Brittany H. Scheid

This paper uses HAVOK analysis to model nonlinear seizure dynamics and improves multi-day seizure risk forecasting by identifying short-period forcings.

The paper develops deep learning algorithms to quantify seizure spread beyond onset zones and finds associations with structural connectivity and surgical outcomes.

The paper introduces Maestro, a network analysis method that identifies synchronized genetic activities in Alzheimer's disease, finding a pattern associated with AD that is significantly more common in cases than controls.