The association between white matter and sleep spindles differs in young and older individuals
Bibliographic record
Abstract
Study Objectives: Sleep is a reliable indicator of cognitive health in older individuals. Sleep spindles (SS) are non-rapid eye movement (NREM) sleep oscillations implicated in sleep-dependent learning. Their generation imply a complex activation of the thalamo-cortico-thalamic loop. Since SS require neuronal synchrony, the integrity of the white matter (WM) underlying these connections is of major importance. During aging, both SS and WM undergo important changes. The goal of this study was to investigate whether WM integrity could predict the age-related reductions in SS characteristics. Methods: Thirty young and 31 older participants underwent a night of polysomnographic recording and a 3T magnetic resonance imaging acquisition including a diffusion sequence. SS were detected in NREM sleep and EEG spectral analysis was performed for the sigma frequency band. WM diffusion metrics were computed in a voxelwise design of analysis. Results: Compared to young participants, older individuals showed lower SS density, amplitude, and sigma power. Diffusion metrics were correlated with SS amplitude and sigma power in tracts connecting the thalamus to the frontal cortex for the young but not for the older group, suggesting a moderation effect. Moderation analyses showed that diffusion metrics explained between 14% and 39% of SS amplitude and sigma power variance in the young participants only. Conclusion: Our results indicate that WM underlying the thalamo-cortico-thalamic loop predicts SS characteristics in young individuals, but does not explain age-related changes in SS. Other neurophysiological factors could better explain the effect of age on SS characteristics.
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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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".