Substance use disorder and altered hemispheric asymmetries: A systematic review
Bibliographic record
Abstract
Substance use disorder (SUD) is characterized by compulsive use despite adverse consequences and may be influenced by brain asymmetry affecting cognitive and emotional processes. This systematic review investigates the relationship between brain asymmetry and SUD. PubMed, Web of Science, and PsycInfo were searched for articles published until July 2025, using the search terms: ((Alcoholism) OR (alcohol abuse) OR (substance abuse) OR (addiction)) AND ((handedness) OR (footedness) OR (dichotic listening) OR (line bisection task) OR (visual half field technique) OR (fMRI asymmetry) OR (EEG asymmetry) OR (structural asymmetry)). Inclusion criteria were (i) subjects having a diagnosis of or meeting the criteria for alcoholism, alcohol abuse, substance abuse, or addiction assessed with a validated clinical inventory, (ii) articles must contain information on handedness, footedness, dichotic listening, line bisection task, the visual half-field technique, or hemispheric differences (iii) data must be given for the clinical group separately, (iv) original research article in the English language. For neuroimaging studies, both hemispheres needed to be examined separately. Exclusion criteria included: (i) review articles; (ii) studies without matched groups; (iii) studies on recreational use only; (iv) those involving prenatal substance exposure or comorbid neurological disorders. Risk of bias was assessed with the Newcastle-Ottawa Scale. Forty-nine studies met the criteria. Structural imaging indicates asymmetric white and grey matter alterations: reduced left-hemispheric white matter integrity and lower grey matter volume in frontal and temporal regions. Functional data show compensatory right-hemispheric activation. Behavioral lateralization findings vary by substance type, sex, and age, with potential implications for personalized treatment strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.002 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".