Relationship between regional gray matter volumes and dopamine D<sub>2</sub> receptor and transporter in living human brains
Bibliographic record
Abstract
Abstract Although striatal dopamine neurotransmission is believed to be functionally linked to the formation of the corticostriatal network, there has been little evidence for this regulatory process in the human brain and its disruptions in neuropsychiatric disorders. Here, we aimed to investigate associations of striatal dopamine transporter (DAT) and D2 receptor availabilities with gray matter (GM) volumes in healthy humans. Positron emission tomography images of D2 receptor (n = 34) and DAT (n = 17) captured with the specific radioligands [11C]raclopride and [18F]FE‐PE2I, respectively, were acquired along with T1‐weighted magnetic resonance imaging data in our previous studies, and were re‐analyzed in this work. We quantified the binding potentials (BPND) of these radioligands in the limbic, executive, and sensorimotor functional subregions of the striatum. Correlations between the radioligand BPND and regional GM volume were then examined by voxel‐based morphometry. In line with the functional and anatomical connectivity, [11C]raclopride BPND in the limbic striatum was positively correlated with volumes of the uncal/parahippocampal gyrus and adjacent temporal areas. Similarly, we found positive correlations between the BPND of this radioligand in the executive striatum and volumes of the prefrontal cortices and their adjacent areas as well as between the BPND in the sensorimotor striatum and volumes of the somatosensory and supplementary motor areas. By contrast, no significant correlation was found between [18F]FE‐PE2I BPND and regional GM volumes. Our results suggest unique structural and functional corticostriatal associations involving D2 receptor in healthy humans, which might be partially independent of the nigrostriatal pathway reflected by striatal DAT.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.002 | 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".