Related Experiment Video
Updated: Mar 17, 2026
Preterm EEG: A Multimodal Neurophysiological Protocol
Published on: February 18, 2012
The suppression curve as a quantitative approach for measuring brain maturation in preterm infants
A Dereymaeker1, N Koolen2, K Jansen3
1Department of Development and Regeneration, University Hospitals Leuven, Neonatal Intensive Care Unit, University of Leuven (KU Leuven), Leuven, Belgium.
Insights
The suppression curve (SC) method automates the assessment of EEG discontinuity in preterm infants, establishing normative interburst interval (IBI) values. This tool tracks EEG maturation and vigilance state development in newborns.
Area of Science:
- Neonatal Neurology
- Neurophysiology
- Developmental Neuroscience
Background:
- Assessing EEG maturation in preterm infants is crucial for understanding neurodevelopment.
- Existing methods for analyzing EEG discontinuity can be labor-intensive.
- Establishing normative data for EEG patterns at different postmenstrual ages (PMA) is essential.
Purpose of the Study:
- To introduce and validate the suppression curve (SC) as an automated method for quantifying EEG discontinuity in preterm infants.
- To define normative values for interburst intervals (IBIs) based on PMA using the SC.
- To correlate EEG maturation markers with PMA in preterm infants.
Main Methods:
- Utilized 92 multichannel EEG recordings from 25 preterm infants (born ≤32 weeks PMA) with normal 9-month outcomes.
- Applied the Line Length method for initial burst detection.
- Defined and calculated the suppression curve (SC) and interburst intervals (IBIs), correlating them with PMA.
Main Results:
- Demonstrated a decrease in EEG discontinuity with increasing PMA, showing a strong linear correlation between mean SC and PMA until 34 weeks.
- Observed reduced differences between discontinuous and continuous EEG from 30 weeks PMA, indicated by a decreasing standard deviation of the SC.
- Found significant correlations between IBIs and PMA.
Conclusions:
- The suppression curve (SC) enables automated detection of maturational changes in EEG discontinuity.
- SC analysis reflects key developmental changes including more continuous tracing, reduced amplitude variations, and shorter suppression periods, indicative of vigilance state development.
- The SC facilitates straightforward clinical application for automated EEG maturation assessment and generation of PMA-specific IBI values.
Objectives:
We apply the suppression curve (SC) as an automated approach to describe the maturational change in EEG discontinuity in preterm infants. This method allows to define normative values of interburst intervals (IBIs) at different postmenstrual ages (PMA).
Methods:
Ninety-two multichannel EEG recordings from 25 preterm infants (born ⩽32weeks) with normal developmental outcome at 9months, were first analysed using the Line Length method, an established method for burst detection. Subsequently, the SC was defined as the 'level of EEG discontinuity'. The mean and the standard deviation of the SC, as well as the IBIs from each recording were calculated and correlated with PMA.
Results:
Over the course of development, there is a decrease in EEG discontinuity with a strong linear correlation between the mean SC and PMA till 34weeks. From 30weeks PMA, differences between discontinuous and continuous EEG become smaller, which is reflected by the decrease of the standard deviation of the SC. IBIs are found to have a significant correlation with PMA.
Conclusions:
Automated detection of individual maturational changes in EEG discontinuity is possible with the SC. These changes include more continuous tracing, less amplitude differences and shorter suppression periods, reflecting development of the vigilance states.
Significance:
The suppression curve facilitates automated assessment of EEG maturation. Clinical applicability is straight forward since values for IBIs according to PMA are generated automatically.
