title: Age trends and sex differences of alpha rhythms including split alpha peaks.
abstract: OBJECTIVE
  To investigate age trends, sex differences, and splitting of alpha peaks of the EEG spectrum in the healthy population.
  
  
  METHODS
  An automated multi-site algorithm was used to parametrize the alpha rhythm in 1498 healthy subjects aged 6-86 years. Alpha peaks identified from multiple electrode sites were organized into clusters of similar frequencies whose sex differences and age trends were investigated.
  
  
  RESULTS
  Significant age-related trends were observed for frequency, position, and amplitude of dominant alpha peaks. Occipital sites had alpha clusters of higher average frequency, higher power, and greater presence across the scalp. Frequency and power differences were found between the sexes.
  
  
  CONCLUSIONS
  Observed increases in alpha frequency in children and decreases in the elderly were consistent with those from earlier studies. A large fraction of participants (≈ 44%) showed multiple distinct alpha rhythm thus investigations which only examine the alpha frequency with the highest peak power can produce misleading results. The strong dependence of alpha frequency on age and anterior-posterior position indicates use of a fixed alpha frequency band is insufficient to capture the full characteristics of the alpha rhythm.
  
  
  CONCLUSIONS
  This study establishes alpha rhythm parameter ranges (including power and frequency) in the healthy population, and quantifies the variation in alpha frequency across the scalp. The automated characterization enables objective evaluations of alpha band activities over large samples. These findings are potentially useful in testing theories of alpha generation, where splitting of the alpha rhythm has been theoretically predicted to occur in individuals with large differences in axon length between anterior and posterior corticothalamic loops.
authors.affiliation: School of Physics, University of Sydney, NSW 2006, Australia. chiang@physics.usyd.edu.au
authors.forename: A K I
authors.initials: AK
authors.lastname: Chiang
authors.forename: C J
authors.initials: CJ
authors.lastname: Rennie
authors.forename: P A
authors.initials: PA
authors.lastname: Robinson
authors.forename: S J
authors.initials: SJ
authors.lastname: van Albada
authors.forename: C C
authors.initials: CC
authors.lastname: Kerr
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000502:physiology*; D000465:Algorithms; D000513:Alpha Rhythm / Q000502:physiology*; D001921:Brain / Q000502:physiology*; D002648:Child; D016000:Cluster Analysis; D004569:Electroencephalography / Q000379:methods; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D016011:Normal Distribution; D012727:Sex Characteristics; D055815:Young Adult