Spacetop: A multimodal fMRI dataset unifying naturalistic processes with a rich array of experimental tasks
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 data...
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| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-08-01
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| Series: | Scientific Data |
| Online Access: | https://doi.org/10.1038/s41597-025-05154-x |
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| Summary: | 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. |
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| ISSN: | 2052-4463 |