title: Seizure anticipation: do mathematical measures correlate with video-EEG evaluation?
abstract: OBJECTIVE
  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.
authors.affiliation: Montreal Neurological Institute and Hospital, McGill University, Montréal, Québec, Canada.
authors.forename: Vincent
authors.initials: V
authors.lastname: Navarro
authors.forename: Jacques
authors.initials: J
authors.lastname: Martinerie
authors.forename: Michel
authors.initials: M
authors.lastname: Le Van Quyen
authors.forename: Michel
authors.initials: M
authors.lastname: Baulac
authors.forename: François
authors.initials: F
authors.lastname: Dubeau
authors.forename: Jean
authors.initials: J
authors.lastname: Gotman
mesh_terms: D000293:Adolescent; D000328:Adult; D001143:Arousal / Q000502:physiology; D001931:Brain Mapping; D002540:Cerebral Cortex / Q000503:physiopathology*; D004567:Electrodes, Implanted; D004569:Electroencephalography / Q000706:statistics & numerical data*; D004828:Epilepsies, Partial / Q000175:diagnosis* / Q000503:physiopathology; D005260:Female; D007839:Functional Laterality / Q000502:physiology; D006801:Humans; D008297:Male; D008875:Middle Aged; D008991:Monitoring, Physiologic / Q000706:statistics & numerical data; D009044:Motor Cortex / Q000503:physiopathology; D009434:Neural Pathways / Q000503:physiopathology; D017711:Nonlinear Dynamics; D011300:Preoperative Care; D011336:Probability; D011446:Prospective Studies; D014743:Videotape Recording