Far visual acuity is unremarkable in autism: Do we need to focus on crowding?
Bibliographic record
Abstract
Although autism presents a unique perceptual phenotype defined in part by atypical (often enhanced) analysis of spatial information, few biologically plausible hypotheses have been advanced to explain its neural underpinnings. One plausible explanation is functional but altered lateral connectivity mediating early or local mechanisms selectively responsive to different stimulus attributes, including spatial frequency and contrast. The goal of the present study was first to assess far visual acuity in autism using Landolt-C optotypes defined by different local stimulus attributes. Second, we investigated whether acuity is differentially affected in autism when target optotypes are simultaneously presented with flanking stimuli at different distances. This typical detrimental "crowding effect" of flanking stimuli on target optotype discrimination is attributed to lateral inhibitory interaction of neurons encoding for visual properties of distracters close to the target. Results failed to demonstrate a between-group difference in acuity to Landolt-C optotypes, whether defined by luminance- or texture-contrast. However, the expected crowding effect at one gap-size opening distance was evidenced for the control group only; a small effect was observed for the autism group at two gap-size opening. These results suggest that although far visual acuity is unremarkable in autism, altered local lateral connectivity within early perceptual areas underlying spatial information processing in autism is atypical. Altered local lateral connectivity in autism might originate from an imbalance in excitatory/inhibitory neural signaling, resulting in changes regarding elementary feature extraction and subsequent downstream visual integration and visuo-spatial analysis. This notion is discussed within the context of characteristic lower- and higher-level perceptual processing in autism.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.000 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 0.007 |
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; both teacher heads agree on what is shown here.
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".