Gain modulation by serotonin in pyramidal neurones of the rat prefrontal cortex
Bibliographic record
Abstract
Serotonin (5-HT) is widely implicated in brain functions and diseases. The vertebrate brain is extensively innervated by 5-HT fibres originating from the brain stem, and 5-HT axon terminals interact with other neurones in complex ways. The cellular mechanisms underlying 5-HT function in the brain are not well understood. The present study examined the effect of 5-HT on the responsiveness of neurones in the neocortex. Using patch-clamp recording in acute slices, we showed that 5-HT substantially increased the slope (gain) of the firing rate-current curve in layer 5 pyramidal neurones of the rat prefrontal cortex. The effect of 5-HT on gain is confined to the range of firing rate (0-10 Hz) that is known to be behaviourally relevant. 5-HT also changed current threshold for spike train generation, but this effect was inconsistent, and was independent of the effect on gain. The gain modulation by 5-HT was mediated by 5-HT2 receptors, and involved postsynaptic mechanisms. 5-HT2-mediated gain increase could not be attributed to changes in the membrane potential, the input resistance or the properties of action potentials, but was associated with a reduction of the afterhyperpolarization and an induction of the slow afterdepolarization. Blocking Ca2+ entry with Cd2+ increased the gain by itself and blocked 5-HT2- mediated gain increase. Buffering [Ca2+](i) with 25 mM EGTA also substantially reduced 5-HT2- mediated gain increase. Noradrenaline, which blocked the afterhyperpolarization, also induced a moderate increase in gain. Together, our results suggest that 5-HT may regulate the dynamics of cortical circuits through multiplicative scaling.
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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) | 0.000 | 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".