Dorsal Striatal D<sub>2</sub>-Like Receptor Availability Covaries with Sensitivity to Positive Reinforcement during Discrimination Learning
Bibliographic record
Abstract
Deviations in reward sensitivity and behavioral flexibility, particularly in the ability to change or stop behaviors in response to changing environmental contingencies, are important phenotypic dimensions of several neuropsychiatric disorders. Neuroimaging evidence suggests that variation in dopamine signaling through dopamine D(2)-like receptors may influence these phenotypes, as well as associated psychiatric conditions, but the specific neurocognitive mechanisms through which this influence is exerted are unknown. To address this question, we examined the relationship between behavioral sensitivity to reinforcement during discrimination learning and D(2)-like receptor availability in vervet monkeys. Monkeys were assessed for their ability to acquire, retain, and reverse three-choice, visual-discrimination problems, and once behavioral performance had stabilized, they received positron emission tomography (PET) scans. D(2)-like receptor availability in dorsal aspects of the striatum was not related to individual differences in the ability to acquire or retain visual discriminations but did relate to the number of trials required to reach criterion in the reversal phase of the task. D(2)-like receptor availability was also strongly correlated with behavioral sensitivity to positive, but not negative, feedback during learning. These results go beyond electrophysiological findings by demonstrating the involvement of a striatal dopaminergic marker in individual differences in feedback sensitivity and behavioral flexibility, providing insight into the neural mechanisms that are affected in neuropsychiatric disorders that feature these deficits.
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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".