ArticleNeuroImage2022
Predicting brain age from functional connectivity in symptomatic and preclinical Alzheimer disease.
Article in NeuroImage, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
36 citing papers in PubMed, 1 synthesis or guideline pooled it, 68 citations in OpenAlex.
- BrainAGE, brain health, and mental disorders: A systematic review.Neuroscience and biobehavioral reviews · 2024Pooled it
- Investigating the Contribution of Molecular-Enriched Functional Connectivity to Brain-Age Analysis.Human brain mapping · 2026Article
- Source-space EEG alpha activity reveals brain age gaps due to neurodegeneration and disparity.Communications biology · 2026Article
- Normative growth trajectories of fetal brain regions validated by satisfactory maturation of neurodevelopmental domains at 2 years of age.Nature communications · 2026Article
- Neonatal brain age estimation from T2-weighted magnetic resonance images using shallow regression analysis.Scientific reports · 2026Article
- Functional network collapse in neurodegenerative disease.Nature communications · 2025Article
- Investigating the Contribution of Molecular-Enriched Functional Connectivity to Brain-Age Analysis.bioRxiv : the preprint server for biology · 2025Article
- Dynamic Brain Age Modeling Identifies Network-Specific Cognitive Deficits in Schizophrenia.Research square · 2025Article
- Intervention on Modifiable Lifestyle and Physiological Factors via Variational Autoencoder Reveals Changes in Functional Connectivity-Mediated Risk for Alzheimer's Disease.medRxiv : the preprint server for health sciences · 2025Article
- Functional Brain Age Acceleration from Dynamic and Static Connectivity Predicts Working Memory and Attention Deficits in Schizophrenia.medRxiv : the preprint server for health sciences · 2025Article
- Predicting response speed and age from task-evoked effective connectivity.Network neuroscience (Cambridge, Mass.) · 2025Article
- Joint Aging Patterns in Brain Function and Structure Revealed Using 27,793 Samples.Research (Washington, D.C.) · 2025Article
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- A Demographic-Conditioned Variational Autoencoder for fMRI Distribution Sampling and Removal of Confounds.ArXiv · 2024Article
- Age Prediction Using Resting-State Functional MRI.Neuroinformatics · 2024Article
- Somatomotor-visual resting state functional connectivity increases after 2 years in the UK Biobank longitudinal cohort.Journal of medical imaging (Bellingham, Wash.) · 2024Article
- Predicting brain age across the adult lifespan with spontaneous oscillations and functional coupling in resting brain networks captured with magnetoencephalography.Imaging neuroscience (Cambridge, Mass.) · 2024Article
- Network-level enrichment provides a framework for biological interpretation of machine learning results.Network neuroscience (Cambridge, Mass.) · 2024Article
- Associations between polygenic risk scores and accelerated brain ageing in smokers.Psychological medicine · 2023Article
Corrections and comments
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Authors and funding
17 authors at 7 institutions in 5 countries.
Funding
Abstract
"Brain-predicted age" quantifies apparent brain age compared to normative neuroimaging trajectories. Advanced brain-predicted age has been well established in symptomatic Alzheimer disease (AD), but is underexplored in preclinical AD. Prior brain-predicted age studies have typically used structural MRI, but resting-state functional connectivity (FC) remains underexplored. Our model predicted age from FC in 391 cognitively normal, amyloid-negative controls (ages 18-89). We applied the trained model to 145 amyloid-negative, 151 preclinical AD, and 156 symptomatic AD participants to test group differences. The model accurately predicted age in the training set. FC-predicted brain age gaps (FC-BAG) were significantly older in symptomatic AD and significantly younger in preclinical AD compared to controls. There was minimal correspondence between networks predictive of age and AD. Elevated FC-BAG may reflect network disruption during symptomatic AD. Reduced FC-BAG in preclinical AD was opposite to the expected direction, and may reflect a biphasic response to preclinical AD pathology or may be driven by inconsistency between age-related vs. AD-related networks. Overall, FC-predicted brain age may be a sensitive AD biomarker.
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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.