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Predicting memory from the network structure of naturalistic events
When we remember events, we often do not only recall individual events, but also the connections between them. However, extant research has focused on how humans segment and remember discrete events from continuous input, with far less attention given to how the structure of connections between even...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9307577/ https://www.ncbi.nlm.nih.gov/pubmed/35869083 http://dx.doi.org/10.1038/s41467-022-31965-2 |
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author | Lee, Hongmi Chen, Janice |
author_facet | Lee, Hongmi Chen, Janice |
author_sort | Lee, Hongmi |
collection | PubMed |
description | When we remember events, we often do not only recall individual events, but also the connections between them. However, extant research has focused on how humans segment and remember discrete events from continuous input, with far less attention given to how the structure of connections between events impacts memory. Here we conduct a functional magnetic resonance imaging study in which participants watch and recall a series of realistic audiovisual narratives. By transforming narratives into networks of events, we demonstrate that more central events—those with stronger semantic or causal connections to other events—are better remembered. During encoding, central events evoke larger hippocampal event boundary responses associated with memory formation. During recall, high centrality is associated with stronger activation in cortical areas involved in episodic recollection, and more similar neural representations across individuals. Together, these results suggest that when humans encode and retrieve complex real-world experiences, the reliability and accessibility of memory representations is shaped by their location within a network of events. |
format | Online Article Text |
id | pubmed-9307577 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-93075772022-07-24 Predicting memory from the network structure of naturalistic events Lee, Hongmi Chen, Janice Nat Commun Article When we remember events, we often do not only recall individual events, but also the connections between them. However, extant research has focused on how humans segment and remember discrete events from continuous input, with far less attention given to how the structure of connections between events impacts memory. Here we conduct a functional magnetic resonance imaging study in which participants watch and recall a series of realistic audiovisual narratives. By transforming narratives into networks of events, we demonstrate that more central events—those with stronger semantic or causal connections to other events—are better remembered. During encoding, central events evoke larger hippocampal event boundary responses associated with memory formation. During recall, high centrality is associated with stronger activation in cortical areas involved in episodic recollection, and more similar neural representations across individuals. Together, these results suggest that when humans encode and retrieve complex real-world experiences, the reliability and accessibility of memory representations is shaped by their location within a network of events. Nature Publishing Group UK 2022-07-22 /pmc/articles/PMC9307577/ /pubmed/35869083 http://dx.doi.org/10.1038/s41467-022-31965-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Lee, Hongmi Chen, Janice Predicting memory from the network structure of naturalistic events |
title | Predicting memory from the network structure of naturalistic events |
title_full | Predicting memory from the network structure of naturalistic events |
title_fullStr | Predicting memory from the network structure of naturalistic events |
title_full_unstemmed | Predicting memory from the network structure of naturalistic events |
title_short | Predicting memory from the network structure of naturalistic events |
title_sort | predicting memory from the network structure of naturalistic events |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9307577/ https://www.ncbi.nlm.nih.gov/pubmed/35869083 http://dx.doi.org/10.1038/s41467-022-31965-2 |
work_keys_str_mv | AT leehongmi predictingmemoryfromthenetworkstructureofnaturalisticevents AT chenjanice predictingmemoryfromthenetworkstructureofnaturalisticevents |