Brain Activity Classifies Adolescents with and without a Familial History of Substance Use Disorders

We aimed to uncover differences in brain circuits of adolescents with parental positive or negative histories of substance use disorders (SUD), when performing a task that elicits emotional conflict, testing whether the brain circuits could serve as endophenotype markers to distinguish these adolesc...

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Main Authors: Jianping eQiao, Zhishun eWang, Lupo eGeronazzo-Alman, Lawrence eAmsel, Cristiane eDuarte, Seonjoo eLee, George eMusa, Jun eLong, Xiaofu eHe, Thao eDoan, Joy eHirsch, Christina W Hoven
Format: Article
Language:English
Published: Frontiers Media S.A. 2015-04-01
Series:Frontiers in Human Neuroscience
Subjects:
Online Access:http://journal.frontiersin.org/Journal/10.3389/fnhum.2015.00219/full
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spelling doaj-81a119e85f724d408ea4a115bb15d59a2020-11-25T03:05:27ZengFrontiers Media S.A.Frontiers in Human Neuroscience1662-51612015-04-01910.3389/fnhum.2015.00219125899Brain Activity Classifies Adolescents with and without a Familial History of Substance Use DisordersJianping eQiao0Zhishun eWang1Lupo eGeronazzo-Alman2Lawrence eAmsel3Cristiane eDuarte4Seonjoo eLee5George eMusa6Jun eLong7Xiaofu eHe8Thao eDoan9Joy eHirsch10Christina W Hoven11Shandong Normal UniversityColumbia UniversityColumbia UniversityColumbia UniversityColumbia UniversityColumbia UniversityColumbia UniversityCentral South UniversityColumbia UniversityColumbia UniversityYale School of MedicineColumbia UniversityWe aimed to uncover differences in brain circuits of adolescents with parental positive or negative histories of substance use disorders (SUD), when performing a task that elicits emotional conflict, testing whether the brain circuits could serve as endophenotype markers to distinguish these adolescents. We acquired functional magnetic resonance imaging data from 11 adolescents with a positive familial history of SUD (FH+ group) and 7 adolescents with a negative familial history of SUD (FH- group) when performing an emotional stroop task. We extracted brain features from the conflict-related contrast images in group level analyses and granger causality indices (GCIs) that measure the causal interactions among regions. Support vector machine was applied to classify the FH+ and FH- adolescents. Adolescents with FH+ showed greater activity and weaker connectivity related to emotional conflict, decision making and reward system including anterior cingulate cortex (ACC), prefrontal cortex (PFC) and ventral tegmental area (VTA). High classification accuracies were achieved with leave-one-out cross validation (89.75% for the maximum conflict, 96.71% when combining maximum conflict and general conflict contrast, 97.28% when combining activity of the two contrasts and GCIs). Individual contributions of the brain features to the classification were further investigated, indicating that activation in PFC, ACC, VTA and effective connectivity from PFC to ACC play the most important roles. We concluded that fundamental differences of neural substrates underlying cognitive behaviors of adolescents with parental positive or negative histories of SUD provide new insight into potential neurobiological mechanisms contributing to the elevated risk of FH+ individuals for developing SUD.http://journal.frontiersin.org/Journal/10.3389/fnhum.2015.00219/fullfMRImachine learningriskbrain connectivitysubstance use disordersEmotional Conflict
collection DOAJ
language English
format Article
sources DOAJ
author Jianping eQiao
Zhishun eWang
Lupo eGeronazzo-Alman
Lawrence eAmsel
Cristiane eDuarte
Seonjoo eLee
George eMusa
Jun eLong
Xiaofu eHe
Thao eDoan
Joy eHirsch
Christina W Hoven
spellingShingle Jianping eQiao
Zhishun eWang
Lupo eGeronazzo-Alman
Lawrence eAmsel
Cristiane eDuarte
Seonjoo eLee
George eMusa
Jun eLong
Xiaofu eHe
Thao eDoan
Joy eHirsch
Christina W Hoven
Brain Activity Classifies Adolescents with and without a Familial History of Substance Use Disorders
Frontiers in Human Neuroscience
fMRI
machine learning
risk
brain connectivity
substance use disorders
Emotional Conflict
author_facet Jianping eQiao
Zhishun eWang
Lupo eGeronazzo-Alman
Lawrence eAmsel
Cristiane eDuarte
Seonjoo eLee
George eMusa
Jun eLong
Xiaofu eHe
Thao eDoan
Joy eHirsch
Christina W Hoven
author_sort Jianping eQiao
title Brain Activity Classifies Adolescents with and without a Familial History of Substance Use Disorders
title_short Brain Activity Classifies Adolescents with and without a Familial History of Substance Use Disorders
title_full Brain Activity Classifies Adolescents with and without a Familial History of Substance Use Disorders
title_fullStr Brain Activity Classifies Adolescents with and without a Familial History of Substance Use Disorders
title_full_unstemmed Brain Activity Classifies Adolescents with and without a Familial History of Substance Use Disorders
title_sort brain activity classifies adolescents with and without a familial history of substance use disorders
publisher Frontiers Media S.A.
series Frontiers in Human Neuroscience
issn 1662-5161
publishDate 2015-04-01
description We aimed to uncover differences in brain circuits of adolescents with parental positive or negative histories of substance use disorders (SUD), when performing a task that elicits emotional conflict, testing whether the brain circuits could serve as endophenotype markers to distinguish these adolescents. We acquired functional magnetic resonance imaging data from 11 adolescents with a positive familial history of SUD (FH+ group) and 7 adolescents with a negative familial history of SUD (FH- group) when performing an emotional stroop task. We extracted brain features from the conflict-related contrast images in group level analyses and granger causality indices (GCIs) that measure the causal interactions among regions. Support vector machine was applied to classify the FH+ and FH- adolescents. Adolescents with FH+ showed greater activity and weaker connectivity related to emotional conflict, decision making and reward system including anterior cingulate cortex (ACC), prefrontal cortex (PFC) and ventral tegmental area (VTA). High classification accuracies were achieved with leave-one-out cross validation (89.75% for the maximum conflict, 96.71% when combining maximum conflict and general conflict contrast, 97.28% when combining activity of the two contrasts and GCIs). Individual contributions of the brain features to the classification were further investigated, indicating that activation in PFC, ACC, VTA and effective connectivity from PFC to ACC play the most important roles. We concluded that fundamental differences of neural substrates underlying cognitive behaviors of adolescents with parental positive or negative histories of SUD provide new insight into potential neurobiological mechanisms contributing to the elevated risk of FH+ individuals for developing SUD.
topic fMRI
machine learning
risk
brain connectivity
substance use disorders
Emotional Conflict
url http://journal.frontiersin.org/Journal/10.3389/fnhum.2015.00219/full
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