Biomagnetic Framework for Identifying Network Dysfunction in dementia
Lead Research Organisation:
University of Cambridge
Department Name: Clinical Neurosciences
Abstract
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People |
ORCID iD |
Laura Hughes (Principal Investigator) |
Publications
Hughes LE
(2019)
Biomagnetic biomarkers for dementia: A pilot multicentre study with a recommended methodological framework for magnetoencephalography.
in Alzheimer's & dementia (Amsterdam, Netherlands)
Vaghari D
(2022)
A multi-site, multi-participant magnetoencephalography resting-state dataset to study dementia: The BioFIND dataset.
in NeuroImage
Vaghari D
(2022)
Late combination shows that MEG adds to MRI in classifying MCI versus controls.
in NeuroImage
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 |