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

Area of Science:

• Neuroscience
• Medical Imaging
• Human Brain Research

Background:

• The need for large-scale, multi-modal neuroimaging datasets is critical for understanding brain structure and function.
• Existing datasets may lack the multi-scale resolution or advanced imaging techniques required for in-depth analysis.
• The Welsh Advanced Neuroimaging Database (WAND) was developed to address these limitations.

Purpose of the Study:

• To introduce and describe the Welsh Advanced Neuroimaging Database (WAND).
• To provide a rich, multi-modal dataset for investigating the healthy human brain across multiple scales.
• To facilitate advanced neuroimaging research by offering high-field MRI, MEG, and TMS data.

Main Methods:

• Collected in vivo brain data from 170 healthy volunteers (aged 18-63 years).
• Utilized 3 Tesla (3T) and 7T magnetic resonance imaging (MRI), including ultra-strong gradients, structural and functional MRI, and nuclear magnetic resonance spectroscopy.
• Incorporated magnetoencephalography (MEG), transcranial magnetic stimulation (TMS), trait questionnaires, and cognitive data, organized using the Brain Imaging Data Structure (BIDS).

Main Results:

• The WAND dataset includes raw imaging data, processed images (e.g., brain-extracted T1-weighted), and quality reports.
• Data are accessible via a GIN repository with a data access management system for efficient retrieval.
• Participant exclusion reasons are documented, enhancing data transparency and usability.

Conclusions:

• The WAND dataset represents a significant resource for multi-scale and multi-modal investigations of the healthy human brain.
• The combination of advanced imaging techniques (high-field MRI, MEG, TMS) and comprehensive phenotyping enables novel research avenues.
• This database will support a deeper understanding of brain mechanisms and individual variability in healthy populations.