Nonlinear dynamics of epileptic seizures on basis of intracranial EEG recordings.
OBJECTIVE
An understanding of the principles governing the behavior of complex neuronal networks, in particular their capability of generating epileptic seizures implies the characterization of the conditions under which a transition from the interictal to the ictal state takes place. Signal analysis methods derived from the theory of nonlinear dynamics provide new tools to characterize the behavior of such networks, and are particularly relevant for the analysis of epileptiform activity.


METHODS
We calculated the correlation dimension, tested for irreversibility, and made recurrence plots of EEG signals recorded intracranially both during interictal and ictal states in temporal lobe epilepsy patients who were surgical candidates.


RESULTS
Epileptic seizure activity often, but not always, emerges as a low-dimensional oscillation. In general, the seizure behaves as a nonstationary phenomenon during which both phases of low and high complexity may occur. Nevertheless a low dimension may be found mainly in the zone of ictal onset and nearby structures. Both the zone of ictal onset and the pattern of propagation of seizure activity in the brain could be identified using this type of analysis. Furthermore, the results obtained were in close agreement with visual inspection of the EEG records.


CONCLUSIONS
Application of these mathematical tools provides novel insights into the spatio-temporal dynamics of "epileptic brain states". In this way it may be of practical use in the localization of an epileptogenic region in the brain, and thus be of assistance in the presurgical evaluation of patients with localization-related epilepsy.
Pijn
J P
JP
Instituut voor Epilepsiebestrijding, Meer en Bosch/De Cruquiushoeve, Heemstede, The Netherlands. pijn@dds.nl
Velis
D N
DN
van der Heyden
M J
MJ
DeGoede
J
J
van Veelen
C W
CW
Lopes da Silva
F H
FH
D000328:Adult; D003198:Computer Simulation; D004569:Electroencephalography / Q000706:statistics & numerical data*; D004833:Epilepsy, Temporal Lobe / Q000503:physiopathology*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D017711:Nonlinear Dynamics; D012815:Signal Processing, Computer-Assisted