ArticleDevelopmental cognitive neuroscience2022
Resting-state functional connectivity identifies individuals and predicts age in 8-to-26-month-olds.
Article in Developmental cognitive neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 1 of them a synthesis that pooled it.
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Who cites it
32 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Quantitative assessment of neurodevelopmental maturation: a comprehensive systematic literature review of artificial intelligence-based brain age prediction in pediatric populations.Frontiers in neuroinformatics · 2024Pooled it
- Functional brain connectivity from the fetal period through infancy: A narrative review of resting-state fMRI studies.Developmental cognitive neuroscience · 2026Review
- Language network functional connectivity in infancy predicts developmental language trajectories.Developmental cognitive neuroscience · 2026Article
- The Roles of Delayed Cortical Maturation and Lower Anticipatory Reward Activation in Predicting Addictive Screen Use in Youth.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2026Article
- Cognitive and affective neurodevelopment in youth exposed to deprivation and threat.bioRxiv : the preprint server for biology · 2026Article
- Neighborhood air pollution is associated with attenuated neurocognitive maturation over early adolescence.Developmental cognitive neuroscience · 2026Article
- BIBSNet: A deep learning baby image brain segmentation network for MRI scans.Developmental cognitive neuroscience · 2026Article
- Revolutionizing Pediatric Neurophysiology With Magnetoencephalography.Psychophysiology · 2026Review
- Lesions Associated With Autism Symptoms Map to a Cerebellar Brain Network in Tuberous Sclerosis Complex.Annals of the Child Neurology Society · 2026Article
- Commonality and Variability in Functional Networks in Children Under 5 Years Old.bioRxiv : the preprint server for biology · 2026Article
- Aperiodic parameters of the fMRI power spectrum associate with preterm birth and neonatal age.Communications biology · 2026Article
- Cross-paradigm fNIRS brain activity in 1-month-old infants across The Gambia and the United Kingdom.Neurophotonics · 2026Article
- From rest to meaning: default mode network neuroscience as a design constraint for early childhood education.Frontiers in psychology · 2026Review
- Identifying left and right hemispheres using functional connectivity.bioRxiv : the preprint server for biology · 2025Article
- Comparative Evaluation of Assumption Lean Community Detection Methods for Human Connectome Networks.bioRxiv : the preprint server for biology · 2025Article
- Assessing neurocognitive maturation in early adolescence based on baby and adult functional brain landscapes.Developmental cognitive neuroscience · 2025Article
- The generalizability of cortical area parcellations across early childhood.Cerebral cortex (New York, N.Y. : 1991) · 2025Article
- Functional Brain Connectivity Predictors of Prospective Substance Use Initiation and Their Environmental Correlates.Biological psychiatry. Cognitive neuroscience and neuroimaging · 2025Article
- Deep learning-based embedding of functional connectivity profiles for precision functional mapping.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- A Subset of Cortical Areas Exhibit Adult-like Functional Network Patterns in Early Childhood.bioRxiv : the preprint server for biology · 2024Article
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21 authors.
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Abstract
Resting-state functional connectivity (rsFC) measured with fMRI has been used to characterize functional brain maturation in typically and atypically developing children and adults. However, its reliability and utility for predicting development in infants and toddlers is less well understood. Here, we use fMRI data from the Baby Connectome Project study to measure the reliability and uniqueness of rsFC in infants and toddlers and predict age in this sample (8-to-26 months old; n = 170). We observed medium reliability for within-session infant rsFC in our sample, and found that individual infant and toddler's connectomes were sufficiently distinct for successful functional connectome fingerprinting. Next, we trained and tested support vector regression models to predict age-at-scan with rsFC. Models successfully predicted novel infants' age within ± 3.6 months error and a prediction R
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