The local inversion effect in biological motion perception is acceleration-based
Bibliographic record
Abstract
The ability to discriminate direction from spatially scrambled point-light displays relies on the orientation of the foot dot motions (Troje & Westhoff, 2006). We present two experiments that investigated this local motion-based inversion effect by testing direction discrimination from novel biological motion displays that exaggerate and display solely foot-specific information. In Experiment 1, we isolated the foot motion of a treadmill human walker, human runner, cat, and pigeon and presented observers (n = 20) with 1000 ms displays consisting of 10 copies of two foot dots that traced 150 ms segments at counterphase positions of the gait cycle. For each foot type, we derived left and right signalling displays from five such segment pairs that collectively sampled the entire gait cycle and presented them at both upright and inverted orientations. Direction discrimination accuracies varied with foot type, orientation, and segment pair. Significantly, the decrease in accuracies due to inversion was most substantial for the runner stimuli which exhibit the most pronounced vertical velocity changes and smallest for the cat stimuli which carry little vertical motion. In Experiment 2, a new group of observers (n = 20) were presented with the natural human walker stimuli of Experiment 1 and with stimuli that were spatiotemporally-matched to the natural stimuli but moved with constant velocities. Here, overall discrimination accuracies did not differ per foot type, decreased with inversion, and varied with segment pair. Critically, performances were higher for upright than for inverted displays for the natural stimuli only. Upright and inverted versions of the constant velocity stimuli did not differ. The results suggest that the local inversion effect in biological motion perception is carried by the velocity gradients of the foot motions. We conjecture that the visual system is sensitive to characteristic velocity changes exhibited by biological movements in a gravity-driven environment.
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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 | 0.003 |
| 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 | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".