Miriam Guendelman

The paper examines sleep initiation in children with neurodevelopmental conditions, finding weaker neural and physiological transitions linked to longer sleep onset latencies.

This paper introduces a data-driven framework for sleep analysis using PCA, GHMM, and ICA to uncover sleep dynamics from electrophysiological signals, achieving results comparable to manual scoring.

This paper classifies seizure dynamotypes from surface EEG using visual and automated methods, finding bifurcation prevalence aligns with intracranial data and varies by clinical factors.