectures 2023: Proceedings of the 14th Annual Meeting of the BICA Society |
Series | Studies in Computational Intelligence series |
Editors | Samsonovich, A.V. and Liu, T. |
ISSN | 1860-949X |
1860-9503 | |
ISBN | 9783031503801 |
Paperback | 9783031503832 |
Electronic | 9783031503818 |
Publisher | Springer |
Publication dates | |
Online | 14 Feb 2024 |
14 Feb 2024 | |
Publication process dates | |
Accepted | 15 Jun 2023 |
Deposited | 17 Aug 2023 |
Output status | Published |
Accepted author manuscript | File Access Level Open |
Copyright Statement | This version of the paper has been accepted for publication, after peer review and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-ma...), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/978-3-031-50381-8_43 |
Digital Object Identifier (DOI) | https://doi.org/10.1007/978-3-031-50381-8_43 |
Web address (URL) of conference proceedings | https://link.springer.com/book/9783031503801 |
Language | English |
https://repository.mdx.ac.uk/item/9xqq5
Restricted files
Accepted author manuscript
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