Ebbinghaus Illusion Distortions in Amblyopia: Impairments of Visual Size Processing and Interocular Integration
Bibliographic record
Abstract
Purpose: The perceived size of an object can be manipulated by its surroundings. In the current study, we wanted to investigate whether amblyopic patients have normal object size perception and how their perception is affected by abnormal interocular interactions. Methods: Sixteen adult amblyopes and 16 controls participated in this experiment. We measured the Ebbinghaus illusion magnitude with large and small inducers under one binocular, two monocular, and four dichoptic viewing configurations. Exploratory factor analysis was used to extract common structures and underlying mechanisms in different conditions. Results: The mean Ebbinghaus illusion magnitude in amblyopia was smaller with large inducers (F1,30 = 5.874, P = 0.021) and larger with small inducers (F1,30 = 5.814, P = 0.022) than in controls. For the small-inducer geometry, the interaction effect between groups and viewing configurations (F6,180 = 4.472, P < 0.001) was significant. Compared to the control population, the exploratory factor analysis in amblyopia extracted three more factors mainly accounting for dichoptic viewing configurations. Conclusions: Amblyopes tended to overestimate the object size relative to controls in the Ebbinghaus illusion, thereby amplifying it in the small-inducer geometry and diminishing it in the large-inducer geometry. Our factor analysis revealed a limited interocular transfer of the Ebbinghaus illusion in amblyopia, suggesting a defective mechanism in local binocular integration circuitry.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".