Behavioral and brain signatures of substance use vulnerability in childhood. (December 2020)
- Record Type:
- Journal Article
- Title:
- Behavioral and brain signatures of substance use vulnerability in childhood. (December 2020)
- Main Title:
- Behavioral and brain signatures of substance use vulnerability in childhood
- Authors:
- 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. - Abstract:
- Abstract: 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 (partialAbstract: 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 [rp ]: 0.07-0.21). By contrast, functional connectivity was a weak predictor of familial risk factors associated with substance use (PC2) (rp : 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. … (more)
- Is Part Of:
- Developmental cognitive neuroscience. Volume 46(2020)
- Journal:
- Developmental cognitive neuroscience
- Issue:
- Volume 46(2020)
- Issue Display:
- Volume 46, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 46
- Issue:
- 2020
- Issue Sort Value:
- 2020-0046-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-12
- Subjects:
- Connectome-based predictive modeling -- ABCD -- Substance use -- Vulnerability
Cognitive neuroscience -- Periodicals
Developmental neurobiology -- Periodicals
Neuropsychology -- Periodicals
Neuropsychiatry -- Periodicals
612.8233 - Journal URLs:
- http://www.sciencedirect.com/ ↗
- DOI:
- 10.1016/j.dcn.2020.100878 ↗
- Languages:
- English
- ISSNs:
- 1878-9293
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
British Library STI - ELD Digital store - Ingest File:
- 15528.xml