The development of contrast sensitivity for gratings and natural images: Revisiting the golden standard
Bibliographic record
Abstract
Our recent work suggests the children's sensitivity to changes in the spatial frequency content of natural images cannot be predicted by their spatial contrast sensitivity function (CSF) measured with sinusoidal gratings (VSS 07 & 08). The present study compared root-mean-square CS for natural images, phase-scrambled versions of the same images, and Gabors in children aged 6, 8, and 10 years (n = 16 per age) and in adults (mean age = 22). Natural and phase-scrambled images were band-pass filtered (1 octave) at one of five frequencies (0.33, 1, 3, 10, & 20 cpd). In this way, we were able to create an equivalent CS metric for natural and phase-scrambled images as that used with Gabors. Detection thresholds were measured using a temporal 2AFC task combined with a QUEST staircase. As expected, CS with Gabors was adult-like for 8-year-olds. However, our results raise three new issues regarding CS. First, for both adults and children, the shape of the CSF is different for natural images in comparison to gratings and phase-scrambled images. For natural images, peak sensitivity lies at higher spatial frequencies and the slope of the high spatial frequency turn-down is much shallower. Second, adult sensitivity is higher for natural images than for the two other stimulus types. Finally, CSF for natural images is still immature for 10-year-olds and the difference in threshold between children and adults is greater for natural images than for gratings or phase-scrambled images, indicating that sensitivity to natural images develops more slowly. Given the important developmental differences between traditional measures of CS using gratings and CS measured with natural images, the latter might be more relevant for the clinical assessment of visual development and visual pathology.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".