更正：WAND：一个多模态数据集，集成了先进的MRI， MEG和TMS，用于多尺度大脑分析。

IF 6.9 2区综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES

Scientific Data Pub Date : 2025-07-03 DOI:10.1038/s41597-025-05476-w

Carolyn B McNabb, Ian D Driver, Vanessa Hyde, Garin Hughes, Hannah L Chandler, Hannah Thomas, Christopher Allen, Eirini Messaritaki, Carl J Hodgetts, Craig Hedge, Maria Engel, Sophie F Standen, Emma L Morgan, Elena Stylianopoulou, Svetla Manolova, Lucie Reed, Matthew Ploszajski, Mark Drakesmith, Michael Germuska, Alexander D Shaw, Lars Mueller, Holly Rossiter, Christopher W Davies-Jenkins, Tom Lancaster, C John Evans, David Owen, Gavin Perry, Slawomir Kusmia, Emily Lambe, Adam M Partridge, Allison Cooper, Peter Hobden, Hanzhang Lu, Kim S Graham, Andrew D Lawrence, Richard G Wise, James T R Walters, Petroc Sumner, Krish D Singh, Derek K Jones

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Correction: WAND: A multi-modal dataset integrating advanced MRI, MEG, and TMS for multi-scale brain analysis.

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来源期刊

Scientific Data Social Sciences-Education

CiteScore

11.20

自引率

4.10%

发文量

689

审稿时长

16 weeks

期刊介绍： Scientific Data is an open-access journal focused on data, publishing descriptions of research datasets and articles on data sharing across natural sciences, medicine, engineering, and social sciences. Its goal is to enhance the sharing and reuse of scientific data, encourage broader data sharing, and acknowledge those who share their data. The journal primarily publishes Data Descriptors, which offer detailed descriptions of research datasets, including data collection methods and technical analyses validating data quality. These descriptors aim to facilitate data reuse rather than testing hypotheses or presenting new interpretations, methods, or in-depth analyses.