Can Epileptic Seizures be Predicted? Evidence from Nonlinear Time Series Analysis of Brain Electrical Activity
- 1 June 1998
- journal article
- research article
- Published by American Physical Society (APS) in Physical Review Letters
- Vol. 80 (22), 5019-5022
- https://doi.org/10.1103/physrevlett.80.5019
Abstract
We evaluate the capability of nonlinear time series analysis to extract features from brain electrical activity (EEG) predictive of epileptic seizures. Time-resolved analysis of the EEG recorded in 16 patients from within the seizure-generating area of the brain indicate marked changes in nonlinear characteristics for up to several minutes prior to seizures as compared to other states or recording sites. If interpreted as a loss of complexity in brain electrical activity these changes could reflect the hypothesized continuous increase of synchronization between pathologically discharging neurons and allow one to study seizure-generating mechanisms in humans.Keywords
This publication has 25 references indexed in Scilit:
- Nonlinear Time Series AnalysisPublished by Cambridge University Press (CUP) ,2003
- Spatio-temporal dynamics of the primary epileptogenic area in temporal lobe epilepsy characterized by neuronal complexity lossElectroencephalography and Clinical Neurophysiology, 1995
- On the evidence for low-dimensional chaos in an epileptic electroencephalogramPhysics Letters A, 1995
- Propagation of Epileptiform Activity During Development of Amygdala Kindling in Rats: Linear and Non‐linear Association Between lpsi‐ and Contralateral SitesEuropean Journal of Neuroscience, 1993
- Nonlinear Dynamical Analysis of The EEGPublished by World Scientific Pub Co Pte Ltd ,1993
- Chaos or noise in EEG signals; dependence on state and brain siteElectroencephalography and Clinical Neurophysiology, 1991
- NONLINEAR TIME SEQUENCE ANALYSISInternational Journal of Bifurcation and Chaos, 1991
- Phase space topography and the Lyapunov exponent of electrocorticograms in partial seizuresBrain Topography, 1990
- Low-dimensional chaos in an instance of epilepsy.Proceedings of the National Academy of Sciences, 1986
- Characterization of Strange AttractorsPhysical Review Letters, 1983