Dopamine Preferentially Inhibits NMDA Receptor-Mediated EPSCs by Acting on Presynaptic D1 Receptors in Nucleus Accumbens during Postnatal Development
Bibliographic record
Abstract
Nucleus accumbens (nAcb), a major site of action of drugs of abuse and dopamine (DA) signalling in MSNs (medium spiny neurons), is critically involved in mediating behavioural responses of drug addiction. Most studies have evaluated the effects of DA on MSN firing properties but thus far, the effects of DA on a cellular circuit involving glutamatergic afferents to the nAcb have remained rather elusive. In this study we attempted to characterize the effects of dopamine (DA) on evoked glutamatergic excitatory postsynaptic currents (EPSCs) in nAcb medium spiny (MS) neurons in 1 to 21 day-old rat pups. The EPSCs evoked by local nAcb stimuli displayed both AMPA/KA and NMDA receptor-mediated components. The addition of DA to the superfusing medium produced a marked decrease of both components of the EPSCs that did not change during the postnatal period studied. Pharmacologically isolated AMPA/KA receptor-mediated response was inhibited on average by 40% whereas the isolated NMDA receptor-mediated EPSC was decreased by 90%. The effect of DA on evoked EPSCs were mimicked by the D1-like receptor agonist SKF 38393 and antagonized by the D1-like receptor antagonist SCH 23390 whereas D2-like receptor agonist or antagonist respectively failed to mimic or to block the action of DA. DA did not change the membrane input conductance of MS neurons or the characteristics of EPSCs produced by the local administration of glutamate in the presence of tetrodotoxin. In contrast, DA altered the paired-pulse ratio of evoked EPSCs. The present results show that the activation D1-like dopaminergic receptors modulate glutamatergic neurotransmission by preferentially inhibiting NMDA receptor-mediated EPSC through presynaptic mechanisms.
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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".