Skip to main content
Journal cover image

Comparisons of EEG sleep state-specific spectral values between healthy full-term and preterm infants at comparable postconceptional ages.

Publication ,  Journal Article
Scher, MS; Sun, M; Steppe, DA; Banks, DL; Guthrie, RD; Sclabassi, RJ
Published in: Sleep
February 1994

Differences in state-specific electroencephalographic (EEG) spectral values are described between groups of preterm and full-term neonates at comparable postconceptional term ages. Eighteen healthy preterm neonates of < or = 32 weeks gestation were selected from an inborn population of a neonatal intensive care unit. Twenty-four-channel recordings were obtained at a full-term age and compared with studies of 22 healthy full-term neonates. The initial three hours of each 12-hour study were recorded on paper from which EEG sleep state scores per minute were visually assessed. Six mean spectral values (i.e. total EEG, electromyogram, delta, theta, alpha and beta energies) were calculated from each corresponding minute of digitized data, which was also assigned one of six EEG sleep states. Each neonatal group displayed statistically significant differences among sleep-state segments for all spectral values. The alpha- and beta-range spectral values of the preterm group, compared to the full-term control group, were lower during all sleep state segments. Spectral values for the theta band were lower during both quiet sleep segments only, whereas spectral values for delta were lower during all sleep stages, except tracé-alternant quiet sleep. Significant differences in EEG spectral values were noted among states of sleep for both preterm and full-term infants of similar postconceptional term ages. These data also suggest differences in central nervous system maturation between neonatal populations. These findings strengthen our previously stated contention that there is a functional alteration in brain development of the preterm infant as reflected in sleep organization that results from a prolonged extrauterine experience and/or prematurity.

Duke Scholars

Published In

Sleep

DOI

EISSN

1550-9109

ISSN

0161-8105

Publication Date

February 1994

Volume

17

Issue

1

Start / End Page

47 / 51

Related Subject Headings

  • Sleep
  • Neurology & Neurosurgery
  • Male
  • Infant, Premature
  • Infant, Newborn
  • Humans
  • Female
  • Electroencephalography
  • Brain
  • Analysis of Variance
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Scher, M. S., Sun, M., Steppe, D. A., Banks, D. L., Guthrie, R. D., & Sclabassi, R. J. (1994). Comparisons of EEG sleep state-specific spectral values between healthy full-term and preterm infants at comparable postconceptional ages. Sleep, 17(1), 47–51. https://doi.org/10.1093/sleep/17.1.47
Scher, M. S., M. Sun, D. A. Steppe, D. L. Banks, R. D. Guthrie, and R. J. Sclabassi. “Comparisons of EEG sleep state-specific spectral values between healthy full-term and preterm infants at comparable postconceptional ages.Sleep 17, no. 1 (February 1994): 47–51. https://doi.org/10.1093/sleep/17.1.47.
Scher MS, Sun M, Steppe DA, Banks DL, Guthrie RD, Sclabassi RJ. Comparisons of EEG sleep state-specific spectral values between healthy full-term and preterm infants at comparable postconceptional ages. Sleep. 1994 Feb;17(1):47–51.
Scher, M. S., et al. “Comparisons of EEG sleep state-specific spectral values between healthy full-term and preterm infants at comparable postconceptional ages.Sleep, vol. 17, no. 1, Feb. 1994, pp. 47–51. Epmc, doi:10.1093/sleep/17.1.47.
Scher MS, Sun M, Steppe DA, Banks DL, Guthrie RD, Sclabassi RJ. Comparisons of EEG sleep state-specific spectral values between healthy full-term and preterm infants at comparable postconceptional ages. Sleep. 1994 Feb;17(1):47–51.
Journal cover image

Published In

Sleep

DOI

EISSN

1550-9109

ISSN

0161-8105

Publication Date

February 1994

Volume

17

Issue

1

Start / End Page

47 / 51

Related Subject Headings

  • Sleep
  • Neurology & Neurosurgery
  • Male
  • Infant, Premature
  • Infant, Newborn
  • Humans
  • Female
  • Electroencephalography
  • Brain
  • Analysis of Variance