A common perceptual inference for cross-modally induced illusions of body schema
Bibliographic record
Abstract
Abstract Body-schema, or the multimodal representation of one’s own body attributes, has been demonstrated previously to be malleable. In the rubber-hand illusion (Botvinick & Cohen, 1998), synchronous visual and tactile stimulation cause a fake hand to be perceived as one’s own. Similarly, if a stranger’s voice is heard synchronously with one’s own vocal production, that voice comes to be attributed to oneself (Zheng et al., 2011). Multimodal illusions like these involve distorting body schema based on correlated input, yet the degree to which different instances of distortion are perceived within the same individuals has never been examined. Here we show that participants embraced the ownership of a fake hand and a stranger’s voice to a similar degree, controlling both for individual suggestibility and for general susceptibility to illusion of body schema. Our findings suggest that the perceptual inference that leads to the distortion of body schema is a stable trait.
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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 | 0.001 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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".