Distribution and terminal arborizations of cutaneous mechanoreceptors in the glabrous finger pads of the monkey
Bibliographic record
Abstract
Recent electrophysiological studies demonstrated that neurons in the somatosensory cortex of monkeys respond to tangential forces applied to glabrous skin. To unravel the peripheral basis for this cortical response, we determined the distribution of presumptive low-threshold mechanoreceptors innervating the distal finger pads of monkeys. Endings were reconstructed in immunolabeled serial sections imaged by epifluorescence and confocal microscopy. Although classically implicated as cutaneous stretch receptors, no Ruffini corpuscles were found in the glabrous skin. Ruffini-like endings were only detected at the base of the finger nails. Pacinian corpuscles were sparsely distributed in the deep dermis. Meissner corpuscles (MCs) in dermal papillary ridges had a comparably high density in the thumb, index, and fifth fingers. Each MC was innervated by several large-caliber axons. Within the limits of our reconstructions, some of these axons terminated in only one MC, whereas others innervated several MCs. Merkel endings covered about 80% of the base of the intermediate epidermal ridges that form the pattern of fingerprints. In some cases, the distal tip of a Merkel-related axon gave rise to a several terminal branches that supplied endings to tightly circumscribed (30-70 microm) clusters of Merkel cells. In other cases, the nodes of axons gave rise to en passant branches that formed extended chains of endings among Merkel cells spread over territories up to 300 microm long. Based on their relatively diffuse distributions, the axons that innervate multiple MCs or the axons with en passant Merkel terminations seem most suited to transduce tangential forces.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".