Descending analgesia – When the spine echoes what the brain expects
Bibliographic record
Abstract
Changes in pain produced by psychological factors (e.g., placebo analgesia) are thought to result from the activity of specific cortical regions. However, subcortical nuclei, including the periaqueductal gray and the rostroventral medulla, also show selective activation when subjects expect pain relief. These brainstem regions send inhibitory projections to the spine and produce diffuse analgesic responses. Regrettably the precise contribution of spinal mechanisms in predicting the strength of placebo analgesia is unknown. Here, we show that expectations regarding pain radically change the strength of spinal nociceptive responses in humans. We found that contrary to expectations of analgesia, expectations of hyperalgesia completely blocked the analgesic effects of descending inhibition on spinal nociceptive reflexes. Somatosensory-evoked brain potentials and pain ratings further confirmed changes in spino-thalamo-cortical responses consistent with expectations and with changes in the spinal response. These findings provide direct evidence that the modulation of pain by expectations is mediated by endogenous pain modulatory systems affecting nociceptive signal processing at the earliest stage of the central nervous system. Expectation effects, therefore, depend as much about what takes place in the spine as they do about what takes place in the brain. Furthermore, complete suppression of the analgesic response normally produced by descending inhibition suggests that anti-analgesic expectations can block the efficacy of pharmacologically valid treatments which has important implications for clinical practice.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".