Focal acetylcholinergic modulation of the human midcingulo‐insular network during attention: Meta‐analytic neuroimaging and behavioral evidence
Bibliographic record
Abstract
The basal forebrain cholinergic neurons provide acetylcholine to the cortex via large projections. Recent molecular imaging work in humans indicates that the cortical cholinergic innervation is not uniformly distributed, but rather may disproportionately innervate cortical areas relevant to supervisory attention. In this study, we therefore reexamined the spatial relationship between acetylcholinergic modulation and attention in the human cortex using meta-analytic strategies targeting both pharmacological and non-pharmacological neuroimaging studies. We found that pharmaco-modulation of acetylcholine evoked both increased activity in the anterior cingulate and decreased activity in the opercular and insular cortex. In large independent meta-analyses of non-pharmacological neuroimaging research, we demonstrate that during attentional engagement these cortical areas exhibit (1) task-related co-activation with the basal forebrain, (2) task-related co-activation with one another, and (3) spatial overlap with dense cholinergic innervations originating from the basal forebrain, as estimated by multimodal positron emission tomography and magnetic resonance imaging. Finally, we provide meta-analytic evidence that pharmaco-modulation of acetylcholine also induces a speeding of responses to targets with no apparent tradeoff in accuracy. In sum, we demonstrate in humans that acetylcholinergic modulation of midcingulo-insular hubs of the ventral attention/salience network via basal forebrain afferents may coordinate selection of task relevant information, thereby facilitating cognition and 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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".