Cholinergic excitation in mouse primary vs. associative cortex: region‐specific magnitude and receptor balance
Bibliographic record
Abstract
Cholinergic stimulation of the cerebral cortex is essential for tasks requiring attention; however, there is still some debate over which cortical regions are required for such tasks. There is extensive cholinergic innervation of both primary and associative cortices, and transient release of acetylcholine (ACh) is detected in deep layers of the relevant primary and/or associative cortex, depending on the nature of the attention task. Here, we investigated the electrophysiological effects of ACh in layer VI, the deepest layer, of the primary somatosensory cortex, the primary motor cortex, and the associative medial prefrontal cortex. Layer VI pyramidal neurons are a major source of top-down modulation of attention, and we found that the strength and homogeneity of their direct cholinergic excitation was region-specific. On average, neurons in the primary cortical regions showed weaker responses to ACh, mediated by a balance of contributions from both nicotinic and muscarinic ACh receptors. Conversely, neurons in the associative medial prefrontal cortex showed significantly stronger excitation by ACh, mediated predominantly by nicotinic receptors. The greatest diversity of responses to ACh was found in the primary somatosensory cortex, with only a subset of neurons showing nicotinic excitation. In a mouse model with attention deficits only under demanding conditions, cholinergic excitation was preserved in primary cortical regions but not in the associative medial prefrontal cortex. These findings demonstrate that the effect of ACh is not uniform throughout the cortex, and suggest that its ability to enhance attention performance may involve different cellular mechanisms across cortical regions.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".