Detection of spike and wave discharges in the cortical EEG of genetic absence epilepsy rats from Strasbourg

Genetic absence epilepsy rats from Strasbourg (GAERS) are a strain of Wistar rats in which all animals present spontaneous occurrence of spike and wave discharges (SWD) in the cortical electroencephalogram (EEG). In this paper, we present a method for the detection of SWD, based on the key observati...

Full description

Saved in:
Bibliographic Details
Published in:Physics in medicine & biology 2003-06, Vol.48 (12), p.1685-1700
Main Authors: Hese, P Van, Martens, J-P, Boon, P, Dedeurwaerdere, S, Lemahieu, I, Walle, R Van de
Format: Article
Language:English
Subjects:
Action Potentials
Animals
Biological and medical sciences
Biophysical Phenomena
Biophysics
Cerebral Cortex - physiopathology
Electroencephalography - statistics & numerical data
Epilepsy, Absence - genetics
Epilepsy, Absence - physiopathology
Medical sciences
Models, Neurological
Rats
Rats, Wistar
ROC Curve
Sensitivity and Specificity
Sleep - physiology
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Genetic absence epilepsy rats from Strasbourg (GAERS) are a strain of Wistar rats in which all animals present spontaneous occurrence of spike and wave discharges (SWD) in the cortical electroencephalogram (EEG). In this paper, we present a method for the detection of SWD, based on the key observation that SWD are quasi-periodic signals. A spectral-comb based analysis method is used to extract the fundamental frequency and the percentage of energy explained by the harmonic spectral components is subsequently used as a detection parameter. It is shown that a maximum sensitivity and specificity of up to 96 per cent can be achieved. We also compared the performance of this method with the methods presented in the literature and conclude that the surplus value of the novel detection method lies in the higher specificity that can be obtained in the analysis of long-term EEG fragments, which are contaminated by artefacts and contain large portions of slow-wave sleep.
ISSN:0031-9155
1361-6560
DOI:10.1088/0031-9155/48/12/302