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Updated: Jul 13, 2025

Transcutaneous Microcirculatory Imaging in Preterm Neonates
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Microstate Analysis Reflects Maturation of the Preterm Brain.

Tim Hermans1, Mohammad Khazaei2, Khadijeh Raeisi2

  • 1Department of Electrical Engineering (ESAT), STADIUS Center for Dynamical Systems, Signal Processing and Data Analytics, KU Leuven, Leuven, Belgium.

Brain Topography
|October 12, 2023
PubMed
Summary

Microstate (MS) analysis of electroencephalography (EEG) reveals significant changes in preterm neonate brain dynamics during maturation. These findings suggest MS analysis is a valuable tool for monitoring brain development in preterm infants.

Keywords:
Biomedical signal processingBrain maturationMicrostate analysisNeonatal EEGQuantitative EEG

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Area of Science:

  • Neuroscience
  • Developmental Biology
  • Biomedical Engineering

Background:

  • Preterm neonates face risks of neurodevelopmental impairments due to disrupted brain development.
  • Electroencephalography (EEG) offers insights into neonatal brain maturation.
  • Microstate (MS) analysis is an emerging technique for evaluating global brain dynamics.

Purpose of the Study:

  • To explore the utility of MS analysis in assessing global brain dynamics during maturation in preterm neonates with normal neurodevelopmental outcomes.
  • To establish reference data for MS metrics in relation to postmenstrual age.

Main Methods:

  • Analysis of 135 EEGs from 48 preterm neonates across four age groups (26.4 to 47.7 weeks).
  • Extraction of 5-minute epochs during quiet sleep (QS) and non-quiet sleep (NQS).
  • Comparison of group-level and individual MS maps and metrics, including topography, transitions, duration, occurrence, and Hurst exponent.

Main Results:

  • Four group-level MS maps explained ~70% of global variance, exhibiting non-random syntax.
  • Significant changes in MS topographies and transitions were observed around 37 weeks postmenstrual age.
  • MS duration decreased and occurrence increased with age, correlating strongly with postmenstrual age (up to r=0.74).
  • Hurst exponent of individual MS sequences decreased with age.

Conclusions:

  • Observed changes in MS metrics likely reflect neural network formation during preterm brain development.
  • MS analysis shows promise as a tool for monitoring preterm neonatal brain maturation.
  • This study provides a valuable reference for analyzing EEGs in neonates with abnormal neurodevelopmental outcomes.