The Influence of Release Modality on Synaptic Transmission at a Developing Central Synapse
Bibliographic record
Abstract
The auditory brainstem is comprised of a number of synapses specialized for the transmission of high-fidelity synaptic signals. Within the first three postnatal weeks, these pathways acquire the ability to process high-frequency signals without compromising timing information. However, little is known regarding developmental adaptations which confer this ability. Situated in the sound localization pathway, the calyx of Held-medial nucleus of the trapezoid body synapse provides an ideal model for investigating such adaptations as both the pre- and postsynaptic neurons are accessible to electrophysiological experimentation. Using this synapse, we have shown herein that the spatial coupling between voltage-gated calcium channels (VGCCs) and synaptic vesicles (SVs) tightens during development. Immature synapses use a loosely-coupled arrangement of many N- and P/Q-type VGCCs (“microdomain” modality) while mature synapses use a tightly-coupled arrangement of fewer P/Q-type VGCCs, to release SVs (“nanodomain” modality). As a consequence of this tightening, synaptic delay (SD) shortens. By fluorescence- and electron microscopy of SVs near active zones, we further identified the filamentous protein septin 5 as a molecular substrate, differentiating the two release modalities, which may act as a spatial barrier separating VGCCs and SVs in immature synapses. Finally, we have demonstrated that changes in release modality affect the nature of short-term plasticity observed at this synapse. Using trains of action potentials as presynaptic voltage-commands, we showed that, downstream of calcium influx, the microdomain modality promotes short-term facilitation in excitatory postsynaptic currents (IEPSC), and calcium-dependent decreases in SD, with these being absent in synapses employing the nanodomain modality. In contrast, we found that as a result of depletion of SVs, short-term depression of IEPSC dominates in synapses using the nanodomain modality, and correlates with calcium-dependent increases in SD.\n\tThese findings imply that the type of release modality has a significant impact on the strength and timing of synaptic responses. The microdomain modality imparts greater dynamic range in timing and strength, but does so at the cost of efficiency and fidelity, while the nanodomain modality is a key accomplishment consolidating the high-fidelity abilities of this synapse.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".