Distribution of sleep and wakefulness EEG patterns in 24-h recordings of preterm and full-term newborns

E Biagioni1, A Boldrini, F Giganti

  • 1Department of Developmental Neuroscience, Stella Maris Scientific Institute, University of Pisa, 56018 Calambrone, Pisa, Italy.

Insights

This study analyzed 24-hour electroencephalogram (EEG) patterns in preterm and near-term neonates. Key EEG patterns shift with postmenstrual age and show distinct diurnal variations, impacting sleep organization.

Area of Science:

  • Neonatal Neurology
  • Sleep Medicine
  • Developmental Neuroscience

Background:

  • Neonatal electroencephalogram (EEG) patterns are crucial indicators of brain development and function.
  • Understanding the typical organization and evolution of these patterns is essential for identifying neurological abnormalities.
  • Previous research often relied on shorter EEG recordings, limiting insights into 24-hour sleep-wake cycles and developmental changes.

Purpose of the Study:

  • To evaluate the organization of EEG patterns over 24-hour recordings in preterm and near-term neonates.
  • To analyze the distribution of different EEG patterns based on postmenstrual age (PMA).
  • To investigate variations in sleep-related EEG pattern organization during daytime and nighttime hours.

Main Methods:

  • Utilized 24-hour continuous EEG recordings from preterm and near-term neonates.
  • Classified and quantified various EEG patterns throughout the recording periods.
  • Correlated EEG pattern distribution and sleep organization with postmenstrual age and time of day (day vs. night).

Main Results:

  • Confirmed the age-dependent appearance of neonatal EEG patterns previously described in shorter studies.
  • Observed a decrease in medium-voltage continuous EEG (pattern "3") as neonates approached term, coinciding with the emergence of low-voltage continuous patterns (patterns "1" and "2") associated with active sleep and wakefulness.
  • Found that discontinuous EEG (pattern "7"), linked to quiet sleep, decreased with age but was significantly more prevalent during daytime hours compared to nighttime.

Conclusions:

  • Neonatal EEG pattern organization exhibits significant changes with increasing postmenstrual age, reflecting neurodevelopmental maturation.
  • Diurnal variations in EEG patterns are evident, with specific patterns showing differential distribution between day and night, impacting sleep state organization.
  • Continuous 24-hour EEG monitoring provides a comprehensive understanding of neonatal brain activity and sleep architecture crucial for clinical assessment.