Strength and stability of EEG functional connectivity predict treatment response in infants with epileptic spasms

Objective: Epileptic spasms (ES) are associated with pathological neuronal networks, which may underlie characteristic EEG patterns such as hypsarrhythmia. Here we evaluate EEG functional connectivity as a quantitative marker of treatment response, in comparison to classic visual EEG features. Methods: We retrospectively identified 21 ES patients and 21 healthy controls. EEG data recorded before treatment and after ≥10 days of treatment underwent blinded visual assessment, and functional connectivity was measured using cross-correlation techniques. Short-term treatment response and long-term outcome data were collected. Results: Subjects with ES had stronger, more stable functional networks than controls. After treatment initiation, all responders (defined by cessation of spasms) exhibited decreases in functional connectivity strength, while an increase in connectivity strength occurred only in non-responders. There were six subjects with unusually strong pre-treatment functional connectivity, and all were responders. Visually assessed EEG features were not predictive of treatment response. Conclusions: Changes in network connectivity and stability correlate to treatment response for ES, and high pre-treatment connectivity may predict favorable short-term treatment response. Quantitative measures outperform visual analysis of the EEG. Significance: Functional networks may have value as objective markers of treatment response in ES, with potential to facilitate rapid identification of personalized, effective treatments.