OBJECTIVE: To quantify the electroencephalography (EEG) burst frequency spectrum of preterm infants by automated analysis and to describe the topography of maturational change in spectral parameters.
METHODS: Eighteen preterm infants <32weeks gestation and normal neurological follow-up at 2years underwent weekly 4-h EEG recordings (10-20 system). The recordings (n=77) represent a large variability in postmenstrual age (PMA, 28-36weeks). We applied an automated burst detection algorithm and performed spectral analysis. The frequency spectrum was divided into δ1 (0.5-1Hz), δ2 (1-4Hz), θ (4-8Hz), α (8-13Hz) and β (13-30Hz) bands. Spectral parameters were evaluated as a function of PMA by regression analysis. Results were interpolated and topographically visualised.
RESULTS: The 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.
CONCLUSIONS: Topographic distribution of maturational changes in spectral parameters corresponds with studies showing ongoing gyration and postnatal white matter maturation in frontal and temporal lobes.
SIGNIFICANCE: Computer analysis of EEG may allow objective and reproducible analysis for long-term prognosis and/or stratification of clinical treatment.
- Brain Mapping
- Child, Preschool
- Follow-Up Studies
- Frontal Lobe
- Infant, Newborn
- Infant, Premature
- Longitudinal Studies
- Spectrum Analysis
- Temporal Lobe