Control of synaptic specificity by limiting promiscuous synapse formation
Bibliographic record
Abstract
SUMMARY The ability of neurons to distinguish appropriate from inappropriate synaptic partners in their local environment is fundamental to the proper assembly and function of neural circuits. How synaptic partner selection is regulated is a longstanding question in Neurobiology. A prevailing hypothesis is that appropriate partners express complementary molecules that match them together and promote synaptogenesis. Dpr and DIP IgSF proteins bind heterophilically and are expressed in a complementary manner between synaptic partners in the Drosophila visual system. Here, we show that in the lamina, DIP mis-expression is sufficient to promote synapse formation with Dpr-expressing neurons, and that DIP proteins are not necessary for synaptogenesis but rather function to prevent ectopic synapse formation. These findings indicate that Dpr-DIP interactions regulate synaptic specificity by biasing synapse formation towards specific cell-types. We propose that synaptogenesis occurs independent of synaptic partner choice, and that precise synaptic connectivity is established by limiting promiscuous synapse 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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".