Modulation of pain via expectation of its location
Bibliographic record
Abstract
BACKGROUND: The spatial precision of expectancy effects on pain is unclear. We hypothesized that expecting nociceptive stimuli at particular skin sites would have an analgesic effect on nociceptive stimuli presented between them (middle zone). METHODS: Laser stimuli (evoking pin-prick pain) were delivered to three discrete skin zones on the forearm, under two conditions. During 'Localization', participants' expectation of stimuli was spatially divided between two locations (expected stimuli in only the outer two skin zones): pain intensity and stimulus location were judged. During 'No-localization' (control condition), participants had no expectation concerning stimulus location; only pain intensity was rated. Additional experiments assessed the importance of the actual location on the forearm by: shifting all skin zones proximally towards the elbow (control for joint proximity, Experiment 2); adding a fourth zone distally (control for interaction between joint proximity and enhanced distal inhibition, Experiment 3). RESULTS: All experiments demonstrated spatially specific pain modulation, but only Experiment 2 (near elbow) supported our hypothesis: middle zone pain intensity was significantly lower (p = 0.02) during Localization than No-localization. Experiment 1 (near wrist) found reduced pain intensity during Localization only for the distal zone (p = 0.04). Experiment 3 confirmed this effect: reduced pain during Localization occurred only for the most distal zone (p = 0.046). CONCLUSION: Expecting a painful stimulus in non-adjacent skin sites has spatially specific effects on pain modulation, but this reflects an interaction between the expected location of stimulation and the actual location. This suggests a more complex connection between somatotopic maps and nociceptive modulation than previously thought; several distinct mechanisms likely contribute.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.010 |
| 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) | 0.000 | 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; both teacher heads agree on what is shown here.
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".