Spatial summation for pain perception: interaction of inhibitory and excitatory mechanisms
Bibliographic record
Abstract
To study the relation between size of the surface stimulated and perceived pain intensity (spatial summation effect), subjects sequentially immersed predetermined segments of the surface of their arm, between the fingertips and the shoulder, in circulating nociceptive hot water. Immersion sessions were of three types: (i) increasing session (immersion beginning at fingertips and increasing to shoulder); (ii) decreasing session (immersion beginning at shoulder and decreasing to fingertips); and (iii) whole arm+increasing session (preliminary immersion of the whole arm up to shoulder, followed by an increasing session from fingertips to shoulder). Results showed a positive spatial summation effect (pain perception positively correlated to the size of the surface stimulated) during both the decreasing session and the whole arm+increasing session. However, no spatial summation effect was found during the increasing session (fingertips to shoulder). In addition, pain perceived for a surface area was less intense during the decreasing session compared to the increasing session. One possible explanation for the lack of a spatial summation effect during the increasing session is that inhibitory mechanisms are gradually recruited at the same time as excitatory afferences, thus 'cancelling out' any measurable spatial summation effect. The results obtained during the decreasing session and the whole arm+increasing session may be explained by inhibitory mechanisms being fully recruited at the beginning of the session with the immersion of the largest surface area (whole arm). The results are a shift of the pain perception curve and a positive relation between the surface stimulated and pain perception.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".