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. 2025 Feb 6;12(1):220.
doi: 10.1038/s41597-024-04154-7.

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

Carolyn B McNabb  1 , Ian D Driver  2 , Vanessa Hyde  2 , Garin Hughes  2 , Hannah L Chandler  2 , Hannah Thomas  2 , Christopher Allen  3 , Eirini Messaritaki  2 , Carl J Hodgetts  2   4 , Craig Hedge  5 , Maria Engel  2 , Sophie F Standen  2 , Emma L Morgan  2 , Elena Stylianopoulou  2 , Svetla Manolova  2 , Lucie Reed  2 , Matthew Ploszajski  2 , Mark Drakesmith  2 , Michael Germuska  6 , Alexander D Shaw  7 , Lars Mueller  8 , Holly Rossiter  2 , Christopher W Davies-Jenkins  9   10 , Tom Lancaster  11 , C John Evans  2 , David Owen  2 , Gavin Perry  2 , Slawomir Kusmia  2   12 , Emily Lambe  2 , Adam M Partridge  2   13 , Allison Cooper  2 , Peter Hobden  2 , Hanzhang Lu  9   10 , Kim S Graham  2   14 , Andrew D Lawrence  2   14 , Richard G Wise  2   15   16 , James T R Walters  17 , Petroc Sumner  2 , Krish D Singh  2 , Derek K Jones  2
Affiliations

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

Carolyn B McNabb et al. Sci Data. .

Erratum in

  • Correction: WAND: A multi-modal dataset integrating advanced MRI, MEG, and TMS for multi-scale brain analysis.
    McNabb CB, Driver ID, Hyde V, Hughes G, Chandler HL, Thomas H, Allen C, Messaritaki E, Hodgetts CJ, Hedge C, Engel M, Standen SF, Morgan EL, Stylianopoulou E, Manolova S, Reed L, Ploszajski M, Drakesmith M, Germuska M, Shaw AD, Mueller L, Rossiter H, Davies-Jenkins CW, Lancaster T, Evans CJ, Owen D, Perry G, Kusmia S, Lambe E, Partridge AM, Cooper A, Hobden P, Lu H, Graham KS, Lawrence AD, Wise RG, Walters JTR, Sumner P, Singh KD, Jones DK. McNabb CB, et al. Sci Data. 2025 Jul 3;12(1):1136. doi: 10.1038/s41597-025-05476-w. Sci Data. 2025. PMID: 40610530 Free PMC article. No abstract available.

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 field gradients, structural and functional MRI and nuclear magnetic resonance spectroscopy at 3 T and 7 T, 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.

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Conflict of interest statement

Competing interests: Peter Hobden was a coinventor of ‘MRIFocus’ (MR-safe vision correction system; Cambridge Research Systems Ltd. crsltd.com), which was used on the 3 T Siemens Prisma and 3 T Connectom for WAND. No other authors have competing interests.

Figures

Fig. 1
Fig. 1
Reasons for exclusion of individuals from the Welsh Advanced Neuroimaging Database.
Fig. 2
Fig. 2
Age distribution of WAND participants. Females are shown in yellow; males are shown in purple. Dashed lines represent the median age for each sex.
Fig. 3
Fig. 3
Summary of self-reported ethnicity data across WAND participants. Data were categorised using ethnic group classifications from the 2021 UK Census, as reported by the Office for National Statistics (https://www.ons.gov.uk/census/census2021dictionary/variablesbytopic/ethnicgroupnationalidentitylanguageandreligionvariablescensus2021/ethnicgroup/classifications).
Fig. 4
Fig. 4
Recruitment and participant flow through the Welsh Advanced Neuroimaging Database. Numbers presented are the total number of individuals with any data for that imaging session (ses). Median number of days between testing was 2 (day 1 to day 2), 8 (day 2 to day 3) and 6 (day 3 to day 4). MINI: Mini International Neuropsychiatric Interview; HARDI: high angular resolution diffusion-weighted imaging; DWI: diffusion-weighted imaging; fMRI: functional magnetic resonance imaging; pCASL: Pseudo-continuous arterial spin labelling; TRUST: T2-relaxation-under-spin-tagging.
Fig. 5
Fig. 5
Example images from session 02, Diffusion and quantitative MRI using ultra strong magnetic gradients. T1w: T1-weighted structural image (acquired with MPRAGE); DWI: diffusion weighted image; SPGR: 3D spoiled gradient-recalled echo sequence; SPGR-IR: inversion recovery-prepped spoiled gradient-recalled echo sequence; SSFP: steady-state free precession; MT: quantitative magnetization transfer image.
Fig. 6
Fig. 6
Example images from session 03, 3 T functional and perfusion MRI. T1w: T1-weighted structural image (acquired with MPRAGE); T2w: T2-weighted turbo spin echo; BOLD: blood oxygen level dependent functional MRI; pCASL: pseudo-continuous arterial spin labelling; TRUST: T2 relaxation under spin tagging; T1-IR: T1 inversion recovery.
Fig. 7
Fig. 7
Example images from session 06, 3 T functional and perfusion MRI. MP2RAGE: magnetization prepared 2 rapid gradient echoes; B1map: B1 inhomogeneity map; BOLD: blood oxygen level dependent functional MRI; MGRE: Multi-echo 3D gradient echo.
Fig. 8
Fig. 8
Example images from session 07, 3 T functional and perfusion MRI. TRUST: T2 relaxation under spin tagging; T1-IR: T1 inversion recovery; pCASL: pseudo-continuous arterial spin labelling; GRE: Single-echo 3D gradient echo sequence; EPI: echo planar image.
See this image and copyright information in PMC

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