Examination of Anti-Suppression Therapy for Amblyopia
Bibliographic record
Abstract
Amblyopia, a developmental disorder associated with abnormal early visual experience, is defined by a deficit in visual acuity in the amblyopic eye (AE) which cannot be optically corrected. Although some research on amblyopes suggested visual information from the eyes is not combined, a growing body of studies report that binocular mechanisms are intact, but suppressed. Using dichoptic presentation of stimuli of relatively high and low contrasts to AE and non-AE, respectively, Hess et al. (2010, Optometry & Vision Science) demonstrated that binocular perceptual training can reduce suppression from the non-AE and improve visual acuity and stereoacuity. We examined the influence of binocular perceptual learning on the visual acuity, crowding, stereovision, binocular motion coherence thresholds, and binocular integration in five individuals with severe amblyopia. Binocular integration was measured as the contrast at which noise dots presented to the non-AE influenced the perception of the direction of motion of the signal dots in the AE. Initially, participants demonstrated visual acuity in the AE greater than 1.0 logMAR and nonmeasureable stereoacuity. Whereas 2 participants demonstrated suppression on the Worth 4-dot test, 4 participants evidenced suppression on the binocular integration task. After training on the binocular integration task for 20 to 24 hours, all participants reported better vision and increased ability to focus with the AE, which were supported by better visual acuity (t(4) = 14.3, p < 0.05) and less crowding (t(4) = 2.8, p < 0.05). In contrast, neither stereoacuity measured on the Randot tests nor suppression measured on the Worth 4-dot test improved. The influence of binocular perceptual training on binocular motion coherence thresholds and binocular integration evidenced individual variation. Our data are consistent with those of previous studies indicating that perceptual training can benefit adult amblyopes' visual experience.
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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 | 0.001 | 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) | 0.001 | 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".