Altered white matter structure in auditory tracts following early monocular enucleation
Bibliographic record
Abstract
PURPOSE: Similar to early blindness, monocular enucleation (the removal of one eye) early in life results in crossmodal behavioral and morphological adaptations. Previously it has been shown that partial visual deprivation from early monocular enucleation results in structural white matter changes throughout the visual system (Wong et al., 2018). The current study investigated structural white matter of the auditory system in adults who have undergone early monocular enucleation compared to binocular control participants. METHODS: We reconstructed four auditory and audiovisual tracts of interest using probabilistic tractography and compared microstructural properties of these tracts to binocularly intact controls using standard diffusion indices. RESULTS: Although both groups demonstrated asymmetries in indices in intrahemispheric tracts, monocular enucleation participants showed asymmetries opposite to control participants in the auditory and A1-V1 tracts. Monocular enucleation participants also demonstrated significantly lower fractional anisotropy in the audiovisual projections contralateral to the enucleated eye relative to control participants. CONCLUSIONS: Partial vision loss from early monocular enucleation results in altered structural connectivity that extends into the auditory system, beyond tracts primarily dedicated to vision.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".