Project Summary:Sleep is crucial for early brain development, yet preterm infants often have disrupted sleep patterns that may impact their long-term outcomes. This project will use advanced EEG analysis to map the development of sleep microstructure in preterm babies and relate this to preschool neurodevelopmental milestones. By identifying sleep EEG biomarkers of brain vulnerability, we aim to enable earlier detection of infants at risk, informing personalised care strategies to protect and nurture the preterm brain. The project combines advanced signal processing, longitudinal clinical assessments, and a multidisciplinary perspective to shed new light on the complex interplay between sleep and neurodevelopment.Project Description:Background:Preterm birth affects 10% of live births globally, with survivors at increased risk of neurodevelopmental impairments [1]. This project will focus on moderate to late preterm infants, born between 32 and 36 weeks gestation, who compromise about 84% of all preterm births [2]. Despite being considered lower risk than very preterm infants, moderate to late preterm infants are known to have poorer neurodevelopmental outcomes compared to term-born peers. These infants face increased risks of cognitive deficits, language delays, attention problems, and behavioural issues [3,4]. For instance, they have a 36% higher risk of developmental delay or disability at age 2 compared to term-born infants [5].Sleep is critical for early brain development, but preterm infants have significantly disrupted sleep patterns compared to term-born infants [6]. These abnormalities persist across the neonatal period and may contribute to adverse neurodevelopmental outcomes, possibly by impairing brain connectivity during critical windows [7,8]. However, the specific mechanisms linking preterm sleep disruption to impaired outcomes remain poorly understood. Traditional sleep analysis methods lack the resolution to capture prognostically relevant features. Recent advances in EEG signal processing and machine learning enable automated, high-resolution analysis of sleep microstructure, offering new possibilities to identify early biomarkers of neurodevelopmental risk [9,10].Please click on the 'visit institution website' on the right hand side to apply for this project