Synapse-specific burst coding sustained by local axonal translation
Bibliographic record
Abstract
Neurotransmission in the brain is unreliable, suggesting that high-frequency spike bursts rather than individual spikes carry the neural code. For instance, cortical pyramidal neurons rely on bursts in memory formation. Protein synthesis is another key factor in long-term synaptic plasticity and learning but is widely considered unnecessary for synaptic transmission. Here, however, we show that burst neurotransmission at synapses between neocortical layer 5 pyramidal cells depends on axonal protein synthesis linked to presynaptic NMDA receptors and mTOR. We localized protein synthesis to axons with laser axotomy and puromycylation live imaging. We whole-cell recorded connected neurons to reveal how translation sustained readily releasable vesicle pool size and replenishment rate. We live imaged axons and found sparsely docked RNA granules, suggesting synapse-specific regulation. In agreement, translation boosted neurotransmission onto excitatory but not inhibitory basket or Martinotti cells. Local axonal mRNA translation is thus a hitherto unappreciated principle for sustaining burst coding at specific synapse types.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".