Le Petit Prince multilingual naturalistic fMRI corpus.
Journal
Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192
Informations de publication
Date de publication:
29 08 2022
29 08 2022
Historique:
received:
07
10
2021
accepted:
10
08
2022
entrez:
29
8
2022
pubmed:
30
8
2022
medline:
1
9
2022
Statut:
epublish
Résumé
Neuroimaging using more ecologically valid stimuli such as audiobooks has advanced our understanding of natural language comprehension in the brain. However, prior naturalistic stimuli have typically been restricted to a single language, which limited generalizability beyond small typological domains. Here we present the Le Petit Prince fMRI Corpus (LPPC-fMRI), a multilingual resource for research in the cognitive neuroscience of speech and language during naturalistic listening (OpenNeuro: ds003643). 49 English speakers, 35 Chinese speakers and 28 French speakers listened to the same audiobook The Little Prince in their native language while multi-echo functional magnetic resonance imaging was acquired. We also provide time-aligned speech annotation and word-by-word predictors obtained using natural language processing tools. The resulting timeseries data are shown to be of high quality with good temporal signal-to-noise ratio and high inter-subject correlation. Data-driven functional analyses provide further evidence of data quality. This annotated, multilingual fMRI dataset facilitates future re-analysis that addresses cross-linguistic commonalities and differences in the neural substrate of language processing on multiple perceptual and linguistic levels.
Identifiants
pubmed: 36038567
doi: 10.1038/s41597-022-01625-7
pii: 10.1038/s41597-022-01625-7
pmc: PMC9424229
doi:
Types de publication
Dataset
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
530Subventions
Organisme : National Science Foundation (NSF)
ID : 1903783
Organisme : National Science Foundation (NSF)
ID : 1607251
Informations de copyright
© 2022. The Author(s).
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