Brianne Magouirk Bettcher

This paper uses single-channel sleep EEG features to predict health outcomes like age, sex, and disease risk using machine learning models.

The paper maps sleep oscillatory events as biomarkers for early Alzheimer's disease by analyzing EEG and CSF biomarkers in aging adults.

This study examines how slow wave/spindle coupling changes across NREM sleep cycles and how these changes relate to sleep depth and age-related differences in SWA composition.

The paper identifies distinct subtypes of slow wave and spindle coupling during sleep across the human lifespan and shows their composition shifts with age.