Status Epilepticus (SE) is the condition in which the epileptic brain is in a state of persistent seizure activity. SE is a major health concern with an estimated 42,000 deaths every year in the USA alone. We developed a novel methodology, based on information flow and graph theory, and applied to intracranial electroencephalographic (EEG) recordings from rats induced to SE in the Lithium-Pilocarpine animal model of epilepsy. We defined two measures of the transition of the brain network into and out of SE: the network density (ND) and the network node in-out degree correlation (NIODc). The measures correspond to familiar ones from graph theory with estimates of connectivity based on the Generalized Partial Directed Coherence (GPDC). We consistently observed an increase in the connectivity between brain sites and imbalance in the information flow from and to brain sites at the start of SE, with a progressive trend towards restoration of their baseline values by the end of SE and thereafter. These findings could contribute to the development of novel tools for monitoring and more efficient treatment of status epilepticus.
|Original language||English (US)|
|Title of host publication||Optimization in Science and Engineering: In Honor of the 60th Birthday of Panos M. Pardalos|
|Publisher||Springer New York|
|Number of pages||10|
|ISBN (Print)||9781493908080, 1493908073, 9781493908073|
|State||Published - Jul 1 2014|
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