<scp>P</scp>osterior dopamine D2/3 receptors and brain network functional connectivity
Bibliographic record
Abstract
Abstract Recent studies suggest that dopaminergic tone influences resting state activity in multiple brain networks. Although dopamine receptors and transporters have been identified in the posteromedial and parietal cortices, which are linked to functional networks such as the default mode network (DMN), the relationship between dopamine receptor distribution in these posterior regions and resting‐state connectivity has yet to be explored. Here, we used a multi‐modal neuroimaging strategy, combining resting‐state functional magnetic resonance imaging (rsfMRI) and [18 F]‐fallypride high‐resolution positron emission tomography (PET), to examine the association between within‐network functional connectivity and the dopamine D2/3 receptor distribution in the posterior portion of the brain in 13 healthy adults. Our results indicate that the posterior distribution of D2/3 receptors coincides primarily with the posterior portion of the DMN. Furthermore, in the posterior portion of the brain, the level of [18 F]‐fallypride binding in the posteromedial cortex correlated positively with the functional connectivity strength of the DMN and sensorimotor network, and negatively with the functional connectivity strength of the dorsal attention network, the salience network, and a network that included the anterior part of the temporo‐parietal junction. On the basis of these findings, we propose that posterior brain dopamine influences the configuration of the posterior DMN and several other functional brain networks. The posterior distribution of D2/3 receptors binding (hot colour spectrum) coincides with the functional connectivity of the posterior portion of the default mode network (green colour spectrum). The mean BP ND in a posteromedial cortex and the mean ICA‐Z score in the precuneus showed significant positive correlation.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".