Literature DB >> 17082199

Assessing seizure dynamics by analysing the correlation structure of multichannel intracranial EEG.

Kaspar Schindler1, Howan Leung, Christian E Elger, Klaus Lehnertz.   

Abstract

Epileptic seizures are commonly characterized as 'hypersynchronous states'. This habit is doubly misleading, because seizures are not necessarily synchronous and are not unchanging 'states' but dynamic processes. Here the temporal evolution of the correlation structure in the course of 100 focal onset seizures of 60 patients recorded by intracranial multichannel EEG was assessed. To this end a multivariate method was applied that at its core consists of computing the eigenvalue spectrum of the zero-lag correlation matrix of a short sliding window. Our results show that there are clearly observable and statistically significant changes of the correlation structure of focal onset seizures. Specifically, these changes indicate that the zero-lag correlation of multi-channel EEG either remains approximately unchanged or-especially in the case of secondary generalization-decreases during the first half of the seizures. Then correlation gradually increases again before the seizures terminate. This development was qualitatively independent of the anatomical location of the seizure onset zone and therefore seems to be a generic property of focal onset seizures. We suggest that the decorrelation of EEG activity is due to the different propagation times of locally synchronous ictal discharges from the seizure onset zone to other brain areas. Furthermore we speculate that the increase of correlation during the second half of the seizures may be causally related to seizure termination.

Entities:  

Mesh:

Year:  2006        PMID: 17082199     DOI: 10.1093/brain/awl304

Source DB:  PubMed          Journal:  Brain        ISSN: 0006-8950            Impact factor:   13.501


  97 in total

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3.  State-dependent precursors of seizures in correlation-based functional networks of electrocorticograms of patients with temporal lobe epilepsy.

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4.  Microscale spatiotemporal dynamics during neocortical propagation of human focal seizures.

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5.  Random fields--union intersection tests for detecting functional connectivity in EEG/MEG imaging.

Authors:  Felix Carbonell; Keith J Worsley; Nelson J Trujillo-Barreto; Roberto C Sotero
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6.  Visualizing dynamical neural assemblies with a fuzzy synchronization clustering analysis.

Authors:  Shu Zhou; Yan Wu; Claudia C Dos Santos
Journal:  Neuroinformatics       Date:  2009-12

Review 7.  Connectivity measures applied to human brain electrophysiological data.

Authors:  R E Greenblatt; M E Pflieger; A E Ossadtchi
Journal:  J Neurosci Methods       Date:  2012-03-16       Impact factor: 2.390

8.  Dynamics of high-frequency synchronization during seizures.

Authors:  Giri P Krishnan; Gregory Filatov; Maxim Bazhenov
Journal:  J Neurophysiol       Date:  2013-02-20       Impact factor: 2.714

9.  'Functional connectivity' is a sensitive predictor of epilepsy diagnosis after the first seizure.

Authors:  Linda Douw; Marjolein de Groot; Edwin van Dellen; Jan J Heimans; Hanneke E Ronner; Cornelis J Stam; Jaap C Reijneveld
Journal:  PLoS One       Date:  2010-05-26       Impact factor: 3.240

10.  Epilepsy is related to theta band brain connectivity and network topology in brain tumor patients.

Authors:  Linda Douw; Edwin van Dellen; Marjolein de Groot; Jan J Heimans; Martin Klein; Cornelis J Stam; Jaap C Reijneveld
Journal:  BMC Neurosci       Date:  2010-08-23       Impact factor: 3.288

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