Cutaneous Receptors Contribute to Kinesthesia at the Index Finger, Elbow, and Knee
Bibliographic record
Abstract
The neural mechanisms underlying the sense of joint position and movement remain controversial. While cutaneous receptors are known to contribute to kinesthesia for the fingers, the present experiments test the hypothesis that they contribute at other major joints. Illusory movements were evoked at the interphalangeal (IP) joints of the index finger, the elbow, and the knee by stimulation of populations of cutaneous and muscle spindle receptors, both separately and together. Subjects matched perceived movements with voluntary movements of homologous joints on the contralateral side. Cutaneous receptors were activated by stretch of the skin (using 2 intensities of stretch) and vibration activated muscle spindle receptors. Stimuli were designed to activate receptors that discharge during joint flexion. For the index finger, vibration was applied over the extensor tendons on the dorsum of the hand, to evoke illusory metacarpophalangeal (MCP) joint flexion, and skin stretch was delivered around the IP joints. The strong skin stretch evoked the illusion of flexion of the proximal IP joint in 6/8 subjects (12 +/- 5 degrees, mean +/- SE). For the group, strong skin stretch delivered during vibration increased the perceived flexion of the proximal IP joint by eight times with a concomitant decrease in perceived flexion of the MCP joint compared with vibration alone (P < 0.05). For the elbow, vibration was applied over the distal tendon of triceps brachii and skin stretch over the dorsal forearm. When delivered alone, strong skin stretch evoked illusory elbow flexion in 5/10 subjects (9 +/- 4 degrees). Simultaneous strong skin stretch and vibration increased the illusory elbow flexion for the group by 1.5 times compared with vibration (P < 0.05). For the knee, vibration was applied over the patellar tendon and skin stretch over the thigh. Skin stretch alone evoked illusory knee flexion in 3/10 subjects (8 +/- 4 degrees) and when delivered during vibration, perceived knee flexion increased for the group by 1.4 times compared with vibration (P < 0.05). Hence inputs from cutaneous receptors, muscle receptors, and combined inputs from both receptors likely subserve kinesthesia at joints throughout the body.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".