Effects of serotonin on the intrinsic membrane properties of layer II medial entorhinal cortex neurons
Bibliographic record
Abstract
Although serotonin (5-HT) is an important neuromodulator in the superficial layers of the medial entorhinal cortex (mEC), there is some disagreement concerning its influences upon the membrane properties of neurons within this region. We performed whole cell recordings of mEC Layer II projection neurons in rat brain slices in order to characterize the intrinsic influences of 5-HT. In current clamp, 5-HT evoked a biphasic response consisting of a moderately short latency and large amplitude hyperpolarization followed by a slowly developing, long lasting, and small amplitude depolarization. Correspondingly, in voltage clamp, 5-HT evoked a robust outward followed by a smaller inward shift of holding current. The outward current evoked by 5-HT showed a consistent current/voltage (I/V) relationship across cells with inward rectification, and demonstrating a reversal potential that was systematically dependent upon the extracellular concentration of K(+), suggesting that it was predominantly carried by potassium ions. However, the inward current showed a less consistent I/V relationship across different cells, suggesting multiple independent ionic mechanisms. The outward current was mediated through activation of 5-HT(1A) receptors via a G-protein dependent mechanism while inward currents were evoked in a 5-HT(1A)-independent fashion. A significant proportion of the inward current was blocked by the I(h) inhibitor ZD7288 and appeared to be due to 5-HT modulation of I(h) as 5-HT shifted the activation curve of I(h) in a depolarizing fashion. Serotonin is thus likely to influence, in a composite fashion, the information processing of Layer II neurons in the mEC and thus, the passage of neocortical information via the perforant pathway to the hippocampus.
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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) | 0.001 | 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".