Fluctuation of Waking Electroencephalogram and Subjective Alertness during a 25-Hour Sleep-Deprivation Episode in Young and Middle-Aged Subjects
Bibliographic record
Abstract
STUDY OBJECTIVES: To evaluate the effects of a 25-hour sleep-deprivation episode on quantitative waking electroencephalogram (EEG) and subjective alertness in young and middle-aged subjects. DESIGN: A 25-hour constant-routine protocol followed by a daytime recuperative sleep episode. SETTING: Chronobiology laboratory. PARTICIPANTS: Twenty-five normal subjects separated into 2 groups: young (aged 20-39 years) and middle-aged (aged 40-60 years). INTERVENTIONS: None. MEASUREMENTS AND RESULTS: Waking EEGs were recorded every 2 hours and subjective measures of alertness every 30 minutes during the 25-hour sleep-deprivation episode. Overall, results indicated no age-related differences over a 25-hour constant routine in the temporal evolution of subjective alertness and of spectral power in the theta/alpha (4-12 Hz) frequencies of the waking EEG. The middle-aged compared to the young subjects showed a reduced rebound of slow-wave activity in the recovery-sleep episode. While the waking EEG and subjective alertness levels showed strong correlations in both groups, there was no relationship between theta rise during wakefulness and slow-wave activity rebound in the recovery-sleep episode. CONCLUSIONS: These results suggest a dissociation in the middle-aged population between the sensitivity of their alertness level on the one hand and the sensitivity of their sleep on the other to the number of hours of wakefulness. Hence, alertness of young and middle-aged subjects would show the same deterioration with an accumulation of wakefulness (possibly reflecting a similar sleep need), yet the middle-aged subjects would be less able to increase their recuperative sleep intensity following enhanced time awake (reduction in sleep ability).
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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) | 0.001 | 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".