Resting EEG in offspring of male alcoholics: beta frequencies

Int J Psychophysiol. 2004 Feb;51(3):239-51. doi: 10.1016/j.ijpsycho.2003.09.003.


This study examines the differences in beta (12-28 Hz) band power in offspring of male alcoholics from densely affected alcoholic families. We have attempted to investigate if the increase in beta power is a 'state' or 'trait' marker for alcoholism. This study also explores the gender differences in the expression of this potential risk marker. Absolute beta power in three bands-beta 1(12-16 Hz), beta 2 (16-20 Hz), and beta 3 (20-28 Hz)-in the eyes closed EEG of 171 high risk (HR) subjects who were offspring of male alcoholics and 204 low risk (LR) subjects with no family history of alcoholism, were compared for each gender separately using a repeated measures analysis of variance design. Alcoholic and non-alcoholic subjects within the high risk group were compared using a repeated measures design as a follow-up analysis. The present study demonstrated increased beta power in the resting EEG of offspring of male alcoholics. Male HR subjects had higher beta 1 (12-16 Hz) power and female HR subjects had increased power in beta 2 (16-20 Hz) and beta 3 (20-28 Hz) as compared with low risk participants. Female HR subjects also showed significantly increased beta 2 and beta 3 power if they had two or more alcoholic first-degree relatives when compared with HR females having only an affected father. Risk characteristics are expressed differentially in males and females and may be an index of differential vulnerability to alcoholism. The results indicate that increased EEG beta power can be considered as a likely marker of risk for developing alcoholism and may be used as a predictive endophenotype.

Publication types

  • Comparative Study
  • Multicenter Study
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adolescent
  • Adult
  • Alcoholism / genetics
  • Alcoholism / physiopathology*
  • Analysis of Variance
  • Beta Rhythm* / methods
  • Beta Rhythm* / statistics & numerical data
  • Electroencephalography / methods
  • Electroencephalography / statistics & numerical data
  • Female
  • Humans
  • Male
  • Risk Factors
  • Sex Characteristics*