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Record W4410503255 · doi:10.1093/sleep/zsaf090.0294

0294 Childhood Sleep Spindle Density and Frequency Are Associated with Adolescent Working Memory and Nonverbal Ability

2025· article· en· W4410503255 on OpenAlexaff
Melany Morales-Ghinaglia, Fan He, Susan L. Calhoun, Jidong Fang, Alexandros N. Vgontzas, Duanping Liao, Edward O. Bixler, Magdy Younes, Anna Ricci, Julio Fernández‐Mendoza

Bibliographic record

VenueSLEEP · 2025
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsNonverbal communicationPsychologyWorking memorySleep (system call)AudiologyDevelopmental psychologyCognitive psychologyMedicineCognitionNeuroscienceComputer science

Abstract

fetched live from OpenAlex

Abstract Introduction Sleep spindles are an underlying mechanism of cognition. Prior research was primarily cross-sectional or conducted in experimental studies of highly selective samples of youth. We aimed to clarify the longitudinal relationship between sleep spindles and cognition in the transition from childhood to adolescence in both typically developing (TD) and unmedicated youth diagnosed with psychiatric/learning disorders. Methods We leveraged 836 sleep EEGs from 9-hour in-lab polysomnography recordings of the Penn State Child Cohort, a longitudinal population-based sample (N=418). We analyzed 261 TD youth who were 5-12y (median 8y) at baseline and 12-23y at follow-up (median 16y) as well as 88 unmedicated youth with psychiatric/learning disorders, including attention deficit/hyperactivity disorder comorbid with learning disorders (ADHD/LD), of the same baseline and follow-up ages. Medicated youth were excluded (n=69). We calculated sleep spindle density (SSD; number of spindles/minute) and peak spindle frequency (PSF; 10-16 Hz range) at central derivations during stage N2 using MSS software. Wechsler intelligence testing assessed working memory (WM), verbal and non-verbal (NVIQ) IQ. Linear regression models examined the longitudinal association of SSD and PSF with cognitive outcomes, while adjusting for age, sex, race/ethnicity, PSG system, insomnia symptoms, body mass and apnea/hypopnea indices. Results In TD youth, higher childhood SSD (B=0.937, SE=0.443, p=0.036) and a smaller change in PSF from childhood to adolescence (B=-3.561, SE=1.732, p=0.041) were longitudinally associated with better NVIQ; neither childhood SSD (B=0.157, SE=0.139, p=0.261) nor change in SSD (B=0.171, SE=0.127, p=0.179) were longitudinally associated with WM in TD adolescents. In youth diagnosed with ADHD/LD, lower childhood PSF (B=-2.621, SE=1.005, p=0.012) and a smaller change in PSF from childhood to adolescence (B=-2.188, SE=0.750, p=0.005) were longitudinally associated with better WM; neither childhood SSD (B=-0.263, SE=0.279, p=0.350) nor change in SSD (B=0.033, SE=0.245, p=0.893) were associated with WM (or NVIQ, p=0.070) in unmedicated adolescents. Conclusion Sleep spindles may serve as a biomarker for neural and cognitive maturation in TD adolescents, with higher childhood density and lower frequency supporting NVIQ. While this relationship is altered in youth with unmedicated psychiatric/behavioral disorders, low-frequency spindles may serve as a protective mechanism supporting WM in adolescents with ADHD/LD. Support (if any) R01MH118308; R01MH136472; UL1TR000127

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.023
Threshold uncertainty score0.884

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.008
GPT teacher head0.232
Teacher spread0.225 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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