Calcium Sensitivity of Neurotransmitter Release Differs at Phasic and Tonic Synapses
Bibliographic record
Abstract
The efficacy of synaptic transmission varies greatly among synaptic contacts. We have explored the origins of differences between phasic and tonic crustacean neuromuscular junctions. Synaptic boutons of a phasic motor neuron release three orders of magnitude more quanta to a single action potential and show strong depression to a train, whereas tonic synapses are nearly unresponsive to single action potentials and display an immense facilitation. Phasic and tonic synapses display a similar nonlinear dependence on extracellular [Ca2+]. We imposed similar spatially uniform intracellular [Ca2+] ([Ca2+]i) steps in phasic and tonic synapses by photolysis of presynaptic caged calcium. [Ca2+]i was measured fluorometrically while transmitter release was monitored electrophysiologically from single boutons in which the [Ca2+]i was elevated. Phasic synapses released the readily releasable pool (RRP) of vesicles at a much higher rate and with a shorter delay than did tonic synapses. Comparison of several kinetic models of molecular events showed that a difference in Ca2+-sensitive priming of vesicles in the RRP combined with a revision of the kinetic Ca2+-binding sequence to the secretory trigger produced the best fit to the markedly different responses to Ca2+ steps and action potentials and of the characteristic features of synaptic plasticity in phasic and tonic synapses. The results reveal processes underlying one aspect of synaptic diversity that may also regulate changes in synaptic strength during development and learning and memory formation.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".