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Familiarity Detection and Memory Consolidation in Cortical Assemblies
Humans have a large capacity of recognition memory (Dudai, 1997), a fundamental property of higher-order brain functions such as abstraction and generalization (Vogt and Magnussen, 2007). Familiarity is the first step towards recognition memory. We have previously demonstrated using unsupervised neu...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Society for Neuroscience
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7215585/ https://www.ncbi.nlm.nih.gov/pubmed/32122957 http://dx.doi.org/10.1523/ENEURO.0006-19.2020 |
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author | Zhang, Xiaoyu Yeh, Fang-Chin Ju, Han Jiang, Yuheng Quan, Gabriel Foo Wei VanDongen, Antonius M.J. |
author_facet | Zhang, Xiaoyu Yeh, Fang-Chin Ju, Han Jiang, Yuheng Quan, Gabriel Foo Wei VanDongen, Antonius M.J. |
author_sort | Zhang, Xiaoyu |
collection | PubMed |
description | Humans have a large capacity of recognition memory (Dudai, 1997), a fundamental property of higher-order brain functions such as abstraction and generalization (Vogt and Magnussen, 2007). Familiarity is the first step towards recognition memory. We have previously demonstrated using unsupervised neural network simulations that familiarity detection of complex patterns emerges in generic cortical microcircuits with bidirectional synaptic plasticity. It is therefore meaningful to conduct similar experiments on biological neuronal networks to validate these results. Studies of learning and memory in dissociated rodent neuronal cultures remain inconclusive to date. Synchronized network bursts (SNBs) that occur spontaneously and periodically have been speculated to be an intervening factor. By optogenetically stimulating cultured cortical networks with random dot movies (RDMs), we were able to reduce the occurrence of SNBs, after which an ability for familiarity detection emerged: previously seen patterns elicited higher firing rates than novel ones. Differences in firing rate were distributed over the entire network, suggesting that familiarity detection is a system level property. We also studied the change in SNB patterns following familiarity encoding. Support vector machine (SVM) classification results indicate that SNBs may be facilitating memory consolidation of the learned pattern. In addition, using a novel network connectivity probing method, we were able to trace the change in synaptic efficacy induced by familiarity encoding, providing insights on the long-term impact of having SNBs in the cultures. |
format | Online Article Text |
id | pubmed-7215585 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Society for Neuroscience |
record_format | MEDLINE/PubMed |
spelling | pubmed-72155852020-05-12 Familiarity Detection and Memory Consolidation in Cortical Assemblies Zhang, Xiaoyu Yeh, Fang-Chin Ju, Han Jiang, Yuheng Quan, Gabriel Foo Wei VanDongen, Antonius M.J. eNeuro Research Article: New Research Humans have a large capacity of recognition memory (Dudai, 1997), a fundamental property of higher-order brain functions such as abstraction and generalization (Vogt and Magnussen, 2007). Familiarity is the first step towards recognition memory. We have previously demonstrated using unsupervised neural network simulations that familiarity detection of complex patterns emerges in generic cortical microcircuits with bidirectional synaptic plasticity. It is therefore meaningful to conduct similar experiments on biological neuronal networks to validate these results. Studies of learning and memory in dissociated rodent neuronal cultures remain inconclusive to date. Synchronized network bursts (SNBs) that occur spontaneously and periodically have been speculated to be an intervening factor. By optogenetically stimulating cultured cortical networks with random dot movies (RDMs), we were able to reduce the occurrence of SNBs, after which an ability for familiarity detection emerged: previously seen patterns elicited higher firing rates than novel ones. Differences in firing rate were distributed over the entire network, suggesting that familiarity detection is a system level property. We also studied the change in SNB patterns following familiarity encoding. Support vector machine (SVM) classification results indicate that SNBs may be facilitating memory consolidation of the learned pattern. In addition, using a novel network connectivity probing method, we were able to trace the change in synaptic efficacy induced by familiarity encoding, providing insights on the long-term impact of having SNBs in the cultures. Society for Neuroscience 2020-05-08 /pmc/articles/PMC7215585/ /pubmed/32122957 http://dx.doi.org/10.1523/ENEURO.0006-19.2020 Text en Copyright © 2020 Zhang et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed. |
spellingShingle | Research Article: New Research Zhang, Xiaoyu Yeh, Fang-Chin Ju, Han Jiang, Yuheng Quan, Gabriel Foo Wei VanDongen, Antonius M.J. Familiarity Detection and Memory Consolidation in Cortical Assemblies |
title | Familiarity Detection and Memory Consolidation in Cortical Assemblies |
title_full | Familiarity Detection and Memory Consolidation in Cortical Assemblies |
title_fullStr | Familiarity Detection and Memory Consolidation in Cortical Assemblies |
title_full_unstemmed | Familiarity Detection and Memory Consolidation in Cortical Assemblies |
title_short | Familiarity Detection and Memory Consolidation in Cortical Assemblies |
title_sort | familiarity detection and memory consolidation in cortical assemblies |
topic | Research Article: New Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7215585/ https://www.ncbi.nlm.nih.gov/pubmed/32122957 http://dx.doi.org/10.1523/ENEURO.0006-19.2020 |
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