Application of modulation spectrum for iEEG seizure analysis

Millions of people worldwide suffer with recurrent epileptic seizures that often require hospitalized intracranial electroencephalography (iEEG) for diagnosing their seizure onset zone (SOZ) for surgical therapy. The standard diagnostic procedures for the brain signals rely on time-consuming human review of data via visual analysis. This study investigates whether modulation spectrum measures, with further study, could provide a quantitative algorithmic approach to reliably identify the SOZ for a patient and reduce or eliminate the burden of manual iEEG review. In a pilot dataset of four patients (one seizure per person), we analyzed human iEEG before, during, and after their seizure from signals inside and outside their clinically annotated SOZ to observe changes in 49 modulation spectrum measures. Regarding electrode location effects (i.e., inside vs. outside SOZ), we observed statistically significant differences (p <; 0.001) in modulation measures at certain cross-frequency bins (e.g., δ:γ bandwidths) with high effect size (g ≥ 0.80) for some patients. For seizure state effects, we observed significant differences with high effect size in many measures across almost all cross-frequency bins between various pairings of seizure states (e.g., during vs. before) for all patients. We concluded that the modulation spectrum had potential in quantifying SOZ and seizure states for diagnostic purposes and in understanding the effect of seizures on brain networks.