α5GABA<sub>A</sub>Receptor Activity Sets the Threshold for Long-Term Potentiation and Constrains Hippocampus-Dependent Memory
Bibliographic record
Abstract
Synaptic plasticity, which is the neuronal substrate for many forms of hippocampus-dependent learning, is attenuated by GABA type A receptor (GABA(A)R)-mediated inhibition. The prevailing notion is that a synaptic or phasic form of GABAergic inhibition regulates synaptic plasticity; however, little is known about the role of GABA(A)R subtypes that generate a tonic or persistent inhibitory conductance. We studied the regulation of synaptic plasticity by alpha5 subunit-containing GABA(A)Rs (alpha5GABA(A)Rs), which generate a tonic inhibitory conductance in CA1 pyramidal neurons using electrophysiological recordings of field and whole-cell potentials in hippocampal slices from both wild-type and null mutant mice for the alpha5 subunit of the GABA(A)R (Gabra5(-/-) mice). In addition, the strength of fear-associated memory was studied. The results showed that alpha5GABA(A)R activity raises the threshold for induction of long-term potentiation in a highly specific band of stimulation frequencies (10-20 Hz) through mechanisms that are predominantly independent of inhibitory synaptic transmission. The deletion or pharmacological inhibition of alpha5GABA(A)Rs caused no change in baseline membrane potential or input resistance but increased depolarization during 10 Hz stimulation. The encoding of hippocampus-dependent memory was regulated by alpha5GABA(A)Rs but only under specific conditions that generate moderate but not robust forms of fear-associated learning. Thus, under specific conditions, alpha5GABA(A)R activity predominates over synaptic inhibition in modifying the strength of both synaptic plasticity in vitro and certain forms of memory in vivo.
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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) | 0.002 | 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".