Integrating Multilevel, Multidomain and Multimodal Neuroimaging Factors to Predict Early Alcohol Exposure Trajectories Using Explainable AI
Open accessPreprint — published as 10.1016/j.dcn.2025.101597 · Paper page
Abstract
Alcohol consumption tends to increase from childhood to adolescence, and risk factors at the individual, family, and environmental level (multilevel, multidomain factors), as well as changes in brain structure and function, have been associated with the likelihood of developing alcohol use disorder (AUD) or binge drinking later in life. Most studies have focused on limited subsets of multilevel or neuroimaging factors, typically emphasizing the risk of alcohol initiation, binge drinking, or AUD in cross-sectional designs rather than exploring longitudinal alcohol consumption trajectories. Our study addresses these gaps by examining a comprehensive set of multilevel, multidomain factors and multimodal brain imaging features to prospectively predict early alcohol sipping trajectories over time with large data from the Adolescent Brain Cognitive Development Study. We applied machine learning methods to baseline individual, family, and environmental factors as well as structural and functional brain connectivity features, analyzing these predictors separately and in combination. Key findings reveal that functional connectivity and multilevel factors distinguish youth with an increasing alcohol sipping trajectory from those who initially experimented with alcohol but reduced their consumption over time. Moreover, we found important structural and functional features that predicted those who increasingly sipped over time versus the ones who did not engage in alcohol experimentation. Stable interactions between age, socioeconomical status and positive attitudes towards drinking could predict a pattern of increasing alcohol sipping over time. These trends could inform how individual, family, and environmental factors together with brain imaging features impact the development of different alcohol sipping trajectories over time.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538 · see citing works
Regression shrinkage and selection via the lasso
Tibshirani, R. (1996) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1996.tb02080.x · Cited by 51,482 · see citing works
Regularization and Variable Selection Via the Elastic Net
Zou, H., & Hastie, T. (2005) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.1467-9868.2005.00503.x · Cited by 20,957 · see citing works
A tutorial on support vector regression
Smola, A. J., & Schölkopf, B. (2004) · Statistics and Computing · doi:10.1023/b:stco.0000035301.49549.88 · Cited by 13,482 · see citing works
Classification And Regression Trees
Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (2017) · doi:10.1201/9781315139470 · Cited by 11,417 · see citing works
He, H., & Garcia, E. A. (2009) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2008.239 · Cited by 10,359 · see citing works
Building Predictive Models in R Using the caret Package
Kühn, M. (2008) · Journal of Statistical Software · doi:10.18637/jss.v028.i05 · Cited by 9,986 · see citing works
Fischl, B. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.021 · Cited by 9,526 · see citing works
Ridge Regression: Applications to Nonorthogonal Problems
Hoerl, A. E., & Kennard, R. (1970) · Technometrics · doi:10.1080/00401706.1970.10488635 · Cited by 2,762 · see citing works
The Adolescent Brain Cognitive Development (ABCD) study: Imaging acquisition across 21 sites
Casey, B. J., Cannonier, T., Conley, M. I., Cohen, A. O., Barch, D. M., Heitzeg, M. M., Soules, M. E., Teslovich, T., Dellarco, D. V., Garavan, H., et al. (2018) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2018.03.001 · Cited by 2,167 · see citing works
Visualizing the effects of predictor variables in black box supervised learning models
Apley, D. W., & Zhu, J. (2020) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/rssb.12377 · Cited by 1,535 · see citing works
Image processing and analysis methods for the Adolescent Brain Cognitive Development Study
Hagler, D. J., Hatton, S. N., Cornejo, M. D., Makowski, C., Fair, D. A., Dick, A. S., Sutherland, M. T., Casey, B. J., Barch, D. M., Harms, M. P., et al. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116091 · Cited by 1,060 · see citing works
Self-citationA Review of Feature Selection Methods for Machine Learning-Based Disease Risk Prediction
Pudjihartono, N., Fadason, T., Kempa-Liehr, A. W., & O'Sullivan, J. M. (2022) · Frontiers in Bioinformatics · doi:10.3389/fbinf.2022.927312 · Cited by 965 · see citing works
Training and assessing classification rules with imbalanced data
Menardi, G., & Torelli, N. (2012) · Data Mining and Knowledge Discovery · doi:10.1007/s10618-012-0295-5 · Cited by 769 · see citing works
The role of early life stress as a predictor for alcohol and drug dependence
Enoch, M.-A. (2011) · Psychopharmacology · doi:10.1007/s00213-010-1916-6 · Cited by 668 · see citing works
Social and Cultural Contexts of Alcohol Use: Influences in a Social-Ecological Framework
Sudhinaraset, M. (2016) · Alcohol Research: Current Reviews · doi:10.35946/arcr.v38.1.05 · Cited by 533 · see citing works
Predicting brain-age from multimodal imaging data captures cognitive impairment
Liem, F., Varoquaux, G. P., Kynast, J., Beyer, F., Masouleh, S. K., Huntenburg, J. M., Lampe, L., Rahim, M., Abraham, A., Craddock, R. C., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.11.005 · Cited by 502 · see citing works
Impulsivity-related personality traits and adolescent alcohol use: A meta-analytic review
Stautz, K., & Cooper, A. J. (2013) · Clinical Psychology Review · doi:10.1016/j.cpr.2013.03.003 · Cited by 486 · see citing works
Effect of alcohol use on the adolescent brain and behavior
Lees, B., Meredith, L. R., Kirkland, A. E., Bryant, B. E., & Squeglia, L. M. (2020) · Pharmacology Biochemistry and Behavior · doi:10.1016/j.pbb.2020.172906 · Cited by 411 · see citing works
A review of multivariate methods for multimodal fusion of brain imaging data
Jing Sui （Beijing Normal University）， my correct affiliation is beijing normal university, N. Q. U. O. S. A. T., Adalı, T., Yu, Q., Chen, J., & Calhoun, V. D. (2011) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2011.10.031 · Cited by 403 · see citing works
Bryant, A. L., Schulenberg, J. E., O'Malley, P. M., Bachman, J. G., & Johnston, L. D. (2003) · Journal of Research on Adolescence · doi:10.1111/1532-7795.1303005 · Cited by 374 · see citing works
Adolescent brain cognitive development (ABCD) study: Overview of substance use assessment methods
Lisdahl, K. M., Sher, K. J., Conway, K. P., González, R., Ewing, S. W. F., Nixon, S. J., Tapert, S. F., Bartsch, H., Goldstein, R. Z., & Heitzeg, M. M. (2018) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2018.02.007 · Cited by 370 · see citing works
Iterative random forests to discover predictive and stable high-order interactions
Basu, S., Kumbier, K., Brown, J. B., & Yu, B. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1711236115 · Cited by 317 · see citing works
Disrupted Ventromedial Prefrontal Function, Alcohol Craving, and Subsequent Relapse Risk
Seo, D., Lacadie, C., Tuit, K. L., Hong, K., Constable, R. T., & Sinha, R. (2013) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2013.762 · Cited by 302 · see citing works
Neural activation during inhibition predicts initiation of substance use in adolescence
Norman, A. L., Pulido, C., Squeglia, L. M., Spadoni, A. D., Paulus, M. P., & Tapert, S. F. (2011) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2011.06.019 · Cited by 244 · see citing works
Zucker, R. A., Gonzalez, R., Feldstein Ewing, S. W., Paulus, M. P., Arroyo, J., Fuligni, A., Morris, A. S., Sanchez, M., & Wills, T. (2018) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2018.03.004 · Cited by 221 · see citing works
Socio‐economic status predicts drinking patterns but not alcohol‐related consequences independently
Huckle, T., You, R. Q., & Casswell, S. (2010) · Addiction · doi:10.1111/j.1360-0443.2010.02931.x · Cited by 219 · see citing works
Advances in Independent Component Analysis
(2000) · Perspectives in neural computing · doi:10.1007/978-1-4471-0443-8 · Cited by 197 · see citing works
Feldstein Ewing, S. W., Sakhardande, A., & Blakemore, S.-J. (2014) · NeuroImage: Clinical · doi:10.1016/j.nicl.2014.06.011 · Cited by 185 · see citing works
Multi-ancestry study of the genetics of problematic alcohol use in over 1 million individuals
Zhou, H., Kember, R. L., Deak, J. D., Xu, H., Toikumo, S., Yuan, K., Lind, P. A., Farajzadeh, L., Wang, L., Hatoum, A. S., et al. (2023) · Nature Medicine · doi:10.1038/s41591-023-02653-5 · Cited by 175 · see citing works
Self-citationLópez‐Caneda, E., Holguı́n, S. R., Cadaveira, F., Corral, M., & Doallo, S. (2013) · Alcohol and Alcoholism · doi:10.1093/alcalc/agt168 · Cited by 154 · see citing works
Barch, D. M., Albaugh, M. D., Baskin-sommers, A. R., Bryant, B. E., Clark, D. B., Dick, A. S., Feczko, E., Foxe, J. J., Gee, D. G., Giedd, J. N., et al. (2021) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2021.101031 · Cited by 146 · see citing works
Self-citationFunctional brain connectivity changes across the human life span: From fetal development to old age
Edde, M., Leroux, G., Altena, E., & Chanraud, S. (2021) · Journal of Neuroscience Research · doi:10.1002/jnr.24669 · Cited by 143 · see citing works
Neural Predictors of Initiating Alcohol Use During Adolescence
Squeglia, L. M., Ball, T. M., Jacobus, J., Brumback, T., McKenna, B. S., Nguyen‐Louie, T. T., Sorg, S. F., Paulus, M. P., & Tapert, S. F. (2016) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2016.15121587 · Cited by 140 · see citing works
Fan, C. C., Marshall, A. T., Smolker, H. R., Gonzalez, M. R., Tapert, S. F., Barch, D. M., Sowell, E. R., Dowling, G. J., Cardenas‐Iniguez, C., Ross, J. M., et al. (2021) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2021.101030 · Cited by 140 · see citing works
Self-citationAcculturation and parental attachment in Asian-American adolescents’ alcohol use
Hahm, H. C., Lahiff, M., & Guterman, N. B. (2003) · Journal of Adolescent Health · doi:10.1016/s1054-139x(03)00058-2 · Cited by 138 · see citing works
Testing a social ecological model of alcohol use: the California 50-city study
Gruenewald, P. J., Remer, L. G., & LaScala, E. A. (2013) · Addiction · doi:10.1111/add.12438 · Cited by 135 · see citing works
Wingo, A. P., Ressler, K. J., & Bradley, B. (2014) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2014.01.007 · Cited by 131 · see citing works
Conservative and disruptive modes of adolescent change in human brain functional connectivity
Váša, F., Romero-García, R., Kitzbichler, M. G., Seidlitz, J., Whitaker, K. J., Vaghi, M. M. S., Kundu, P., Patel, A. X., Fonagy, P., Dolan, R. J., et al. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1906144117 · Cited by 131 · see citing works
Sleep and circadian contributions to adolescent alcohol use disorder
Hasler, B. P., Soehner, A. M., & Clark, D. B. (2015) · Alcohol · doi:10.1016/j.alcohol.2014.06.010 · Cited by 123 · see citing works
Vergara, V. M., Liu, J., Claus, E. D., Hutchison, K. E., & Calhoun, V. D. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.11.012 · Cited by 116 · see citing works
Korhonen, T., Kujala, U. M., Rose, R. J., & Kaprio, J. A. (2009) · Twin Research and Human Genetics · doi:10.1375/twin.12.3.261 · Cited by 115 · see citing works
Social anxiety and motives for alcohol use among adolescents.
Blumenthal, H., Leen‐Feldner, E. W., Frala, J. L., Badour, C. L., & Ham, L. S. (2010) · Psychology of Addictive Behaviors · doi:10.1037/a0019794 · Cited by 86 · see citing works
Cservenka, A., Casimo, K., Fair, D. A., & Nagel, B. J. (2014) · Psychiatry Research: Neuroimaging · doi:10.1016/j.pscychresns.2013.12.004 · Cited by 86 · see citing works
Adolescence and drug use vulnerability: findings from neuroimaging
Squeglia, L. M., & Cservenka, A. (2017) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2016.12.005 · Cited by 83 · see citing works
Life stress in adolescence predicts early adult reward-related brain function and alcohol dependence
Casement, M. D., Shaw, D. S., Sitnick, S. L., Musselman, S. C., & Forbes, E. E. (2015) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsu061 · Cited by 82 · see citing works
Kinreich, S., Meyers, J. L., Maron-Katz, A., Kamarajan, C., Pandey, A. K., Chorlian, D. B., Zhang, J., Pandey, G., Subbie-Saenz de Viteri, S., Pitti, D., et al. (2021) · Molecular Psychiatry · doi:10.1038/s41380-019-0534-x · Cited by 80 · see citing works
Silveira, S., Shah, R., Nooner, K. B., Nagel, B. J., Tapert, S. F., de Bellis, M. D., & Mishra, J. (2020) · Biological Psychiatry: Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2020.01.011 · Cited by 68 · see citing works
Resting state connectivity best predicts alcohol use severity in moderate to heavy alcohol users
Fede, S. J., Grodin, E. N., Dean, S., Diazgranados, N., & Momenan, R. (2019) · NeuroImage Clinical · doi:10.1016/j.nicl.2019.101782 · Cited by 66 · see citing works
Meque, I., Dachew, B. A., Maravilla, J. C., Salom, C., & Alati, R. (2019) · Australian & New Zealand Journal of Psychiatry · doi:10.1177/0004867419844308 · Cited by 64 · see citing works
Lee, M. R., Sankar, V., Hammer, A., Kennedy, W. G., Barb, J. J., McQueen, P. G., & Leggio, L. (2019) · EClinicalMedicine · doi:10.1016/j.eclinm.2019.05.008 · Cited by 62 · see citing works
Convergent Evidence for Predispositional Effects of Brain Gray Matter Volume on Alcohol Consumption
Baranger, D. A. A., Demers, C. H., Elsayed, N. M., Knodt, A. R., Radtke, S. R., Desmarais, A., Few, L. R., Arpana Agrawal, A., Heath, A. C., Barch, D. M., et al. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2019.08.029 · Cited by 50 · see citing works
Vidal-Ribas, P., Janiri, D., Doucet, G. E., Pornpattananangkul, N., Nielson, D. M., Frangou, S., & Stringaris, A. (2021) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2020.20020120 · Cited by 45 · see citing works
Adolescent risk-taking and resting state functional connectivity
DeWitt, S. J., Aslan, S., & Filbey, F. M. (2014) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2014.03.009 · Cited by 45 · see citing works
Lappalainen, H., & Miskin, J. W. (2000) · Perspectives in neural computing · doi:10.1007/978-1-4471-0443-8_5 · Cited by 41 · see citing works
Suk, J.-W., Hwang, S., & Cheong, C. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.742228 · Cited by 38 · see citing works
Neuropsychosocial markers of binge drinking in young adults
Gowin, J. L., Manza, P., Ramchandani, V. A., & Volkow, N. D. (2020) · Molecular Psychiatry · doi:10.1038/s41380-020-0771-z · Cited by 35 · see citing works
Robert, G. H., Luo, Q., Yu, T., Chu, C., Ing, A., Jia, T., Orfanos, D. P., Quinlan, E. B., Desrivières, S., Ruggeri, B., et al. (2019) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2019.4063 · Cited by 34 · see citing works
A machine learning approach to college drinking prediction and risk factor identification
Bi, J., Sun, J., Wu, Y., Tennen, H. A., & Armeli, S. (2013) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/2508037.2508053 · Cited by 33 · see citing works
Explicit drinking identity and alcohol problems: The mediating role of drinking to cope
DiBello, A. M., Miller, M. B., Young, C. M., Neighbors, C., & Lindgren, K. P. (2017) · Addictive Behaviors · doi:10.1016/j.addbeh.2017.07.031 · Cited by 23 · see citing works
Gu, Z., Barch, D. M., & Luo, Q. (2023) · PNAS Nexus · doi:10.1093/pnasnexus/pgae003 · Cited by 21 · see citing works
Aloi, J. M., Blair, K. S., Crum, K. I., Bashford‐Largo, J., Zhang, R., Lukoff, J., Carollo, E., White, S. F., Hwang, S., Filbey, F. M., et al. (2020) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2020.02.003 · Cited by 20 · see citing works
Adolescent substance use and functional connectivity between the ventral striatum and hippocampus
Huntley, E. D., Marusak, H. A., Berman, S. E., Zundel, C. G., Hatfield, J. R. B., Keating, D. P., & Rabinak, C. A. (2020) · Behavioural Brain Research · doi:10.1016/j.bbr.2020.112678 · Cited by 18 · see citing works
Purba, A. K., Henderson, M., Baxter, A. J., Katikireddi, S. V., & Pearce, A. (2023) · European Journal of Public Health · doi:10.1093/eurpub/ckad163 · Cited by 16 · see citing works
Negative urgency, PTSD symptoms, and alcohol risk in college students
Hallihan, H., Bing‐Canar, H., Paltell, K. C., & Berenz, E. C. (2023) · Addictive Behaviors Reports · doi:10.1016/j.abrep.2023.100480 · Cited by 15 · see citing works
Wells, L., & Östberg, V. (2018) · SSM - Population Health · doi:10.1016/j.ssmph.2018.09.001 · Cited by 13 · see citing works
Wahlström, J., Magnusson, C., Svensson, J., & Låftman, S. B. (2023) · Nordic Studies on Alcohol and Drugs · doi:10.1177/14550725231157152 · Cited by 13 · see citing works
Morales, A. M., Stark, N. A., & Nagel, B. J. (2021) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2021.109010 · Cited by 12 · see citing works
Watts, A. L., Doss, M. I., Bernard, D. L., & Sher, K. J. (2023) · Development and Psychopathology · doi:10.1017/s0954579423000184 · Cited by 12 · see citing works
May, A. C., Jacobus, J., Simmons, A. N., & Tapert, S. F. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.886848 · Cited by 11 · see citing works
Family and Parent Predictors of Anxiety Disorder Onset in Offspring of Anxious Parents
Ginsburg, G. S., Schleider, J. L., Tein, J. Y., & Drake, K. L. (2017) · Child & Youth Care Forum · doi:10.1007/s10566-017-9432-z · Cited by 10 · see citing works
Social Media Use and Alcohol Sipping in Early Adolescents: A Prospective Cohort Study
Nagata, J. M., Sajjad, O. M., Smith, N., Zamora, G., Dhama, S., Al-Shoaibi, A. A. A., Ganson, K. T., Testa, A. M., Moreno, M. A., Kiss, O., et al. (2024) · Substance Use & Misuse · doi:10.1080/10826084.2024.2310501 · Cited by 10 · see citing works
An investigation of multimodal predictors of adolescent alcohol initiation
Moore, A. J., Lewis, B., Elton, A., Squeglia, L. M., & Nixon, S. J. (2024) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2024.112491 · Cited by 9 · see citing works
Amialchuk, A. A., Sapci, O., & Elhai, J. D. (2021) · Addiction Research & Theory · doi:10.1080/16066359.2021.1887147 · Cited by 8 · see citing works
Ferariu, A., Taylor, A., Chang, H., & Zhang, F. (2024) · Alcoholism Clinical and Experimental Research · doi:10.1111/acer.15393 · Cited by 7 · see citing works
Self-citationPredicting Alcohol Consumption Behaviours of the Secondary Level StudentsPreprint
Shukla, A. K., Singh, P., & Vardhan, M. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3170173 · Cited by 7 · see citing works
Kardan, O., Weigard, A. S., Cope, L. M., Martz, M. E., Angstadt, M., McCurry, K. L., Michael, C., Hardee, J. E., Hyde, L. W., Sripada, C., et al. (2024) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2024.10.002 · Cited by 6 · see citing works
Honarvar, F., Arfaie, S., Edalati, H., Ghasroddashti, A., Solgi, A., Mashayekhi, M. S., Mofatteh, M., Ren, L. Y., Kwan, A. T. H., & Keramatian, K. (2023) · Alcohol and Alcoholism · doi:10.1093/alcalc/agad049 · Cited by 5 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
The ABCD Study at 10: The NIH perspective on progress, impact, and the road ahead
Volkow, N. D., Koob, G. F., Klein, W. M., Hobin, J. A., Wargo, E. M., Alkire, D. R., Hoffman, E. A., Weiss, S. R. B., & Dowling, G. J. (2026) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2026.101790
Environmental Influences using Linked External Data in ABCD: A Review of the First Decade
Abad, S., Flores, M. M. H., Thompson, E. L., Floyd, T. E., Reuben, A., Ip, K. I., Gonzalez, M., Shen, K.-Q., Iyob, N., Marshall, A., et al. (2026) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2026.101822 · Cited by 1 · see citing works
Distinct structural abnormalities in obsessive-compulsive and alcohol use disorders
Shukrun, D., Shalev, H., Gulevsky, T., Harel, M., & Zangen, A. (2026) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-026-02375-y
- Authors
- Ferariu, A., Chang, H., Kumar, A., Sahl, A., Gorka, S., Wang, L., Thompson, W. K., & Zhang, F.
- Affiliations
- Drexel University (US)
- The Ohio State University (US)
- Laureate Institute for Brain Research (US)
- Corresponding author
- Zhang, Fengqing
- ORCID
- Venue
- Developmental Cognitive Neuroscience
- Publisher
- openRxiv
- Published
- 2025-03-14
- Volume
- 75
- Pages
- 101597-101597
- ISSN
- 1878-9293 (ISSN-L)
- PMC
- PMC12301842
- OpenAlex
- W4412447428
- Cited by
- 3
- References
- 78
- Citations by year
- 2026: 3
- FWCI
- 2.08
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Developmental Cognitive Neuroscience (publishedVersion, cc-by-nc)
- medRxiv (acceptedVersion, cc-by-nc-nd)
- SSRN Electronic Journal (acceptedVersion)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health
- National Institute on Drug Abuse (U01DA041106, U01DA051037, U01DA041120, U01DA041156, U01DA041174, U01DA050987, U01DA050989, U01DA050988, U01DA041048, U24DA041147, U01DA041148, U01DA041022, U01DA041028, U01DA051039, U01DA041134, U01DA041025, U24DA041123, U01DA051038, U01DA041093, U01DA041089, U01DA051016, U01DA041117, U01DA051018)
- National Institute of Environmental Health Sciences (R01ES031074, R01ES032295)
- Topics
- Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- adolescent alcohol use, alcoholism, binge drinking, functional connectivity, brain structure, socioeconomic status, attitudes toward alcohol, family factors, environmental factors, explainable AI, Adolescent Brain Cognitive Development Study, alcohol initiation
- MeSH terms
- Machine Learning, Adolescent, Alcohol Drinking, Alcoholism, Brain, Female, Humans, Longitudinal Studies, Magnetic Resonance Imaging, Male, Neuroimaging, Binge Drinking, Multimodal Imaging
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
