Inability of Lyapunov exponents to predict epileptic seizures
- PMID: 12935113
- DOI: 10.1103/PhysRevLett.91.068102
Inability of Lyapunov exponents to predict epileptic seizures
Abstract
It has been claimed that Lyapunov exponents computed from electroencephalogram or electrocorticogram (ECoG) time series are useful for early prediction of epileptic seizures. We show, by utilizing a paradigmatic chaotic system, that there are two major obstacles that can fundamentally hinder the predictive power of Lyapunov exponents computed from time series: finite-time statistical fluctuations and noise. A case study with an ECoG signal recorded from a patient with epilepsy is presented.
Comment in
-
Comment on "Inability of Lyapunov exponents to predict epileptic seizures".Phys Rev Lett. 2005 Jan 14;94(1):019801; author reply 019802. doi: 10.1103/PhysRevLett.94.019801. Epub 2005 Jan 3. Phys Rev Lett. 2005. PMID: 15698148 No abstract available.
Similar articles
-
Controlled test for predictive power of Lyapunov exponents: their inability to predict epileptic seizures.Chaos. 2004 Sep;14(3):630-42. doi: 10.1063/1.1777831. Chaos. 2004. PMID: 15446973
-
Comment on "Inability of Lyapunov exponents to predict epileptic seizures".Phys Rev Lett. 2005 Jan 14;94(1):019801; author reply 019802. doi: 10.1103/PhysRevLett.94.019801. Epub 2005 Jan 3. Phys Rev Lett. 2005. PMID: 15698148 No abstract available.
-
Does spatiotemporal synchronization of EEG change prior to absence seizures?Brain Res. 2008 Jan 10;1188:207-21. doi: 10.1016/j.brainres.2007.10.048. Epub 2007 Oct 26. Brain Res. 2008. PMID: 18036512
-
Cortical excitability as a potential clinical marker of epilepsy: a review of the clinical application of transcranial magnetic stimulation.Int J Neural Syst. 2014 Mar;24(2):1430001. doi: 10.1142/S0129065714300010. Epub 2014 Jan 13. Int J Neural Syst. 2014. PMID: 24475894 Review.
-
[Intraoperative Monitoring of epileptic foci: usefulness of multimodality image-guided epilepsy surgery performed in combination with electrocorticography].Brain Nerve. 2011 Apr;63(4):321-9. Brain Nerve. 2011. PMID: 21441635 Review. Japanese.
Cited by
-
A Brief Survey of Computational Models of Normal and Epileptic EEG Signals: A Guideline to Model-based Seizure Prediction.J Med Signals Sens. 2011 Jan;1(1):62-72. J Med Signals Sens. 2011. PMID: 22606660 Free PMC article.
-
Seizure prediction: methods.Epilepsy Behav. 2011 Dec;22 Suppl 1(Suppl 1):S94-101. doi: 10.1016/j.yebeh.2011.09.001. Epilepsy Behav. 2011. PMID: 22078526 Free PMC article.
-
Complexity measures of brain wave dynamics.Cogn Neurodyn. 2011 Jun;5(2):171-82. doi: 10.1007/s11571-011-9151-3. Epub 2011 Feb 9. Cogn Neurodyn. 2011. PMID: 22654989 Free PMC article.
-
A distance-based dynamical transition analysis of time series signals and application to biological systems.J Biol Phys. 2012 Mar;38(2):293-303. doi: 10.1007/s10867-011-9248-2. Epub 2011 Dec 10. J Biol Phys. 2012. PMID: 23449743 Free PMC article.
-
Detection of seizure rhythmicity by recurrences.Chaos. 2008 Sep;18(3):033124. doi: 10.1063/1.2973817. Chaos. 2008. PMID: 19045462 Free PMC article.
Publication types
MeSH terms
Grants and funding
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical