title: Probability distributions of the electroencephalogram envelope of preterm infants.
abstract: OBJECTIVE
  To determine the stationary characteristics of electroencephalogram (EEG) envelopes for prematurely born (preterm) infants and investigate the intrinsic characteristics of early brain development in preterm infants.
  
  
  METHODS
  Twenty neurologically normal sets of EEGs recorded in infants with a post-conceptional age (PCA) range of 26-44 weeks (mean 37.5 ± 5.0 weeks) were analyzed. Hilbert transform was applied to extract the envelope. We determined the suitable probability distribution of the envelope and performed a statistical analysis.
  
  
  RESULTS
  It was found that (i) the probability distributions for preterm EEG envelopes were best fitted by lognormal distributions at 38 weeks PCA or less, and by gamma distributions at 44 weeks PCA; (ii) the scale parameter of the lognormal distribution had positive correlations with PCA as well as a strong negative correlation with the percentage of low-voltage activity; (iii) the shape parameter of the lognormal distribution had significant positive correlations with PCA; (iv) the statistics of mode showed significant linear relationships with PCA, and, therefore, it was considered a useful index in PCA prediction.
  
  
  CONCLUSIONS
  These statistics, including the scale parameter of the lognormal distribution and the skewness and mode derived from a suitable probability distribution, may be good indexes for estimating stationary nature in developing brain activity in preterm infants.
  
  
  CONCLUSIONS
  The stationary characteristics, such as discontinuity, asymmetry, and unimodality, of preterm EEGs are well indicated by the statistics estimated from the probability distribution of the preterm EEG envelopes.
authors.affiliation: Brain Science Institute, Tamagawa University, Tokyo, Japan. Electronic address: ryosaji@tamagawa.ac.jp.
authors.forename: Ryoya
authors.initials: R
authors.lastname: Saji
authors.affiliation: Tokyo Women's Medical University Hospital, Tokyo, Japan.
authors.forename: Kyoko
authors.initials: K
authors.lastname: Hirasawa
authors.affiliation: Tokyo Women's Medical University Hospital, Tokyo, Japan.
authors.forename: Masako
authors.initials: M
authors.lastname: Ito
authors.affiliation: Tokyo Women's Medical University Hospital, Tokyo, Japan.
authors.forename: Satoshi
authors.initials: S
authors.lastname: Kusuda
authors.affiliation: Center for Baby Science, Doshisha University, Kyoto, Japan.
authors.forename: Yukuo
authors.initials: Y
authors.lastname: Konishi
authors.affiliation: Graduate School of Education, The University of Tokyo, Tokyo, Japan.
authors.forename: Gentaro
authors.initials: G
authors.lastname: Taga
mesh_terms: D001921:Brain / Q000254:growth & development* / Q000502:physiology; D004569:Electroencephalography / Q000379:methods*; D005260:Female; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007234:Infant, Premature / Q000254:growth & development* / Q000502:physiology; D008297:Male; D011336:Probability
keywords: Brain maturation; Electroencephalogram (EEG); Envelope; Prematurely born (preterm) infant; Probability distribution; Statistical mathematical analysis