Training improves orientation-in-noise thresholds in an animal model of amblyopia
Bibliographic record
Abstract
Binocular visual experience is necessary for the normal fine tuning of neural circuits in the visual cortex and the emergence of optimal signal-to-noise processing. A number of studies have suggested that the loss of visual acuity and contrast sensitivity after early monocular deprivation are a result of increased neural noise in the visual cortex. Here, our purpose is to determine the long-term effects of early monocular deprivation on neural signal-to-noise and whether intensive training with a visual signal-in-noise stimulus can ameliorate the visual deficits. We reared cats with either normal vision or a short period (2 weeks) of monocular deprivation early in the critical period. We then compared the impact of early training with a noise-free or noisy stimulus by measuring the developmental trajectory for grating acuity from one litter and orientation-in-noise thresholds from the other litter. The short period of monocular deprivation did not alter the developmental trajectory for either stimulus, or the adult grating acuity. Brief deprivation did, however, lead to poorer adult performance on the noise stimulus. Compared to normal cats, the deprived eye of cats with early training on noise required 10–15% more orientation signal to discriminate the target from noise. Surprisingly, even the non-deprived eye was affected, requiring 5–10% more orientation signal at threshold. Next, we measured orientation-in-noise thresholds for cats trained on grating acuity during development. Their thresholds were substantially worse, needing ∼ 30–50% more signal to make the discrimination; but after 2-3 weeks of intensive daily training, the thresholds began to improve. These findings reveal a prolonged development for the maturation of visual signal-in-noise processing with the deprived eye deficit not apparent until many weeks after the end of monocular deprivation. Finally, intensive training during development, or in young adults, can ameliorate much of the noise discrimination deficit caused by early visual deprivation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".