WAND: A multi-modal dataset integrating advanced MRI, MEG, and TMS for multi-scale brain analysis
Abstract This paper introduces the Welsh Advanced Neuroimaging Database (WAND), a multi-scale, multi-modal imaging dataset comprising in vivo brain data from 170 healthy volunteers (aged 18–63 years), including 3 Tesla (3 T) magnetic resonance imaging (MRI) with ultra-strong (300 mT/m) magnetic fiel...
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Main Authors: | 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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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-02-01
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Series: | Scientific Data |
Online Access: | https://doi.org/10.1038/s41597-024-04154-7 |
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