Noradrenergic regulation of cue-guided decision making and impulsivity is doubly dissociable across frontal brain regions
Bibliographic record
Abstract
RATIONALE: Win-paired stimuli can promote risk taking in experimental gambling paradigms in both rats and humans. We previously demonstrated that atomoxetine, a noradrenaline reuptake inhibitor, and guanfacine, a selective α2A adrenergic receptor agonist, reduced risk taking on the cued rat gambling task (crGT), a rodent assay of risky choice in which wins are accompanied by salient cues. Both compounds also decreased impulsive premature responding. OBJECTIVE: The key neural loci mediating these effects were unknown. The lateral orbitofrontal cortex (lOFC) and the medial prefrontal cortex (mPFC), which are highly implicated in risk assessment, action selection, and impulse control, receive dense noradrenergic innervation. We therefore infused atomoxetine and guanfacine directly into either the lOFC or prelimbic (PrL) mPFC prior to task performance. RESULTS: When infused into the lOFC, atomoxetine improved decision making score and adaptive lose-shift behaviour in males, but not in females, without altering motor impulsivity. Conversely, intra-PrL atomoxetine improved impulse control in risk preferring animals of both sexes, but did not alter decision making. Guanfacine administered into the PrL, but not lOFC, also altered motor impulsivity in all subjects, though in the opposite direction to atomoxetine. CONCLUSIONS: These data highlight a double dissociation between the behavioural effects of noradrenergic signaling across frontal regions with respect to risky choice and impulsive action. Given that the influence of noradrenergic manipulations on motor impulsivity could depend on baseline risk preference, these data also suggest that the noradrenaline system may function differently in subjects that are susceptible to the risk-promoting lure of win-associated cues.
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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 | 0.000 |
| 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".