» Articles » PMID: 9593809

Nonlinear Interdependencies of EEG Signals in Human Intracranially Recorded Temporal Lobe Seizures

Overview
Journal Brain Res
Specialty Neurology
Date 1998 Jun 24
PMID 9593809
Citations 21
Authors
Affiliations
Soon will be listed here.
Abstract

The degree of interdependence between intracranial EEG channels was investigated in four epileptic patients with complex partial seizures of mesial temporal lobe origin. With a new method to characterize nonlinear dynamical interdependence-the mutual nonlinear prediction-we demonstrated here a possibility to quantify, during epileptic seizures, the relationships between EEG signals of electrode contacts in the epileptogenic area. During the interictal period, the degree of nonlinear interdependences were very low or absent. In contrast, it was found that transient patterns of nonlinear interdependences emerge at the initial spread of the seizure, during essential parts of its development, and at seizure end, but the maintenance of these interactions are not observed throughout the seizure activity. These results suggest that the nonlinear associations plays an important role in epileptogenesis, and that the process of neuronal entrainment during seizure onset involves a transient interaction between a distributed network of neuronal aggregates, but the maintenance of this interaction is not required for sustained seizure activity. Furthermore, this technique can describe properly the spatio-temporal organisation of the seizures of medio-temporal lobe origin and could become a very useful tool to aid the localization of the epileptogenic regions at the origin of epileptic seizures and their pathways of propagation.

Citing Articles

Universal Cointegration and Its Applications.

Tu C, Fan Y, Fan J iScience. 2019; 19:986-995.

PMID: 31522121 PMC: 6744394. DOI: 10.1016/j.isci.2019.08.048.


What graph theory actually tells us about resting state interictal MEG epileptic activity.

Niso G, Carrasco S, Gudin M, Maestu F, Del-Pozo F, Pereda E Neuroimage Clin. 2015; 8:503-15.

PMID: 26106575 PMC: 4475779. DOI: 10.1016/j.nicl.2015.05.008.


Traumatic brain injury detection using electrophysiological methods.

Rapp P, Keyser D, Albano A, Hernandez R, Gibson D, Zambon R Front Hum Neurosci. 2015; 9:11.

PMID: 25698950 PMC: 4316720. DOI: 10.3389/fnhum.2015.00011.


Assessing directionality and strength of coupling through symbolic analysis: an application to epilepsy patients.

Lehnertz K, Dickten H Philos Trans A Math Phys Eng Sci. 2014; 373(2034).

PMID: 25548267 PMC: 4281866. DOI: 10.1098/rsta.2014.0094.


Identification of the Epileptogenic Zone from Stereo-EEG Signals: A Connectivity-Graph Theory Approach.

Panzica F, Varotto G, Rotondi F, Spreafico R, Franceschetti S Front Neurol. 2013; 4:175.

PMID: 24223569 PMC: 3818576. DOI: 10.3389/fneur.2013.00175.