Chaotic time series analyses of epileptic seizures

Frank, Gregory W; Lookman, Turab; Nerenberg, M. A. H.; Essex, Christopher; Lemieux, John F.; Blume, Warren T.

doi:10.1016/0167-2789(90)90103-v

Cited by 151 publications

(50 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Apart from physiological (i.e. non-pathological) changes in brain state (22,25), the present and previous findings (3,10,26) suggest that the fluctuations of Diff as well as of other non-linear measures (4,5,7,27,28) at least partly depend on the spatiotemporal dynamics of the epileptic process. This view is further supported by a recent finding of an inverse relationship between L* and the serum level of anticonvulsant medication (Carbamazepine) spatially restricted to the primary epileptogenic area, reflecting the nonlinear nature of the underlying synchronization phenomena (29).…”

Section: Discussionmentioning

confidence: 80%

Neuronal Complexity Loss in Interictal EEG Recorded with Foramen Ovale Electrodes Predicts Side of Primary Epileptogenic Area in Temporal Lobe Epilepsy: A Replication Study

et al. 1998

View full text Add to dashboard Cite

Summary:Purpose: To investigate whether a correct lateralization of the primary epileptogenic area by means of neuronal complexity loss analysis can be obtained from interictal EEG recordings using semi-invasive foramen ovale electrodes. In a previous study with recordings from intrahippocampal depth and subdural strip electrodes it was shown that the dynamics of the primary epileptogenic area can be characterized by an increased loss of neuronal complexity in patients with unilateral temporal lobe epilepsy (TLE).Methods: Neuronal complexity loss analysis was applied. This analysis method is derived from the theory of nonlinear dynamics and provides a topological diagnosis even in cases where no actual seizure activity can be recorded. We examined interictal EEG recorded intracranially from multipolar foramen ovale electrodes in 19 patients with unilateral TLE undergoing presurgical evaluation.Results: The primary epileptogenic area was correctly lateralized in 16 of the 19 investigated patients. The misclassification of the side of seizure onset in three patients might be attributed to the larger distance between the foramen ovale electrodes and the mesial temporal structures as compared to intrahippocampal depth electrodes.Conclusions: Our results confirm the previous findings and provide further evidence for the usefulness of nonlinear timeseries analysis for the characterization of the spatiotemporal dynamics of the primary epileptogenic area in mesial temporal lobe epilepsy. Key Words: Neuronal complexity lossCorrelation dimension-Foramen ovale electrodes-Primary epileptogenic area-Temporal lobe epilepsy.Nonlinear time-series analyses have been repeatedly applied to recordings of brain electrical activity. In early investigations, it has been shown that the extracted quantities, such as the correlation dimension D,, Lyapunovexponents or the Kolmogorov-entropy, provide new information on the dynamics of human surface EEG (1). Although correlation dimension during the preictal state was tracked, and it was argued that these measures might serve as precursors of an imminent seizure (4-8). Apart from basic research, nonlinear time-series analyses provide additional tools for seizure detection and classification '(9). Moreover, Lehnertz and Elger (10) showed that the extraction of the so-called neuronal complexity loss L* of interictal EEG recordings allowed the correct lateralization of the primary epileptogenic area in 20 patients with pharmaco-resistant mesial temporal lobe epilepsy-(MTLE) undergoing presurgical evaluation. The logic of that investigation was based on the finding that even during the interictal state, neuronal networks involved in the epileptic process exhibit a decreased level of complexity, a phenomenon which has previously been demonstrated in studies of animal models of focal epilepsy (11,12). In the above cited studies of epilepsy in human patients, however, nonlinear time-series analyses were mainly applied to invasively recorded EEG using chronically implanted depth electrodes or su...

show abstract

Section: Discussionmentioning

confidence: 80%

Neuronal Complexity Loss in Interictal EEG Recorded with Foramen Ovale Electrodes Predicts Side of Primary Epileptogenic Area in Temporal Lobe Epilepsy: A Replication Study

et al. 1998

View full text Add to dashboard Cite

show abstract

“…We compared, for the first time, the D 2 values with those of corresponding surrogate (randomized) signals and found conspicuous differences for the ictal EEGs. Frank et al (1990) and Theiler (1995) have analyzed partly overlapping ictal EEG from the same data set (scalp recording). Theiler concluded that he failed to find clear low values for D2: the results were hardly different from those obtained using randomized signals.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear dynamics of epileptic seizures on basis of intracranial EEG recordings

et al. 1997

View full text Add to dashboard Cite

Pijn, J.P.; Velis, D.N.; van der Heyden, M.; de Goede, J.; van Veelen, C.W.M. General rightsIt is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulationsIf you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: http://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. 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 ietal 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.

show abstract

“…Many research works indicate that chaos is the most common phenomenon in the nature [1]. Being a kind of deterministic signals, chaos draws great attention for its characteristics of internal randomness, meaning that chaotic signals are deterministic but their behavior appears to be random [2].…”

Section: Introductionmentioning

confidence: 99%

Convergence Analysis for Initial Condition Estimation in Coupled Map Lattice Systems

Lin

Shen

et al. 2012

IEEE Trans. Signal Process.

View full text Add to dashboard Cite

In this paper, we focus on studying the problem of initial condition estimation for chaotic signals within the coupled map lattice (CML) systems. To investigate the effectiveness of a CML initial condition estimation method with different maps and coupling coefficients, the convergence and divergence properties of the inverse CML systems are analyzed. Inverse largest Lyapunov exponent (ILLE) is proposed to investigate the strength of convergence and divergence in the inverse CML systems, and it can determine if the CML initial condition estimation method is effective. Computer simulations are included to verify the relationship between the effectiveness of the CML initial condition estimation method and its corresponding ILLE.

show abstract

Chaotic time series analyses of epileptic seizures

Cited by 151 publications

References 23 publications

Neuronal Complexity Loss in Interictal EEG Recorded with Foramen Ovale Electrodes Predicts Side of Primary Epileptogenic Area in Temporal Lobe Epilepsy: A Replication Study

Neuronal Complexity Loss in Interictal EEG Recorded with Foramen Ovale Electrodes Predicts Side of Primary Epileptogenic Area in Temporal Lobe Epilepsy: A Replication Study

Nonlinear dynamics of epileptic seizures on basis of intracranial EEG recordings

Convergence Analysis for Initial Condition Estimation in Coupled Map Lattice Systems

Contact Info

Product

Resources

About