Literature DB >> 9919830

Higher-order spectral analysis of burst patterns in EEG.

J Muthuswamy1, D L Sherman, N V Thakor.   

Abstract

Burst suppression patterns in electroencephalograms (EEG's) have been observed in a variety of situations including recovery of a subject from a traumatic brain injury. They are associated with grave prognostic outcomes in neonates. We study power spectral parameters and bispectral parameters of the EEG at baseline, during early recovery from an asphyxic arrest (EEG burst patterns) and during late recovery after EEG evolves into a more continuous activity. The bicoherence indexes, which indicate the degree of phase coupling between two frequency components of a signal, are significantly higher within the delta-theta band of the EEG bursts than in the baseline or late recovery waveforms. The bispectral parameters show a more detectable trend than the power spectral parameters. In the second part of the study, we looked into the possibility of higher (> 2)--order nonlinearities in the EEG bursts using the diagonal slices of the polyspectrum. The diagonal elements of the polyspectrum reveal the presence of self-frequency and self-phase coupling of orders higher than two in majority of the EEG bursts studied. The bicoherence indexes and the diagonal elements of the polyspectrum strongly indicate the presence of nonlinearities of order two and in many cases higher, in the EEG generator during episodes of bursting. This indication of nonlinearity in EEG signals provides a novel quantitative measure of brain's response to injury.

Entities:  

Mesh:

Year:  1999        PMID: 9919830     DOI: 10.1109/10.736762

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  13 in total

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Journal:  J Clin Monit Comput       Date:  2002-02       Impact factor: 2.502

2.  Time-variant investigation of quadratic phase couplings caused by amplitude modulation in electroencephalic burst-suppression patterns.

Authors:  Matthias Arnold; Herbert Witte; Christoph Schelenz
Journal:  J Clin Monit Comput       Date:  2002-02       Impact factor: 2.502

3.  Canonical bicoherence analysis of dynamic EEG data.

Authors:  Huixia He; David J Thomson
Journal:  J Comput Neurosci       Date:  2009-07-23       Impact factor: 1.621

4.  Methodological Considerations on the Use of Different Spectral Decomposition Algorithms to Study Hippocampal Rhythms.

Authors:  Y Zhou; A Sheremet; Y Qin; J P Kennedy; N M DiCola; S N Burke; A P Maurer
Journal:  eNeuro       Date:  2019-08-01

5.  Theta-gamma cascades and running speed.

Authors:  A Sheremet; J P Kennedy; Y Qin; Y Zhou; S D Lovett; S N Burke; A P Maurer
Journal:  J Neurophysiol       Date:  2018-12-05       Impact factor: 2.714

6.  Decoding Adaptive Visuomotor Behavior Mediated by Non-linear Phase Coupling in Macaque Area MT.

Authors:  Mohammad Bagher Khamechian; Mohammad Reza Daliri
Journal:  Front Neurosci       Date:  2020-04-03       Impact factor: 4.677

7.  Objective measure of sleepiness and sleep latency via bispectrum analysis of EEG.

Authors:  Vinayak Swarnkar; Udantha Abeyratne; Craig Hukins
Journal:  Med Biol Eng Comput       Date:  2010-11-25       Impact factor: 2.602

8.  Spectrum Degradation of Hippocampal LFP During Euthanasia.

Authors:  Yuchen Zhou; Alex Sheremet; Jack P Kennedy; Nicholas M DiCola; Carolina B Maciel; Sara N Burke; Andrew P Maurer
Journal:  Front Syst Neurosci       Date:  2021-04-23

9.  Cardiac health diagnosis using higher order spectra and support vector machine.

Authors:  Chua Kuang Chua; Vinod Chandran; Rajendra U Acharya; Lim Choo Min
Journal:  Open Med Inform J       Date:  2009-02-26

10.  Empirical mode decomposition and k-nearest embedding vectors for timely analyses of antibiotic resistance trends.

Authors:  Douglas Teodoro; Christian Lovis
Journal:  PLoS One       Date:  2013-04-25       Impact factor: 3.240

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