The suppression curve as a quantitative approach for measuring brain maturation in preterm infants

• We apply the suppression curve for automated detection of maturational changes in multichannel preterm EEG.
• The suppression curve reflects the decrease in EEG discontinuity with advancing postmenstrual age in healthy preterm infants.
• Interburst intervals values are calculated automatically and correlated with postmenstrual age.

ObjectivesWe 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).MethodsNinety-two multichannel EEG recordings from 25 preterm infants (born ⩽32 weeks) with normal developmental outcome at 9 months, 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.ResultsOver the course of development, there is a decrease in EEG discontinuity with a strong linear correlation between the mean SC and PMA till 34 weeks. From 30 weeks 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.ConclusionsAutomated 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.SignificanceThe suppression curve facilitates automated assessment of EEG maturation. Clinical applicability is straight forward since values for IBIs according to PMA are generated automatically.