Spatial frequency channels depend on stimulus bandwidth in normal and amblyopic vision: an exploratory factor analysis
Bibliographic record
Abstract
The Contrast Sensitivity Function (CSF) is the measure of an observer's contrast sensitivity as a function of spatial frequency. It is a sensitive measure to assess visual function in fundamental and clinical settings. Human contrast sensitivity is subserved by different spatial frequency channels. Also, it is known that amblyopes have deficits in contrast sensitivity, particularly at high spatial frequencies. Therefore, the aim of this study was to assess whether the contrast sensitivity function is subtended by the same spatial frequency channels in control and amblyopic populations. To determine these spatial frequency channels, we performed an exploratory factor analysis on five datasets of contrasts sensitivity functions of amblyopic and control participants measured using either gratings or noise patches, taken from our previous studies. In the range of 0.25-10 c/d, we identified two spatial frequency channels. When the CSF was measured with noise patches, the spatial frequency channels presented very similar tuning in the amblyopic eye and the fellow eye and were also similar to what was observed in controls. The only major difference was that the weight attributed to the high frequency channel was reduced by approximately 50% in the amblyopic eye. However, when the CSF was measured using gratings, the spatial frequency channels of the amblyopic eye were tuned toward lower spatial frequencies. These findings suggest that there is no mechanistic deficit for contrast sensitivity in amblyopia and that amblyopic vision may just be subjected to excessive internal noise and attenuation at higher spatial frequencies, thereby supporting the use of therapeutic strategies that involve rebalancing contrast.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".