PT  - JOURNAL ARTICLE
AU  - Nastase, Samuel A.
AU  - Liu, Yun-Fei
AU  - Hillman, Hanna
AU  - Zadbood, Asieh
AU  - Hasenfratz, Liat
AU  - Keshavarzian, Neggin
AU  - Chen, Janice
AU  - Honey, Christopher J.
AU  - Yeshurun, Yaara
AU  - Regev, Mor
AU  - Nguyen, Mai
AU  - Chang, Claire H. C.
AU  - Baldassano, Christopher
AU  - Lositsky, Olga
AU  - Simony, Erez
AU  - Chow, Michael A.
AU  - Leong, Yuan Chang
AU  - Brooks, Paula P.
AU  - Micciche, Emily
AU  - Choe, Gina
AU  - Goldstein, Ariel
AU  - Vanderwal, Tamara
AU  - Halchenko, Yaroslav O.
AU  - Norman, Kenneth A.
AU  - Hasson, Uri
TI  - Narratives: fMRI data for evaluating models of naturalistic language comprehension
AID  - 10.1101/2020.12.23.424091
DP  - 2020 Jan 01
TA  - bioRxiv
PG  - 2020.12.23.424091
4099  - http://biorxiv.org/content/early/2020/12/23/2020.12.23.424091.short
4100  - http://biorxiv.org/content/early/2020/12/23/2020.12.23.424091.full
AB  - The “Narratives” collection aggregates a variety of functional MRI datasets collected while human subjects listened to naturalistic spoken stories. The current release includes 345 subjects, 891 functional scans, and 27 diverse stories of varying duration totaling ~4.6 hours of unique stimuli (~43,000 words). This data collection is well-suited for naturalistic neuroimaging analysis, and is intended to serve as a benchmark for models of language and narrative comprehension. We provide standardized MRI data accompanied by rich metadata, preprocessed versions of the data ready for immediate use, and the spoken story stimuli with time-stamped phoneme- and word-level transcripts. All code and data are publicly available with full provenance in keeping with current best practices in transparent and reproducible neuroimaging.Competing Interest StatementThe authors have declared no competing interest.