Rebeccah Slater

This paper shows that sensory-evoked potentials can accurately predict age in premature infants, with potential for early detection of abnormal neurodevelopment.

This paper develops a deep learning model to estimate brain age from neonatal EEG signals, achieving high accuracy with short recordings and showing correlation with neurodevelopmental outcomes.

This paper introduces a framework to study brain ontogeny and phylogeny by integrating connectivity maps across species and developmental stages.

The paper uses functional and diffusion MRI to predict infants' noxious-evoked brain activity from resting-state data and links it to white matter microstructure.

This paper translates adult fMRI pain signatures to infants, finding similar basic nociceptive encoding but differences in higher-level cognitive modulation of pain.