Changes in Rapid Eye Movement Sleep Associated with Placebo-Induced Expectations and Analgesia
Bibliographic record
Abstract
The experience of a sensory event is extensively shaped by past experience and expectations. Placebo analgesia, one of the most studied models of expectation-mediated effects, can be induced by suggestion of analgesia and conditioning. The present study examined the possibility that sleep might contribute to the consolidation of new expectations and consequently influence the generation of expectation-mediated placebo effects. Strong expectations of analgesia were generated before sleep by conditioning manipulations wherein the intensity of thermal pain stimulation was surreptitiously reduced after the application of a topical placebo cream. Expectations and placebo analgesic effects were measured the following morning and compared with those of a control daytime group without sleep. Although placebo effects were observed in both groups, correlation analysis suggests that the mediating effect of expectations on placebo responses was strongest in the overnight group. Moreover, after exposure to a convincing analgesia experience, the relative duration of rapid eye movement (REM) sleep decreased in subjects showing higher analgesic expectations and placebo responses the next morning. In a third group exposed to less consistent analgesic experiences before sleep, expectations reported in the morning were comparable with other groups. However, expectations were positively correlated with REM sleep and did not emerge as a significant mediator of the analgesic effect. Together, these findings show that sleep-related processes may influence the association between expectations and placebo analgesia and that REM sleep can predict placebo-induced expectations of pain relief. However, equivocal previous experience with treatments may significantly alter the relationship between relief expectation, REM sleep, and placebo effects.
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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".