title: Information theoretic measures of network coordination in high-frequency scalp EEG reveal dynamic patterns associated with seizure termination.
abstract: How a seizure terminates is still under-studied and, despite its clinical importance, remains an obscure phase of seizure evolution. Recent studies of seizure-related scalp EEGs at frequencies >100 Hz suggest that neural activity, in the form of oscillations and/or neuronal network interactions, may play an important role in preictal/ictal seizure evolution (Andrade-Valenca et al., 2011; Stamoulis et al., 2012). However, the role of high-frequency activity in seizure termination, is unknown, if it exists at all. Using information theoretic measures of network coordination, this study investigated ictal and immediate postictal neurodynamic interactions encoded in scalp EEGs from a relatively small sample of 8 patients with focal epilepsy and multiple seizures originating in temporal and/or frontal brain regions, at frequencies ≤ 100 Hz and >100 Hz, respectively. Despite some heterogeneity in the dynamics of these interactions, consistent patterns were also estimated. Specifically, in several seizures, linear or non-linear increase in high-frequency neuronal coordination during ictal intervals, coincided with a corresponding decrease in coordination at frequencies <100 Hz, suggesting a potential interference role of high-frequency activity, to disrupt abnormal ictal synchrony at lower frequencies. These changes in network synchrony started at least 20-30s prior to seizure offset, depending on the seizure duration. Opposite patterns were estimated at frequencies ≤ 100 Hz in several seizures. These results raise the possibility that high-frequency interference may occur in the form of progressive network coordination during the ictal interval, which continues during the postictal interval. This may be one of several possible mechanisms that facilitate seizure termination. In fact, inhibition of pairwise interactions between EEGs by other signals in their spatial neighborhood, quantified by negative interaction information, was estimated at frequencies ≤ 100 Hz, at least in some seizures.
authors.affiliation: Harvard Medical School, United States. caterina.stamoulis@childrens.harvard.edu
authors.forename: Catherine
authors.initials: C
authors.lastname: Stamoulis
authors.forename: Donald L
authors.initials: DL
authors.lastname: Schomer
authors.forename: Bernard S
authors.initials: BS
authors.lastname: Chang
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001921:Brain / Q000503:physiopathology*; D001931:Brain Mapping; D058256:Brain Waves / Q000502:physiology*; D004569:Electroencephalography / Q000379:methods; D005260:Female; D006801:Humans; D007257:Information Theory; D008297:Male; D008875:Middle Aged; D016571:Neural Networks, Computer; D012640:Seizures / Q000175:diagnosis / Q000503:physiopathology*
keywords: Epileptic seizure termination; High-frequency scalp EEG; Information theory; Neuronal network coordination