Plasticity of Prefrontal Attention Circuitry: Upregulated Muscarinic Excitability in Response to Decreased Nicotinic Signaling Following Deletion of α5 or β2 Subunits
Bibliographic record
Abstract
Attention depends on cholinergic stimulation of nicotinic and muscarinic acetylcholine receptors in the medial prefrontal cortex. Pyramidal neurons in layer VI of this region express cholinergic receptors of both families and play an important role in attention through their feedback projections to the thalamus. Here, we investigate how nicotinic and muscarinic cholinergic receptors affect the excitability of these neurons using whole-cell recordings in acute brain slices of prefrontal cortex. Since attention deficits have been documented in both rodents and humans having genetic abnormalities in nicotinic receptors, we focus in particular on how the cholinergic excitation of layer VI neurons is altered by genetic deletion of either of two key nicotinic receptor subunits, the accessory α5 subunit or the ligand-binding β2 subunit. We find that the cholinergic excitation of layer VI neurons is dominated by nicotinic receptors in wild-type mice and that the reduction or loss of this nicotinic stimulation is accompanied by a surprising degree of plasticity in excitatory muscarinic receptors. These findings suggest that disrupting nicotinic receptors fundamentally alters the mechanisms and timing of excitation in prefrontal attentional circuitry.
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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 | 0.000 |
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".