The role of nucleus accumbens shell GABA receptors on ventral tegmental area intracranial self-stimulation and a potential role for the 5-HT <sub>2C</sub> receptor
Bibliographic record
Abstract
Brain γ-aminobutyric acid (GABA) and 5-hydroxytryptamine (5-HT)(2C) receptors are implicated in the neuronal regulation of reward- and aversion-related behaviour. Within the mesocorticolimbic pathways of the brain, relationships between GABA containing neurons and 5-HT(2C) receptor activity may be important in this context. The primary aim of this study was to investigate the role of NAc shell GABA receptors on ventral tegmental area intracranial self-stimulation (ICSS) and to examine the systemic effects of GABAergic ligands in this context. The second aim was to investigate the relationship between GABA receptor- and 5-HT(2C) receptor-related ICSS behaviour, using systemic administration of the selective agonist WAY 161503. Locomotor activity was assessed to compare the potential motor effects of drugs; feeding behaviour and intra-NAc injections of amphetamine (1.0 µg/side) were used as positive controls. When administered systemically the GABA(A) receptor agonist muscimol and antagonist picrotoxin did not selectively change ICSS reward thresholds, although the 5-HT(2C) receptor agonist WAY 161503 (1.0 mg/kg) decreased reward measures. Intra-NAc shell administration of muscimol (225 ng/side) and picrotoxin (125 ng/side), respectively, decreased and increased measures of reward. Intra-NAc shell baclofen (0-225 ng/side; GABA(B) receptor agonist) did not affect any ICSS measures although it increased feeding. Combining picrotoxin and WAY 161503 attenuated the effects of each. These results suggest that a 5-HT(2C) and GABA(A) receptor-mediated neuronal relationship in the NAc shell may be relevant for the regulation of brain reward pathways.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".