Bibliographic record
Abstract
Abstract Information is coded in the brain as patterns of electrical impulses that are transmitted along nerve processes. These impulses are passed from one neuron to the next primarily at chemical synapses where the electrical event is converted to the release of a neurotransmitter substance that activates the next neuron in the pathway. Neurotransmitter release is triggered by the opening of ‘voltage‐sensitive’ calcium channels, the admission of a pulse of Ca 2+ ions and the binding of these ions to the neurotransmitter secretion apparatus culminating in the fusion and discharge of a transmitter‐filled secretory vesicle. Increasing evidence suggests that at many synapses an individual release site is gated by ion influx through one or a few nearby calcium channels while at others Ca 2+ from many channels summates to drive release. In this section, we explore the physiology of this impulse‐to‐secretion gating mechanism. Key Concepts Information is transmitted between one neuron and the next at synapses where an upstream (presynaptic) neuron interacts with the membrane of the downstream (postsynaptic) one. Synapses transmit by secreting a chemical neurotransmitter, often across a narrow space (cleft) between pre‐ and postsynaptic surface membranes. Most neurotransmitters are stored in tiny membrane ‘packets’ called synaptic vesicles which can be triggered to secrete by fusing with the presynaptic membrane. The synaptic vesicles are ‘docked’ at the release site ready for secretion which is dependent upon a large local increase in [Ca 2+ ]. Transmitter secretion is triggered by an electrical impulse that travels down the presynaptic axon or into a dendrite to release sites. Influx of calcium ions through Ca 2+ selective, voltage‐sensitive ion channels links the voltage transient of the action potential to the triggering of secretory vesicle discharge. Ca 2+ channels are positioned very close to the secretory vesicles so that when they open the spurt of entering Ca 2+ ions, called a ‘calcium domain’, can rapidly and effectively access the triggering sites for synaptic vesicle fusion.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".