Journal
SCIENTIFIC DATA
Volume 5, Issue -, Pages -Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/sdata.2018.110
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Funding
- ERC Starting Grant [SLAB ERC-YStG-676943]
- EU-H2020 Marie Curie ChildBrain Innovative Training Network [641652]
- NWO-VIDI Grant [864.14.011]
- Natural Science and Engineering Research Council of Canada [436355-13]
- NIH [2R01EB009048-05]
- Brain Canada Foundation [PSG15-3755]
- Medical Research Council [MR/K005464/1]
- Wellcome [203147/Z/16/Z]
- AXA Research Fund
- Tanenbaum Open Science Institute (Montreal, Canada)
- MRC [MR/K005464/1, MC_UU_00005/8] Funding Source: UKRI
- Marie Curie Actions (MSCA) [641652] Funding Source: Marie Curie Actions (MSCA)
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We present a significant extension of the Brain Imaging Data Structure (BIDS) to support the specific aspects of magnetoencephalography (MEG) data. MEG measures brain activity with millisecond temporal resolution and unique source imaging capabilities. So far, BIDS was a solution to organise magnetic resonance imaging (MRI) data. The nature and acquisition parameters of MRI and MEG data are strongly dissimilar. Although there is no standard data format for MEG, we propose MEG-BIDS as a principled solution to store, organise, process and share the multidimensional data volumes produced by the modality. The standard also includes well-defined metadata, to facilitate future data harmonisation and sharing efforts. This responds to unmet needs from the multimodal neuroimaging community and paves the way to further integration of other techniques in electrophysiology. MEG-BIDS builds on MRI-BIDS, extending BIDS to a multimodal data structure. We feature several dataanalytics software that have adopted MEG-BIDS, and a diverse sample of open MEG-BIDS data resources available to everyone.
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