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Journal of Neuroscience
Article . 1998 . Peer-reviewed
License: CC BY NC SA
Data sources: Crossref
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Low Doses of Ethanol Reduce Evidence for Nonlinear Structure in Brain Activity

Authors: Dean Prichard; James Havstad; Cindy L. Ehlers; James Theiler;

Low Doses of Ethanol Reduce Evidence for Nonlinear Structure in Brain Activity

Abstract

Recent theories of the effects of ethanol on the brain have focused on its direct actions on neuronal membrane proteins. However, neuromolecular mechanisms whereby ethanol produces its CNS effects in low doses typically used by social drinkers (e.g., 2–3 drinks, 10–25 mm, 0.05–0.125 gm/dl) remain less well understood. We propose the hypothesis that ethanol may act by introducing a level of randomness or “noise” in brain electrical activity. We investigated the hypothesis by applying a battery of tests originally developed for nonlinear time series analysis and chaos theory to EEG data collected from 32 men who had participated in an ethanol/placebo challenge protocol. Because nonlinearity is a prerequisite for chaos and because we can detect nonlinearity more reliably than chaos, we concentrated on a series of measures that quantitated different aspects of nonlinearity. For each of these measures the method of surrogate data was used to assess the significance of evidence for nonlinear structure. Significant nonlinear structure was found in the EEG as evidenced by the measures of time asymmetry, determinism, and redundancy. In addition, the evidence for nonlinear structure in the placebo condition was found to be significantly greater than that for ethanol. Nonlinear measures, but not spectral measures, were found to correlate with a subject’s overall feeling of intoxication. These findings are consistent with the notion that ethanol may act by introducing a level of randomness in neuronal processing as assessed by EEG nonlinear structure.

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Keywords

Adult, Male, Adolescent, Ethanol, Poisoning, Models, Neurological, Brain, Central Nervous System Depressants, Electroencephalography, Placebos, Nonlinear Dynamics, Multivariate Analysis, Reaction Time, Humans

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