Opioid Receptor PET Reveals the Psychobiologic Correlates of Reward Processing
Bibliographic record
Abstract
UNLABELLED: Little is known about the neurobiologic correlates of human personality. On the basis of the key role of the central opioidergic system in addiction and substance abuse, we investigated the relationship between certain personality traits that are supposed to be relevant in addiction and the opioid receptor status in healthy subjects. METHODS: We investigated 23 healthy male volunteers who were extensively clinically tested to exclude substance abuse. All of the subjects underwent 1 PET scan with the subtype-nonselective opioidergic radioligand 18F-fluoroethyl-diprenorphine under resting conditions without sensory or cognitive stimulation. Subsequently, the subjects were psychologically tested for the personality traits novelty seeking, harm avoidance, reward dependence, and persistence, according to Cloninger's biosocial model of personality. The binding potential (BP) as a parameter of regional cerebral opioid receptor availability was computed by means of the modified Logan plot using the occipital cortex as a reference region. Further imaging data analysis was performed using statistical parametric mapping; after stereotactic normalization, the correlations were calculated between the regional BP and the psychologic scores on a voxel-by-voxel basis. RESULTS: The correlation analysis between personality dimensions and opioid receptor availability showed a significant (P < 0.001) positive correlation between the scores of reward dependence and the BP of the bilateral ventral striatum with nucleus accumbens (z scores, 4.52 and 4.33, respectively). The additionally performed region-of-interest-based correlation analysis yielded correlation coefficients of r = 0.84 and r = 0.81 for the left and right ventral striata, respectively. No further significant correlations were detectable between the other personality dimensions and cerebral opioid receptor binding. CONCLUSION: In healthy subjects, personality traits, which might be predisposing for addictive behavior, are correlated to the opioidergic neurotransmission in core structures of the human reward system.
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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) | 0.003 | 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".