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A Computational Model of Working Memory Based on Spike-Timing-Dependent Plasticity

Working memory is closely involved in various cognitive activities, but its neural mechanism is still under exploration. The mainstream view has long been that persistent activity is the neural basis of working memory, but recent experiments have observed that activity-silent memory can also be corr...

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Detalles Bibliográficos
Autores principales: Huang, Qiu-Sheng, Wei, Hui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8096998/
https://www.ncbi.nlm.nih.gov/pubmed/33967727
http://dx.doi.org/10.3389/fncom.2021.630999
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author Huang, Qiu-Sheng
Wei, Hui
author_facet Huang, Qiu-Sheng
Wei, Hui
author_sort Huang, Qiu-Sheng
collection PubMed
description Working memory is closely involved in various cognitive activities, but its neural mechanism is still under exploration. The mainstream view has long been that persistent activity is the neural basis of working memory, but recent experiments have observed that activity-silent memory can also be correctly recalled. The underlying mechanism of activity-silent memory is considered to be an alternative scheme that rejects the theory of persistent activity. We propose a working memory model based on spike-timing-dependent plasticity (STDP). Different from models based on spike-rate coding, our model adopts temporal patterns of action potentials to represent information, so it can flexibly encode new memory representation. The model can work in both persistent and silent states, i.e., it is compatible with both of these seemingly conflicting neural mechanisms. We conducted a simulation experiment, and the results are similar to the real experimental results, which suggests that our model is plausible in biology.
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spelling pubmed-80969982021-05-06 A Computational Model of Working Memory Based on Spike-Timing-Dependent Plasticity Huang, Qiu-Sheng Wei, Hui Front Comput Neurosci Neuroscience Working memory is closely involved in various cognitive activities, but its neural mechanism is still under exploration. The mainstream view has long been that persistent activity is the neural basis of working memory, but recent experiments have observed that activity-silent memory can also be correctly recalled. The underlying mechanism of activity-silent memory is considered to be an alternative scheme that rejects the theory of persistent activity. We propose a working memory model based on spike-timing-dependent plasticity (STDP). Different from models based on spike-rate coding, our model adopts temporal patterns of action potentials to represent information, so it can flexibly encode new memory representation. The model can work in both persistent and silent states, i.e., it is compatible with both of these seemingly conflicting neural mechanisms. We conducted a simulation experiment, and the results are similar to the real experimental results, which suggests that our model is plausible in biology. Frontiers Media S.A. 2021-04-21 /pmc/articles/PMC8096998/ /pubmed/33967727 http://dx.doi.org/10.3389/fncom.2021.630999 Text en Copyright © 2021 Huang and Wei. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Huang, Qiu-Sheng
Wei, Hui
A Computational Model of Working Memory Based on Spike-Timing-Dependent Plasticity
title A Computational Model of Working Memory Based on Spike-Timing-Dependent Plasticity
title_full A Computational Model of Working Memory Based on Spike-Timing-Dependent Plasticity
title_fullStr A Computational Model of Working Memory Based on Spike-Timing-Dependent Plasticity
title_full_unstemmed A Computational Model of Working Memory Based on Spike-Timing-Dependent Plasticity
title_short A Computational Model of Working Memory Based on Spike-Timing-Dependent Plasticity
title_sort computational model of working memory based on spike-timing-dependent plasticity
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8096998/
https://www.ncbi.nlm.nih.gov/pubmed/33967727
http://dx.doi.org/10.3389/fncom.2021.630999
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