Thermal and mechanical modalities converge in the noxious range
Bibliographic record
Abstract
Summary There are competing theories on how nociceptive input is encoded by sensory fibers. That sensory modalities are exclusively conveyed by distinct populations of fibers is supported by ablation studies, indicating that TRPV1 + and MrgprD + afferents selectively encode for heat and mechanical input, respectively. However, interpreting ablation results can be clouded by compensatory plasticity. Furthermore, a population-level parametric analysis of afferent response profiles to natural stimuli in vivo is still scarce. Using functional imaging in vivo in mice, we found that most TRPV1 + neurons responded to noxious heat, but not cooling. While none of them responded to innocuous mechanical input, about half were also sensitive to noxious mechanical stimuli. In contrast, 80% of MrgprD + neurons responded to noxious mechanical stimuli. Yet, 70% were also sensitive to noxious thermal stimuli. Of innocuous mechanosensitive MrgprD + neurons, <15% responded to innocuous warming and none to innocuous cooling. Polymodality in the innocuous thermal and mechanical range also occurred in <10% of all primary afferents. Acute silencing of TRPV1 + or MrgprD + afferents inhibited both thermal and mechanical nociception. In contrast, ablation did not reproduce a combined loss of sensitivity, which appeared to be due to compensatory central disinhibition. Our findings reveal that modality separation dominates in the innocuous regime, while polymodality predominates in the noxious range.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".