EEG Frequency Spectrum Characteristics of Sleep States in Full-Term and Preterm Infants¹

Abstract

ManitobaHavlicek, V., Childiaeva, R. and Chernick, V.: EEG frequency spectrum characteristics of sleep states in full-term and preterm infants. Neuropadiatrie 6: 24-40 (1975). Spectral analysis of the EEG using fast Fourier transform in preterm and full-term infants revealed significant maturational changes in all three stages of sleep. In quiet sleep full-term infants differed from preterm babies (< 37 weeks gestation) by significantly higher power in delta and theta frequencies (1.6-7.5 Hz). During indeterminate sleep the slowest frequencies (0.1--1.5 Hz) showed significantly less power, while power of faster frequencies (1.6-7.5 Hz) was significantly greater in full-term infants. REM sleep differed in slowest (0.1-1.5 Hz) and fastest (17.5-25 Hz) frequency bands, showing significantly lower power in the former and significantly higher in the latter in full-term infants. From the diagnostic point of view the most important maturational EEG changes were found by computing the REM sleep-quiet frequency spectrum difference. This showed significantly higher power during quiet sleep over a wide range of frequencies (0.1-12.5 Hz) in fullterm infants, while preterm infants had an almost identical spectrum during these two stages of sleep with a significant intensity drop only in theta2 (5.6-7.5 Hz) during REM sleep. Since these differences can be readily identified in the individual infant it is suggested that the assessment of the EEG may be useful for the early detection of delays in maturation. Brain maturation EEG spectrum sleep full-term infants premature infantsIntroduction infants have been described by DreyfusThe physiology and pathology of Brisac et al -(1956), Dreyfus-Brisac sleep in infants has attracted increasing (1962), Parmelee et al. (1968). These interest recently. Since infants and authors were able to predict the postyoung children spend most of the time conceptional age of the infant on the sleeping the EEG and polygraphic re-basis of visual inspection of the EEG. cording during sleep have become a new These and other studies confirmed the important diagnostic and research tool, dualistic nature of adult sleep discoverThe maturational changes of the EEG edbyAserinskyandKleitman (1953). during sleep in premature and full-term By means of the polygraphic record

Visual evoked potentials are similar in polysomnographically defined quiet and active sleep in healthy newborns

“…However, contrary to our hypothesis, there were no significant differences in latencies and amplitudes of VEP components between QS and AS, as it happens in adults, and as it is expected from the different mechanisms involved in REM and NREM sleep, which, although not yet fully developed, they show clear differences in sleep EEG activity in the first month of life activity (Grigg‐Damberger, 2016; Mizrahi et al, 2011; Anders et al, 1971). We found that AP of the Delta, Theta and Alpha broad bands was significantly higher in QS than in AS, consistent with previous findings (Scher et al, 1997; Havlicek et al, 1975).…”

“…While AS shows an EEG low‐voltage irregular activity and maintains a similar, stable appearance throughout the first month of life (Mizrahi et al, 2011), QS shows persistence of alternating tracing until 43–44 weeks of post‐conception age (Grigg‐Damberger, 2016; Mizrahi et al, 2011), thus, persistence of alternation of flat periods may have contributed to the lower reproducibility found for this sleep state. Another source of lower reproducibility in QS than in AS is the significant larger Delta, Theta and Alpha absolute power in this sleep state found in this study, as well as in previous studies (Scher et al, 1997; Havlicek et al, 1975). There is the possibility that random slow activity in the EEG background during QS could cancel VEP amplitude after averaging resulting in no identifiable components.…”

Automated State Analyses: Proposed Applications to Neonatal Neurointensive Care

“…Previous neonatal sleep studies initially applied automated techniques to assess functional brain maturation using analyses that were based on assumptions of stationarity, without consideration of time-dependent changes (Bes et al, 1988;Connell et al, 1987;Eyre et al, 1988;Giaquinto et al, 1977;Havlicek et al, 1975;Kuks et al, 1988;Lombroso, 1979;Sterman et al, 1977;Willekens et al, 1984). The preferred methodological approach was the fast-Fourier transform analysis, studied initially with fullterm neonates (Eiselt et al, 2001;Field et al, 2002;Ktonas et al, 1995;Lehtonen et al, 1998;Witte et al, 1997), followed by more recent reports in preterm infants (Eisalt et al, 1997;Holthausen et al, 2000;Kuhle et al, 2001;Myers et al, 1997;Sawaguchi et al, 1996;Schramm et al, 2000;Vanhatalo et al, 2002).…”

Ontogeny of EEG sleep from neonatal through infancy periods

“…Previous neonatal sleep studies initially applied automated techniques to assess functional brain maturation, using analyses that were based on assumptions of linearity, without consideration of time-dependent changes (Havlicek et al, 1975;Giaquinto et al, 1977;Sterman et al, 1977;Lombroso, 1979;Willekens et al, 1984;Connell et al, 1987;Bes et al, 1988;Eyre et al, 1988; Kuks et al, 1988). The preferred methodological approach has been fast Fourier transform analyses, studied initially with full-term neonates (Ktonas et al, 1995;Witte et al, 1997;Lehtonen et al, 1998;Eiselt et al, 2001;Field et al, 2002), followed by more recent reports in preterm infants (Sawaguchi et al, 1996;Eiselt et al, 1997;Myers et al, 1997;Holthausen et al, 2000;Schramm et al, 2000;Kuhle et al, 2001;Vanhatalo et al, 2002).…”