Muscarinic acetylcholine receptor activation prevents disinhibition-mediated LTP in the hippocampus
Bibliographic record
Abstract
Disinhibition-mediated long-term potentiation (LTP) in the CA1 region of the hippocampus involves GABAergic synaptic plasticity at feedforward inhibitory inputs, resulting in the reduced shunting of glutamatergic excitatory currents. The GABAergic plasticity which underlies disinhibition-mediated LTP results from a Ca(2+)-dependent decrease in the activity of the K(+)-Cl(-) cotransporter (KCC2), depolarizing the reversal potential for GABAA receptor-mediated currents (EGABA), thereby attenuating inhibition. Muscarinic acetylcholine receptor (mAChR) activation has previously been shown to regulate classic glutamatergic LTP, modulate intracellular [Ca(2+)] and signaling, and facilitate the excitability of GABAergic interneurons in the CA1. Based on these effects, and the ability of mAChR activation to regulate CA1 pyramidal neuron KCC2 expression, we proposed that mAChR activation would modulate disinhibition-mediated LTP. To test this prediction, we made whole cell recordings from CA1 pyramidal neurons in hippocampal slices. Disinhibition-mediated LTP was induced using a spike timing-dependent plasticity (STDP) protocol, which involved coincident pre-synaptic stimulation and post-synaptic current injection (at 5 Hz for 60 s). We found that mAChR activation via carbachol (CCh) prevented the induction of disinhibition-mediated LTP. Moreover, in the presence of CCh, EGABA failed to depolarize following plasticity induction. Lastly, we recorded the paired-pulse ratio (PPR) during the induction of disinhibition-mediated LTP and found that in the presence of CCh, plasticity induction induced a significant paired-pulse depression. This suggests that pre-synaptic mAChR activation may prevent the post-synaptic expression of disinhibition-mediated LTP.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.002 |
| 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".