Classification of patterns of EEG synchronization for seizure prediction

@article{Mirowski2009ClassificationOP,
  title={Classification of patterns of EEG synchronization for seizure prediction},
  author={Piotr Mirowski and Deepak Madhavan and Yann LeCun and Ruben Kuzniecky},
  journal={Clinical Neurophysiology},
  year={2009},
  volume={120},
  pages={1927-1940}
}
OBJECTIVE Research in seizure prediction from intracranial EEG has highlighted the usefulness of bivariate measures of brainwave synchronization. Spatio-temporal bivariate features are very high-dimensional and cannot be analyzed with conventional statistical methods. Hence, we propose state-of-the-art machine learning methods that handle high-dimensional inputs. METHODS We computed bivariate features of EEG synchronization (cross-correlation, nonlinear interdependence, dynamical entrainment… CONTINUE READING
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