Extended visuomotor experience with inverted movements can overcome the inversion effect in biological motion perception
Bibliographic record
Abstract
Studies have demonstrated that perceiving human and animal movements as point-light displays is effortless. However, simply inverting the display can significantly impair this ability. Compared to non-dancers and typical dancers, vertical dancers have the unique experience of observing and performing movements upside down as being suspended in the air. We studied whether this unique visuomotor experience makes them better at perceiving the inverted movements. We presented ten pairs of dance movements as point-light displays. Each pair included a version performed on the ground whereas the other was in the air. We inverted the display in half of the trials and asked vertical dancers, typical dancers, and non-dancers about whether the display was inverted. We found that only vertical dancers, who have extended visual and motor experience with the configural and dynamic information of the movements, could identify the inversion of movements performed in the air. Neither typical dancers nor non-dancers, who have no motor experience with performing the inverted movements, could detect the inversion. Our findings suggest that motor experience plays a more critical role in enabling the observers to use dynamic information for identifying artificial inversion in biological motion.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".