Cerebellar skew deviation and the torsional vestibuloocular reflex
Bibliographic record
Abstract
BACKGROUND: Skew deviation is typically caused by brainstem damage, and has not been identified with focal cerebellar lesions. This vertical strabismus has been attributed to asymmetric disruption of vestibuloocular reflex (VOR) projections from otolithic receptors of the utricle to ocular motoneurons, but asymmetry of the utriculo-ocular counter-roll reflex has not been detected. METHODS: Lesions localized to the cerebellum were identified by MRI in five patients with vertical strabismus. Their skew deviation was measured by prism cover tests in all patients and by search coils in three patients. The angular VOR was tested in patients and 10 controls during sinusoidal +/- 10 degree torsional, vertical, and horizontal head-on-body rotations at 0.5, 1, and 2 Hz. Static torsional VOR gain was measured by the change in torsional eye position divided by change in head position during maintained head tilt. RESULTS: Static torsional VOR gains were asymmetric in each patient. Three patterns of asymmetry were identified: 1) decreased static gain in one eye in both directions; 2) decreased gains in both eyes in one direction; and 3) asymmetric gain in one direction in one eye alone. Dynamic torsional VOR gains were symmetrically reduced in both directions in both eyes in all patients. CONCLUSIONS: Focal cerebellar lesions can cause skew deviation. The static torsional vestibuloocular reflex (VOR) is linked to cerebellar control of vertical vergence. Asymmetry between the eyes or in direction of the static torsional VOR provides evidence that monocular or binocular imbalance of the utriculo-ocular reflex leads to cerebellar skew deviation.
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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 | 0.000 |
| 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".