Objective: Seven measures of neonatal EEG-sleep behavior were evaluated using multivariate analyses to ascertain if physiologic differences exist between healthy full- and preterm cohorts.
Methods: A total of 381 24-channel EEG-sleep studies were analyzed, including 125 recordings on 50 healthy fullterm and 256 recordings on 59 asymptomatic preterm infants between 28 and 70.6 weeks post-conceptional age. One EEG study for each subject was randomly assigned (109 studies) within the time window of 38-44 weeks post-conceptional age. A multivariate analytic procedure was applied to the data sets, by which a 'dysmaturity index' was assigned for each infant, based on 7 EEG-sleep measures. This index was defined in terms of the distance from the fullterm group's centroid (i.e. Mahalanobis distance). Receiver-operating characteristic curves (ROCs) were calculated for several different combinations of 7 EEG-sleep measures to describe differences between neonatal cohorts.
Results: The ROC curve corresponding to all 7 EEG-sleep measures covered the substantially largest area among the curves for the sets of variables considered, suggesting that all 7 measures of sleep behavior were required to best discriminate between cohorts.
Conclusions: This methodology exemplifies how EEG-sleep analyses can be applied to the study of functional brain maturation of infants at risk for neurodevelopment problems.
Significance: Changes in EEG-sleep behavior in the preterm infant may represent altered activity-dependent development of neural circuitry, resulting in remodeling of the immature brain as a reflection of adaptation to conditions of prematurity.