Perception of egocentric direction: retinal and extra-retinal influences
Bibliographic record
Abstract
Perception of egocentric direction, that is the direction of an object relative to the body, is critical for visual guidance of action. What information is used to judge the direction of an object? Classically it is assumed that extra-retinal information about the orientation of the head on the shoulders, and the eye in the head, is combined with retinal object location to transform from a retinal to trunk-centric coordinate frame. However, theoretical analysis indicates that it should be possible to pick up head-centric direction directly from retinal or optic information, or that retinal information could be used to determine eye-orientation. I report a series of experiments that bear on this matter. Observers performed a body-alignment procedure to indicate the perceived egocentric direction of an object (they turn to face a target object so that if they began walking they would end up colliding with it). Perceived egocentric direction was perturbed with displacing prisms. It is found that in a laboratory setting, prisms have less of an effect (in line with Rock et al's report of ‘immediate adaptation’) than would be expected from their optical displacement and the consequent error in extra-retinal eye-orientation signal. Typically, the effect is between 60% and 65% of that expected. This finding is robust and holds when observers align themselves with point-lights in an otherwise dark room, or view alignment targets monocularly. In these two case potentially useful information contained in the field of vertical and horizontal disparities is absent. However, a particularly striking finding is that approximately 95% of the expected effect of the prism is observed when the experiment is performed out of doors, in an open field, with distant targets. The consequence of these results for understanding of the perception of egocentric direction, and the interesting case of visual guidance of locomotion, will be discussed.
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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 | 0.001 | 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".