Relating the Past with the Present: Information Integration and Segregation during Ongoing Narrative Processing.


Journal

Journal of cognitive neuroscience
ISSN: 1530-8898
Titre abrégé: J Cogn Neurosci
Pays: United States
ID NLM: 8910747

Informations de publication

Date de publication:
01 05 2021
Historique:
entrez: 24 8 2021
pubmed: 25 8 2021
medline: 29 10 2021
Statut: ppublish

Résumé

This study examined how the brain dynamically updates event representations by integrating new information over multiple minutes while segregating irrelevant input. A professional writer custom-designed a narrative with two independent storylines, interleaving across minute-long segments (ABAB). In the last (C) part, characters from the two storylines meet and their shared history is revealed. Part C is designed to induce the spontaneous recall of past events, upon the recurrence of narrative motifs from A/B, and to shed new light on them. Our fMRI results showed storyline-specific neural patterns, which were reinstated (i.e., became more active) during storyline transitions. This effect increased along the processing timescale hierarchy, peaking in the default mode network. Similarly, the neural reinstatement of motifs was found during Part C. Furthermore, participants showing stronger motif reinstatement performed better in integrating A/B and C events, demonstrating the role of memory reactivation in information integration over intervening irrelevant events.

Identifiants

pubmed: 34428791
pii: 98114
doi: 10.1162/jocn_a_01707
pmc: PMC9155984
mid: NIHMS1810666
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1106-1128

Subventions

Organisme : NIMH NIH HHS
ID : R01 MH112357
Pays : United States
Organisme : NIMH NIH HHS
ID : R01-MH112357
Pays : United States

Informations de copyright

© 2021 Massachusetts Institute of Technology.

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Auteurs

Christina Lazaridi (C)

Columbia University.

Yaara Yeshurun (Y)

Tel Aviv University.

Kenneth A Norman (KA)

Princeton University.

Uri Hasson (U)

Princeton University.

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Classifications MeSH