Clayton C. McIntyre, Mohammadreza Khodaei, Robert G. Lyday, Jeffrey L. Weiner, Paul J. Laurienti, Heather M. Shappell
{"title":"Triple network dynamics and future alcohol consumption in adolescents","authors":"Clayton C. McIntyre, Mohammadreza Khodaei, Robert G. Lyday, Jeffrey L. Weiner, Paul J. Laurienti, Heather M. Shappell","doi":"10.1111/acer.70043","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>The human brain is a highly interconnected and dynamic system. The study of neuroimaging indicators of future teen drinking has primarily focused on the activation of individual brain regions. We applied novel methodology to identify relationships between functional brain network dynamics and future drinking outcomes in non/low drinking teens.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>Resting-state functional magnetic resonance imaging (fMRI) time series from 17-year-old non-/low drinking participants (<i>n</i> = 295) of the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) study were used to fit a Hidden semi-Markov Model (HSMM). Regions of the default mode network (DMN), salience network (SN), and central executive network (CEN), collectively known as the Triple Network, were included in modeling. The HSMM identified each participant's most likely brain state sequence through five brain states. Poisson regression models assessed relationships between occupancy time in brain states and future drinking frequency/intensity. Sex differences were assessed with permutation testing and interaction terms in regression models.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>No sex differences in network dynamics were observed. However, the relationship between occupancy times and future drinking frequency differed by sex for three brain states. Occupancy time in a state characterized by high activation in the DMN and SN, but low activation in the CEN, was negatively associated with future drinking in both sexes.</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>Brain network dynamics may be useful neural markers of teen drinking predisposition. Brain dynamics that make teens vulnerable or resilient to drinking may differ between sexes.</p>\n </section>\n </div>","PeriodicalId":72145,"journal":{"name":"Alcohol (Hanover, York County, Pa.)","volume":"49 6","pages":"1206-1220"},"PeriodicalIF":3.0000,"publicationDate":"2025-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/acer.70043","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Alcohol (Hanover, York County, Pa.)","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/acer.70043","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"SUBSTANCE ABUSE","Score":null,"Total":0}
引用次数: 0
Abstract
Background
The human brain is a highly interconnected and dynamic system. The study of neuroimaging indicators of future teen drinking has primarily focused on the activation of individual brain regions. We applied novel methodology to identify relationships between functional brain network dynamics and future drinking outcomes in non/low drinking teens.
Methods
Resting-state functional magnetic resonance imaging (fMRI) time series from 17-year-old non-/low drinking participants (n = 295) of the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) study were used to fit a Hidden semi-Markov Model (HSMM). Regions of the default mode network (DMN), salience network (SN), and central executive network (CEN), collectively known as the Triple Network, were included in modeling. The HSMM identified each participant's most likely brain state sequence through five brain states. Poisson regression models assessed relationships between occupancy time in brain states and future drinking frequency/intensity. Sex differences were assessed with permutation testing and interaction terms in regression models.
Results
No sex differences in network dynamics were observed. However, the relationship between occupancy times and future drinking frequency differed by sex for three brain states. Occupancy time in a state characterized by high activation in the DMN and SN, but low activation in the CEN, was negatively associated with future drinking in both sexes.
Conclusions
Brain network dynamics may be useful neural markers of teen drinking predisposition. Brain dynamics that make teens vulnerable or resilient to drinking may differ between sexes.