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Updated: Jul 7, 2026
Preterm EEG: A Multimodal Neurophysiological Protocol
Published on: February 18, 2012
Functional connectivity as a prognostic biomarker for neurodevelopmental outcomes in preterm infants without severe
Yi-Tien Li1,2,3, Li-Wen Chen4, Chia-Lin Koh5
1Translational Imaging Research Center, Taipei Medical University Hospital, Taipei 11031, Taiwan.
Insights
Brain connectivity at term-equivalent age can predict neurodevelopmental impairment severity in preterm infants. Early functional MRI assessments may identify infants needing timely interventions for better outcomes.
Area of Science:
- Neuroscience
- Developmental Pediatrics
- Medical Imaging
Background:
- Neurodevelopmental impairment (NDI) is common in preterm infants, even without severe neonatal brain injury.
- Early identification of NDI risk is crucial for timely interventions.
- Brain dysmaturation, indicated by altered functional connectivity, may serve as an early biomarker.
Purpose of the Study:
- To investigate if brain functional connectivity alterations at term-equivalent age predict NDI severity at 24 months corrected age in preterm infants without severe neonatal brain injury.
- To explore the relationship between specific connectivity patterns and cognitive, language, and motor outcomes.
- To assess the predictive value of functional connectivity and neonatal factors for NDI severity.
Main Methods:
- Observational cohort study of preterm infants (< 31 weeks' gestation) without severe neonatal brain injury.
- Resting-state functional MRI at term-equivalent age.
- Neurodevelopmental assessment at 24 months corrected age (Bayley-III, cerebral palsy, neurosensory impairments).
- Analysis of functional connectivity alterations and machine learning for predictive modeling.
Main Results:
- Functional connectivity alterations, including increased clustering coefficient and decreased global efficiency, were associated with increased NDI severity.
- Infants with no/mild NDI showed enhanced connectivity in the limbic system and thalamus-basal ganglia pathways, which weakened with greater impairment.
- Thalamo-cortical, thalamo-basal ganglia, and thalamo-cerebellar connectivity correlated with cognitive, language, and motor performance.
- A predictive model combining functional connectivity and neonatal exposures achieved 82% accuracy.
Conclusions:
- Disruptions in brain functional connectivity at term-equivalent age can predict NDI severity in very preterm infants without severe neonatal brain injury.
- Early functional connectivity assessment shows promise as a biomarker for identifying high-risk infants.
- This approach may facilitate timely neurodevelopmental interventions to improve outcomes.
Abstract:
Despite a decline in severe neonatal brain injury in preterm infants, neurodevelopmental impairment remains prevalent. Identifying early biomarkers for neurodevelopmental impairment, particularly in infants without severe neonatal brain injury, is crucial for intervention. This study explores whether brain dysmaturation, indicated by functional connectivity alterations at term-equivalent age, predicts neurodevelopmental impairment severity at 24 months corrected age in preterm infants without severe neonatal brain injury. In this observational cohort study, preterm infants born < 31 weeks' gestation without severe neonatal brain injury underwent resting-state functional MRI at term-equivalent age. Neurodevelopmental outcomes at corrected age 24 months were assessed using Bayley-III cognitive and motor composite scores, cerebral palsy severity, and neurosensory impairments. Functional connectivity alterations were analyzed in relation to cognitive, language, and motor outcomes. Machine learning models were applied to assess the predictive value of functional connectivity features alongside neonatal exposures for neurodevelopmental impairment severity. Among the 122 preterm infants, 89 (73%) infants had no/mild neurodevelopmental impairment, 27 (22%) had moderate neurodevelopmental impairment, and 6 (5%) showed severe neurodevelopmental impairment. Compared with the no/mild neurodevelopmental impairment group, the moderate/severe neurodevelopmental impairment group was significantly lower in gestational age, and required longer durations of invasive mechanical ventilation, oxygen therapy, vasopressors, and total parenteral nutrition during admission. Compared with term-born controls, a clear trend emerged across neurodevelopmental impairment severity levels: as impairment increased from the no/mild group to the moderate and severe groups, the clustering coefficient increased, whereas the global efficiency decreased. Statistical comparisons between the no/mild and moderate/severe groups, relative to term-born controls, confirmed these patterns (clustering coefficient: t = -4.38, P < 0.001; global efficiency: t = 3.44, P < 0.001). Infants with no/mild neurodevelopmental impairment exhibited enhanced connectivity in the limbic system (t = -5.21, P < 0.001) and between the thalamus and basal ganglia (t = -5.9, P < 0.001), but this compensatory connectivity weakened with increasing neurodevelopmental impairment severity. The thalamo-cortical (frontal lobe, limbic system), thalamo-basal ganglia, and thalamo-cerebellar connectivity were strongly associated with cognitive, language, and motor performance at follow-up. A predictive model incorporating these functional connectivity features and neonatal adverse exposure parameters achieved 82% accuracy. Distinct disruptions in functional connectivity at term-equivalent age in very preterm infants without severe neonatal brain injury may predict the severity of later neurodevelopmental impairment. Early functional connectivity assessment holds promise as a biomarker for identifying high-risk infants who may benefit from timely neurodevelopmental interventions.
