Low-level and high-level maximum motion displacement deficits in amblyopic children
Bibliographic record
Abstract
Direction discrimination thresholds for maximum motion displacement (Dmax) are not fixed values but are highly dependent on stimulus parameters. Dmax increases with reduced dot probability (Boulton & Baker, 1993; Ramachandran & Anstis, 1983) or increased dot size (Cavanagh et al., 1985; Morgan, 1992). It has been theorized that the increase in Dmax under these conditions might reflect a switch in processing from low-level to high-level motion mechanisms in normal observers (Nishida & Sato, 1995; Sato, 1998). The proposed low-level process is reliant on spatial-frequency-tuned motion detectors and the high-level process is mediated by feature matching mechanisms. To determine whether this “switch” in motion mechanisms is observed in amblyopic individuals, thresholds were obtained in both eyes of 9 children with unilateral amblyopia and 9 controls. Each subject performed the task under three random dot display parameters: 20 min size at 5% density (baseline condition), 20 min size at 0.5% density (reduced probability condition), and 1 deg size at 5% density (increased dot size condition). A significant increase in Dmax was observed for displays with reduced dot probability and increased dot size relative to baseline in both groups. However, on the baseline and reduced dot probability conditions, Dmax was significantly lower in both eyes of the amblyopic group compared to the control group. For the increased dot size condition, Dmax was significantly lower in the amblyopic eye but significantly higher in the fellow eye compared to the control group. Extent of binocularity and subtype of amblyopia were not predictive of abnormal performance in this small sample. The results suggest that amblyopic children show the expected shift from low- to high-level motion mechanisms, but both mechanisms appear to be deficient. Our findings implicate abnormal binocular motion processing mechanisms in the neural deficit underlying amblyopia.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".