Optics and Spatial Vision in Children and Young Adults With Autism Spectrum Disorder
Bibliographic record
Abstract
Purpose. Autism spectrum disorder (ASD) is an increasingly diagnosed neurodevelopmental disorder, with an incidence in children now greater than 1%. Surprisingly, given the assumption that ASD impacts the processing of visual stimuli, systematic studies of even basic visual functioning have yet to be conducted on this population, and the limited available reports are equivocal. Here we conduct the first comprehensive study of the development of spatial vision and refractive status in this population. Methods. 44 children and young adults (age range: 3-22 years) with a primary diagnosis of ASD were tested with a battery of tests developed for an early childhood eye and vision screening program (Adams et al: VSS 07, 08). These included measures of visual acuity, alignment, stereoacuity, refractive error, contrast sensitivity (CS), and Vernier acuity. Children were tested monocularly and with optical correction if prescribed. Results. Children were very compliant with 95% completing all tests in both eyes. Compared to controls, 3-to- 6 year-olds (n =21) showed moderate deficits in visual acuity (M = 0.38 LogMAR; 20/48), CS (M= 53 CS units), Vernier acuity (M = 0.70 log min), stereoacuity (M = 2.28 log arcsec) and ocular alignment (31% failed). Older 7-22-year-olds (n = 23) performed even more poorly, showing significant deficits in visual acuity (20/94; 0.67 LogMAR), Vernier acuity (0.85 log min), stereoacuity (2.41 log arcsec) and ocular alignment (65% failed), but only a moderate deficit in CS (M = 56 CS units).Conversely, refractive error showed a relatively normal age distribution. Conclusions. Children with ASD are at risk for eye and visual dysfunction. However, given that most of these children had relatively normal levels of refractive error, the basis of their deficits appears to be within the central visual pathways and/or the visual cortex and is perhaps related to the neural origin of the disease.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".