The Role of the Anterior Cingulate Cortex in Choices based on Reward Value and Reward Contingency
Bibliographic record
Abstract
Although several studies have emphasized the role of the anterior cingulate cortex (ACC) in associating actions with reward value, its role in guiding choices on the basis of changes in reward value has not been assessed. Accordingly, we compared rhesus monkeys with ACC lesions and controls on object- and action-based reinforcer devaluation tasks. Monkeys were required to associate an object or an action with one of two reward outcomes, and we assessed the monkey's shift in choices of objects or actions after changes in the value of 1 outcome. No group differences emerged on either task. For comparison, we tested the same monkeys on their ability to make choices guided by reward contingency in object- and action-based reversal learning tasks. Monkeys with ACC lesions were impaired in using rewarded trials to sustain the selection of the correct object during object reversal learning. They were also impaired in using errors to guide choices in action reversal learning. These data indicate that the role of the ACC is not restricted to linking specific actions with reward outcomes, as previously reported. Instead, the data suggest a more general role for the ACC in using information about reward and nonreward to sustain effective choice 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 | 0.000 | 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 | 0.000 | 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".