Distortions of the perceptual body affect basic tactile properties
Bibliographic record
Abstract
The internal representation of the body can be altered by artificially stimulating arm tendons which distort the body’s idea of where the limbs are. If the limbs are touching another body part, then this can distort the perceived size of that body part (Lackner, 1988). Here we explore whether two-point tactile discrimination and tactile sensitivity are affected by such perceptual distortions. We used tendon vibration to distort the length of an arm and the width of the waist. Vibrotactile stimuli were delivered with an array of 5 tactors that were spaced by 3 cms on a belt that was either laid on the arm or worn on the stomach. Two-point discrimination and tactile sensitivity detection tasks were performed using two-interval forced choice designs. The arm’s perceptual length was modified by having it held by the other arm while the biceps and triceps tendons were activated by vibration. Perceived waist thickness was modified by holding the arms akimbo and stimulating the extensor or flexor tendons on both arms simultaneously (Ehrsson et al., 2005). Both two-point discrimination thresholds and sensitivity thresholds were increased when the arm was perceptually lengthened and when the waist was extended. Two-point thresholds and sensitivity thresholds were unaffected when the arm was shortened but increased when the waist was made to feel smaller. We conclude that fundamental sensory properties determining discrimination and sensitivity thresholds are not exclusively determined by cutaneous mechanisms but depend on higher-level representations in the brain that can be distorted.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".