Computational Studies of Gain Modification by Serotonin in Pyramidal Neurons of Prefrontal Coxtex
Bibliographic record
Abstract
Serotonin (5-HT) is widely implicated in brain functions and diseases, but the cellular mechanisms underlying 5-HT functions in the brain are not well understood (Zhang and Arsenault, 2005). Recent experiments (Zhang and Arsenault, 2005) have shown that 5-HT substantially increased the slope (gain) of the firing rate current (F-I) curve in layer 5 pyramidal neurons of the rat prefrontal cortex and this effect was limited to the range of firing rate (0-10 Hz) that is known to behaviourally relevant. Furthermore, it was found that 5-HT mediated gain increase was due to a reduction of the afterhyperpolarization (AHP) and an induction of the slow afterdepolarization (ADP), regardless of changes in the membrane potential, the input resistance or the properties of action potentials. To investigate this frequency-dependent gain modulation of 5-HT on the prefrontal cortex neurons, conductance-based Hodgkin-Huxley type models of the regular spiking (RS) cells in the prefrontal cortex are developed using a step by step approach. We first show that a model with an A current displays a square-root form F-I curve with higher slope at low frequency. However, for the same range of current injection steps used in experiment, the frequency range goes beyond 20 Hz, suggesting the presence of other hyperpolarizing currents in the model. As suggested by the experiment (Zhang and Arsenault, 2005), AHP currents (fast AHP, medium AHP and slow AHP) are included in the model to simulate 5-HT effect. Simulations show that AHP currents effectively linearize the F-I curve and decrease the slope of F-I curve in general, thus reducing the neuronal excitability. Since the slow AHP current is a target of 5-HT, the strength of this current is reduced gradually and the F-I curves are plotted together for comparison. The results indicate that with decreasing slow AHP strength, the current thresholds for repetitive spiking decreases and the slopes of the F-I curves increase in general. A square-root form F-I curve is not evident until the slow AHP current is blocked completely. This suggests that the medium AHP current also play a role in linearizing the F-I curve besides the slow AHP current. Based on current findings, a full model with both A current and AHP currents is being constructed to match the experimental data more closely so the mechanism of 5-HT on gain modulation of prefrontal cortical neurons can be better understood.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".