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Behavioral and brain signatures of substance use vulnerability in childhood
The prevalence of risky behavior such as substance use increases during adolescence; however, the neurobiological precursors to adolescent substance use remain unclear. Predictive modeling may complement previous work observing associations with known risk factors or substance use outcomes by develo...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7662869/ https://www.ncbi.nlm.nih.gov/pubmed/33181393 http://dx.doi.org/10.1016/j.dcn.2020.100878 |
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author | Rapuano, Kristina M. Rosenberg, Monica D. Maza, Maria T. Dennis, Nicholas J. Dorji, Mila Greene, Abigail S. Horien, Corey Scheinost, Dustin Todd Constable, R. Casey, B.J. |
author_facet | Rapuano, Kristina M. Rosenberg, Monica D. Maza, Maria T. Dennis, Nicholas J. Dorji, Mila Greene, Abigail S. Horien, Corey Scheinost, Dustin Todd Constable, R. Casey, B.J. |
author_sort | Rapuano, Kristina M. |
collection | PubMed |
description | The prevalence of risky behavior such as substance use increases during adolescence; however, the neurobiological precursors to adolescent substance use remain unclear. Predictive modeling may complement previous work observing associations with known risk factors or substance use outcomes by developing generalizable models that predict early susceptibility. The aims of the current study were to identify and characterize behavioral and brain models of vulnerability to future substance use. Principal components analysis (PCA) of behavioral risk factors were used together with connectome-based predictive modeling (CPM) during rest and task-based functional imaging to generate predictive models in a large cohort of nine- and ten-year-olds enrolled in the Adolescent Brain & Cognitive Development (ABCD) study (NDA release 2.0.1). Dimensionality reduction (n = 9,437) of behavioral measures associated with substance use identified two latent dimensions that explained the largest amount of variance: risk-seeking (PC1; e.g., curiosity to try substances) and familial factors (PC2; e.g., family history of substance use disorder). Using cross-validated regularized regression in a subset of data (Year 1 Fast Track data; n>1,500), functional connectivity during rest and task conditions (resting-state; monetary incentive delay task; stop signal task; emotional n-back task) significantly predicted individual differences in risk-seeking (PC1) in held-out participants (partial correlations between predicted and observed scores controlling for motion and number of frames [r(p)]: 0.07-0.21). By contrast, functional connectivity was a weak predictor of familial risk factors associated with substance use (PC2) (r(p): 0.03-0.06). These results demonstrate a novel approach to understanding substance use vulnerability, which—together with mechanistic perspectives—may inform strategies aimed at early identification of risk for addiction. |
format | Online Article Text |
id | pubmed-7662869 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-76628692020-11-20 Behavioral and brain signatures of substance use vulnerability in childhood Rapuano, Kristina M. Rosenberg, Monica D. Maza, Maria T. Dennis, Nicholas J. Dorji, Mila Greene, Abigail S. Horien, Corey Scheinost, Dustin Todd Constable, R. Casey, B.J. Dev Cogn Neurosci Articles from the Special Issue from the Flux Congress 2019: Cutting edge approaches to developmental neuroscience; Edited by Deanna Barch. The prevalence of risky behavior such as substance use increases during adolescence; however, the neurobiological precursors to adolescent substance use remain unclear. Predictive modeling may complement previous work observing associations with known risk factors or substance use outcomes by developing generalizable models that predict early susceptibility. The aims of the current study were to identify and characterize behavioral and brain models of vulnerability to future substance use. Principal components analysis (PCA) of behavioral risk factors were used together with connectome-based predictive modeling (CPM) during rest and task-based functional imaging to generate predictive models in a large cohort of nine- and ten-year-olds enrolled in the Adolescent Brain & Cognitive Development (ABCD) study (NDA release 2.0.1). Dimensionality reduction (n = 9,437) of behavioral measures associated with substance use identified two latent dimensions that explained the largest amount of variance: risk-seeking (PC1; e.g., curiosity to try substances) and familial factors (PC2; e.g., family history of substance use disorder). Using cross-validated regularized regression in a subset of data (Year 1 Fast Track data; n>1,500), functional connectivity during rest and task conditions (resting-state; monetary incentive delay task; stop signal task; emotional n-back task) significantly predicted individual differences in risk-seeking (PC1) in held-out participants (partial correlations between predicted and observed scores controlling for motion and number of frames [r(p)]: 0.07-0.21). By contrast, functional connectivity was a weak predictor of familial risk factors associated with substance use (PC2) (r(p): 0.03-0.06). These results demonstrate a novel approach to understanding substance use vulnerability, which—together with mechanistic perspectives—may inform strategies aimed at early identification of risk for addiction. Elsevier 2020-11-03 /pmc/articles/PMC7662869/ /pubmed/33181393 http://dx.doi.org/10.1016/j.dcn.2020.100878 Text en © 2020 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Articles from the Special Issue from the Flux Congress 2019: Cutting edge approaches to developmental neuroscience; Edited by Deanna Barch. Rapuano, Kristina M. Rosenberg, Monica D. Maza, Maria T. Dennis, Nicholas J. Dorji, Mila Greene, Abigail S. Horien, Corey Scheinost, Dustin Todd Constable, R. Casey, B.J. Behavioral and brain signatures of substance use vulnerability in childhood |
title | Behavioral and brain signatures of substance use vulnerability in childhood |
title_full | Behavioral and brain signatures of substance use vulnerability in childhood |
title_fullStr | Behavioral and brain signatures of substance use vulnerability in childhood |
title_full_unstemmed | Behavioral and brain signatures of substance use vulnerability in childhood |
title_short | Behavioral and brain signatures of substance use vulnerability in childhood |
title_sort | behavioral and brain signatures of substance use vulnerability in childhood |
topic | Articles from the Special Issue from the Flux Congress 2019: Cutting edge approaches to developmental neuroscience; Edited by Deanna Barch. |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7662869/ https://www.ncbi.nlm.nih.gov/pubmed/33181393 http://dx.doi.org/10.1016/j.dcn.2020.100878 |
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