6-Containing GABAA Receptors Are the Principal Mediators of Inhibitory Synapse Strengthening by Insulin in Cerebellar Granule Cells
Bibliographic record
Abstract
Activity-dependent strengthening of central synapses is a key factor driving neuronal circuit behavior in the vertebrate CNS. At fast inhibitory synapses, strengthening is thought to occur by increasing the number of GABAA receptors (GABARs) of the same subunit composition to preexisting synapses. Here, we show that strengthening of mouse cerebellar granule cell GABAergic synapses occurs by a different mechanism. Specifically, we show that the neuropeptide hormone, insulin, strengthens inhibitory synapses by recruiting α6-containing GABARs rather than accumulating more α1-containing receptors that are resident to the synapse. Because α6-receptors are targeted to functionally distinct postsynaptic sites from α1-receptors, we conclude that only a subset of all inhibitory synapses are strengthened. Together with our recent findings on stellate cells, we propose a general mechanism by which mature inhibitory synapses are strengthened. In this scenario, α1-GABARs resident to inhibitory synapses form the hardwiring of neuronal circuits with receptors of a different composition fulfilling a fundamental, but unappreciated, role in synapse strengthening.
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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 | 0.000 |
| 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 | 0.001 |
| 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".