Novel computational methods for neonatal EEG analysis

Electroencephalography (EEG) is a standard tool for brain monitoring in the neonatal intensive care unit, although traditionally only with limited channel montages and all clinical interpretation performed manually by eye. In research environments, there has been significant progress in developing high-density electrode montages and machine-learning-based algorithms for automated interpretation. These enable mapping of brain activity across the cortex, extraction of information not easily discerned visually, and the prospect for new diagnostic and prognostic biomarkers. This talk will present our recent advances in computational analysis of neonatal EEG. This includes estimating functional brain age as a marker of maturation, automated seizure detection, measuring large-scale functional network activity in infants at risk of adverse neurodevelopment, and assessing the extent to which personalized MRI-derived cortical surfaces affect EEG source reconstruction versus standard template brains. Challenges in translating these tools to the clinic will also be discussed.