GluN2B-mediated regulation of silent synapses for receptor specification and addiction memory
Bibliographic record
Abstract
Abstract Psycho-stimulants including cocaine elicit stereotyped, addictive behaviors. Re-emergence of silent synapses containing only NMDA-type glutamate receptors (NMDARs) is a critical mediator of addiction memory and seeking behaviors. Despite the predominant abundance of GluN2B-containing NMDARs in silent synapses, their operational mechanisms are not fully understood. Using conditional depletion/deletion of GluN2B at D1-expressing accumbal medium spiny neurons, we examine the synaptic and behavioral actions that silent synapses incur after repeated exposure to cocaine. GluN2B ablation reduces the proportion of silent synapses, but some of them can persist by substitution to GluN2C, which drives the aberrantly-facilitated synaptic incorporation of calcium-impermeable AMPA-type glutamate receptors (AMPARs). The resultant precocious maturation of silent synapses impairs addiction memory but elevates locomotor activity, which can be normalized by blockade of calcium-impermeable AMPAR trafficking. Collectively, GluN2B supports the competence of cocaine-induced silent synapses for specifying subunit composition of AMPARs, and thereby expression of addition memory and the related behaviors.
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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) | 0.002 | 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".