Delayed expression of activity-dependent gating switch in synaptic AMPARs at a central synapse
Bibliographic record
Abstract
Abstract Developing central synapses exhibit robust plasticity and undergo experience-dependent remodeling. Evidently, synapses in sensory systems such as auditory brainstem circuits mature rapidly to achieve high-fidelity neurotransmission for sound localization. This depends on a developmental switch in AMPAR composition from slow-gating GluA1-dominant to fast-gating GluA4-dominant, but the mechanisms underlying this switch remain unknown. We hypothesize that patterned stimuli mimicking spontaneous/sound evoked activity in the early postnatal stage drives this gating switch. We examined activity-dependent changes in evoked and miniature excitatory postsynaptic currents (eEPSCs and mEPSCs) at the calyx of Held synapse by breaking through the postsynaptic membrane at different time points following 2 min of theta burst stimulation (TBS) to afferents in mouse brainstem slices. We found the decay time course of eEPSCs accelerated, but this change was not apparent until > 30 min after TBS. Histogram analyses of the decay time constants of mEPSCs for naive and tetanized synapses revealed two populations centered around τfast ≈ 0.4 and 0.8 ms, but the relative weight of the τ0.4 population over the τ0.8 population increased significantly only in tetanized synapses. Such changes are blocked by NMDAR or mGluR1/5 antagonists or inhibitors of CaMKII, PKC and protein synthesis, and more importantly precluded in GluA4−/− synapses, suggesting GluA4 is the substrate underlying the acceleration. Our results demonstrate a novel form of plasticity working through NMDAR and mGluR activation to trigger a gating switch of AMPARs with a temporally delayed onset of expression, ultimately enhancing the development of high-fidelity synaptic transmission.
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".