ArticleNeuroImage2022
A multi-site, multi-participant magnetoencephalography resting-state dataset to study dementia: The BioFIND dataset.
Article in NeuroImage, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed, 1 synthesis or guideline pooled it, 23 citations in OpenAlex.
- From Single-Modal to Multi-Modal Artificial Intelligence in Alzheimer's Disease: A Systematic Review of Databases, Modalities, Diagnostic Performance, and Clinical Translation Challenges.Sensors (Basel, Switzerland) · 2026Pooled it
- Magnetoencephalography in human neuroscience research: planning, piloting, implementation and quality assurance.Nature protocols · 2026Review
- The ENIGMA MEG Pipeline: Automated cortically localized spectral analysis of multi-site resting state MEG datasets.bioRxiv : the preprint server for biology · 2026Article
- Revolutionizing Pediatric Neurophysiology With Magnetoencephalography.Psychophysiology · 2026Review
- Fifteen years on: a review of the Cam-CAN study of the cognitive neuroscience of ageing.GeroScience · 2026Review
- Divergence of cortical neurophysiology across different neurodegenerative disorders compared to healthy ageing.Progress in neurobiology · 2026Article
- AI-driven magnetoencephalography biomarkers in dementia risk prediction: current evidence, challenges and future perspectives.Frontiers in dementia · 2026Review
- Multimodal non-invasive approaches for early Alzheimer's disease detection: a review of neuroelectrophysiological and neuroimaging techniques.Frontiers in psychiatry · 2026Review
- FEDI-CODE: A federated and causally-informed framework for dementia risk prediction using multi-site patient data.PloS one · 2026Article
- Exploring the neuromagnetic signatures of cognitive decline from mild cognitive impairment to Alzheimer's disease dementia.EBioMedicine · 2025Article
- A Shift Toward Supercritical Brain Dynamics Predicts Alzheimer's Disease Progression.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2025Article
- Neural markers of reduced arousal and consciousness in mild cognitive impairment.International journal of geriatric psychiatry · 2024Article
- Enhancing early Alzheimer's disease classification accuracy through the fusion of sMRI and rsMEG data: a deep learning approach.Frontiers in neuroscience · 2024Article
- A machine learning approach for identifying anatomical biomarkers of early mild cognitive impairment.PeerJ · 2024Article
- Neuroimaging to Facilitate Clinical Trials in Huntington's Disease: Current Opinion from the EHDN Imaging Working Group.Journal of Huntington's disease · 2024Review
- Modified MRI Anonymization (De-Facing) for Improved MEG Coregistration.Bioengineering (Basel, Switzerland) · 2022Article
- Article
- Combining aperiodic 1/f slopes and brain simulation: An EEG/MEG proxy marker of excitation/inhibition imbalance in Alzheimer's disease.Alzheimer's & dementia (Amsterdam, Netherlands)Article
- Multi-site harmonization for magnetoencephalography spectral power data.Imaging neuroscience (Cambridge, Mass.)Article
- Canonical Hidden Markov Model Networks for studying M/EEG.Imaging neuroscience (Cambridge, Mass.)Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 3 countries.
Funding
Abstract
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.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.