Topography of homeostatic sleep pressure dissipation across the night in young and middle-aged men and women
Bibliographic record
Abstract
Decline in slow-wave activity (SWA) across the night is believed to reflect dissipation of the homeostatic sleep drive. This study evaluated the effects of age, sex and topography on SWA dissipation. The sleep electroencephalogram of 48 young [22 women, 26 men; mean = 23.3 years; standard deviation (SD) = 2.4] and 39 middle-aged (21 women, 18 men; mean = 51.9 years; SD = 4.6) healthy volunteers was analysed. Spectral analysis (0.5-22.0 Hz) was performed per non-rapid eye movement period for Fp1, F3, C3, P3 and O1. SWA (1.0-5.0 Hz) dissipation was modelled using linear and exponential decay functions applied to each age and sex subgroup data set for each derivation. The relative adequacy of both functions was compared using Akaike's information criterion. Results suggest that the exponential model provides a better data fit than the linear fit independently of age, gender and brain location. In women, age reduced the span (distance between the y intercept and the asymptote) of SWA decay in Fp1, F3, P3 and O1. In men, however, the effect of age on the span of SWA decay was limited to Fp1 and F3. In all age and sex subgroups, anterior regions showed a higher span than posterior regions. The asymptote was lower in anterior regions in young but not in middle-aged subjects. These results suggest that the homeostatic process operates on a larger scale in anterior regions. Importantly, ageing reduced the scale of homeostatic dissipation in both sexes, but this effect was more widespread across the brain in women.
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 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 | 0.000 |
| 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) | 0.001 | 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".