Effect of Vergence Adaptation and Positive Fusional Vergence Training on Oculomotor Parameters
Bibliographic record
Abstract
PURPOSE: Clinical studies have shown that positive fusional vergence (PFV) can be trained through a program of orthoptic exercises. Models of accommodation and vergence predict that training PFV would require a reduction in the convergence accommodation (CA) cross-link. Recent investigations have found that the CA/C ratio is not changed in a clinical population after orthoptics. We hypothesized that such orthoptic programs may instead act to reduce CA through changes in the relationship between fast and slow vergence components. METHODS.: Eleven visually normal subjects were tested. Phoria adaptation to a 12-Delta base-out (BO) wedge prism and the resulting CA responses were monitored every 3 min for 15 min to a DoG target at 0.4 m. These measures were repeated after 2 weeks of orthoptics. Phorias, stimulus accommodative convergence (AC)/A and CA/C ratios, and PFV amplitudes at near were also determined. Before the orthoptics program, these measures were repeated under "adapted" conditions. RESULTS: Phoria adaptation following prolonged viewing through the 12-Delta BO wedge prism was associated with a concomitant reduction in the CA. These changes were asymptotic over time with 95% of the change occurring within the first 3 to 6 min. After 2 week of orthoptics, the rates and magnitudes of both phoria adaptation and CA reduction increased significantly (p < 0.01). PFV at 40-cm limits showed increases with orthoptics and under vergence adaptation. CA/C and AC/A ratios were unchanged after orthoptics, but the former was reduced, and the latter increased under the vergence adapted condition. CONCLUSIONS: Orthoptics acts to change the time constant and magnitude of vergence adaptation to BO prisms, which leads to a concomitant reduction of CA over a similar time course. This process appears to underlie the increase in positive fusion limits. Although reductions in CA/C ratio occur under the vergence adapted state, this ratio is not directly changed with orthoptics.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".