Spectral analysis of infant EEG and behavioral outcome at age five

Abstract

Power spectral and discriminant analysis techniques were used to compare EEG records obtained at term and at 3 months past term from 5 groups of varying risk and developmental outcome. The groups were: (1) healthy full-terms; (2) healthy pre-terms with normal outcomes; (3) sick pre-terms with normal outcomes; (4) sick pre-terms with delayed development; (5) sick pre-terms with later neurological problems. The EEG samples recorded at term were identified as belonging to the correct subject group at 52–70% accurracy, 20% being chance for 5 groups. The accuraacy varied with the 4 classes of EEG patterns used. The individual subjects were also classified into their correct groups with few exceptions. Similar success was obtained with EEG samples selected from recording at 3 months past term. The predominant power spectral discriminating features were changes in intra- and inter-hemispheric coherence, and increased power, particularly in the middle and higher frequency range. Thus, computer analyses of EEG samples, using features not readily identified visually, differentiated risk from non-risk infants and also differentiated infants with substantial neonatal medical complications who have good or poor developmental outcomes.