Professor Robert Chen
Editor-in-Chief, Clinical Neurophysiology
Johannes Mader, Manfred Hartmann, Katrin Klebermass-Schrehof, Tobias Werther, Anastasia Dressler, Lisa Oberdorfer, Nadine Pointner, Renate Fuiko, Angelika Berger, Tilmann Kluge, Vito Giordano.
Preterm infants represent more than 10% of newborn. Despite advances in neonatal care, they are at risk of adverse neurodevelopmental outcome. Conventional EEG montages such as the 10-20 system are difficult to apply in the neonatal intensive care unit, while EEG monitors with 2 to 4 active electrodes that displayed filtered and compressed EEG, known as amplitude-integrated EEG (aEEG), are easier to use. In this volume of Clinical Neurophysiology, Mader et al. used machine learning and aEEG data from neonates to predict EEG maturational age. The difference between EEG maturational age and postmenstrual age was found to predict abnormal cognitive outcomes. EEG recordings that are often available in neonatal intensive care units can potentially be used to assess neurodevelopmental risk. This may lead to close monitoring and early intervention for at risk infants.