Sex and Pubertal Differences in the Maturational Trajectories of Sleep Spindles in the Transition from Childhood to Adolescence: A Population-Based Study
Bibliographic record
Abstract
Abstract Sleep spindles, bursts of electroencephalogram (EEG) activity in the σ-frequency (11–16 Hz) range, may be biomarkers of cortical development. Studies capturing the transition to adolescence are needed to delineate age-related, sex-related, and pubertal-related changes in sleep spindles at the population-level. We analyzed the sleep EEG of 572 subjects 6–21 years (48% female) and 332 subjects 5–12 years (46% female) followed-up at 12–22 years. From 6 to 21 years, spindle density (pquadratic = 0.019) and fast (12–16 Hz) spindle percent (pquadratic = 0.016) showed inverted U-shaped trajectories, with plateaus after 15 and 19 years, respectively. Spindle frequency increased (plinear < 0.001), while spindle power decreased (plinear < 0.001) from 6 to 21 years. The trajectories of spindle density, frequency, and fast spindle percent diverged between females and males, in whom density plateaued by 14 years, fast spindle percent by 16 years, and frequency by 18 years, while fast spindle percent and spindle frequency continued to increase until 21 years in females. Males experienced a longitudinal increase in spindle density 31% greater than females by 12–14 years (p = 0.006). Females experienced an increase in spindle frequency and fast spindle percent 2% and 41% greater, respectively, than males by 18–22 years (bothp = 0.004), while males experienced a 14% greater decline in spindle power by 18–22 years (p = 0.018). Less mature adolescents (86% male) experienced a longitudinal increase in spindle density 36% greater than mature adolescents by 12–14 years (p = 0.002). Overall, males experience greater maturational changes in spindle density in the transition to adolescence, driven by later pubertal development, and sex differences become prominent in early adulthood when females have greater spindle power, frequency, and fast spindle percent.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".