Literature DB >> 25270401

An interictal EEG spectral metric for temporal lobe epilepsy lateralization.

Giridhar P Kalamangalam1, Lukas Cara2, Nitin Tandon3, Jeremy D Slater2.   

Abstract

OBJECTIVE: Visually-obvious abnormalities in the resting baseline EEG--slowing, spiking and high-frequency oscillations (HFOs)--are cardinal, though incompletely understood, features of the seizure onset zone in focal epilepsy. We hypothesized that evidence of cortical network dysfunction in temporal lobe epilepsy (TLE) would persist in the absence of visually-classifiable abnormalities in the baseline EEG recorded within the conventional passband, and that metrics of such dysfunction could serve as a lateralizing diagnostic in TLE.
METHODS: Epochs of resting EEG without significant abnormalities in light sleep over several days were compared between a group of 10 patients with proven TLE and 10 subjects without epilepsy. A novel laterality metric computed from the line length of normalized power spectra from the temporal channels was compared between the two groups.
RESULTS: Significant group differences in spectral line length laterality metric were found between the TLE and control group. At the individual level, seven of 10 TLE patients had highly significant laterality metrics, all concordant with the known laterality of their disease. SIGNIFICANCE: Detailed spectral analysis offers novel insight into TLE network behavior, independent of the orthodox abnormalities of EEG slowing, spikes or HFOs. The results may be deployed in a practical diagnostic manner, offer insight into the EEG manifestations of disordered cellular network architecture in TLE, and maybe understood through simple analogy with the theory of linear time-invariant physical systems.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Epilepsy surgery; Partial epilepsy; Synchronization

Mesh:

Year:  2014        PMID: 25270401      PMCID: PMC4252661          DOI: 10.1016/j.eplepsyres.2014.09.002

Source DB:  PubMed          Journal:  Epilepsy Res        ISSN: 0920-1211            Impact factor:   3.045


  15 in total

1.  Interictal scalp fast oscillations as a marker of the seizure onset zone.

Authors:  Daniel M Goldenholz; Masud Seyal; Lisa M Bateman; Jean Gotman; Luciana Andrade-Valenca; Rina Zelmann; Francois Dubeau
Journal:  Neurology       Date:  2012-01-17       Impact factor: 9.910

2.  Noninvasive correlates of subdural grid electrographic outcome.

Authors:  Giridhar P Kalamangalam; Harold H Morris; Jayanthi Mani; Deepak K Lachhwani; Shyam Visweswaran; William M Bingaman
Journal:  J Clin Neurophysiol       Date:  2009-10       Impact factor: 2.177

3.  Interictal infraslow activity in patients with epilepsy.

Authors:  E Rodin; T Constantino; J Bigelow
Journal:  Clin Neurophysiol       Date:  2013-11-13       Impact factor: 3.708

4.  Automatic epileptic seizure detection in EEGs based on line length feature and artificial neural networks.

Authors:  Ling Guo; Daniel Rivero; Julián Dorado; Juan R Rabuñal; Alejandro Pazos
Journal:  J Neurosci Methods       Date:  2010-06-02       Impact factor: 2.390

5.  Abnormal interictal gamma activity may manifest a seizure onset zone in temporal lobe epilepsy.

Authors:  Andrei V Medvedev; Anthony M Murro; Kimford J Meador
Journal:  Int J Neural Syst       Date:  2011-04       Impact factor: 5.866

Review 6.  Prognostic significance of interictal epileptiform discharges in newly diagnosed seizure disorders.

Authors:  Elaine C Wirrell
Journal:  J Clin Neurophysiol       Date:  2010-08       Impact factor: 2.177

7.  Dynamic mechanisms underlying afterdischarge: a human subdural recording study.

Authors:  Giridhar P Kalamangalam; Nitin Tandon; Jeremy D Slater
Journal:  Clin Neurophysiol       Date:  2013-12-04       Impact factor: 3.708

8.  Absolute spike frequency predicts surgical outcome in TLE with unilateral hippocampal atrophy.

Authors:  R Krendl; S Lurger; C Baumgartner
Journal:  Neurology       Date:  2008-07-09       Impact factor: 9.910

9.  Electric source imaging of interictal activity accurately localises the seizure onset zone.

Authors:  Pierre Mégevand; Laurent Spinelli; Mélanie Genetti; Verena Brodbeck; Shahan Momjian; Karl Schaller; Christoph M Michel; Serge Vulliemoz; Margitta Seeck
Journal:  J Neurol Neurosurg Psychiatry       Date:  2013-07-30       Impact factor: 10.154

10.  Ripple classification helps to localize the seizure-onset zone in neocortical epilepsy.

Authors:  Shuang Wang; Irene Z Wang; Juan C Bulacio; John C Mosher; Jorge Gonzalez-Martinez; Andreas V Alexopoulos; Imad M Najm; Norman K So
Journal:  Epilepsia       Date:  2012-10-25       Impact factor: 5.864

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  1 in total

1.  A unified statistical model for the human electrocorticogram.

Authors:  Giridhar P Kalamangalam; Mircea I Chelaru; Jeremy D Slater
Journal:  Clin Neurophysiol       Date:  2016-07-05       Impact factor: 3.708

  1 in total

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