Long‐term depression requires postsynaptic AMPA GluR2 receptor in adult mouse cingulate cortex
Bibliographic record
Abstract
Synaptic long-term depression (LTD) is thought to be important for various brain functions such as learning, memory, and development. Although anterior cingulated cortex (ACC) has been demonstrated to contribute to learning and memory, no studies has been reported about the synaptic mechanisms for cingulate LTD. Here, we used integrative genetic, pharmacological and electrophysiological approaches to demonstrate that AMPA GluR2, but not GluR3, subunit is critical for cingulate LTD. We found that LTD was absent in adult cingulate slices of GluR2 knockout mice. Furthermore, postsynaptic injections of peptides that inhibit AMPA GluR2-PDZ interactions blocked the induction of LTD. To determine if the requirement for AMPA receptor-PDZ interaction is time-dependent, we injected the same inhibiting peptide into the postsynaptic cells 5 min after the induction of LTD. We found that LTD was not affected by the peptide, providing the first evidence that postsynaptic AMPA GluR2-mediated depression occurs rapidly (within t = 5 min). Genetic deletion of GluR3 did not affect cingulate LTD. Our results provide the first study of cingulate LTD mechanism using whole-cell patch-clamp recording in adult cortical slices and demonstrate that postsynaptic AMPA GluR2 subunit is crucial for synaptic depression in the ACC of adult mice.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".