Dissociable Contributions by Prefrontal D1 and D2 Receptors to Risk-Based Decision Making
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Bibliographic record
Abstract
Choices between certain and uncertain rewards of different magnitudes have been proposed to be mediated by both the frontal lobes and the mesocorticolimbic dopamine (DA) system. In rats, systemic manipulations of DA activity or inactivation of the medial prefrontal cortex (PFC) disrupt decision making about risks and rewards. However, it is unclear how PFC DA transmission contributes to these processes. We addressed this issue by examining the effects of pharmacological manipulations of D(1) and D(2) receptors in the medial (prelimbic) PFC on choice between small, certain and large, yet probabilistic rewards. Rats were trained on a probabilistic discounting task where one lever delivered one pellet with 100% probability, and the other delivered four pellets, but the probability of receiving reward decreased across blocks of trials (100, 50, 25, 12.5%). D(1) blockade (SCH23390) in the medial PFC decreased preference for the large/risky option. In contrast, D(2) blockade (eticlopride) reduced probabilistic discounting and increased risky choice. The D(1) agonist SKF81297 caused a slight, nonsignificant increase in preference for the large/risky lever. However, D(2) receptor stimulation (quinpirole) induced a true impairment in decision making, flattening the discounting curve and biasing choice away from or toward the risky option when it was more or less advantageous, respectively. These findings suggest that PFC D(1) and D(2) receptors make dissociable, yet complementary, contributions to risk/reward judgments. By striking a fine balance between D(1)/D(2) receptor activity, DA may help refine these judgments, promoting either exploitation of current favorable circumstances or exploration of more profitable ones when conditions change.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it