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Seizure Anticipation: Do Mathematical Measures Correlate with Video‐EEG Evaluation?
Author(s) -
Navarro Vincent,
Martinerie Jacques,
Le Van Quyen Michel,
Baulac Michel,
Dubeau François,
Gotman Jean
Publication year - 2005
Publication title -
epilepsia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.687
H-Index - 191
eISSN - 1528-1167
pISSN - 0013-9580
DOI - 10.1111/j.0013-9580.2005.15504.x
Subject(s) - electroencephalography , ictal , vigilance (psychology) , epilepsy , psychology , anticipation (artificial intelligence) , audiology , neuroscience , medicine , artificial intelligence , computer science
Summary: Purpose: Analysis of the EEG signal has recently shown evidence of dynamic changes preceding ictal onset in seizures selected from patients with clear epileptogenic foci. Most of the studies were conducted in highly selected EEG epochs and patients. In addition, these studies relied mostly on mathematical approaches and neglected clinical and visual EEG parameters. We therefore performed a systematic comparison of a nonlinear method (the similarity measure) with classic visual inspection of the EEG and the patient's clinical state. Methods: We analyzed the dynamics of long epochs of intracranial EEG containing 129 electroclinical and 45 electrographic seizures in 13 successive unselected patients undergoing presurgical evaluation. Results: (a) The similarity measure detected preictal dynamical changes of the EEG signal in two thirds of the seizures whether or not a clear focus was identified, and whether seizures were electroclinical or purely electrographic. The mean duration of preictal changes was 12 min. (b) The preictal changes were correlated with various visually detectable EEG changes in 78.9% of electroclinical seizures. (c) 81.5% of the preictal dynamic changes were correlated with changes of vigilance or behavior. (d) Fluctuations of the dynamics were not necessarily followed by seizures. Conclusions: Our results indicate that EEG dynamics frequently change before seizures. These preictal changes are most often associated with the EEG changes accompanying transitions between states of vigilance. The preictal dynamic changes may represent physiologic changes acting as facilitating factors or pathologic changes reflecting a network dysfunction.