Literature DB >> 26386645

A comparison of the power spectral density of scalp EEG and subjacent electrocorticograms.

Ognen A Petroff1, Dennis D Spencer2, Irina I Goncharova3, Hitten P Zaveri3.   

Abstract

OBJECTIVE: Our study investigated the effects of the intact skull on background EEG rhythms recorded simultaneously by subdural electrocorticography (ECoG) and scalp EEG.
METHODS: We performed a retrospective analysis of twenty patients undergoing intracranial EEG monitoring. EEG and ECoG were recorded simultaneously from the central and occipital scalp and subjacent subdural electrodes removed (median 46 mm, interquartile 27-65) from the craniotomy. The power spectral density (PSD) of artifact-free EEG and ECoG segments and ratio of the scalp EEG to subjacent ECoG PSD was calculated.
RESULTS: Overall both ECoG and scalp EEG power decreased by over three orders of magnitude from delta to gamma frequency band with an empirical inverse power relationship. The ratio of scalp EEG to ECoG PSD decreased across the delta and theta frequency bands, remained the same across the alpha, beta and low gamma bands, but increased at the higher frequency bands.
CONCLUSIONS: EEG PSD mirrored changes in ECoG PSD across the frequency bands. As ECoG power continued to decrease above 42 Hz, extracranial voltage sources contributed to a greater fraction of scalp EEG power. SIGNIFICANCE: Monitoring the gamma frequency band using scalp EEG was limited by low power on ECoG and masking by extracranial voltage sources.
Copyright © 2015 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Epilepsy monitoring; Gamma frequencies; Intracranial electrodes; Power spectral density; Scalp EEG; Subdural ECoG

Mesh:

Year:  2015        PMID: 26386645     DOI: 10.1016/j.clinph.2015.08.004

Source DB:  PubMed          Journal:  Clin Neurophysiol        ISSN: 1388-2457            Impact factor:   3.708


  4 in total

1.  EEG Signal Reconstruction Using a Generative Adversarial Network With Wasserstein Distance and Temporal-Spatial-Frequency Loss.

Authors:  Tian-Jian Luo; Yachao Fan; Lifei Chen; Gongde Guo; Changle Zhou
Journal:  Front Neuroinform       Date:  2020-04-30       Impact factor: 4.081

Review 2.  Decoding Movement From Electrocorticographic Activity: A Review.

Authors:  Ksenia Volkova; Mikhail A Lebedev; Alexander Kaplan; Alexei Ossadtchi
Journal:  Front Neuroinform       Date:  2019-12-03       Impact factor: 4.081

3.  An Adaptive EEG Feature Extraction Method Based on Stacked Denoising Autoencoder for Mental Fatigue Connectivity.

Authors:  Zhongliang Yu; Lili Li; Wenwei Zhang; Hangyuan Lv; Yun Liu; Umair Khalique
Journal:  Neural Plast       Date:  2021-01-20       Impact factor: 3.599

4.  Source Localization of EEG Brainwaves Activities via Mother Wavelets Families for SWT Decomposition.

Authors:  Tarek Frikha; Najmeddine Abdennour; Faten Chaabane; Oussama Ghorbel; Rami Ayedi; Osama R Shahin; Omar Cheikhrouhou
Journal:  J Healthc Eng       Date:  2021-04-28       Impact factor: 2.682

  4 in total

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