Vestibulo-ocular reflex gain improvements at peak head acceleration and velocity following onset of unilateral vestibular neuritis: Insights into neural compensation mechanisms
Bibliographic record
Abstract
BACKGROUND AND AIMS: An acute unilateral peripheral vestibular deficit (aUPVD) due to vestibular neuritis causes deficient yaw axis vestibular ocular reflex (VOR) gains. Using video head impulse tests (vHITs), we examined phasic and tonic velocity gains of the VOR over time to determine if these differed at onset and during subsequent improvement. METHODS: The VOR responses of 61 patients were examined within 5 days of aUPVD onset, and 3 and 7 weeks later using vHIT with mean peak yaw angular velocities of 177°/s (sd 45°/s) and mean peak accelerations of 3660°/s2 (sd 1300°/s2). The phasic velocity or acceleration gain (aG) was computed as the ratio of eye to head velocity around peak head acceleration, and the tonic velocity gain (vG) was calculated as the same ratio around peak head velocity. RESULTS: aG increased ipsi-deficit from 0.45 at onset to 0.67 at 3 weeks and 7 weeks later, and vG increased ipsi-deficit from 0.29 to 0.51 and 0.53, respectively, yielding a significant time effect (p < 0.001). Deficit side aG was significantly greater (p < 0.001) than vG at all time points. Deficit side gain improvements in aG and vG were similar. Contra-deficit aG increased from 0.86 to 0.95 and 0.94 at 3 weeks and 7 weeks, and vG contra-deficit increased from 0.84, to 0.89 and 0.87, respectively, also yielding a significant time effect (p = 0.004). Contra-deficit aG and vG were normal at 3 weeks. Mean canal paresis values improved from 91% to 67% over the 7 weeks. CONCLUSIONS: Acceleration and velocity VOR gains on the deficit side are reduced by aUPVD and improve most in the first 3 weeks after aUPVD onset. Deficit side aG is consistently higher than deficit side vG following an aUPVD, suggesting that acceleration rather than velocity sensitive compensatory neural mechanisms are predominant during the compensation process for aUPVD.
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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".