Daniel W. Shrey

The paper predicts treatment response in infantile epileptic spasms syndrome using EEG phase-amplitude coupling, finding that lower pre-treatment modulation index values correlate with better treatment outcomes.

The paper uses EEG functional connectivity to track progression from infantile epileptic spasms syndrome to Lennox-Gastaut Syndrome and identifies patterns associated with treatment response and disease markers.

This study evaluates whether optimizing automated HFO detection using visual markings improves SOZ localization accuracy, finding no significant improvement.

This paper introduces a method to dynamically alter electrode size in vivo to study the impact of electrode size on intracranial EEG features across different brain regions.

The paper identifies computational EEG features that distinguish epileptic spasms patients from controls with high accuracy.

This study develops an automated method to detect high-frequency oscillations (HFOs) in long-term scalp EEG from infantile spasms patients and healthy controls, showing higher HFO rates in patients and a significant reduction after ACTH treatment.

This study examines how functional brain networks in infants change over long time scales using EEG data, finding stable network patterns during sleep and wakefulness with temporal variations in network properties.

The paper investigates how interictal epileptiform discharges affect EEG-based functional connectivity networks, finding increased connectivity strength in infantile spasms but no structural changes.