title: Relative brain signature: a population-based feature extraction procedure to identify functional biomarkers in the brain of alcoholics.
abstract: BACKGROUND
  A novel feature extraction technique, Relative-Brain-Signature (RBS), which characterizes subjects' relationship to populations with distinctive neuronal activity, is presented. The proposed method transforms a set of Electroencephalography's (EEG) time series in high dimensional space to a space of fewer dimensions by projecting time series onto orthogonal subspaces.
  
  
  METHODS
  We apply our technique to an EEG data set of 77 abstinent alcoholics and 43 control subjects. To characterize subjects' relationship to the alcoholic and control populations, one RBS vector with respect to the alcoholic and one with respect to the control population is constructed. We used the extracted RBS vectors to identify functional biomarkers over the brain of alcoholics. To achieve this goal, the classification algorithm was used to categorize subjects into alcoholics and controls, which resulted in 78% accuracy.
  
  
  CONCLUSIONS
  Using the results of the classification, regions with distinctive functionality in alcoholic subjects are detected. These affected regions, with respect to their spatial extent, are frontal, anterior frontal, centro-parietal, parieto-occiptal, and occipital lobes. The distribution of these regions over the scalp indicates that the impact of the alcohol in the cerebral cortex of the alcoholics is spatially diffuse. Our finding suggests that these regions engage more of the right hemisphere relative to the left hemisphere of the alcoholics' brain.
authors.affiliation: School of Physics, Astronomy, and Computational Sciences, George Mason University Fairfax, Virginia ; National Institute of Child Health and Human Development, National Institutes of Health Bethesda, Maryland.
authors.forename: Nader
authors.initials: N
authors.lastname: Karamzadeh
authors.affiliation: National Institute of Child Health and Human Development, National Institutes of Health Bethesda, Maryland.
authors.forename: Yasaman
authors.initials: Y
authors.lastname: Ardeshirpour
authors.affiliation: National Institute of Child Health and Human Development, National Institutes of Health Bethesda, Maryland.
authors.forename: Matthew
authors.initials: M
authors.lastname: Kellman
authors.affiliation: National Institute of Child Health and Human Development, National Institutes of Health Bethesda, Maryland.
authors.forename: Fatima
authors.initials: F
authors.lastname: Chowdhry
authors.affiliation: National Institute of Child Health and Human Development, National Institutes of Health Bethesda, Maryland.
authors.forename: Afrouz
authors.initials: A
authors.lastname: Anderson
authors.affiliation: Henri Begleiter Neurodynamics Laboratory, Department of Psychiatry, SUNY Downstate Medical Center Brooklyn, New York.
authors.forename: David
authors.initials: D
authors.lastname: Chorlian
authors.affiliation: School of Physics, Astronomy, and Computational Sciences, George Mason University Fairfax, Virginia.
authors.forename: Edward
authors.initials: E
authors.lastname: Wegman
authors.affiliation: National Institute of Child Health and Human Development, National Institutes of Health Bethesda, Maryland.
authors.forename: Amir
authors.initials: A
authors.lastname: Gandjbakhche
mesh_terms: D000328:Adult; D000437:Alcoholism / Q000145:classification / Q000503:physiopathology*; D000465:Algorithms; D001921:Brain / Q000503:physiopathology*; D001931:Brain Mapping; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D008297:Male; D008875:Middle Aged; D009483:Neuropsychological Tests; D012815:Signal Processing, Computer-Assisted; D014796:Visual Perception / Q000502:physiology; D055815:Young Adult
keywords: Alcoholism; classification; electroencephalography's; functional biomarker