A periodic cerebral rhythm in newborn infants

• Published in: Experimental neurology Vol. 25; no. 4; pp. 575 - 584
• Main Authors: Parmelee, A.H., Akiyama, Y., Stern, E., Harris, M.A.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.01.1969
• Subjects: Age Factors; Analysis of Variance; Brain - growth & development; Brain - physiology; Brain - physiopathology; Down Syndrome - physiopathology; Electroencephalography; Humans; Infant, Newborn; Infant, Premature; Periodicity; Sleep; Sleep Stages
• ISSN: 0014-4886; 1090-2430
• DOI: 10.1016/0014-4886(69)90100-9

In premature and full-term infants the EEG during quiet sleep is characterized by bursts of large amplitude slow waves with superimposed rapid rhythms, alternating with attenuated periods of mixed frequencies. To trace the ontogenetic development of this pattern, the duration of the large amplitude activity (bursts) and attenuated periods (flats) was measured in recordings done at 29, 33, and 40 weeks conceptional age in premature infants and at 40 weeks in full-term and trisomy-21 (Down's syndrome) infants. All age-related changes were statistically significant. Between 29 and 40 weeks the length of the burst increased from 3.3 to 5.9 sec, the flat decreased from 9.3 to 4.4 sec, and the complete burst-flat unit decreased from 12.6 to 10.3 sec. The only difference between the groups occurred in the duration of bursts, which were longer in the prematures recorded at 40 weeks. Full-term and trisomy-21 infants of the same age showed no differences. The age changes were primarily due to numerous very long burst-to-burst intervals in the small premature infants. The modal interval at all ages was 9 sec, which suggests the presence of a central pacemaker that is not altered by maturation during intrauterine development. Consideration of parallels between EEG of immature animals and human infants led to the hypothesis that continuity of EEG activity (increasing burst length) is a function of cortical maturation involving increases in the complexity of interneuronal interaction and feedback circuits.