Literature DB >> 22410338

High-frequency neuronal network modulations encoded in scalp EEG precede the onset of focal seizures.

Catherine Stamoulis1, Lawrence J Gruber, Donald L Schomer, Bernard S Chang.   

Abstract

Modulations of neuronal network interactions by seizure precursors are only partially understood and difficult to measure, in part due to inherent intra- and inter-patient seizure heterogeneities and EEG variability. This study investigated preictal neuromodulations associated with seizures originating in the temporal and/or frontal lobes, using information theoretic parameters estimated from awake scalp EEGs in two frequency ranges, ≤100 Hz and >100 Hz, respectively. Seizure-related activity at high frequencies has not been extensively estimated in awake scalp EEGs. Based on the statistical similarity of preictal and ictal information parameters, preictal network interactions appeared to be specifically modulated at frequencies >100 Hz, but not at lower frequencies. The dynamics of these parameters varied distinctly according to the origin of seizure onset (temporal versus frontal). Although preliminary, and based on a small patient sample for which the potential heterogeneity of multiple anticonvulsive medications was difficult to control, these results suggest that preictal modulations may be estimated from high-frequency scalp EEGs using directional information measures with high specificity to ictal events, and may thus be promising for improving seizure prediction.
Copyright © 2012 Elsevier Inc. All rights reserved.

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Year:  2012        PMID: 22410338      PMCID: PMC3320023          DOI: 10.1016/j.yebeh.2012.01.001

Source DB:  PubMed          Journal:  Epilepsy Behav        ISSN: 1525-5050            Impact factor:   2.937


  51 in total

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5.  Kulback-Leibler and renormalized entropies: applications to electroencephalograms of epilepsy patients.

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Review 6.  Characterizing neurodynamic changes before seizures.

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Review 7.  Seizure prediction: the long and winding road.

Authors:  Florian Mormann; Ralph G Andrzejak; Christian E Elger; Klaus Lehnertz
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9.  Peri-ictal correlation dynamics of high-frequency (80-200 Hz) intracranial EEG.

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10.  Detection of seizure precursors from depth-EEG using a sign periodogram transform.

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  8 in total

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2.  Modeling noninvasive neurostimulation in epilepsy as stochastic interference in brain networks.

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Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2012-06-04       Impact factor: 3.802

3.  Information theoretic measures of network coordination in high-frequency scalp EEG reveal dynamic patterns associated with seizure termination.

Authors:  Catherine Stamoulis; Donald L Schomer; Bernard S Chang
Journal:  Epilepsy Res       Date:  2013-04-19       Impact factor: 3.045

4.  Space-time adaptive processing for improved estimation of preictal seizure activity.

Authors:  Catherine Stamoulis; Bernard S Chang
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2012

5.  Signal subspace integration for improved seizure localization.

Authors:  Catherine Stamoulis; Iván Sánchez Fernández; Bernard S Chang; Tobias Loddenkemper
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Review 6.  The role of high-frequency oscillations in epilepsy surgery planning.

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Review 7.  High-Frequency Oscillations in the Scalp Electroencephalogram: Mission Impossible without Computational Intelligence.

Authors:  Peter Höller; Eugen Trinka; Yvonne Höller
Journal:  Comput Intell Neurosci       Date:  2018-08-07

Review 8.  The role of high-frequency oscillations in epilepsy surgery planning.

Authors:  David Gloss; Sarah J Nolan; Richard Staba
Journal:  Cochrane Database Syst Rev       Date:  2014-01-15
  8 in total

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