Biomagnetic Framework for Identifying Network Dysfunction in dementia

Lead Research Organisation: University of Cambridge
Department Name: Clinical Neurosciences

Abstract

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Title BioFIND Framework 
Description The principal aim of BioFIND was to define a methodological framework for magnetoencephalography (MEG) to identify sensitive and specific biomarkers of neurodegeneration in Alzheimer's disease (AD) and other dementias. This working group brought together leading international centres for dementia research and brain imaging to establish the optimal paradigms, analyses and standardised reporting methods for MEG dementia research. A large integrated data set created from two separate sites was used to test a mutually agreed pipeline for preprocessing data, and provide direct comparisons of different analytic methods to quantify performance and potential for a future trial-ready platform. This pivotal work provides protocols that are transferable and scalable across multiple sites, enable standardised data sharing, and facilitate large-scale collaborative projects. The framework describes a protocol for an MEG 'eyes closed' resting-state paradigm, a guide for data acquisition procedures and details of a 'ready to use' preprocessing pipeline. 
Type Of Material Model of mechanisms or symptoms - human 
Year Produced 2018 
Provided To Others? Yes  
Impact The framework has very recently been finalised, but will lead the way for future collaborations, and will facilitate the research of other groups who can access and use the guidelines and processing scripts. 
 
Title BioFIND database 
Description The data set was created to test the standardized framework of data acquisition and analyses across MEG sites, and to further examine a set of methods used to identify potential biomarkers of MCI/AD. The data were pooled from two main sites (the CBU in Cambridge and CTB in Madrid), and included an MEG eyes-closed resting-state paradigm, from patients with MCI / early AD and age-matched healthy controls. The data were selected by compatibility and shareability: all data were acquired on Neuromag MEG, had similar acquisition protocols, similar groups of patients/controls and approved agreements for data sharing. 
Type Of Material Database/Collection of data 
Year Produced 2018 
Provided To Others? Yes  
Impact The research is ongoing, and impact to be seen. 
URL https://portal.dementiasplatform.uk/CohortDirectory/Item?fingerPrintID=BioFIND
 
Description BioFIND Groups 
Organisation Complutense University of Madrid
Department Department of Psychology
Country Spain 
Sector Academic/University 
PI Contribution The collaboration between the MEG teams in Cambridge and the other groups created a shared pool of data from patients with MCI and healthy controls. Methods and analyses were compared and a consensus framework agreed of recommendations for MEG research in dementia.
Collaborator Contribution The collaboration between the MEG teams in Cambridge and the other groups created a shared pool of data from patients with MCI and healthy controls. Methods and analyses were compared and a consensus framework agreed of recommendations for MEG research in dementia.
Impact A final report describes the outcome of the research, published on the JPND website.
Start Year 2016
 
Description BioFIND Groups 
Organisation Helsinki University Hospital
Country Finland 
Sector Hospitals 
PI Contribution The collaboration between the MEG teams in Cambridge and the other groups created a shared pool of data from patients with MCI and healthy controls. Methods and analyses were compared and a consensus framework agreed of recommendations for MEG research in dementia.
Collaborator Contribution The collaboration between the MEG teams in Cambridge and the other groups created a shared pool of data from patients with MCI and healthy controls. Methods and analyses were compared and a consensus framework agreed of recommendations for MEG research in dementia.
Impact A final report describes the outcome of the research, published on the JPND website.
Start Year 2016
 
Description BioFIND Groups 
Organisation University of Oxford
Department Oxford Centre for Human Brain Activity (OHBA)
Country United Kingdom 
Sector Academic/University 
PI Contribution The collaboration between the MEG teams in Cambridge and the other groups created a shared pool of data from patients with MCI and healthy controls. Methods and analyses were compared and a consensus framework agreed of recommendations for MEG research in dementia.
Collaborator Contribution The collaboration between the MEG teams in Cambridge and the other groups created a shared pool of data from patients with MCI and healthy controls. Methods and analyses were compared and a consensus framework agreed of recommendations for MEG research in dementia.
Impact A final report describes the outcome of the research, published on the JPND website.
Start Year 2016
 
Description BioFIND Groups 
Organisation VU University Medical Center
Country Netherlands 
Sector Academic/University 
PI Contribution The collaboration between the MEG teams in Cambridge and the other groups created a shared pool of data from patients with MCI and healthy controls. Methods and analyses were compared and a consensus framework agreed of recommendations for MEG research in dementia.
Collaborator Contribution The collaboration between the MEG teams in Cambridge and the other groups created a shared pool of data from patients with MCI and healthy controls. Methods and analyses were compared and a consensus framework agreed of recommendations for MEG research in dementia.
Impact A final report describes the outcome of the research, published on the JPND website.
Start Year 2016