title: What is the present-day EEG evidence for a preictal state?
abstract: EEG-based seizure prediction has undergone phases of optimism when analyses based on limited EEG samples suggested high sensitivity and specificity for several algorithms extracting features from raw preictal EEG data. When using long-term recordings, a more realistic view emerged which suggests that statistically significant predictions might be possible from surface and intracranial EEG, but no algorithm has yet demonstrated performance allowing for clinical application. Here, progress in EEG recording techniques, EEG analysis, and requirements for proper statistical validation of results are reported and discussed as they pertain to clinical implementation.
authors: Dept. of Neurology, University of Michigan, USA.
authors: William
authors: W
authors: Stacey
authors: Michel
authors: M
authors: Le Van Quyen
authors: Florian
authors: F
authors: Mormann
authors: Andreas
authors: A
authors: Schulze-Bonhage
mesh_terms: D000465:Algorithms; D001931:Brain Mapping; D004566:Electrodes; D004569:Electroencephalography / Q000295:instrumentation / Q000379:methods*; D005189:False Positive Reactions; D006801:Humans; D008137:Longitudinal Studies; D011237:Predictive Value of Tests; D012640:Seizures / Q000175:diagnosis* / Q000503:physiopathology; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted