α5GABA<sub>A</sub> Receptors Regulate the Intrinsic Excitability of Mouse Hippocampal Pyramidal Neurons
Bibliographic record
Abstract
GABA(A) receptors generate both phasic and tonic forms of inhibition. In hippocampal pyramidal neurons, GABA(A) receptors that contain the alpha5 subunit generate a tonic inhibitory conductance. The physiological role of this tonic inhibition is uncertain, although alpha5GABA(A) receptors are known to influence hippocampal-dependent learning and memory processes. Here we provide evidence that alpha5GABA(A) receptors regulate the strength of the depolarizing stimulus that is required to generate an action potential in pyramidal neurons. Neurons from alpha5 knock-out (alpha5-/-) and wild-type (WT) mice were studied in brain slices and cell cultures using whole cell and perforated-patch-clamp techniques. Membrane resistance was 1.6-fold greater in alpha5-/- than in WT neurons, but the resting membrane potential and chloride equilibrium potential were similar. Membrane hyperpolarization evoked by an application of exogenous GABA was greater in WT neurons. Inhibiting the function of alpha5GABA(A) receptor with nonselective (picrotoxin) or alpha5 subunit-selective (L-655,708) compounds depolarized WT neurons by approximately 3 mV, whereas no change was detected in alpha5-/- neurons. The depolarizing current required to generate an action potential was twofold greater in WT than in alpha5-/- neurons, whereas the slope of the input-output relationship for action potential firing was similar. We conclude that shunting inhibition mediated by alpha5GABA(A) receptors regulates the firing of action potentials and may synchronize network activity that underlies hippocampal-dependent behavior.
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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 | 0.001 |
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".