A multimodal neuroimaging study of youth at risk for substance use disorders: Functional magnetic resonance imaging and [<scp><sup>18</sup>F</scp>]fallypride positron emission tomography
Bibliographic record
Abstract
Abstract Background Adolescent alcohol use is the norm, but only some develop a substance use disorder. The increased risk might reflect heightened mesocorticolimbic responses to reward‐related cues but results published to date have been inconsistent. Methods Young social drinkers (age 18.5 ± 0.6 y.o.) who have been followed since birth were recruited from high‐ versus low‐risk trajectories based on externalizing (EXT) behavioral traits. All had functional magnetic resonance imaging (fMRI) scans to measure mesocorticolimbic responses to alcohol, juice, and water cues (High EXT: 20F/10M; Low EXT: 15F/12M). Most had positron emission tomography (PET) [18F]fallypride scans to measure brain regional dopamine D2 receptor availabilities (n = 47). Results Compared with the low EXT group, high EXT participants reported larger subjective responses to the alcohol and juice cues (vs. water). Despite this, a main effect of group was not seen for brain activation responses to the alcohol and juice cues. Instead, low EXT participants exhibited higher mesocorticolimbic activations to alcohol than juice, whereas these activations did not differ in the high EXT group. Across all participants, alcohol (vs. water) blood oxygen level‐dependent (BOLD) responses in the striatum and amygdala were associated with midbrain [18F]fallypride BPND values. Conclusion Young social drinkers at high versus low risk for substance use disorders did not exhibit larger mesocorticolimbic BOLD activations to alcohol‐related cues and their responses poorly differentiated alcohol from juice. These observations raise the possibility that (i) diminished mesocorticolimbic BOLD differentiations between reward‐related cues might be a marker of increased risk for substance use disorders, and (ii) previously reported large BOLD responses to drug‐related cues in people with substance use disorders might better identify the disease than pre‐existing vulnerability.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".