Poor fixation stability does not account for motion perception deficits in amblyopia
Bibliographic record
Abstract
People with amblyopia show deficits in global motion perception, especially at slow speeds. These observers are also known to have unstable fixation when viewing stationary fixation targets, relative to healthy controls. It is possible that poor fixation stability during motion viewing interferes with the fidelity of the input to motion-sensitive neurons in visual cortex. To probe these mechanisms at a behavioral level, we assessed motion coherence thresholds in adults with amblyopia while measuring fixation stability. Consistent with prior work, participants with amblyopia had elevated coherence thresholds for the slow speed stimuli, but not the fast speed stimuli, using either the amblyopic or the fellow eye. Fixation stability was elevated in the amblyopic eye relative to controls across all motion stimuli, and not selective for conditions on which perceptual deficits were observed. Fixation stability was not related to visual acuity, nor did it predict coherence thresholds. These results suggest that motion perception deficits might not be a result of poor input to the motion processing system due to unstable fixation, but rather due to processing deficits in motion-sensitive visual areas.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".