Thresholds of cutaneous afferents related to perceptual threshold across the human foot sole
Bibliographic record
Abstract
Perceptual thresholds are known to vary across the foot sole, despite a reported even distribution in cutaneous afferents. Skin mechanical properties have been proposed to account for these differences; however, a direct relationship between foot sole afferent firing, perceptual threshold, and skin mechanical properties has not been previously investigated. Using the technique of microneurography, we recorded the monofilament firing thresholds of cutaneous afferents and associated perceptual thresholds across the foot sole. In addition, receptive field hardness measurements were taken to investigate the influence of skin hardness on these threshold measures. Afferents were identified as fast adapting [FAI (n = 48) or FAII (n = 13)] or slowly adapting [SAI (n = 21) or SAII (n = 20)], and were grouped based on receptive field location (heel, arch, metatarsals, toes). Overall, perceptual thresholds were found to most closely align with firing thresholds of FA afferents. In contrast, SAI and SAII afferent firing thresholds were found to be significantly higher than perceptual thresholds and are not thought to mediate monofilament perceptual threshold across the foot sole. Perceptual thresholds and FAI afferent firing thresholds were significantly lower in the arch compared with other regions, and skin hardness was found to positively correlate with both FAI and FAII afferent firing and perceptual thresholds. These data support a perceptual influence of skin hardness, which is likely the result of elevated FA afferent firing threshold at harder foot sole sites. The close coupling between FA afferent firing and perceptual threshold across foot sole indicates that small changes in FA afferent firing can influence perceptual thresholds.
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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 | 0.000 | 0.000 |
| 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 | 0.001 | 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; a candidate call from one teacher head, 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".