Analysis of Absence Seizure Generation using EEG Spatial-temporal Regularity Measures
Abstract
Epileptic seizures are generated and evolve through an underlying anomaly of synchronization in the activity of groups of neuronal populations. The related dynamic scenario of state transitions is revealed by detecting changes in the dynamical properties of Electroencephalography (EEG) signals. The recruit- ment procedure ending with the crisis can be analyzed by means of a spatial-temporal plot from which to extract suitable descriptors that are able to monitor and quantify the evolving synchronization level from the EEG tracings. In this paper, a spatial-temporal analysis of EEG synchronization based on the concept of Permutation Entropy (PE) is proposed. The performance of PE are tested on a database of 24 patients affected by absence (generalized) seizures. The results achieved are compared to the dynamical behavior of the EEG of 40 healthy subjects. Being PE a feature which is dependent on two-parameters, an extensive study of the sensitivity of the performance of PE with respect to the parameters’ setting was carried out on scalp EEG. Once the optimal PE configuration was determined, its ability to detect the different brain states was evaluated. One relevant result of the study is that, in contrast to the widely accepted interpretation of the transition to absence seizure as an abrupt change, within the limits of the analyzed database, the “jump” transition to the epileptic status is heralded well before the seizure on- set. Indeed, ever since the interictal stages, the frontal-temporal scalp areas appear constantly associated to PE levels that are higher compared to the remaining electrodes, whereas the parieto-occipital areas appear associated to lower-PE values. The EEG of healthy subjects does not show any similar dynamic behavior nor exhibits any recurrent portrait in PE topography.
Autore Pugliese
Tutti gli autori
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N. MAMMONE , D. LABATE , A. LAY EKUAKILLE , F.C. MORABITO
Titolo volume/Rivista
INTERNATIONAL JOURNAL OF NEURAL SYSTEMS
Anno di pubblicazione
2012
ISSN
0129-0657
ISBN
Non Disponibile
Numero di citazioni Wos
Nessuna citazione
Ultimo Aggiornamento Citazioni
Non Disponibile
Numero di citazioni Scopus
33
Ultimo Aggiornamento Citazioni
28/04/2018
Settori ERC
Non Disponibile
Codici ASJC
Non Disponibile
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