Direct comparisons of neural activity during placebo analgesia and nocebo hyperalgesia between humans and rats
Bibliographic record
Abstract
Placebo analgesia and nocebo hyperalgesia can profoundly alter pain perception, offering critical implications for pain management. While animal models are increasingly used to explore the underlying mechanisms of these phenomena, it remains unclear whether animals experience placebo and nocebo effects in a manner comparable to humans or whether the associated neurobiological pathways are conserved across species. In this study, we introduce a novel framework for comparing brain activity between humans and rodents during placebo analgesia and nocebo hyperalgesia. Using c-Fos immunohistochemistry in rats and fMRI in humans, we examined neural activity in 70 pain-related brain regions, identifying both conserved and species-specific connectivity changes. Functional connectivity analysis, refined by pruning connections based on known anatomical pathways, revealed significant overlap in key regions, including the amygdala, anterior cingulate cortex, and nucleus accumbens, highlighting conserved circuits driving placebo and nocebo responses. This cross-species methodology offers a powerful new approach for investigating the neurobiology of pain modulation, bridging the gap between animal models and human studies. Identifying these common connections validates the use of animal models and enables preclinical researchers to focus on circuits that are conserved across species, ensuring greater translational relevance when developing new and effective treatments for pain conditions.
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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 | 0.000 |
| 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".