The neurobiology of impulsivity and substance use disorders: implications for treatment
Bibliographic record
Abstract
Impulsivity is strongly associated with substance use disorders (SUDs). Our review discusses impulsivity as an underlying vulnerability marker for SUDs, and treatment of co-occurring impulsivity in SUDs. Three factors should be considered for the complex relationship between impulsivity and a SUD: (1) the trait effect of impulsivity, centering on decreased cognitive and response inhibition, (2) the state effect resulting from either acute or chronic substance use on brain structure and function, and (3) the genetic and environmental factors (e.g., age and sex) may influence impulsive behavior associated with SUDs. Both subjective and objective measures are used to assess impulsivity. Together, treatment developments (pharmacological, behavioral, and neurophysiological) should consider these clinically relevant dimensions assessed by a variety of measures, which have implications for treatment matching in individuals with SUD. Despite its heterogeneity, impulsivity is a marker associated with SUDs and may be understood as an imbalance of bottom-up and top-down neural systems. Further investigation of these relationships may lead to more effective SUD treatments.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".