Spacetop: A multimodal fMRI dataset unifying naturalistic processes with a rich array of experimental tasks

Cognitive neuroscience has advanced significantly due to the availability of openly shared datasets. Large sample sizes, large amounts of data per person, and diversity in tasks and data types are all desirable, but are difficult to achieve in a single dataset. Here, we present an open dataset with N = 101 participants and 6 hours of scanning per participant, including 6 multifaceted functional tasks, 2 hours of naturalistic movie viewing, structural T1 images and multi-shell diffusion imaging as well as autonomic physiological data. This dataset's combination of sample size, extensive data per participant (>600 iso-hours of data), and a wide range of experimental conditions - including cognitive, affective, social, and somatic/interoceptive tasks - positions it uniquely for probing important questions in cognitive neuroscience.

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Publication Details

Journal
Scientific Data
Published
2025-08-22
DOI
https://doi.org/10.1038/s41597-025-05154-x
Citations
2
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
2.86

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article

Spacetop: A multimodal fMRI dataset unifying naturalistic processes with a rich array of experimental tasks

Tor Dessart Wager, Martin A. Lindquist, Patrick Sadil, Xiaochun Han et al.
2 citations
Scientific Data
Functional Brain Connectivity Studies
2.86
article

Spacetop: A multimodal fMRI dataset unifying naturalistic processes with a rich array of experimental tasks

Tor Dessart Wager, Martin A. Lindquist, Patrick Sadil, Xiaochun Han, Eilis I Murphy, Maryam Amini‎, Bogdan Petre, Mickela Heilicher, Philip A. Kragel, Yaroslav O. Halchenko, Heejung Jung, Zizhuang Miao, Michael M. C. Sun, Owen G. Collins, Bethany J. Hunt
article en
2 citations

Abstract

Cognitive neuroscience has advanced significantly due to the availability of openly shared datasets. Large sample sizes, large amounts of data per person, and diversity in tasks and data types are all desirable, but are difficult to achieve in a single dataset. Here, we present an open dataset with N = 101 participants and 6 hours of scanning per participant, including 6 multifaceted functional tasks, 2 hours of naturalistic movie viewing, structural T1 images and multi-shell diffusion imaging as well as autonomic physiological data. This dataset's combination of sample size, extensive data per participant (>600 iso-hours of data), and a wide range of experimental conditions - including cognitive, affective, social, and somatic/interoceptive tasks - positions it uniquely for probing important questions in cognitive neuroscience.

Scientific DataVol. 12(1)
Dartmouth College (US), University of Wisconsin–Madison (US), Johns Hopkins University (US), Emory University (US), University of California, Irvine (US), Beijing Normal University (CN)
National Institute of Biomedical Imaging and Bioengineering
Openalex Percentile: Top 9%
Functional Brain Connectivity Studies
2.86
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