All-night EEG power spectral analysis of the cyclic alternating pattern at different ages.
OBJECTIVE
To analyze in detail the frequency content of the different EEG components of the Cyclic Alternating Pattern (CAP) in the whole sleep of pre-school and school age children compared to normal young adults.


METHODS
Fourteen pre-school age and 18 school age children and 16 adults were included in this study. Each participant underwent a polysomnographic overnight recording, after an adaptation night; sleep stages and CAP were scored following standard criteria. Average spectra were obtained for each CAP condition from the signal recorded from C3/A2 or C4/A1, separately in sleep stage 2 and slow-wave sleep (SWS), for each subject.


RESULTS
The analysis of the relative power density in the three groups showed that in sleep stage 2 and in SWS, CAP A1, A2, A3 subtypes had a significantly higher power in all frequency ranges in pre-school children than in adults, while school children differed mainly for the lower frequencies (<7 Hz). For non-CAP, pre-school and school children differed from adults at almost all frequencies analyzed. Generally, A1, A2 and A3 showed clear spectral differences in the three different groups of subjects with pre-school age children showing slightly less evident differences.


CONCLUSIONS
CAP subtypes are characterized by clearly different spectra at different ages and also the same subtype shows a different power spectrum, during sleep stage 2 or SWS. This study shows that pre-school children have a different structure of sleep, especially from the microstructural (CAP) point of view: the differences are evident for all the CAP components and for non-CAP in almost all the frequency bands. This finding might be associated to the age-related delta decline in the 0-3 Hz frequency reported in children of the same age.


CONCLUSIONS
Our data seem to provide information not available before and useful for the understanding of the impact of CAP on the sleep EEG neurophysiological dynamics at different ages. This type of information is crucial for a more adequate interpretation of data provided by a growing number of studies analyzing CAP in groups of pediatric patients.
Bruni
Oliviero
O
Pediatric Sleep Center, Department of Developmental Neurology and Psychiatry, Sapienza University, Rome, Italy. oliviero.bruni@uniroma1.it
Novelli
Luana
L
Finotti
Elena
E
Luchetti
Anna
A
Uggeri
Giordana
G
Aricò
Debora
D
Ferri
Raffaele
R
D000328:Adult; D000375:Aging / Q000502:physiology*; D001931:Brain Mapping; D002648:Child; D002675:Child, Preschool; D004569:Electroencephalography; D005260:Female; D006801:Humans; D008297:Male; D010507:Periodicity; D017286:Polysomnography / Q000379:methods; D012016:Reference Values; D012894:Sleep Stages / Q000502:physiology*; D013057:Spectrum Analysis / Q000379:methods; D014851:Wakefulness / Q000502:physiology; D055815:Young Adult