The effects of losing an eye early in life on face and emotional expression processing
Bibliographic record
Abstract
There is a large body of research implicating structures within the right hemisphere (RH) are critical for face processing. Developmental research has shown that early in life retinal sensitivity is best in the nasal portion of the retina, which sends crossed projections from each eye to the opposite hemisphere. However, sensitivity in the temporal retina, which sends the uncrossed projections to ipsilateral cortex, develops closer to age two (Lewis & Maurer, 1990). Early visual experience is critical for normal maturation of visual function. People with early-onset congenital cataract have shown face processing deficits (Le Grand et al., 2003). Specifically, left-eye cataracts (RH deprivation), but not right-eye cataracts (left hemisphere deprivation) are related to impairments in face discrimination, showing that visual input to the RH is critical for establishing the neural substrates for face processing. Another ideal method for assessing the role of crossed connections in developing RH structures required for face processing is studying the effects of removing one eye (enucleation) shortly after birth, disconnecting that eye from the brain. As a result, left eye enucleation early in life eliminates input to the RH. We tested individuals with either left or right eye enucleation compared to binocularly and monocularly viewing controls on face discrimination and emotional expression recognition tasks. This included tests of configural, featural, contour and composite face discrimination and intensity of emotional expression recognition. Unlike congenital cataract, left-eye enucleation does not appear to disrupt face discrimination or emotional expression discrimination. Previous research has shown that unilateral enucleation actually facilitates some aspects of spatial vision compared to controls (e.g. Steeves et al., 2004). It is possible that any enhancement in spatial vision in one-eyed observers reverses potential face-processing deficits in these observers with 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".