Quantitative EEG amplitude across REM sleep periods in depression: preliminary report
Bibliographic record
Abstract
OBJECTIVE: To determine if there are significant differences in the temporal organization of rapid eye movement (REM) sleep microarchitecture between healthy controls and outpatients with major depressive disorder (MDD). METHODS: Forty age-matched subjects, 20 men and 20 women, half with MDD, were selected from an archive of sleep electroencephalography (EEG) data collected under identical conditions. Each participant spent 2 consecutive nights in the Sleep Study Unit of the University of Texas Southwestern Medical Center at Dallas, the first of which served as adaptation. The average amplitude in each of 5 conventional EEG frequency bands was computed for each REM period across the second night. Data were then coded for group and sex. RESULTS: Aside from REM latency, none of the key sleep macroarchitectural variables differentiated MDD patients from controls. REM latency was longest in men with MDD. Sleep microarchitecture, however, did show a number of between-group differences. In general, slower frequencies declined across REM periods, with a significant REM period effect for delta, theta and alpha amplitude. Group x sex interactions were also obtained for theta and alpha. Beta activity showed a unique temporal profile in each group, supported by a significant REM period x group x sex interaction. In addition, the temporal change in theta amplitude across REM periods was most striking in women with MDD. CONCLUSIONS: This study suggests that, like during non-REM sleep, EEG amplitude shows a systematic temporal change over successive REM sleep periods and also shows elements that are both disease- and sex-dependent.
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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".