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. 2019 Jun;130(6):893-902.
doi: 10.1016/j.clinph.2019.02.019. Epub 2019 Mar 18.

Sleep spindle characteristics in adolescents

Aimée Goldstone  1 , Adrian R Willoughby  2 , Massimiliano de Zambotti  2 , Duncan B Clark  3 , Edith V Sullivan  4 , Brant P Hasler  3 , Peter L Franzen  3 , Devin E Prouty  2 , Ian M Colrain  5 , Fiona C Baker  6
Affiliations

Sleep spindle characteristics in adolescents

Aimée Goldstone et al. Clin Neurophysiol. 2019 Jun.

Abstract

Objective: Sleep changes substantially during adolescence; however, our understanding of age-related differences in specific electroencephalographic waveforms during this developmental period is limited.

Method: Sigma power, spindle characteristics and cognitive data were calculated for fast (∼13 Hz) central and slow (∼11 Hz) frontal sleep spindles for a large cross-sectional sample of adolescents (N = 134, aged 12-21 years, from the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) study).

Results: Older age (and advanced pubertal development) was associated with lower absolute sigma power and greater fast spindle density, with spindles having a shorter duration and smaller amplitude and occurring at a faster average frequency than at a younger age. Spindle characteristics were not directly associated with cognition. An indirect relationship (age * density) provided some evidence for an association between better episodic memory performance and greater spindle density only for younger adolescents.

Conclusion: Spindle characteristics in adolescents differed according to age, possibly reflecting underlying differences in thalamo-cortical connectivity, and may play a role in episodic memory early in adolescence.

Significance: Sleep spindles may serve as a marker of adolescent development, likely reflecting brain maturational status. Investigating specific spindle characteristics, in addition to sigma power, is necessary to fully characterize spindles during adolescence.

Keywords: Adolescence; Cognition; Development; EEG; Memory; Sigma.

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Conflict of interest statement

Conflict of interest

None of the authors have potential conflicts of interest to be disclosed.

Figures

Figure 1:
Figure 1:
Significant relationships between age and fast spindle 1) frequency 2) amplitude, 3) duration and 4) central sigma power. To show relationships between spindle characteristics and age after controlling for additional factors, residuals are plotted after adjusting for the effect of site, sex and race. R2 = the R2 of the full model, which included age and demographic variables, β= the β of the main effect of age within each model.
Figure 2:
Figure 2:
Significant relationships between age and slow spindle 1) amplitude, 2) duration and 4) frontal sigma power. To show relationships between spindle characteristics and age after controlling for additional factors, residuals are plotted after adjusting for the effect of site, sex and race. R2 = the R2 of the full model, which included age and demographic variables, β= the β of the main effect of age within each model.
Figure 3:
Figure 3:
A subset of participants (those aged 12-14 and older than 17 years) are plotted for illustrative purposes, to depict the significant age*density interaction that predicted episodic memory performance as assessed by delayed recall on the short visual object learning task (SVOLT-D). Spindle density predicted memory performance for younger participants (seen for ages 12-14 in the plot) but not for participants aged over 17 years.
See this image and copyright information in PMC

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