The genesis of epileptic seizures is nowadays still mostly unknown. The hypothesis that most of scientist share is that an abnormal synchronization of different groups of neurons seems to trigger a recruitment mechanism that leads the brain to the seizure in order to reset this abnormal condition. If we aim to understand the genesis of epileptic seizures so that we can be able to control them, we need a system to be able to detect, follow and interfere with these dynamics. The aim of this paper is to introduce a technique to detect these phenomena and, to this purpose, a powerful brain mapping based on the Permutation Entropy (PE) is proposed. PE topography is constructed and then modelled in order to come up with a spatiotemporal clustering of the areas of the brain. This technique was tested over 24 EEG dataset from patients affected by absence seizures and on 40 EEG from healthy subjects. The results show an abnormal coupling among the electrodes that will be involved in seizure development. In particular, the frontal/temporal area (critical during the ictal stages in these patients) appears steadily associated to higher PE levels, compared to the rest of the brain, even during the interictal stages.

Discovering Network Phenomena in the Epileptic Electroencephalograph through Permutation Entropy Mapping

N. Mammone;F. La Foresta;F. C. Morabito
2011

Abstract

The genesis of epileptic seizures is nowadays still mostly unknown. The hypothesis that most of scientist share is that an abnormal synchronization of different groups of neurons seems to trigger a recruitment mechanism that leads the brain to the seizure in order to reset this abnormal condition. If we aim to understand the genesis of epileptic seizures so that we can be able to control them, we need a system to be able to detect, follow and interfere with these dynamics. The aim of this paper is to introduce a technique to detect these phenomena and, to this purpose, a powerful brain mapping based on the Permutation Entropy (PE) is proposed. PE topography is constructed and then modelled in order to come up with a spatiotemporal clustering of the areas of the brain. This technique was tested over 24 EEG dataset from patients affected by absence seizures and on 40 EEG from healthy subjects. The results show an abnormal coupling among the electrodes that will be involved in seizure development. In particular, the frontal/temporal area (critical during the ictal stages in these patients) appears steadily associated to higher PE levels, compared to the rest of the brain, even during the interictal stages.
978-1-60750-691-1
Brain mapping; EEG; Permutation Entropy
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.12318/8837
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