ArticleNeuroImage2023
Multiscale functional connectivity patterns of the aging brain learned from harmonized rsfMRI data of the multi-cohort iSTAGING study.
Article in NeuroImage, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.
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21 citing papers in PubMed, 24 citations in OpenAlex.
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- Brain Ageing in Social Anxiety Disorder: An ENIGMA-Anxiety Mega-Analysis Across 26 International Cohorts.medRxiv : the preprint server for health sciences · 2026Article
- Age-Related Low Frequency Amplitude Differences in Resting-State Blood Oxygenation Level-Dependent Signal in the Cerebellum.Human brain mapping · 2026Article
- Resting-State Brain Age Predicts Cognitive and Sensorimotor Deficits in Schizophrenia Spectrum Disorders: A Validation & Longitudinal Study.Research square · 2026Article
- Personalized functional topography-based multisite brain age prediction modeling reveals divergent neurodevelopment in major depression.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Neonatal brain age estimation from T2-weighted magnetic resonance images using shallow regression analysis.Scientific reports · 2026Article
- Decoding noncoding RNAs in regulating cardiovascular aging and age-related conditions: the emerging landscape.Science China. Life sciences · 2026Review
- Spatial heterogeneity and subtypes of functional connectivity development in youth.Nature communications · 2026Article
- Taming dimensionality in big neuroimaging data: Efficient orthonormal projective NMF via stochastic learning and data compression.Imaging neuroscience (Cambridge, Mass.) · 2026Article
- Systematic fMRI signal differences across cohorts alter lifespan trajectories of functional brain networks.Imaging neuroscience (Cambridge, Mass.) · 2026Article
- Harmonization of Structural Brain Connectivity Through Distribution Matching.Human brain mapping · 2025Article
- Harmonization of Structural Brain Connectivity through Distribution Matching.bioRxiv : the preprint server for biology · 2025Article
- Generative models of MRI-derived neuroimaging features and associated dataset of 18,000 samples.Scientific data · 2024Article
- Generative models of MRI-derived neuroimaging features and associated dataset of 18,000 samples.ArXiv · 2024Article
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- Brain-age prediction: Systematic evaluation of site effects, and sample age range and size.Human brain mapping · 2024Article
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- Resting state network connectivity alterations in HIV: Parallels with aging.Human brain mapping · 2023Article
- Brain age prediction using the graph neural network based on resting-state functional MRI in Alzheimer's disease.Frontiers in neuroscience · 2023Article
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18 authors at 4 institutions in 1 country.
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Abstract
To learn multiscale functional connectivity patterns of the aging brain, we built a brain age prediction model of functional connectivity measures at seven scales on a large fMRI dataset, consisting of resting-state fMRI scans of 4186 individuals with a wide age range (22 to 97 years, with an average of 63) from five cohorts. We computed multiscale functional connectivity measures of individual subjects using a personalized functional network computational method, harmonized the functional connectivity measures of subjects from multiple datasets in order to build a functional brain age model, and finally evaluated how functional brain age gap correlated with cognitive measures of individual subjects. Our study has revealed that functional connectivity measures at multiple scales were more informative than those at any single scale for the brain age prediction, the data harmonization significantly improved the brain age prediction performance, and the data harmonization in the functional connectivity measures' tangent space worked better than in their original space. Moreover, brain age gap scores of individual subjects derived from the brain age prediction model were significantly correlated with clinical and cognitive measures. Overall, these results demonstrated that multiscale functional connectivity patterns learned from a large-scale multi-site rsfMRI dataset were informative for characterizing the aging brain and the derived brain age gap was associated with cognitive and clinical measures.
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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.