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MEG-BIDS, the brain imaging data structure extended to magnetoencephalography

Authors :
François Tadel
Sylvain Baillet
Robert Oostenveld
Elizabeth Bock
Vladimir Litvak
Julia Guiomar Niso Galan
Jeremy T. Moreau
Guillaume Flandin
Mainak Jas
Richard N. Henson
Jan-Mathijs Schoffelen
Joseph Wexler
Krzysztof J. Gorgolewski
Alexandre Gramfort
Teon L. Brooks
Apollo-University Of Cambridge Repository
Gorgolewski, Krzysztof J [0000-0003-3321-7583]
Brooks, Teon L [0000-0001-7344-3230]
Henson, Richard N [0000-0002-0712-2639]
Oostenveld, Robert [0000-0002-1974-1293]
Baillet, Sylvain [0000-0002-6762-5713]
Apollo - University of Cambridge Repository
Source :
Scientific Data, Scientific Data, ISSN 2052-4463, 2018, Vol. 5, Archivo Digital UPM, Universidad Politécnica de Madrid, Scientific Data, 5, Scientific Data, 5, Article 180110. (2018)
Publication Year :
2018
Publisher :
Springer Science and Business Media LLC, 2018.

Abstract

Contains fulltext : 202961.pdf (Publisher’s version ) (Open Access) 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 data-analytics software that have adopted MEG-BIDS, and a diverse sample of open MEG-BIDS data resources available to everyone. 12 p.

Details

ISSN :
20524463
Database :
OpenAIRE
Journal :
Scientific Data, Scientific Data, ISSN 2052-4463, 2018, Vol. 5, Archivo Digital UPM, Universidad Politécnica de Madrid, Scientific Data, 5, Scientific Data, 5, Article 180110. (2018)
Accession number :
edsair.doi.dedup.....10a0cbb52e3e2052234c7722e5475040
Full Text :
https://doi.org/10.17863/cam.30375