Using optic flow in the far peripheral field
Bibliographic record
Abstract
Self-motion information can be used to update spatial memory of location through an estimate of a change in position. Viewing optic flow alone can create Illusory self-motion or "vection." Early studies suggested that peripheral vision is more effective than central vision in evoking vection, but controlling for retinal area and perceived distance suggests that all retinal areas may be equally effective. However, the contributions of the far periphery, beyond 90°, have been largely neglected. Using a large-field Edgeless Graphics Geometry display (EGG, Christie, Canada, field of view ±112°) and systematically blocking central (±20° to ±90°) or peripheral (viewing through tunnels ±20° to ±40°) parts of the field, we compared the effectiveness of different retinal regions at evoking forwards linear vection. Fifteen participants indicated when they had reached the position of a previously presented target after visually simulating motion down a simulated corridor. The amount of simulated travel needed to match a given target distance was modelled with a leaky spatial integrator model to estimate gains (perceived/actual distance) and a spatial decay factor. When optic flow was presented only in the far periphery (beyond 90°) gains were significantly higher than for the same motion presented full field or in only the central field, resulting in accurate performance in the range of speeds associated with normal walking. The increased effectiveness of optic flow in the peripheral field alone compared to full-field motion is discussed in terms of emerging neurophysiological studies that suggest brain areas dedicated to processing information from the far peripheral field.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".