Rapid switching of vestibulo-motor pathways through voluntary eyelid closure in primates
Bibliographic record
Abstract
Understanding how the brain adjusts movement control based on context is key to explaining adaptive behavior. The vestibulo-ocular reflex (VOR), with its well-defined circuitry, demonstrates adaptability-its primary role in stabilizing vision is suppressed when gaze redirection is required but remains resilient even in complete darkness. Here, we investigated VOR responses during intentional eye closure, when the need for visual stabilization is volitionally removed. Using scleral search coils, we measured human VOR responses and found a rapid ~36-90% reduction across movement directions when participants voluntarily closed their eyes, indicating a broad disruption of VOR pathways. This attenuation coincided with eyelid closure and persisted until the eyes reopened. Parallel experiments in monkeys confirmed these findings, ruling out mechanical factors and revealing a conserved neural mechanism across primates. Moreover, attempts to open restrained eyelids increased VOR gains, suggesting that motor commands for eye opening influence vestibular processing even without eyelid movement. These results demonstrate rapid, sustained VOR suppression linked to eyelid motor control, highlighting an energy-efficient neural strategy that dynamically adjusts sensory-motor processing when visual stabilization is certain to be unnecessary.
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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 | 0.000 |
| 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) | 0.001 | 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".