McNabb, Carolyn, Driver, Ian D, Hyde, Vanessa, Hughes, Garin, Chandler, Hannah L, Thomas, Hannah, Allen, Christopher, Messaritaki, Eirini, Hodgetts, Carl J, Hedge, Craig, Engel, Maria, Standen, Sophie, Morgan, Emma L, Stylianopoulou, Elena, Manolova, Svetla, Reed, Lucie, Ploszajski, Matthew, Drakesmith, Mark, Germuska, Michael, Shaw, Alexander D, Mueller, Lars, Rossiter, Holly, Davies-Jenkins, Christopher W, Lancaster, Tom, Evans, C John, Owen, David, Perry, Gavin, Kusmia, Slawomir, Lambe, Emily, Partridge, Adam M, Cooper, Allison, Hobden, Peter, Lu, Hanzhang, Graham, Kim S, Lawrence, Andrew D, Wise, Richard G, Walters, James T R, Sumner, Petroc, Singh, Krish D and Jones, Derek K (2025). WAND: A multi-modal dataset integrating advanced MRI, MEG, and TMS for multi-scale brain analysis. Scientific Data, 12 ,
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 (3T) magnetic resonance imaging (MRI) with ultra-strong (300 mT/m) magnetic field gradients, structural and functional MRI and nuclear magnetic resonance spectroscopy at 3T and 7T, magnetoencephalography (MEG), and transcranial magnetic stimulation (TMS), together with trait questionnaire and cognitive data. Data are organised using the Brain Imaging Data Structure (BIDS). In addition to raw data, we provide brain-extracted T1-weighted images, and quality reports for diffusion, T1- and T2-weighted structural data, and blood-oxygen level dependent functional tasks. Reasons for participant exclusion are also included. Data are available for download through our GIN repository, a data access management system designed to reduce storage requirements. Users can interact with and retrieve data as needed, without downloading the complete dataset. Given the depth of neuroimaging phenotyping, leveraging ultra-high-gradient, high-field MRI, MEG and TMS, this dataset will facilitate multi-scale and multi-modal investigations of the healthy human brain.
| Publication DOI: | https://doi.org/10.1038/s41597-024-04154-7 |
|---|---|
| Divisions: | College of Health & Life Sciences > School of Psychology College of Health & Life Sciences College of Health & Life Sciences > Aston Institute of Health & Neurodevelopment (AIHN) |
| Funding Information: | The WAND data were acquired at the UK National Facility for In Vivo MR Imaging of Human Tissue Microstructure funded by the EPSRC (grant EP/M029778/1), and The Wolfson Foundation, and supported by a Wellcome Trust Investigator Award (096646/Z/11/Z) and a |
| Additional Information: | Copyright © The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/ |
| Uncontrolled Keywords: | Adolescent,Adult,Brain/diagnostic imaging,Databases, Factual,Female,Humans,Magnetic Resonance Imaging,Magnetoencephalography,Male,Middle Aged,Neuroimaging,Transcranial Magnetic Stimulation,Young Adult |
| Publication ISSN: | 2052-4463 |
| Data Access Statement: | WAND data 22 are available for download from GIN (https://gin.g-node.org/CUBRIC/WAND). BIDS metadata and data organisation: All imaging data are organised using the Brain Imaging Data Structure (BIDS 32 ) or, where no official BIDS recommendation exists, data are structured according to recommendations from BIDS extension proposals current at the time of acquisition. Details of data structure and decision-making related to non-official BIDS formats are included in the README file of the GitLab repository(https://git.cardiff.ac.uk/cubric/wand).<br/>Data are organised first by subject, then session, then data type (e.g., “meg”, “func”, “dwi”, etc.). Sessions are organised such that a single session contains imaging data from only one device on one occasion (see Table S2 for details).<br/>MRI data are stored in NifTI (Neuroimaging Informatics Technology Initiative) format with accompanying metadata stored in JSON format. MRS data are stored as Siemens TWIX files, using a BIDS-like structure but will not be “BIDS-valid”. MEG data are stored in .ds format according to CTF’s data organisation standards. Continuous recordings from physiological monitoring are stored as tab-separated values (TSV) files with accompanying metadata stored in JSON format. Timing and other properties of events recorded during functional MRI tasks are stored as TSV files with accompanying metadata in JSON format. Cognitive and questionnaire data are stored in TSV format with accompanying metadata/data dictionaries in JSON format.<br/><br/>[see full paper for Technical Validation, Usage Notes and Code availability] |
| Last Modified: | 13 Mar 2025 14:43 |
| Date Deposited: | 24 Jan 2025 16:17 |
| Full Text Link: | |
| Related URLs: |
https://www.nat ... 597-024-04154-7
(Publisher URL) |
PURE Output Type: | Article |
| Published Date: | 2025-02-06 |
| Published Online Date: | 2025-02-06 |
| Accepted Date: | 2024-11-18 |
| Authors: |
McNabb, Carolyn
Driver, Ian D Hyde, Vanessa Hughes, Garin Chandler, Hannah L Thomas, Hannah Allen, Christopher Messaritaki, Eirini Hodgetts, Carl J Hedge, Craig ( 
0000-0001-6145-3319)
Engel, Maria Standen, Sophie Morgan, Emma L Stylianopoulou, Elena Manolova, Svetla Reed, Lucie Ploszajski, Matthew Drakesmith, Mark Germuska, Michael Shaw, Alexander D Mueller, Lars Rossiter, Holly Davies-Jenkins, Christopher W Lancaster, Tom Evans, C John Owen, David Perry, Gavin Kusmia, Slawomir Lambe, Emily Partridge, Adam M Cooper, Allison Hobden, Peter Lu, Hanzhang Graham, Kim S Lawrence, Andrew D Wise, Richard G Walters, James T R Sumner, Petroc Singh, Krish D Jones, Derek K |