Disrupted functional connectivity of the brain reward system in substance use problems: A meta‐analysis of functional neuroimaging studies
Bibliographic record
Abstract
Extensive literature suggests that the brain reward system is crucial in understanding the neurobiology of substance use disorders. However, evidence of reliable deficits in functional connectivity across studies on substance use problems remains limited. Therefore, a voxel-wise seed-based meta-analysis using brain regions of the reward system as seeds of interest was conducted on 96 studies representing 5757 subjects with substance use problems. The ventromedial prefrontal cortex exhibited hyperconnectivity with the ventral striatum and hypoconnectivity with the amygdala and hippocampus. The executive striatum showed hyperconnectivity with the motor thalamus and dorsolateral prefrontal cortex and hypoconnectivity with the anterior cingulate cortex and anterior insula. Finally, the limbic striatum was found to be hyperconnected to the orbitofrontal cortex and hypoconnected to the precuneus compared with healthy subjects. The current study provided meta-analytical evidence of deficient functional connectivity between brain regions of the reward system and cortico-striato-thalamocortical loops in addiction. These results are consistent with deficits in motivation and habit formation occurring in addiction, and they highlight alterations in brain regions involved in socio-emotional processing and attention salience.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.008 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".