Plasticity within excitatory and inhibitory pathways of the vestibulo-spinal circuitry guides changes in motor performance
Bibliographic record
Abstract
Investigations of behaviors with well-characterized circuitry are required to understand how the brain learns new motor skills and ensures existing behaviors remain appropriately calibrated over time. Accordingly, here we recorded from neurons within different sites of the vestibulo-spinal circuitry of behaving macaque monkeys during temporally precise activation of vestibular afferents. Behaviorally relevant patterns of vestibular nerve activation generated a rapid and substantial decrease in the monosynaptic responses recorded at the first central stage of processing from neurons receiving direct input from vestibular afferents within minutes, as well as a decrease in the compensatory reflex response that lasted up to 8 hours. In contrast, afferent responses to this same stimulation remained constant, indicating that plasticity was not induced at the level of the periphery but rather at the afferent-central neuron synapse. Strikingly, the responses of neurons within indirect brainstem pathways also remained constant, even though the efficacy of their central input was significantly reduced. Taken together, our results show that rapid plasticity at the first central stage of vestibulo-spinal pathways can guide changes in motor performance, and that complementary plasticity on the same millisecond time scale within inhibitory vestibular nuclei networks contributes to ensuring a relatively robust behavioral output.
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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 | 0.000 |
| 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".