UC Davis

Sleep spindles are intermittent bursts of 11-15 Hz EEG waves that occur during non-rapid eye movement sleep. Spindles are believed to help maintain sleep and to play a role in sleep-dependent memory consolidation. Here we applied an automated sleep spindle detection program to our large longitudinal sleep EEG dataset (98 human subjects, 6-18 years old, >2000 uninterrupted nights) to evaluate maturational trends in spindle wave frequency, density, amplitude, and duration. This large dataset enabled us to apply nonlinear as well as linear age models, thereby extending the findings of prior cross-sectional studies that used linear models. We found that spindle wave frequency increased with remarkable linearity across the age range. Central spindle density increased nonlinearly to a peak at age 15.1 years. Central spindle wave amplitude declined in a sigmoidal pattern with the age of fastest decline at 13.5 years. Spindle duration decreased linearly with age. Of the four measures, only spindle amplitude showed a sex difference in dynamics such that the age of most rapid decline in females preceded that in males by 1.4 years. This amplitude pattern, including the sex difference in timing, paralleled the maturational pattern for δ (1-4 Hz) wave power. We interpret these age-related changes in spindle characteristics as indicators of maturation of thalamocortical circuits and changes in sleep depth. These robust age-effects could facilitate the search for cognitive-behavioral correlates of spindle waveforms and might also help guide basic research on EEG mechanisms and postnatal brain maturation.SIGNIFICANCE STATEMENT The brain reorganization of adolescence produces massive changes in sleep EEG. These changes include the morphology and abundance of sleep spindles, an EEG marker of non-rapid eye movement sleep believed to reflect offline memory processes and/or protection of the sleep state. We analyzed >2000 nights of longitudinal sleep EEG from 98 subjects (age 6-18 years old) to investigate maturational changes in spindle amplitude, frequency, density, and duration. The large dataset enabled us to detect nonlinear as well as linear age changes. All measures showed robust age effects that we hypothesize reflect the maturation of thalamocortical circuits and decreasing sleep depth. These findings could guide further research into the cognitive-behavioral correlates of sleep spindles and their underlying brain mechanisms.