Topography of maturational changes in EEG burst spectral power of the preterm infant with a normal follow-up at 2 years of age

ObjectiveTo quantify the electroencephalography (EEG) burst frequency spectrum of preterm infants by automated analysis and to describe the topography of maturational change in spectral parameters.MethodsEighteen preterm infants <32 weeks gestation and normal neurological follow-up at 2 years underwent weekly 4-h EEG recordings (10–20 system). The recordings (n = 77) represent a large variability in postmenstrual age (PMA, 28–36 weeks). We applied an automated burst detection algorithm and performed spectral analysis. The frequency spectrum was divided into δ1 (0.5–1 Hz), δ2 (1–4 Hz), θ (4–8 Hz), α (8–13 Hz) and β (13–30 Hz) bands. Spectral parameters were evaluated as a function of PMA by regression analysis. Results were interpolated and topographically visualised.ResultsThe majority of spectral parameters show significant change with PMA. Highest correlation is found for δ and θ band. Absolute band powers decrease with increasing PMA, while relative α and β powers increase. Maturational change is largest in frontal and temporal region.ConclusionsTopographic distribution of maturational changes in spectral parameters corresponds with studies showing ongoing gyration and postnatal white matter maturation in frontal and temporal lobes.SignificanceComputer analysis of EEG may allow objective and reproducible analysis for long-term prognosis and/or stratification of clinical treatment.

► Automated quantitative analysis of burst frequency spectra from longitudinal electroencephalography (EEG) observations in normal preterm infants. ► Topographic distribution of maturational changes in spectral parameters corresponds with ongoing postnatal gyration and white matter maturation. ► Computer analysis of EEG may allow objective and reproducible analysis for long-term prognosis and/or stratification of clinical treatment.