Dichotomy in Biological Motion Perception: Pigeons Use Feet Local Motion to Determine Direction
Bibliographic record
Abstract
The study examines the visual processes underlying the detection of the motion of land animals, or biological motion. The ability to process the motion of other living beings has profound ecological implications in the wilderness and in our everyday life. Earlier models suggest that there are two distinct ways to process this information. One uses the shape of an entire figure and one uses the motion of one part of the body. In this experiment, we aim to study whether the local motion of the feet or the configuration of the body is used to determine the direction into which a figure is facing. We do this by training pigeons to discriminate facing direction of a stationary walking point‐light figure. Pigeons chose one of two walkers by pecking on a touch screen. Once the task was learned, catch trials of backwards walkers were introduced. This kind of display gives the pigeon opposing information about direction. While the shape of the walker tells them it is walking one way, the feet give the impression that it is moving in the other. Pigeons were successful in learning to discriminate directions and at the introduction of the catch trials, most birds used the local motion cue of the feet to determine direction. The results indicate that pigeons seem to being using the feet, rather than the shape of a figure, to process direction of movement. In conjunction with previous literature, this study suggests that there exists an innate “life detector” specialized for filtering the movement of the feet.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".