ArticleNeuroImage2016
Machine-learning to characterise neonatal functional connectivity in the preterm brain.
Article in NeuroImage, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers, 2 of them syntheses that pooled it.
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Who cites it
58 citing papers in PubMed, 2 syntheses or guidelines pooled it, 120 citations in OpenAlex.
- Machine Learning and Prediction in Fetal, Infant, and Toddler Neuroimaging: A Review and Primer.Biological psychiatry · 2023Pooled it
- Machine learning for understanding and predicting neurodevelopmental outcomes in premature infants: a systematic review.Pediatric research · 2023Pooled it
- Early Development and Co-Evolution of Microstructural and Functional Brain Connectomes: A Multi-Modal MRI Study in Preterm and Full-Term Infants.Human brain mapping · 2025Article
- Brain connectomes in youth at risk for serious mental illness: a longitudinal perspective.Brain imaging and behavior · 2025Article
- Audiovisual integration and whole-brain networks in preterm and full-term neonates: A two-layer multiplex network perspective on structural and functional connectivity.Imaging neuroscience (Cambridge, Mass.) · 2025Article
- Predicting 2-year neurodevelopmental outcomes in preterm infants using multimodal structural brain magnetic resonance imaging with local connectivity.Scientific reports · 2024Article
- Neonatal brain dynamic functional connectivity in term and preterm infants and its association with early childhood neurodevelopment.Nature communications · 2024Article
- Multi-source multi-modal markers for Bayesian Networks: Application to the extremely preterm born brain.Medical image analysis · 2024Article
- Global trends in neonatal MRI brain neuroimaging research over the last decade: a bibliometric analysis.Quantitative imaging in medicine and surgery · 2024Article
- Distinct Neurodevelopmental Trajectories in Groups of Very Preterm Children Screening Positively for Autism Spectrum Conditions.Journal of autism and developmental disorders · 2024Article
- The relationship between late (≥ 7 days) systemic dexamethasone and functional network connectivity in very preterm infants.Heliyon · 2023Article
- The past, current, and future of neonatal intensive care units with artificial intelligence: a systematic review.NPJ digital medicine · 2023Review
- Structural and functional asymmetry of the neonatal cerebral cortex.Nature human behaviour · 2023Article
- Large-scale brain network dynamics in very preterm children and relationship with socio-emotional outcomes: an exploratory study.Pediatric research · 2023Article
- Parsing brain-behavior heterogeneity in very preterm born children using integrated similarity networks.Translational psychiatry · 2023Article
- Maturation of large-scale brain systems over the first month of life.Cerebral cortex (New York, N.Y. : 1991) · 2023Article
- The confound of head position in within-session connectome fingerprinting in infants.NeuroImage · 2023Article
- The role of artificial intelligence in paediatric neuroradiology.Pediatric radiology · 2022Review
- Thalamocortical functional connectivity in infants with prenatal opioid exposure correlates with severity of neonatal opioid withdrawal syndrome.Neuroradiology · 2022Article
- Interaction of the salience network, ventral attention network, dorsal attention network and default mode network in neonates and early development of the bottom-up attention system.Brain structure & function · 2022Article
Corrections and comments
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Authors and funding
10 authors at 1 institution in 1 country.
Funding
Abstract
Brain development is adversely affected by preterm birth. Magnetic resonance image analysis has revealed a complex fusion of structural alterations across all tissue compartments that are apparent by term-equivalent age, persistent into adolescence and adulthood, and associated with wide-ranging neurodevelopment disorders. Although functional MRI has revealed the relatively advanced organisational state of the neonatal brain, the full extent and nature of functional disruptions following preterm birth remain unclear. In this study, we apply machine-learning methods to compare whole-brain functional connectivity in preterm infants at term-equivalent age and healthy term-born neonates in order to test the hypothesis that preterm birth results in specific alterations to functional connectivity by term-equivalent age. Functional connectivity networks were estimated in 105 preterm infants and 26 term controls using group-independent component analysis and a graphical lasso model. A random forest-based feature selection method was used to identify discriminative edges within each network and a nonlinear support vector machine was used to classify subjects based on functional connectivity alone. We achieved 80% cross-validated classification accuracy informed by a small set of discriminative edges. These edges connected a number of functional nodes in subcortical and cortical grey matter, and most were stronger in term neonates compared to those born preterm. Half of the discriminative edges connected one or more nodes within the basal ganglia. These results demonstrate that functional connectivity in the preterm brain is significantly altered by term-equivalent age, confirming previous reports of altered connectivity between subcortical structures and higher-level association cortex following preterm birth.
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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.