Effects of sustained serotonin reuptake inhibition on the firing of dopamine neurons in the rat ventral tegmental area
Bibliographic record
Abstract
BACKGROUND: Selective serotonin (5-HT) reuptake inhibitors (SSRIs) are efficacious in depression because of their ability to increase 5-HT neurotransmission. However, owing to a purported inhibitory effect of 5-HT on dopamine (DA) neuronal activity in the ventral tegmental area (VTA), this increase in 5-HT transmission might result in a suppression of the firing activity of DA neurons. Since the mesolimbic DA system plays an important role in motivation and reward, a potential decrease in the firing of DA neurons may lead, in some patients, to a lack of adequate response to SSRIs. METHODS: We administered the SSRIs citalopram or escitalopram in rats. We determined DA neuronal activity using in-vivo electrophysiology. RESULTS: Sustained administration of escitalopram robustly decreased the firing rate and burst activity of DA neurons. There was no difference in the mean number of spontaneously active DA neurons per tract among the 3 groups (citalopram, escitalopram, control). This inhibition was reversed by the selective 5-HT(2C) receptor antagonist SB 242084. Citalopram, however, did not alter the overall firing rate but inhibited the burst activity of DA neurons. LIMITATIONS: Our experiments were carried out with the rats under general anesthesia. Therefore, under such conditions the absolute changes produced by SSRIs may heve been different from those occurring in freely moving rats. The exact location of the 5-HT(2C) receptors mediating the inhibitory effects of the SSRIs could not be determined in these studies. CONCLUSION: The difference between escitalopram and citalopram in their effect on DA neuronal activity may be explained by the higher efficacy of escitalopram as a 5-HT reuptake inhibitor. Since the inhibitory effect of escitalopram on DA neuronal activity is mediated via 5-HT(2C) receptors, antagonists of these receptors might be effective adjuncts in SSRI-resistant depression.
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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".