Functional connectivity patterns as an early indicator of later very early preterm outcomes

Abstract

Abnormal functional brain development associated with preterm birth has been widely reported; however, the functional brain architectures of later neurodevelopmental difficulties are not yet fully understood. Here, we applied connectome-based predictive modeling approaches to identify the brain networks associated with later neurocognitive scores at 2-3 years of age in very preterm infants ([&le;]31 weeks gestation, N=79) using resting-state functional magnetic resonance imaging (rs-fMRI). The whole-brain functional connectome soon after birth successfully predicted verbal ability at 3 years of corrected age (r=0.53, = 4.0410!") and motor ability at age 2 (r=0.39, = 0.0004) in very preterm infants. In particular, we found that functional edges between the frontoparietal network and limbic, motor, and medial frontal networks at birth contributed significantly to the prediction of future verbal language ability, while the edges connecting the medial frontal network and motor and basal ganglia networks contributed the most to the prediction of future motor ability. In a separate validation analysis, we demonstrated that the mean connectivity strength among these top brain networks significantly differentiated (average accuracy 76%, p<0.001) poor from normal performers at 2 and 3 years of ages. These findings highlight regional functional connectivity soon after birth as a promising biomarker for identifying risks for later brain disorders, which could inform the targeted development of effective early treatments and interventions.