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Record W4407418740 · doi:10.1093/ijnp/pyae059.079

BRAIN RESPONSES TO ALCOHOL CUES IN YOUTH AT RISK FOR SUBSTANCE USE DISORDERS (SUDS): A FUNCTIONAL MAGNETIC RESONANCE IMAGING STUDY

2025· article· en· W4407418740 on OpenAlexaff
Maja Nikolic, Sylvia M L Cox, Natalia Jaworska, Natalie Castellanos‐Ryan, Alain Dagher, Frank Vitaro, Mara Brendgen, Sophie Parent, Michel Boivin, Sylvana M. Côté, Richard E. Tremblay, Jean R Sé guin, Marco Leyton

Bibliographic record

VenueThe International Journal of Neuropsychopharmacology · 2025
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsUniversité du Québec à MontréalUniversité de MontréalUniversité LavalUniversity of OttawaMcGill University
FundersRussian Science Foundation
KeywordsFunctional magnetic resonance imagingMagnetic resonance imagingSubstance useNeuroimagingPsychologyPsychiatryMedicineNeuroscienceRadiology

Abstract

fetched live from OpenAlex

Abstract Background Adolescent alcohol use is the norm, but only some develop a substance use disorder (SUD). The most common vulnerability traits are characterized by diverse externalizing (EXT) behaviors (e.g., poor impulse-control and emotion regulation). Preliminary studies suggest that this increased risk may be influenced by altered mesocorticolimbic processing of drug and non-drug reward-related cues. The effects are complex. Whereas functional magnetic resonance imaging (fMRI) measured responses to alcohol cues are elevated in young adults with an alcohol use disorder compared to healthy drinkers (1), high-risk youth who have not developed an SUD are reported to poorly differentiate cues associated with high vs low reward; e.g., monetary reward (2). Aims & Objectives Measure brain activation responses to alcohol and non-alcohol cues in high- vs low- EXT youth who have been followed since birth. Method Seventy-one longitudinally followed young social drinkers (age 18.5±0.6) underwent fMRI scans and completed the Alcohol Use Disorders Identification Test (AUDIT), Barratt Impulsiveness Scale (BIS- 11), Substance Use Risk Profile Scale (SURPS), and Sensitivity to Punishment and Sensitivity to Reward Questionnaire (SPSRQ). fMRI blood-oxygen-level-dependent (BOLD) activations were measured while participants received 1ml beverage tastants consisting of their preferred alcohol beverage, their preferred fruit juice, and water. Fourteen participants were excluded due to image quality issues, resulting in a final sample of 57, 27 high EXT (15F/12M) and 30 low EXT (20F/10M). As previously reported, most of these participants also had [18F]fallypride (47/57) and [11C]ABP688 (47/57) positron emission tomography scans and the high EXT group exhibited widespread increases in dopamine DRD2/3 receptors (3) and decreases in type 5 metabotropic glutamate receptors (4). Results As anticipated, high vs low EXT participants had higher AUDIT scores, alcohol binge occasions, lifetime uses of cannabis, impulsivity scores (SURPS and BIS-11), and prevalence of psychiatric disorders (mostly mood, anxiety, ADHD, and mild SUDs). For the alcohol (vs water) fMRI contrast, both groups exhibited activations in the thalamus, but only the high EXT group had significant activations in the anterior and posterior cingulate cortex, right calcarine, and post central gyrus. Significant group differences, in comparison, were only seen when contrasting the two flavored reward cues, alcohol vs juice. Whereas the low EXT group exhibited larger mesocorticolimbic BOLD responses to alcohol (vs water) than juice (vs water), these responses were undifferentiated in the high EXT group. Discussion & Conclusion The results add to the evidence that, in high-risk youth, mesocorticolimbic activations poorly distinguish reward-related cues, extending this observation to alcohol vs juice. The neurotransmitters mediating these responses remain unknown, but disrupted differentiations of reward- related cues might erode the ability to make optimal choices, increasing the risk for SUDs and their commonly comorbid conditions. References 1. Tapert, S. F., Cheung, E. H., Brown, G. G., Frank, L. R., Paulus, M. P., Schweinsburg, A. D., Meloy, M. J., &Brown, S. A. (2003). Neural response to alcohol stimuli in adolescents with alcohol use disorder. Archives of General Psychiatry, 60(7), 727–735. 2.Bü chel, C., Peters, J., Banaschewski, T., Bokde, A. L. W., Bromberg, U., Conrod, P. J., Flor, H., Papadopoulos, D., Garavan, H., Gowland, P., Heinz, A., Walter, H., Ittermann, B., Mann, K., Martinot, J.-L., Paillè re-Martinot, M.-L., Nees, F., Paus, T., Pausova, Z., … IMAGEN consortium. (2017). Blunted ventral striatal responses to anticipated rewards foreshadow problematic drug use in novelty-seeking adolescents. Nature Communications, 8, 14140. 3.Jaworska N, Cox SML, Tippler M, Castellanos-Ryan N, Benkelfat C, Parent S, Dagher A, Vitaro F, Boivin M, Pihl RO, Cô té S, Tremblay RE, Sé guin JR, Leyton M. (2020) Extra-striatal dopamine2/3 receptor availability in youth at-risk for addictions. Neuropsychopharmacology, 45(9), 1498-1505. 4.Cox SML, Tippler M, Jaworska N, Smart K, Castellanos-Ryan N, Durand F, Allard D, Benkelfat C, Parent S, Dagher A, Vitaro F, Boivin M, Pihl RO, Cô té S, Tremblay RE, Sé guin JR, Leyton M. (2020) mGlu5 receptor availability in youth at risk for addictions: effects of vulnerability traits and cannabis use. Neuropsychopharmacology, 45(11), 817-1825.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.049
GPT teacher head0.348
Teacher spread0.299 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2025
Admission routes1
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