Attenuation of Sensory and Affective Responses to Heat Pain: Evidence for Contralateral Mechanisms
Bibliographic record
Abstract
Attenuation of responses to repeated sensory events has been thoroughly studied in many modalities; however, attenuation of pain perception has not yet benefitted from such extensive investigation. Described here are two psychophysical studies that examined the effects of repeated exposure to thermal stimuli, assessing potential attenuation of the perception of pain and its possible spatial specificity. Twenty-two subjects were presented thermal stimuli to the volar surface of the right and left forearms. Twelve subjects in study 1 received the same stimuli and conditions on each of five daily experimental sessions, whereas 10 subjects in study 2 received thermal stimuli, which were restricted to one side for four daily sessions and then applied to the other side on the fifth session. Ratings of warmth intensity, pain intensity, and pain unpleasantness were recorded while the subjects performed a thermal sensory discrimination task. Results of study 1 demonstrate that repeated stimulation with noxious heat can lead to long-term attenuation of pain perception; results of study 2 extend these findings of attenuation to both pain intensity and unpleasantness and show that this effect is highly specific to the exposed body side for both aspects of the pain experience. We suggest that the functional plasticity underlying this attenuation effect lies in brain areas with a strong contralateral pattern of pain-related activation.
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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 | 0.002 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".