ArticleNeurophotonics2025
Brain network evolution in late preterm to term infants: a near-infrared spectroscopy imaging study.
Article in Neurophotonics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Multi-level static and dynamic graph-theoretical analyses of resting-state functional networks in a Chinese cohort of preterm neonates.iScience · 2026Article
- From Cradle to Early-Life Sleep: A Bibliometric Analysis of Global Research on Neonatal Sleep.Nature and science of sleep · 2026Article
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Authors and funding
11 authors.
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Abstract
Significance: Neonatal brain development plays a crucial role in long-term neurodevelopmental outcomes, particularly in preterm infants. Aim: We utilized functional near-infrared spectroscopy (fNIRS) to examine the evolution of brain network connectivity in late preterm and term neonates. Approach: Neonates with a gestational age (GA) between 33 and 41 weeks were included in the study. fNIRS headcaps were placed on the neonates after reaching a stable sleep state. fNIRS data were recorded in continuous-wave mode. Multivariate pattern analysis (MVPA) was conducted to identify distributed patterns of connectivity changes. Results: Significant developmental changes in brain network connectivity were observed at around 37 weeks of GA, marked by enhanced functional connectivity, particularly within brain network connectivity centered on the parietal lobe (PL). MVPA demonstrated high classification accuracy in distinguishing neonates born before 37 weeks from those born at or after 37 weeks, based on the strength of PL-centered brain connectivity. The accuracy values were as follows: PL = 74.17%, PL-FL = 81.10%, PL-TL = 74.68%, and PL-OL = 67.18%. Conclusions: These results underscore the critical role of GA in shaping neonatal brain network functional organization and provide valuable insights for early intervention strategies in preterm infants.
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