The “Narratives” fMRI dataset for evaluating models of naturalistic language comprehension

Samuel A. Nastase; Yun Fei Liu; Hanna Hillman; Asieh Zadbood; Liat Hasenfratz; Neggin Keshavarzian; Janice Chen; Christopher J. Honey; Yaara Yeshurun; Mor Regev; Mai Nguyen; Claire H.C. Chang; Christopher Baldassano; Olga Lositsky; Erez Simony; Michael A. Chow; Yuan Chang Leong; Paula P. Brooks; Emily Micciche; Gina Choe; Ariel Goldstein; Tamara Vanderwal; Yaroslav O. Halchenko; Kenneth A. Norman; Uri Hasson

doi:10.1038/s41597-021-01033-3

The “Narratives” fMRI dataset for evaluating models of naturalistic language comprehension

Samuel A. Nastase, Yun Fei Liu, Hanna Hillman, Asieh Zadbood, Liat Hasenfratz, Neggin Keshavarzian, Janice Chen, Christopher J. Honey, Yaara Yeshurun, Mor Regev, Mai Nguyen, Claire H.C. Chang, Christopher Baldassano, Olga Lositsky, Erez Simony, Michael A. Chow, Yuan Chang Leong, Paula P. Brooks, Emily Micciche, Gina ChoeAriel Goldstein, Tamara Vanderwal, Yaroslav O. Halchenko, Kenneth A. Norman, Uri Hasson

Graduate Institute of Mind Brain and Consciousness

Research output: Contribution to journal › Article › peer-review

53 Citations (Scopus)

Abstract

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.

Original language	English
Article number	250
Journal	Scientific data
Volume	8
Issue number	1
DOIs	https://doi.org/10.1038/s41597-021-01033-3
Publication status	Published - Dec 2021

ASJC Scopus subject areas

Statistics and Probability
Information Systems
Education
Computer Science Applications
Statistics, Probability and Uncertainty
Library and Information Sciences

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Nastase, S. A., Liu, Y. F., Hillman, H., Zadbood, A., Hasenfratz, L., Keshavarzian, N., Chen, J., Honey, C. J., Yeshurun, Y., Regev, M., Nguyen, M., Chang, C. H. C., Baldassano, C., Lositsky, O., Simony, E., Chow, M. A., Leong, Y. C., Brooks, P. P., Micciche, E., ... Hasson, U. (2021). The “Narratives” fMRI dataset for evaluating models of naturalistic language comprehension. Scientific data, 8(1), Article 250. https://doi.org/10.1038/s41597-021-01033-3

Nastase, SA, Liu, YF, Hillman, H, Zadbood, A, Hasenfratz, L, Keshavarzian, N, Chen, J, Honey, CJ, Yeshurun, Y, Regev, M, Nguyen, M, Chang, CHC, Baldassano, C, Lositsky, O, Simony, E, Chow, MA, Leong, YC, Brooks, PP, Micciche, E, Choe, G, Goldstein, A, Vanderwal, T, Halchenko, YO, Norman, KA & Hasson, U 2021, 'The “Narratives” fMRI dataset for evaluating models of naturalistic language comprehension', Scientific data, vol. 8, no. 1, 250. https://doi.org/10.1038/s41597-021-01033-3

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abstract = "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.",

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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

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The “Narratives” fMRI dataset for evaluating models of naturalistic language comprehension

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