Not all effort is equal: the role of the anterior cingulate cortex in different forms of effort-reward decisions
Bibliographic record
Abstract
The rat anterior cingulate cortex (ACC) mediates effort-based decision making when the task requires the physical effort of climbing a ramp. Normal rats will readily climb a barrier leading to high reward whereas rats with ACC lesions will opt instead for an easily obtained small reward. The present study explored whether the role of ACC in cost-benefit decisions extends beyond climbing by testing its role in ramp climbing as well as two novel cost-benefit decision tasks, one involving the physical effort of lifting weights and the other the emotional cost of overcoming fear (i.e., "courage"). As expected, rats with extensive ACC lesions tested on a ramp-climbing task were less likely to choose a high-reward/high-effort arm than sham controls. However, during the first few trials, lesioned rats were as likely as controls to initially turn into the high-reward arm (HRA) but far less likely to actually climb the barrier, suggesting that the role of the ACC is not in deciding which course of action to pursue, but rather in maintaining a course of action in the face of countervailing forces. In the effort-reward decision task involving weight lifting, some lesion animals behaved like controls while others avoided the HRA. However, the results were not statistically significant and a follow-up study using incremental increasing effort failed to show any difference between lesion and control groups. The results suggest that the ACC is not needed for effort-reward decisions involving weight lifting but may affect motor abilities. Finally, a courage task explored the willingness of rats to overcome the fear of crossing an open, exposed arm to obtain a high reward. Both sham and ACC-lesioned animals exhibited equal tendencies to enter the open arm. However, whereas sham animals gradually improved on the task, ACC-lesioned rats did not. Taken together, the results suggest that the role of the ACC in effort-reward decisions may be limited to certain tasks.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".