Sleep slow wave changes during the middle years of life
Bibliographic record
Abstract
Slow waves (SW; < 4 Hz and > 75 μV) during non-rapid eye movement (NREM) sleep in humans are characterized by hyperpolarization [surface electroencephalogram (EEG) SW negative phase], during which cortical neurons are silent, and depolarization (surface EEG positive phase), during which the cortical neurons fire intensively. We assessed the effects of age, sex and topography on the dynamics of SW characteristics in a large population (n=87) of healthy young (23.3 ± 2.4 years) and middle-aged (51.9 ± 4.6 years) volunteers. Older subjects showed lower SW density and amplitude than young subjects. Age-related lower SW density in men was especially marked in prefrontal/frontal brain areas, where they originate more frequently. Older subjects also showed longer SW positive and negative phase durations. These last results indicate that, in young subjects, cortical neurons would synchronously enter the SW hyperpolarization and depolarization phases, whereas this process would take longer in older subjects, leading to lower slope and longer SW positive and negative phases. Importantly, after controlling for SW amplitude, middle-aged subjects still showed lower slope than young subjects in prefrontal, frontal, parietal and occipital derivations. Age-related effects on SW density, frequency and positive phase duration were more prominent at the beginning of the night, when homeostatic sleep pressure is at its highest. Age-related SW changes may be associated with changes in synaptic density and white matter integrity and may underlie greater sleep fragmentation and difficulty in recuperating and maintaining sleep under challenges in older subjects.
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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 | 0.000 |
| 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".