Deficient responses from the lateral geniculate nucleus in humans with amblyopia
Bibliographic record
Abstract
Amblyopia or lazy eye is the most common cause of uniocular blindness in adults. It is caused by a disruption to normal visual development as a consequence of unmatched inputs from the two eyes in early life, arising from a turned eye (strabismus), unequal refractive error (anisometropia) or form deprivation (e.g. cataract). Animal models based on extracellular recordings in anesthetized animals suggest that the earliest site of the anomaly in the primate visual pathway is the primary visual cortex (corresponding to the striate cortex, cytoarchitectonic area 17 and area V1), which is where inputs from the two eyes are first combined in an excitatory fashion, whereas more distal and monocular processing structures such as the retina and lateral geniculate nucleus (LGN) are normal. Using high-field functional magnetic resonance imaging in a group of human adults with amblyopia, we demonstrate that functional deficits are first observable at a thalamic level, that of the LGN. Our results suggest the need to re-evaluate the current models of amblyopia that are based on the assumption of a purely cortical dysfunction, as well as the role for the LGN in visual development.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".