ArticleFrontiers in human neuroscience2019
Predicting Brain Age Based on Spatial and Temporal Features of Human Brain Functional Networks.
Article in Frontiers in human neuroscience, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses 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
21 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Aging-related changes in cognitive flexibility: fMRI meta-analysis.Behavioral and brain functions : BBF · 2025Pooled it
- The older adult brain is less modular, more integrated, and less efficient at rest: A systematic review of large-scale resting-state functional brain networks in aging.Psychophysiology · 2023Pooled it
- Investigating the Contribution of Molecular-Enriched Functional Connectivity to Brain-Age Analysis.Human brain mapping · 2026Article
- Functional connectome fingerprinting related to BMI and its association with impulsivity.Brain imaging and behavior · 2025Article
- Investigating the Contribution of Molecular-Enriched Functional Connectivity to Brain-Age Analysis.bioRxiv : the preprint server for biology · 2025Article
- The negative relationship between brain-age gap and psychological resilience defines the age-related neurocognitive status in older people.GeroScience · 2025Article
- Protective role of parenthood on age-related brain function in mid- to late-life.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Data leakage inflates prediction performance in connectome-based machine learning models.Nature communications · 2024Article
- The effects of data leakage on connectome-based machine learning models.bioRxiv : the preprint server for biology · 2023Article
- A Skewed Loss Function for Correcting Predictive Bias in Brain Age Prediction.IEEE transactions on medical imaging · 2023Article
- Aging brain shows joint declines in brain within-network connectivity and between-network connectivity: a large-sample study (Frontiers in aging neuroscience · 2023Article
- Accelerated functional brain aging in major depressive disorder: evidence from a large scale fMRI analysis of Chinese participants.Translational psychiatry · 2022Article
- Evaluation of functional MRI-based human brain parcellation: a review.Journal of neurophysiology · 2022Review
- Thalamo-cortical inter-subject functional correlation during movie watching across the adult lifespan.Frontiers in neuroscience · 2022Article
- Brain age prediction using fMRI network coupling in youths and associations with psychiatric symptoms.NeuroImage. Clinical · 2022Article
- Accelerated functional brain aging in pre-clinical familial Alzheimer's disease.Nature communications · 2021Article
- Multimodal Image Analysis of Apparent Brain Age Identifies Physical Fitness as Predictor of Brain Maintenance.Cerebral cortex (New York, N.Y. : 1991) · 2021Article
- Correlation Constraints for Regression Models: Controlling Bias in Brain Age Prediction.Frontiers in psychiatry · 2021Article
- Causality-Based Feature Fusion for Brain Neuro-Developmental Analysis.IEEE transactions on medical imaging · 2020Article
- Alterations of local functional connectivity in lifespan: A resting-state fMRI study.Brain and behavior · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The organization of human brain networks can be measured by capturing correlated brain activity with functional MRI data. There have been a variety of studies showing that human functional connectivities undergo an age-related change over development. In the present study, we employed resting-state functional MRI data to construct functional network models. Principal component analysis was performed on the FC matrices across all the subjects to explore meaningful components especially correlated with age. Coefficients across the components, edge features after a newly proposed feature reduction method as well as temporal features based on fALFF, were extracted as predictor variables and three different regression models were learned to make prediction of brain age. We observed that individual's functional network architecture was shaped by intrinsic component, age-related component and other components and the predictive models extracted sufficient information to provide comparatively accurate predictions of brain age.
Indexed as
Identifiers
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.