A multi-site, multi-participant magnetoencephalography resting-state dataset to study dementia: The BioFIND dataset.
Journal
NeuroImage
ISSN: 1095-9572
Titre abrégé: Neuroimage
Pays: United States
ID NLM: 9215515
Informations de publication
Date de publication:
09 2022
09 2022
Historique:
received:
23
07
2021
revised:
26
04
2022
accepted:
30
05
2022
pubmed:
7
6
2022
medline:
14
7
2022
entrez:
6
6
2022
Statut:
ppublish
Résumé
Early detection of Alzheimer's Disease (AD) is vital to reduce the burden of dementia and for developing effective treatments. Neuroimaging can detect early brain changes, such as hippocampal atrophy in Mild Cognitive Impairment (MCI), a prodromal state of AD. However, selecting the most informative imaging features by machine-learning requires many cases. While large publically-available datasets of people with dementia or prodromal disease exist for Magnetic Resonance Imaging (MRI), comparable datasets are missing for Magnetoencephalography (MEG). MEG offers advantages in its millisecond resolution, revealing physiological changes in brain oscillations or connectivity before structural changes are evident with MRI. We introduce a MEG dataset with 324 individuals: patients with MCI and healthy controls. Their brain activity was recorded while resting with eyes closed, using a 306-channel MEG scanner at one of two sites (Madrid or Cambridge), enabling tests of generalization across sites. A T1-weighted MRI is provided to assist source localisation. The MEG and MRI data are formatted according to international BIDS standards and analysed freely on the DPUK platform (https://portal.dementiasplatform.uk/Apply). Here, we describe this dataset in detail, report some example (benchmark) analyses, and consider its limitations and future directions.
Identifiants
pubmed: 35660461
pii: S1053-8119(22)00463-3
doi: 10.1016/j.neuroimage.2022.119344
pmc: PMC7613066
mid: EMS146255
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
119344Subventions
Organisme : Medical Research Council
ID : MR/T033371/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_UU_00030/8
Pays : United Kingdom
Organisme : Department of Health
Pays : United Kingdom
Organisme : Medical Research Council
ID : SUAG/010-RG91365
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/P502017/1
Pays : United Kingdom
Organisme : Biotechnology and Biological Sciences Research Council
ID : BB/H008217/1
Pays : United Kingdom
Organisme : Wellcome Trust
ID : 103838
Pays : United Kingdom
Organisme : Wellcome Trust
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_U105579226
Pays : United Kingdom
Informations de copyright
Copyright © 2022. Published by Elsevier Inc.
Déclaration de conflit d'intérêts
Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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