Signal Processing of EEG: Evidence for Chaos or Noise. An Application to Seizure Activity in Epilepsy

  • Fernando H. Lopes da Silva
  • Jan-Pieter Pijn
  • Demetrios N. Velis

Abstract

The EEG is an important signal for the diagnosis of functional disturbances of the brain, and in particular, of epilepsy. The non-linear dynamical analysis of EEG signals recorded during seizure activity in comparison with on-going signals allowed us to formulate a hypothesis about the generation of epileptic activity. According to this model, epilepsy should be envisaged as a dynamical disease of neuronal networks, that may exhibit different types of attractors, i.e., may present bifurcations. One of these attractors is characterized by the generation of irregular oscillations, typical of epileptic seizures.

Keywords

Lyapunov Exponent Neuronal Network Epileptic Seizure Correlation Dimension Seizure Activity 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1996

Authors and Affiliations

  • Fernando H. Lopes da Silva
    • 1
    • 2
  • Jan-Pieter Pijn
    • 2
  • Demetrios N. Velis
    • 2
  1. 1.Institute of NeurobiologyUniversity of AmsterdamNetherlands
  2. 2.Institute of Epilepsy “Meer en Bosch”HeemstedeThe Netherlands

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