Literature DB >> 8761049

A comparison of EEG signal dynamics in waking, after anesthesia induction and during electroconvulsive therapy seizures.

A D Krystal1, H S Greenside, R D Weiner, D Gassert.   

Abstract

Evidence suggests that quantitative dynamical measures of electroencephalogram (EEG) signals are more appropriate for characterizing the differences between states in an individual rather than as absolute indices. One such measure, the largest Lyapunov exponent (lambda 1), appears to have potential for identifying seizure activity and for being of clinical utility for characterizing electroconvulsive therapy (ECT) seizures. As a result, we compared lambda 1 for the EEG recorded in 8 depressed subjects in 3 states: (1) during right unilateral ECT seizures, (2) during the pre-ECT waking state, and (3) following anesthesia administration but prior to ECT. Spectral amplitude and autocorrelation were also calculated in these states, allowing a comparison of these measures with lambda 1. We hypothesized that lambda 1 would be lowest during the ECT seizures, suggestive of greater EEG signal predictability over time during the seizures. We found that during the seizures lambda 1 was smaller, while spectral amplitude was larger. Significant inter-state differences were not found for the left temporal and occipital regions suggesting that these measures might serve as markers of the degree of seizure involvement of specific brain regions. Spectral amplitude and lambda 1 were uncorrelated and varied independently in some cases. The autocorrelation time was shortest in the waking EEG, and longest for the post-anesthesia EEG, and did not account for the differences seen in lambda 1. In contrast, the persistence of oscillations in the autocorrelation functions was greater for the ictal EEG than the other two states and may relate to lambda 1.

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Year:  1996        PMID: 8761049     DOI: 10.1016/0013-4694(96)95090-7

Source DB:  PubMed          Journal:  Electroencephalogr Clin Neurophysiol        ISSN: 0013-4694


  1 in total

1.  Bifurcation analysis of "synchronization fluctuation": a diagnostic measure of brain epileptic states.

Authors:  Fatemeh Bakouie; Keivan Moradi; Shahriar Gharibzadeh; Farzad Towhidkhah
Journal:  Front Comput Neurosci       Date:  2014-02-06       Impact factor: 2.380

  1 in total

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