Dynamics of glutamatergic synapses in the medial vestibular nucleus of the mouse
Bibliographic record
Abstract
During sinusoidal rotation or translation, primary vestibular afferents modulate their discharge rates at the frequency of motion, effectively transmitting frequency-modulated (FM) signals. This study indicates a possible role for excitatory synapses in the processing of FM signals by vestibular brainstem pathways. Inputs to medial vestibular neurons were activated with FM pulse trains, while inhibitory transmission was blocked. The relationship between the presynaptic pulse rate and the postsynaptic membrane potential was found to be linear within a range of pulse rates. Short-term plasticity was a factor contributing to sensitivity at higher modulating frequencies. The amount of low-pass filtering was correlated with excitatory postsynaptic potential (EPSP) shape, which affected temporal summation during the train. Although the NMDA component of glutamatergic transmission affected EPSP shape, it made only a minor contribution to the dynamics of synaptic transmission. Most responses showed low-pass filtering over the entire 1-16 Hz range. Overall, excitatory synapses in the medial vestibular nucleus contribute a low-pass filter to central vestibular processing and complement the high-pass filtering that is introduced both by peripheral vestibular dynamics and by the intrinsic dynamics of secondary vestibular neurons.
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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 | 0.001 | 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".