Relevance of nonlinear lumped-parameter models in the analysis of depth-EEG epileptic signals

@article{Wendling2000RelevanceON,
  title={Relevance of nonlinear lumped-parameter models in the analysis of depth-EEG epileptic signals},
  author={F. Wendling and J. Bellanger and F. Bartolomei and P. Chauvel},
  journal={Biological Cybernetics},
  year={2000},
  volume={83},
  pages={367-378}
}
Abstract. In the field of epilepsy, the analysis of stereoelectroencephalographic (SEEG, intra-cerebral recording) signals with signal processing methods can help to better identify the epileptogenic zone, the area of the brain responsible for triggering seizures, and to better understand its organization. In order to evaluate these methods and to physiologically interpret the results they provide, we developed a model able to produce EEG signals from “organized” networks of neural populations… Expand
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