[Spectral-topographic features of EEG in patients with varying rates of alcohol dependence progression].

Authors

S A Galkin, N A Bokhan

Published in

Zhurnal nevrologii i psikhiatrii imeni S.S. Korsakova. Volume 126. Issue 9. Pages 146-152.

Abstract

To compare the spectral-topographic characteristics of the background electroencephalogram (EEG) in patients with alcohol dependence, differing in disease progression rate, as part of a pilot study.
A total of 40 male patients with a confirmed diagnosis of alcohol dependence (F10.2 according to ICD-10) were examined. Utilizing a retrospective evaluation of the development of alcohol withdrawal syndrome (AWS), participants were classified into two distinct groups: those exhibiting rapid progression (≤3 years, n=23) and those with slow progression (≥12 years, n=17). Background EEG recordings were obtained using a 16-channel system (10-20 configuration), followed by spectral analysis of absolute power in the theta, alpha-1, alpha-2, beta-1, and beta-2 frequency bands.
The analysis revealed that patients with rapid progression demonstrated a statistically significant reduction in the spectral power of the alpha-1 rhythm across all cortical regions (p<0.002 after correction), with the most pronounced effects observed in frontal and central leads. There were also reductions noted in the power of alpha-2, theta (except the parietal region), and beta-1 (limited to the frontal area) frequency bands. Notably, 74% of patients with rapid progression exhibited a low-amplitude («flattened») EEG pattern, whereas 71% in the slow progression group maintained a normal alpha rhythm.
The results indicate the presence of a distinct neurophysiological endophenotype associated with the rapid progression of alcohol dependence. Key characteristics of this endophenotype include a overall decrease in the power of the alpha-1 rhythm, particularly in the front-central leads; a decline in theta power (excluding the parietal region); a frontal-specific reduction in beta-1 power; and a significant prevalence of low-amplitude EEG patterns.

PMID:
42899929
Bibliographic data and abstract were imported from PubMed on 21 Oct 2026.

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