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Gonçalves PD, Martins SS, Gebru NM, Ryan-Pettes SR, Allgaier N, Potter A, Thompson WK, Johnson ME, Garavan H, Talati A, Albaugh MD. Associations Between Family History of Alcohol and/or Substance Use Problems and Frontal Cortical Development From 9 to 13 Years of Age: A Longitudinal Analysis of the ABCD Study. Biol Psychiatry Glob Open Sci 2024; 4:100284. [PMID: 38312852 PMCID: PMC10837483 DOI: 10.1016/j.bpsgos.2023.100284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 11/24/2023] [Accepted: 12/02/2023] [Indexed: 02/06/2024] Open
Abstract
Background Previous investigations that have examined associations between family history (FH) of alcohol/substance use and adolescent brain development have been primarily cross-sectional. Here, leveraging a large population-based sample of youths, we characterized frontal cortical trajectories among 9- to 13-year-olds with (FH+) versus without (FH-) an FH and examined sex as a potential moderator. Methods We used data from 9710 participants in the Adolescent Brain Cognitive Development (ABCD) Study (release 4.0). FH+ was defined as having ≥1 biological parents and/or ≥2 biological grandparents with a history of alcohol/substance use problems (n = 2433). Our primary outcome was frontal cortical structural measures obtained at baseline (ages 9-11) and year 2 follow-up (ages 11-13). We used linear mixed-effects models to examine the extent to which FH status qualified frontal cortical development over the age span studied. Finally, we ran additional interactions with sex to test whether observed associations between FH and cortical development differed significantly between sexes. Results For FH+ (vs. FH-) youths, we observed increased cortical thinning from 9 to 13 years across the frontal cortex as a whole. When we probed for sex differences, we observed significant declines in frontal cortical thickness among boys but not girls from ages 9 to 13 years. No associations were observed between FH and frontal cortical surface area or volume. Conclusions Having a FH+ is associated with more rapid thinning of the frontal cortex across ages 9 to 13, with this effect driven primarily by male participants. Future studies will need to test whether the observed pattern of accelerated thinning predicts future substance use outcomes.
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Affiliation(s)
- Priscila Dib Gonçalves
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York
- New York State Psychiatric Institute and Department of Psychiatry, Columbia University, New York, New York
| | - Silvia S. Martins
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, New York
| | - Nioud Mulugeta Gebru
- Center for Alcohol and Addiction Studies, Department of Behavioral and Social Sciences, Brown University School of Public Health, Providence, Rhode Island
| | | | - Nicholas Allgaier
- Department of Psychiatry, University of Vermont, Burlington, Vermont
| | - Alexandra Potter
- Department of Psychiatry, University of Vermont, Burlington, Vermont
| | - Wesley K. Thompson
- Center for Population Neuroscience and Genetics, Laureate Institute for Brain Research, Tulsa, Oklahoma
| | - Micah E. Johnson
- Department of Mental Health Law and Policy, College of Behavioral and Community Sciences, University of South Florida, Tampa, Florida
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont, Burlington, Vermont
| | - Ardesheer Talati
- New York State Psychiatric Institute and Department of Psychiatry, Columbia University, New York, New York
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Yuan D, Hahn S, Allgaier N, Owens MM, Chaarani B, Potter A, Garavan H. Machine learning approaches linking brain function to behavior in the ABCD STOP task. Hum Brain Mapp 2023; 44:1751-1766. [PMID: 36534603 PMCID: PMC9921227 DOI: 10.1002/hbm.26172] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Revised: 10/13/2022] [Accepted: 11/14/2022] [Indexed: 12/24/2022] Open
Abstract
The stop-signal task (SST) is one of the most common fMRI tasks of response inhibition, and its performance measure, the stop-signal reaction-time (SSRT), is broadly used as a measure of cognitive control processes. The neurobiology underlying individual or clinical differences in response inhibition remain unclear, consistent with the general pattern of quite modest brain-behavior associations that have been recently reported in well-powered large-sample studies. Here, we investigated the potential of multivariate, machine learning (ML) methods to improve the estimation of individual differences in SSRT with multimodal structural and functional region of interest-level neuroimaging data from 9- to 11-year-olds children in the ABCD Study. Six ML algorithms were assessed across modalities and fMRI tasks. We verified that SST activation performed best in predicting SSRT among multiple modalities including morphological MRI (cortical surface area/thickness), diffusion tensor imaging, and fMRI task activations, and then showed that SST activation explained 12% of the variance in SSRT using cross-validation and out-of-sample lockbox data sets (n = 7298). Brain regions that were more active during the task and that showed more interindividual variation in activation were better at capturing individual differences in performance on the task, but this was only true for activations when successfully inhibiting. Cortical regions outperformed subcortical areas in explaining individual differences but the two hemispheres performed equally well. These results demonstrate that the detection of reproducible links between brain function and performance can be improved with multivariate approaches and give insight into a number of brain systems contributing to individual differences in this fundamental cognitive control process.
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Affiliation(s)
- Dekang Yuan
- Department of Psychiatry, University of Vermont, Burlington, Vermont, USA
| | - Sage Hahn
- Department of Psychiatry, University of Vermont, Burlington, Vermont, USA
| | - Nicholas Allgaier
- Department of Psychiatry, University of Vermont, Burlington, Vermont, USA
| | - Max M Owens
- Department of Psychiatry, University of Vermont, Burlington, Vermont, USA
| | - Bader Chaarani
- Department of Psychiatry, University of Vermont, Burlington, Vermont, USA
| | - Alexandra Potter
- Department of Psychiatry, University of Vermont, Burlington, Vermont, USA
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont, Burlington, Vermont, USA
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Owens MM, Hahn S, Allgaier N, MacKillop J, Albaugh M, Yuan D, Juliano A, Potter A, Garavan H. One-year predictions of delayed reward discounting in the adolescent brain cognitive development study. Exp Clin Psychopharmacol 2022; 30:928-946. [PMID: 34914494 DOI: 10.1037/pha0000532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Delayed reward discounting (DRD) refers to the extent to which an individual devalues a reward based on a temporal delay and is known to be elevated in individuals with substance use disorders and many mental illnesses. DRD has been linked previously with both features of brain structure and function, as well as various behavioral, psychological, and life-history factors. However, there has been little work on the neurobiological and behavioral antecedents of DRD in childhood. This is an important question, as understanding the antecedents of DRD can provide signs of mechanisms in the development of psychopathology. The present study used baseline data from the Adolescent Brain Cognitive Development Study (N = 4,042) to build machine learning models to predict DRD at the first follow-up visit, 1 year later. In separate machine learning models, we tested elastic net regression, random forest regression, light gradient boosting regression, and support vector regression. In five-fold cross-validation on the training set, models using an array of questionnaire/task variables were able to predict DRD, with these findings generalizing to a held-out (i.e., "lockbox") test set of 20% of the sample. Key predictive variables were neuropsychological test performance at baseline, socioeconomic status, screen media activity, psychopathology, parenting, and personality. However, models using magnetic resonance imaging (MRI)-derived brain variables did not reliably predict DRD in either the cross-validation or held-out test set. These results suggest a combination of questionnaire/task variables as antecedents of excessive DRD in late childhood, which may presage the development of problematic substance use in adolescence. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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Garavan H, Chaarani B, Hahn S, Allgaier N, Juliano A, Yuan DK, Orr C, Watts R, Wager TD, Ruiz de Leon O, Hagler DJ, Potter A. The ABCD stop signal data: Response to Bissett et al. Dev Cogn Neurosci 2022; 57:101144. [PMID: 35987133 PMCID: PMC9411576 DOI: 10.1016/j.dcn.2022.101144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 07/12/2022] [Accepted: 08/04/2022] [Indexed: 11/03/2022] Open
Abstract
This paper responds to a recent critique by Bissett et al. of the fMRI Stop task used in the Adolescent Brain Cognitive Development℠ Study (ABCD Study®). The critique focuses primarily on a task design feature related to race model assumptions (i.e., that the Go and Stop processes are fully independent). In response, we note that the race model is quite robust against violations of its assumptions. Most importantly, while Bissett raises conceptual concerns with the task we focus here on analyzes of the task data and conclude that the concerns appear to have minimal impact on the neuroimaging data (the validity of which do not rely on race model assumptions) and have far less of an impact on the performance data than the critique suggests. We note that Bissett did not apply any performance-based exclusions to the data they analyzed, a number of the trial coding errors they flagged were already identified and corrected in ABCD annual data releases, a number of their secondary concerns reflect sensible design decisions and, indeed, their own computational modeling of the ABCD Stop task suggests the problems they identify have just a modest impact on the rank ordering of individual differences in subject performance.
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Affiliation(s)
- H Garavan
- Department of Psychiatry, University of Vermont, Burlington, VT, USA.
| | - B Chaarani
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - S Hahn
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - N Allgaier
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - A Juliano
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - D K Yuan
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - C Orr
- Department of Psychology, Swinburne University, Melbourne, Australia
| | - R Watts
- School of Medicine, Yale University, New Haven, CT, USA
| | - T D Wager
- Department of Psychological and Brain Sciences, Dartmouth College, Hanover, NH, USA
| | - O Ruiz de Leon
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - D J Hagler
- Department of Radiology, University of California, San Diego, La Jolla, CA, USA
| | - A Potter
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
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Owens MM, Albaugh MD, Allgaier N, Yuan D, Robert G, Cupertino RB, Spechler PA, Juliano A, Hahn S, Banaschewski T, Bokde ALW, Desrivières S, Flor H, Grigis A, Gowland P, Heinz A, Brühl R, Martinot JL, Martinot MLP, Artiges E, Nees F, Orfanos DP, Lemaitre H, Paus T, Poustka L, Millenet S, Fröhner JH, Smolka MN, Walter H, Whelan R, Mackey S, Schumann G, Garavan H. Bayesian causal network modeling suggests adolescent cannabis use accelerates prefrontal cortical thinning. Transl Psychiatry 2022; 12:188. [PMID: 35523763 PMCID: PMC9076659 DOI: 10.1038/s41398-022-01956-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2021] [Revised: 04/18/2022] [Accepted: 04/22/2022] [Indexed: 11/21/2022] Open
Abstract
While there is substantial evidence that cannabis use is associated with differences in human brain development, most of this evidence is correlational in nature. Bayesian causal network (BCN) modeling attempts to identify probable causal relationships in correlational data using conditional probabilities to estimate directional associations between a set of interrelated variables. In this study, we employed BCN modeling in 637 adolescents from the IMAGEN study who were cannabis naïve at age 14 to provide evidence that the accelerated prefrontal cortical thinning found previously in adolescent cannabis users by Albaugh et al. [1] is a result of cannabis use causally affecting neurodevelopment. BCNs incorporated data on cannabis use, prefrontal cortical thickness, and other factors related to both brain development and cannabis use, including demographics, psychopathology, childhood adversity, and other substance use. All BCN algorithms strongly suggested a directional relationship from adolescent cannabis use to accelerated cortical thinning. While BCN modeling alone does not prove a causal relationship, these results are consistent with a body of animal and human research suggesting that adolescent cannabis use adversely affects brain development.
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Affiliation(s)
- Max M Owens
- Department of Psychiatry, University of Vermont Larner College of Medicine, Burlington, VT, USA.
| | - Matthew D Albaugh
- Department of Psychiatry, University of Vermont Larner College of Medicine, Burlington, VT, USA
| | - Nicholas Allgaier
- Department of Psychiatry, University of Vermont Larner College of Medicine, Burlington, VT, USA
| | - Dekang Yuan
- Department of Psychiatry, University of Vermont Larner College of Medicine, Burlington, VT, USA
| | - Gabriel Robert
- Psychiatry Department, University of Rennes 1, Rennes, France
- Adult University Psychiatry Department, Guillaume Régnier Hospital, Rennes, France
- U1288 Empenn, UMR 6074, IRISA, Rennes, France
| | - Renata B Cupertino
- Department of Psychiatry, University of Vermont Larner College of Medicine, Burlington, VT, USA
| | | | - Anthony Juliano
- Department of Psychiatry, University of Vermont Larner College of Medicine, Burlington, VT, USA
| | - Sage Hahn
- Department of Psychiatry, University of Vermont Larner College of Medicine, Burlington, VT, USA
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, London, UK
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, F-91191, Gif-sur-Yvette, France
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy Campus Charité Mitte, Charité-Universitätsmedizin, corporate member of Freie Universität Berlin & Humboldt-Universität zu Berlin, Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Braunschweig, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U A10 "Trajectoires développementales en psychiatrie"; Université Paris-Saclay, Ecole Normale supérieure Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherce Médicale, INSERM U A10 "Trajectoires développementales & psychiatrie", University Paris-Saclay, Ecole Normale Supérieure Paris-Saclay, CNRS; Centre Borelli, Gif-sur-Yvette, France
- AP-HP. Sorbonne Université, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM U1299 "Trajectoires développementales en psychiatrie"; Ecole Normale supérieure Paris-Saclay, Université Paris-Saclay, Université de Paris, Centre Borelli; Gif-sur-Yvette, & Department of Psychiatry, EPS Barthélémy Durand, Etampes, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig Holstein, Kiel University, Kiel, Germany
| | | | - Herve Lemaitre
- NeuroSpin, CEA, Université Paris-Saclay, F-91191, Gif-sur-Yvette, France
- Institut des Maladies Neurodégénératives, CNRS UMR 5293, Université de Bordeaux, Centre Broca Nouvelle-Aquitaine, Bordeaux, France
| | - Tomáš Paus
- Departments of Psychiatry and Neuroscience, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, QC, Canada
- Departments of Psychology, University of Toronto, Toronto, ON, Canada
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, von-Siebold-Str. 5, 37075, Göttingen, Germany
| | - Sabina Millenet
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy Campus Charité Mitte, Charité-Universitätsmedizin, corporate member of Freie Universität Berlin & Humboldt-Universität zu Berlin, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Scott Mackey
- Department of Psychiatry, University of Vermont Larner College of Medicine, Burlington, VT, USA
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS), Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin Berlin, Berlin, Germany
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, China
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont Larner College of Medicine, Burlington, VT, USA
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Hahn S, Owens MM, Yuan D, Juliano AC, Potter A, Garavan H, Allgaier N. Performance scaling for structural MRI surface parcellations: a machine learning analysis in the ABCD Study. Cereb Cortex 2022; 33:176-194. [PMID: 35238352 PMCID: PMC9758581 DOI: 10.1093/cercor/bhac060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 01/21/2022] [Accepted: 01/22/2022] [Indexed: 11/13/2022] Open
Abstract
The use of predefined parcellations on surface-based representations of the brain as a method for data reduction is common across neuroimaging studies. In particular, prediction-based studies typically employ parcellation-driven summaries of brain measures as input to predictive algorithms, but the choice of parcellation and its influence on performance is often ignored. Here we employed preprocessed structural magnetic resonance imaging (sMRI) data from the Adolescent Brain Cognitive Development Study® to examine the relationship between 220 parcellations and out-of-sample predictive performance across 45 phenotypic measures in a large sample of 9- to 10-year-old children (N = 9,432). Choice of machine learning (ML) pipeline and use of alternative multiple parcellation-based strategies were also assessed. Relative parcellation performance was dependent on the spatial resolution of the parcellation, with larger number of parcels (up to ~4,000) outperforming coarser parcellations, according to a power-law scaling of between 1/4 and 1/3. Performance was further influenced by the type of parcellation, ML pipeline, and general strategy, with existing literature-based parcellations, a support vector-based pipeline, and ensembling across multiple parcellations, respectively, as the highest performing. These findings highlight the choice of parcellation as an important influence on downstream predictive performance, showing in some cases that switching to a higher resolution parcellation can yield a relatively large boost to performance.
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Affiliation(s)
- Sage Hahn
- Corresponding author: Departments of Complex Systems and Psychiatry, University of Vermont, Burlington, 100 South Prospect Street Burlington, Vermont 05401, United States.
| | - Max M Owens
- Departments of Complex Systems and Psychiatry, University of Vermont, Burlington, VT 05401, United States
| | - DeKang Yuan
- Departments of Complex Systems and Psychiatry, University of Vermont, Burlington, VT 05401, United States
| | - Anthony C Juliano
- Departments of Complex Systems and Psychiatry, University of Vermont, Burlington, VT 05401, United States
| | - Alexandra Potter
- Departments of Complex Systems and Psychiatry, University of Vermont, Burlington, VT 05401, United States
| | - Hugh Garavan
- Departments of Complex Systems and Psychiatry, University of Vermont, Burlington, VT 05401, United States
| | - Nicholas Allgaier
- Departments of Complex Systems and Psychiatry, University of Vermont, Burlington, VT 05401, United States
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Ottino-González J, Uhlmann A, Hahn S, Cao Z, Cupertino RB, Schwab N, Allgaier N, Alia-Klein N, Ekhtiari H, Fouche JP, Goldstein RZ, Li CSR, Lochner C, London ED, Luijten M, Masjoodi S, Momenan R, Oghabian MA, Roos A, Stein DJ, Stein EA, Veltman DJ, Verdejo-García A, Zhang S, Zhao M, Zhong N, Jahanshad N, Thompson PM, Conrod P, Mackey S, Garavan H. White matter microstructure differences in individuals with dependence on cocaine, methamphetamine, and nicotine: Findings from the ENIGMA-Addiction working group. Drug Alcohol Depend 2022; 230:109185. [PMID: 34861493 PMCID: PMC8952409 DOI: 10.1016/j.drugalcdep.2021.109185] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Revised: 10/27/2021] [Accepted: 11/14/2021] [Indexed: 01/03/2023]
Abstract
BACKGROUND Nicotine and illicit stimulants are very addictive substances. Although associations between grey matter and dependence on stimulants have been frequently reported, white matter correlates have received less attention. METHODS Eleven international sites ascribed to the ENIGMA-Addiction consortium contributed data from individuals with dependence on cocaine (n = 147), methamphetamine (n = 132) and nicotine (n = 189), as well as non-dependent controls (n = 333). We compared the fractional anisotropy (FA), axial diffusivity (AD), radial diffusivity (RD) and mean diffusivity (MD) of 20 bilateral tracts. Also, we compared the performance of various machine learning algorithms in deriving brain-based classifications on stimulant dependence. RESULTS The cocaine and methamphetamine groups had lower regional FA and higher RD in several association, commissural, and projection white matter tracts. The methamphetamine dependent group additionally showed lower regional AD. The nicotine group had lower FA and higher RD limited to the anterior limb of the internal capsule. The best performing machine learning algorithm was the support vector machine (SVM). The SVM successfully classified individuals with dependence on cocaine (AUC = 0.70, p < 0.001) and methamphetamine (AUC = 0.71, p < 0.001) relative to non-dependent controls. Classifications related to nicotine dependence proved modest (AUC = 0.62, p = 0.014). CONCLUSIONS Stimulant dependence was related to FA disturbances within tracts consistent with a role in addiction. The multivariate pattern of white matter differences proved sufficient to identify individuals with stimulant dependence, particularly for cocaine and methamphetamine.
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Affiliation(s)
- Jonatan Ottino-González
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, Vermont, United States.
| | - Anne Uhlmann
- Department of Child & Adolescent Psychiatry and Psychotherapy, Technische Universität Dresden, Dresden, Germany
| | - Sage Hahn
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, Vermont, United States
| | - Zhipeng Cao
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, Vermont, United States
| | - Renata B. Cupertino
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, Vermont, United States
| | - Nathan Schwab
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, Vermont, United States
| | - Nicholas Allgaier
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, Vermont, United States
| | - Nelly Alia-Klein
- Department of Psychiatry & Neuroscience, Icahn School of Medicine at Mount Sinai, New York City, New York, United States
| | - Hamed Ekhtiari
- Institute for Cognitive Sciences Studies, University of Tehran, Tehran, Iran,Iranian National Center for Addiction Studies, Tehran University of Medical Sciences, Tehran, Iran
| | - Jean-Paul Fouche
- SA MRC Genomics and Brain Disorders Unit, Department of Psychiatry, Stellenbosch University, Stellenbosch, South Africa
| | - Rita Z. Goldstein
- Department of Psychiatry & Neuroscience, Icahn School of Medicine at Mount Sinai, New York City, New York, United States
| | - Chiang-Shan R. Li
- Department of Psychiatry, Yale University, New Haven, Connecticut, United States
| | - Christine Lochner
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry, Stellenbosch University, Stellenbosch, South Africa
| | - Edythe D. London
- Department of Psychiatry and Biobehavioural Sciences, University of California, Los Angeles, California, United States
| | - Maartje Luijten
- Behavioural Science Institute, Radboud University, Nijmegen, The Netherlands
| | - Sadegh Masjoodi
- Shiraz Neuroscience Research Center, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Reza Momenan
- Clinical Neuroimaging Research Core, National Institutes on Alcohol Abuse & Alcoholism, National Institutes of Health, Bethesda, Maryland, United States
| | - Mohammad Ali Oghabian
- Neuroimaging & Analysis Group, Research Center for Molecular and Cellular Imaging, Tehran University of Medical Sciences, Tehran, Iran
| | - Annerine Roos
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry, Stellenbosch University, Stellenbosch, South Africa,SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Dan J. Stein
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Elliot A. Stein
- Neuroimaging Research Branch, Intramural Research Program, National Institute of Drug Abuse, Baltimore, Maryland, United States
| | - Dick J. Veltman
- Department of Psychiatry, Amsterdam UMC – location VUMC, Amsterdam, the Netherlands
| | - Antonio Verdejo-García
- School of Psychological Sciences & Turner Institute for Brain & Mental Health, Monash University, Melbourne, Australia
| | - Sheng Zhang
- Department of Psychiatry, Yale University, New Haven, Connecticut, United States
| | - Min Zhao
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Na Zhong
- Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Neda Jahanshad
- Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, San Diego, California, United States
| | - Paul M. Thompson
- Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, San Diego, California, United States
| | - Patricia Conrod
- Department of Psychiatry, Université de Montreal, Montreal, Quebec, Canada
| | - Scott Mackey
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, Vermont, United States
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, Vermont, United States
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Lisdahl KM, Tapert S, Sher KJ, Gonzalez R, Nixon SJ, Ewing SWF, Conway KP, Wallace A, Sullivan R, Hatcher K, Kaiver C, Thompson W, Reuter C, Bartsch H, Wade NE, Jacobus J, Albaugh MD, Allgaier N, Anokhin AP, Bagot K, Baker FC, Banich MT, Barch DM, Baskin-Sommers A, Breslin FJ, Brown SA, Calhoun V, Casey BJ, Chaarani B, Chang L, Clark DB, Cloak C, Constable RT, Cottler LB, Dagher RK, Dapretto M, Dick A, Do EK, Dosenbach NUF, Dowling GJ, Fair DA, Florsheim P, Foxe JJ, Freedman EG, Friedman NP, Garavan HP, Gee DG, Glantz MD, Glaser P, Gonzalez MR, Gray KM, Grant S, Haist F, Hawes S, Heeringa SG, Hermosillo R, Herting MM, Hettema JM, Hewitt JK, Heyser C, Hoffman EA, Howlett KD, Huber RS, Huestis MA, Hyde LW, Iacono WG, Isaiah A, Ivanova MY, James RS, Jernigan TL, Karcher NR, Kuperman JM, Laird AR, Larson CL, LeBlanc KH, Lopez MF, Luciana M, Luna B, Maes HH, Marshall AT, Mason MJ, McGlade E, Morris AS, Mulford C, Nagel BJ, Neigh G, Palmer CE, Paulus MP, Pecheva D, Prouty D, Potter A, Puttler LI, Rajapakse N, Ross JM, Sanchez M, Schirda C, Schulenberg J, Sheth C, Shilling PD, Sowell ER, Speer N, Squeglia L, Sripada C, Steinberg J, Sutherland MT, Tomko R, Uban K, Vrieze S, Weiss SRB, Wing D, Yurgelun-Todd DA, Zucker RA, Heitzeg MM. Substance use patterns in 9-10 year olds: Baseline findings from the adolescent brain cognitive development (ABCD) study. Drug Alcohol Depend 2021; 227:108946. [PMID: 34392051 PMCID: PMC8833837 DOI: 10.1016/j.drugalcdep.2021.108946] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Revised: 06/03/2021] [Accepted: 06/05/2021] [Indexed: 01/28/2023]
Abstract
BACKGROUND The Adolescent Brain Cognitive Development ™ Study (ABCD Study®) is an open-science, multi-site, prospective, longitudinal study following over 11,800 9- and 10-year-old youth into early adulthood. The ABCD Study aims to prospectively examine the impact of substance use (SU) on neurocognitive and health outcomes. Although SU initiation typically occurs during teen years, relatively little is known about patterns of SU in children younger than 12. METHODS This study aims to report the detailed ABCD Study® SU patterns at baseline (n = 11,875) in order to inform the greater scientific community about cohort's early SU. Along with a detailed description of SU, we ran mixed effects regression models to examine the association between early caffeine and alcohol sipping with demographic factors, externalizing symptoms and parental history of alcohol and substance use disorders (AUD/SUD). PRIMARY RESULTS At baseline, the majority of youth had used caffeine (67.6 %) and 22.5 % reported sipping alcohol (22.5 %). There was little to no reported use of other drug categories (0.2 % full alcohol drink, 0.7 % used nicotine, <0.1 % used any other drug of abuse). Analyses revealed that total caffeine use and early alcohol sipping were associated with demographic variables (p's<.05), externalizing symptoms (caffeine p = 0002; sipping p = .0003), and parental history of AUD (sipping p = .03). CONCLUSIONS ABCD Study participants aged 9-10 years old reported caffeine use and alcohol sipping experimentation, but very rare other SU. Variables linked with early childhood alcohol sipping and caffeine use should be examined as contributing factors in future longitudinal analyses examining escalating trajectories of SU in the ABCD Study cohort.
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Affiliation(s)
- Krista M Lisdahl
- University of Wisconsin, Milwaukee, WI, United States; Medical College of Wisconsin, Milwaukee, WI, United States.
| | - Susan Tapert
- University of California, San Diego, CA, United States
| | | | - Raul Gonzalez
- Florida International University, Miami, FL, United States
| | - Sara Jo Nixon
- University of Florida, Gainesville, FL, United States
| | | | - Kevin P Conway
- National Institute on Drug Abuse, NIH, Bethesda, MD, United States
| | - Alex Wallace
- University of Wisconsin, Milwaukee, WI, United States
| | - Ryan Sullivan
- University of Wisconsin, Milwaukee, WI, United States
| | - Kelah Hatcher
- University of Wisconsin, Milwaukee, WI, United States
| | | | - Wes Thompson
- University of California, San Diego, CA, United States
| | - Chase Reuter
- University of California, San Diego, CA, United States
| | - Hauke Bartsch
- University of California, San Diego, CA, United States
| | | | | | - M D Albaugh
- University of Vermont, Burlington, VT, United States
| | - N Allgaier
- University of Vermont, Burlington, VT, United States
| | - A P Anokhin
- Washington University, St. Louis, MO, United States
| | - K Bagot
- University of California, San Diego, CA, United States; Icahn School of Medicine at Mount Sinai, United States
| | - F C Baker
- SRI International, Menlo Park, CA, United States
| | - M T Banich
- University of Colorado Boulder, CO, United States
| | - D M Barch
- Washington University, St. Louis, MO, United States
| | | | - F J Breslin
- Laureate Institute for Brain Research, Tulsa, OK, United States
| | - S A Brown
- University of California, San Diego, CA, United States
| | - V Calhoun
- Georgia State University, Atlanta, GA, United States
| | - B J Casey
- Yale University, New Haven, CT, United States
| | - B Chaarani
- University of Vermont, Burlington, VT, United States
| | - L Chang
- University of Maryland School of Medicine, Baltimore, MD, United States
| | - D B Clark
- University of Pittsburgh, Pittsburgh, PA, United States
| | - C Cloak
- University of Maryland School of Medicine, Baltimore, MD, United States
| | | | - L B Cottler
- University of Florida, Gainesville, FL, United States
| | - R K Dagher
- National Institute of Minority Health and Health Disparities, Bethesda, MD, United States
| | - M Dapretto
- University of California, Los Angeles, CA, United States
| | - A Dick
- Florida International University, Miami, FL, United States
| | - E K Do
- Virginia Commonwealth University, Richmond, VA, United States
| | | | - G J Dowling
- National Institute on Drug Abuse, NIH, Bethesda, MD, United States
| | - D A Fair
- University of Minnesota, Minneapolis, MN, United States
| | - P Florsheim
- University of Wisconsin, Milwaukee, WI, United States
| | - J J Foxe
- University of Rochester, Rochester, NY, United States
| | - E G Freedman
- University of Rochester, Rochester, NY, United States
| | - N P Friedman
- University of Colorado Boulder, CO, United States
| | - H P Garavan
- University of Vermont, Burlington, VT, United States
| | - D G Gee
- Yale University, New Haven, CT, United States
| | - M D Glantz
- National Institute on Drug Abuse, NIH, Bethesda, MD, United States
| | - P Glaser
- Washington University, St. Louis, MO, United States
| | - M R Gonzalez
- Children’s Hospital Los Angeles, Los Angeles, CA, United States
| | - K M Gray
- Medical University of South Carolina, Charleston, SC, United States
| | - S Grant
- National Institute on Drug Abuse, NIH, Bethesda, MD, United States
| | - F Haist
- University of California, San Diego, CA, United States
| | - S Hawes
- Florida International University, Miami, FL, United States
| | - S G Heeringa
- University of Michigan, Ann Arbor, MI, United States
| | - R Hermosillo
- Oregon Health & Science University, Portland, OR, United States
| | - M M Herting
- University of Southern California, Los Angeles, CA, United States
| | - J M Hettema
- Virginia Commonwealth University, Richmond, VA, United States
| | - J K Hewitt
- University of Colorado Boulder, CO, United States
| | - C Heyser
- University of California, San Diego, CA, United States
| | - E A Hoffman
- National Institute on Drug Abuse, NIH, Bethesda, MD, United States
| | - K D Howlett
- National Institute on Drug Abuse, NIH, Bethesda, MD, United States
| | - R S Huber
- University of Utah, Salt Lake City, UT, United States
| | - M A Huestis
- University of California, San Diego, CA, United States; Thomas Jefferson University, Philadelphia, PA, United States
| | - L W Hyde
- University of Michigan, Ann Arbor, MI, United States
| | - W G Iacono
- University of Minnesota, Minneapolis, MN, United States
| | - A Isaiah
- University of Maryland School of Medicine, Baltimore, MD, United States
| | - M Y Ivanova
- University of Vermont, Burlington, VT, United States
| | - R S James
- American Psychistric Association, United States
| | - T L Jernigan
- University of California, San Diego, CA, United States
| | - N R Karcher
- Washington University, St. Louis, MO, United States
| | - J M Kuperman
- University of California, San Diego, CA, United States
| | - A R Laird
- Florida International University, Miami, FL, United States
| | - C L Larson
- University of Wisconsin, Milwaukee, WI, United States
| | - K H LeBlanc
- National Institute on Drug Abuse, NIH, Bethesda, MD, United States
| | - M F Lopez
- National Institute on Drug Abuse, NIH, Bethesda, MD, United States
| | - M Luciana
- University of Minnesota, Minneapolis, MN, United States
| | - B Luna
- University of Pittsburgh, Pittsburgh, PA, United States
| | - H H Maes
- Virginia Commonwealth University, Richmond, VA, United States
| | - A T Marshall
- Children’s Hospital Los Angeles, Los Angeles, CA, United States
| | - M J Mason
- University of Tennessee, Knoxville, TN, United States
| | - E McGlade
- University of Utah, Salt Lake City, UT, United States
| | - A S Morris
- Laureate Institute for Brain Research, Tulsa, OK, United States; Oklahoma State University, Stillwater, OK, United States
| | - C Mulford
- National Institute on Drug Abuse, NIH, Bethesda, MD, United States
| | - B J Nagel
- Oregon Health & Science University, Portland, OR, United States
| | - G Neigh
- Virginia Commonwealth University, Richmond, VA, United States
| | - C E Palmer
- University of California, San Diego, CA, United States
| | - M P Paulus
- Laureate Institute for Brain Research, Tulsa, OK, United States
| | - D Pecheva
- University of California, San Diego, CA, United States
| | - D Prouty
- SRI International, Menlo Park, CA, United States
| | - A Potter
- University of Vermont, Burlington, VT, United States
| | - L I Puttler
- University of Michigan, Ann Arbor, MI, United States
| | - N Rajapakse
- National Institute of Minority Health and Health Disparities, Bethesda, MD, United States
| | - J M Ross
- University of Colorado Anschutz Medical Campus, Aurora, CO, United States
| | - M Sanchez
- Florida International University, Miami, FL, United States
| | - C Schirda
- University of Pittsburgh, Pittsburgh, PA, United States
| | - J Schulenberg
- University of Michigan, Ann Arbor, MI, United States
| | - C Sheth
- University of Utah, Salt Lake City, UT, United States
| | - P D Shilling
- University of California, San Diego, CA, United States
| | - E R Sowell
- Children’s Hospital Los Angeles, Los Angeles, CA, United States
| | - N Speer
- University of Colorado Boulder, CO, United States
| | - L Squeglia
- Medical University of South Carolina, Charleston, SC, United States
| | - C Sripada
- University of Michigan, Ann Arbor, MI, United States
| | - J Steinberg
- Virginia Commonwealth University, Richmond, VA, United States
| | - M T Sutherland
- Florida International University, Miami, FL, United States
| | - R Tomko
- Medical University of South Carolina, Charleston, SC, United States
| | - K Uban
- University of California, Irvine, CA, United States
| | - S Vrieze
- University of Minnesota, Minneapolis, MN, United States
| | - S R B Weiss
- National Institute on Drug Abuse, NIH, Bethesda, MD, United States
| | - D Wing
- University of California, San Diego, CA, United States
| | | | - R A Zucker
- University of Michigan, Ann Arbor, MI, United States
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9
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Owens MM, Potter A, Hyatt CS, Albaugh M, Thompson WK, Jernigan T, Yuan D, Hahn S, Allgaier N, Garavan H. Recalibrating expectations about effect size: A multi-method survey of effect sizes in the ABCD study. PLoS One 2021; 16:e0257535. [PMID: 34555056 PMCID: PMC8460025 DOI: 10.1371/journal.pone.0257535] [Citation(s) in RCA: 56] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2020] [Accepted: 09/04/2021] [Indexed: 02/02/2023] Open
Abstract
Effect sizes are commonly interpreted using heuristics established by Cohen (e.g., small: r = .1, medium r = .3, large r = .5), despite mounting evidence that these guidelines are mis-calibrated to the effects typically found in psychological research. This study's aims were to 1) describe the distribution of effect sizes across multiple instruments, 2) consider factors qualifying the effect size distribution, and 3) identify examples as benchmarks for various effect sizes. For aim one, effect size distributions were illustrated from a large, diverse sample of 9/10-year-old children. This was done by conducting Pearson's correlations among 161 variables representing constructs from all questionnaires and tasks from the Adolescent Brain and Cognitive Development Study® baseline data. To achieve aim two, factors qualifying this distribution were tested by comparing the distributions of effect size among various modifications of the aim one analyses. These modified analytic strategies included comparisons of effect size distributions for different types of variables, for analyses using statistical thresholds, and for analyses using several covariate strategies. In aim one analyses, the median in-sample effect size was .03, and values at the first and third quartiles were .01 and .07. In aim two analyses, effects were smaller for associations across instruments, content domains, and reporters, as well as when covarying for sociodemographic factors. Effect sizes were larger when thresholding for statistical significance. In analyses intended to mimic conditions used in "real-world" analysis of ABCD data, the median in-sample effect size was .05, and values at the first and third quartiles were .03 and .09. To achieve aim three, examples for varying effect sizes are reported from the ABCD dataset as benchmarks for future work in the dataset. In summary, this report finds that empirically determined effect sizes from a notably large dataset are smaller than would be expected based on existing heuristics.
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Affiliation(s)
- Max M. Owens
- Department of Psychiatry, University of Vermont, Burlington, VT, United States of America
- * E-mail:
| | - Alexandra Potter
- Department of Psychiatry, University of Vermont, Burlington, VT, United States of America
| | - Courtland S. Hyatt
- Psychology Department, University of Georgia, Athens, GA, United States of America
| | - Matthew Albaugh
- Department of Psychiatry, University of Vermont, Burlington, VT, United States of America
| | - Wesley K. Thompson
- Division of Biostatistics, Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA, United States of America
| | - Terry Jernigan
- University of California, San Diego, CA, United States of America
| | - Dekang Yuan
- Department of Psychiatry, University of Vermont, Burlington, VT, United States of America
| | - Sage Hahn
- Department of Psychiatry, University of Vermont, Burlington, VT, United States of America
| | - Nicholas Allgaier
- Department of Psychiatry, University of Vermont, Burlington, VT, United States of America
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont, Burlington, VT, United States of America
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10
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Chaarani B, Hahn S, Allgaier N, Adise S, Owens MM, Juliano AC, Yuan DK, Loso H, Ivanciu A, Albaugh MD, Dumas J, Mackey S, Laurent J, Ivanova M, Hagler DJ, Cornejo MD, Hatton S, Agrawal A, Aguinaldo L, Ahonen L, Aklin W, Anokhin AP, Arroyo J, Avenevoli S, Babcock D, Bagot K, Baker FC, Banich MT, Barch DM, Bartsch H, Baskin-Sommers A, Bjork JM, Blachman-Demner D, Bloch M, Bogdan R, Bookheimer SY, Breslin F, Brown S, Calabro FJ, Calhoun V, Casey BJ, Chang L, Clark DB, Cloak C, Constable RT, Constable K, Corley R, Cottler LB, Coxe S, Dagher RK, Dale AM, Dapretto M, Delcarmen-Wiggins R, Dick AS, Do EK, Dosenbach NUF, Dowling GJ, Edwards S, Ernst TM, Fair DA, Fan CC, Feczko E, Feldstein-Ewing SW, Florsheim P, Foxe JJ, Freedman EG, Friedman NP, Friedman-Hill S, Fuemmeler BF, Galvan A, Gee DG, Giedd J, Glantz M, Glaser P, Godino J, Gonzalez M, Gonzalez R, Grant S, Gray KM, Haist F, Harms MP, Hawes S, Heath AC, Heeringa S, Heitzeg MM, Hermosillo R, Herting MM, Hettema JM, Hewitt JK, Heyser C, Hoffman E, Howlett K, Huber RS, Huestis MA, Hyde LW, Iacono WG, Infante MA, Irfanoglu O, Isaiah A, Iyengar S, Jacobus J, James R, Jean-Francois B, Jernigan T, Karcher NR, Kaufman A, Kelley B, Kit B, Ksinan A, Kuperman J, Laird AR, Larson C, LeBlanc K, Lessov-Schlagger C, Lever N, Lewis DA, Lisdahl K, Little AR, Lopez M, Luciana M, Luna B, Madden PA, Maes HH, Makowski C, Marshall AT, Mason MJ, Matochik J, McCandliss BD, McGlade E, Montoya I, Morgan G, Morris A, Mulford C, Murray P, Nagel BJ, Neale MC, Neigh G, Nencka A, Noronha A, Nixon SJ, Palmer CE, Pariyadath V, Paulus MP, Pelham WE, Pfefferbaum D, Pierpaoli C, Prescot A, Prouty D, Puttler LI, Rajapaske N, Rapuano KM, Reeves G, Renshaw PF, Riedel MC, Rojas P, de la Rosa M, Rosenberg MD, Ross MJ, Sanchez M, Schirda C, Schloesser D, Schulenberg J, Sher KJ, Sheth C, Shilling PD, Simmons WK, Sowell ER, Speer N, Spittel M, Squeglia LM, Sripada C, Steinberg J, Striley C, Sutherland MT, Tanabe J, Tapert SF, Thompson W, Tomko RL, Uban KA, Vrieze S, Wade NE, Watts R, Weiss S, Wiens BA, Williams OD, Wilbur A, Wing D, Wolff-Hughes D, Yang R, Yurgelun-Todd DA, Zucker RA, Potter A, Garavan HP. Baseline brain function in the preadolescents of the ABCD Study. Nat Neurosci 2021; 24:1176-1186. [PMID: 34099922 PMCID: PMC8947197 DOI: 10.1038/s41593-021-00867-9] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Accepted: 04/30/2021] [Indexed: 02/05/2023]
Abstract
The Adolescent Brain Cognitive Development (ABCD) Study® is a 10-year longitudinal study of children recruited at ages 9 and 10. A battery of neuroimaging tasks are administered biennially to track neurodevelopment and identify individual differences in brain function. This study reports activation patterns from functional MRI (fMRI) tasks completed at baseline, which were designed to measure cognitive impulse control with a stop signal task (SST; N = 5,547), reward anticipation and receipt with a monetary incentive delay (MID) task (N = 6,657) and working memory and emotion reactivity with an emotional N-back (EN-back) task (N = 6,009). Further, we report the spatial reproducibility of activation patterns by assessing between-group vertex/voxelwise correlations of blood oxygen level-dependent (BOLD) activation. Analyses reveal robust brain activations that are consistent with the published literature, vary across fMRI tasks/contrasts and slightly correlate with individual behavioral performance on the tasks. These results establish the preadolescent brain function baseline, guide interpretation of cross-sectional analyses and will enable the investigation of longitudinal changes during adolescent development.
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Affiliation(s)
- B Chaarani
- Department of Psychiatry, University of Vermont, Burlington, VT, USA.
| | - S Hahn
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - N Allgaier
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - S Adise
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - M M Owens
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - A C Juliano
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - D K Yuan
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - H Loso
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - A Ivanciu
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - M D Albaugh
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - J Dumas
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - S Mackey
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - J Laurent
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - M Ivanova
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - D J Hagler
- University of California, San Diego, La Jolla, CA, USA
| | - M D Cornejo
- Institute of Physics UC, Pontificia Universidad Catolica de Chile, Pontificia, Chile
| | - S Hatton
- University of California, San Diego, La Jolla, CA, USA
| | - A Agrawal
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | - L Aguinaldo
- University of California, San Diego, La Jolla, CA, USA
| | - L Ahonen
- University of Pittsburgh, Pittsburgh, PA, USA
| | - W Aklin
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - A P Anokhin
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | - J Arroyo
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, USA
| | - S Avenevoli
- National Institute of Mental Health, Bethesda, MD, USA
| | - D Babcock
- National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - K Bagot
- Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - F C Baker
- SRI International, Menlo Park, CA, USA
| | - M T Banich
- University of Colorado, Boulder, CO, USA
| | - D M Barch
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | - H Bartsch
- Haukeland University Hospital, Bergen, Norway
| | | | - J M Bjork
- Virginia Commonwealth University, Richmond, VA, USA
| | - D Blachman-Demner
- NIH Office of Behavioral and Social Sciences Research, Bethesda, MD, USA
| | - M Bloch
- National Cancer Institute, Bethesda, MD, USA
| | - R Bogdan
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | | | - F Breslin
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - S Brown
- University of California, San Diego, La Jolla, CA, USA
| | - F J Calabro
- University of Pittsburgh, Pittsburgh, PA, USA
| | - V Calhoun
- University of Colorado, Boulder, CO, USA
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Institute of Technology, Emory University, Atlanta, GA, USA
| | | | - L Chang
- University of Maryland School of Medicine, Baltimore, MD, USA
| | - D B Clark
- University of Pittsburgh, Pittsburgh, PA, USA
| | - C Cloak
- University of Maryland School of Medicine, Baltimore, MD, USA
| | | | - K Constable
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - R Corley
- University of Colorado, Boulder, CO, USA
| | | | - S Coxe
- Florida International University, Miami, FL, USA
| | - R K Dagher
- National Institute on Minority Health and Health Disparities, Bethesda, MD, USA
| | - A M Dale
- University of California, San Diego, La Jolla, CA, USA
| | - M Dapretto
- University of California, Los Angeles, CA, USA
| | | | - A S Dick
- Florida International University, Miami, FL, USA
| | - E K Do
- Virginia Commonwealth University, Richmond, VA, USA
| | - N U F Dosenbach
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | - G J Dowling
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - S Edwards
- University of Maryland School of Medicine, Baltimore, MD, USA
| | - T M Ernst
- University of Maryland School of Medicine, Baltimore, MD, USA
| | - D A Fair
- Oregon Health & Science University, Portland, OR, USA
| | - C C Fan
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | - E Feczko
- Oregon Health & Science University, Portland, OR, USA
| | | | | | - J J Foxe
- University of Rochester, Rochester, NY, USA
| | | | | | | | | | - A Galvan
- University of California, Los Angeles, CA, USA
| | - D G Gee
- Yale University, New Haven, CT, USA
| | - J Giedd
- University of California, San Diego, La Jolla, CA, USA
| | - M Glantz
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - P Glaser
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | - J Godino
- University of California, San Diego, La Jolla, CA, USA
| | - M Gonzalez
- Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - R Gonzalez
- Florida International University, Miami, FL, USA
| | - S Grant
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - K M Gray
- Medical University of South Carolina, Charleston, SC, USA
| | - F Haist
- University of California, San Diego, La Jolla, CA, USA
| | - M P Harms
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | - S Hawes
- Florida International University, Miami, FL, USA
| | - A C Heath
- University of California, San Diego, La Jolla, CA, USA
| | - S Heeringa
- University of Michigan, Ann Arbor, MI, USA
| | | | - R Hermosillo
- Oregon Health & Science University, Portland, OR, USA
| | - M M Herting
- University of Southern California, Los Angeles, CA, USA
| | - J M Hettema
- Virginia Commonwealth University, Richmond, VA, USA
| | - J K Hewitt
- University of Colorado, Boulder, CO, USA
| | - C Heyser
- University of California, San Diego, La Jolla, CA, USA
| | - E Hoffman
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - K Howlett
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - R S Huber
- University of Utah, Salt Lake City, UT, USA
| | - M A Huestis
- Thomas Jefferson University, Philadelphia, PA, USA
| | - L W Hyde
- University of Michigan, Ann Arbor, MI, USA
| | - W G Iacono
- University of Minnesota, Minneapolis, MN, USA
| | - M A Infante
- University of California, San Diego, La Jolla, CA, USA
| | - O Irfanoglu
- National Institute of Biomedical Imaging and Bioengineering, Bethesda, MD, USA
| | - A Isaiah
- University of Maryland School of Medicine, Baltimore, MD, USA
| | - S Iyengar
- National Endowment for the Arts, Washington DC, USA
| | - J Jacobus
- University of California, San Diego, La Jolla, CA, USA
| | - R James
- Virginia Commonwealth University, Richmond, VA, USA
| | - B Jean-Francois
- National Institute on Minority Health and Health Disparities, Bethesda, MD, USA
| | - T Jernigan
- University of California, San Diego, La Jolla, CA, USA
| | - N R Karcher
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | - A Kaufman
- National Cancer Institute, Bethesda, MD, USA
| | - B Kelley
- National Institute of Justice, Washington DC, USA
| | - B Kit
- National Heart, Lung, and Blood Institute, Bethesda, MD, USA
| | - A Ksinan
- Virginia Commonwealth University, Richmond, VA, USA
| | - J Kuperman
- University of California, San Diego, La Jolla, CA, USA
| | - A R Laird
- Florida International University, Miami, FL, USA
| | - C Larson
- University of Wisconsin, Milwaukee, WI, USA
| | - K LeBlanc
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - C Lessov-Schlagger
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | - N Lever
- University of Maryland School of Medicine, Baltimore, MD, USA
| | - D A Lewis
- University of Pittsburgh, Pittsburgh, PA, USA
| | - K Lisdahl
- University of Wisconsin, Milwaukee, WI, USA
| | - A R Little
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - M Lopez
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - M Luciana
- University of Minnesota, Minneapolis, MN, USA
| | - B Luna
- University of Pittsburgh, Pittsburgh, PA, USA
| | - P A Madden
- Department of Psychiatry, Washington University in Saint Louis, St. Louis, MO, USA
| | - H H Maes
- Virginia Commonwealth University, Richmond, VA, USA
| | - C Makowski
- University of California, San Diego, La Jolla, CA, USA
| | - A T Marshall
- Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - M J Mason
- University of Tennessee, Knoxville, TN, USA
| | - J Matochik
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, USA
| | | | - E McGlade
- University of Utah, Salt Lake City, UT, USA
| | - I Montoya
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - G Morgan
- National Cancer Institute, Bethesda, MD, USA
| | - A Morris
- Oklahoma State University, Stillwater, OK, USA
| | - C Mulford
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - P Murray
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, USA
| | - B J Nagel
- Oregon Health & Science University, Portland, OR, USA
| | - M C Neale
- Virginia Commonwealth University, Richmond, VA, USA
| | - G Neigh
- Virginia Commonwealth University, Richmond, VA, USA
| | - A Nencka
- Medical College of Wisconsin, Milwaukee, WI, USA
| | - A Noronha
- National Institute on Alcohol Abuse and Alcoholism, Bethesda, MD, USA
| | - S J Nixon
- University of Florida, Gainesville, FL, USA
| | - C E Palmer
- University of California, San Diego, La Jolla, CA, USA
| | - V Pariyadath
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - M P Paulus
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - W E Pelham
- Florida International University, Miami, FL, USA
| | | | - C Pierpaoli
- Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, MD, USA
| | - A Prescot
- University of Utah, Salt Lake City, UT, USA
| | - D Prouty
- SRI International, Menlo Park, CA, USA
| | | | - N Rajapaske
- National Institute on Minority Health and Health Disparities, Bethesda, MD, USA
| | | | - G Reeves
- University of Maryland School of Medicine, Baltimore, MD, USA
| | | | - M C Riedel
- Florida International University, Miami, FL, USA
| | - P Rojas
- Florida International University, Miami, FL, USA
| | - M de la Rosa
- Florida International University, Miami, FL, USA
| | | | - M J Ross
- University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - M Sanchez
- Florida International University, Miami, FL, USA
| | - C Schirda
- University of Pittsburgh, Pittsburgh, PA, USA
| | - D Schloesser
- NIH Office of Behavioral and Social Sciences Research, Bethesda, MD, USA
| | | | - K J Sher
- University of Missouri, Columbia, MO, USA
| | - C Sheth
- University of Utah, Salt Lake City, UT, USA
| | - P D Shilling
- University of California, San Diego, La Jolla, CA, USA
| | - W K Simmons
- Laureate Institute for Brain Research, Tulsa, OK, USA
| | - E R Sowell
- Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - N Speer
- University of Colorado, Boulder, CO, USA
| | - M Spittel
- NIH Office of Behavioral and Social Sciences Research, Bethesda, MD, USA
| | - L M Squeglia
- Medical University of South Carolina, Charleston, SC, USA
| | - C Sripada
- University of Michigan, Ann Arbor, MI, USA
| | - J Steinberg
- Virginia Commonwealth University, Richmond, VA, USA
| | - C Striley
- University of Florida, Gainesville, FL, USA
| | | | - J Tanabe
- University of Colorado, Boulder, CO, USA
| | - S F Tapert
- University of California, San Diego, La Jolla, CA, USA
| | - W Thompson
- University of California, San Diego, La Jolla, CA, USA
| | - R L Tomko
- Medical University of South Carolina, Charleston, SC, USA
| | - K A Uban
- University of California, Irvine, CA, USA
| | - S Vrieze
- University of Minnesota, Minneapolis, MN, USA
| | - N E Wade
- University of California, San Diego, La Jolla, CA, USA
| | - R Watts
- Yale University, New Haven, CT, USA
| | - S Weiss
- National Institute on Drug Abuse, Bethesda, MD, USA
| | - B A Wiens
- University of Florida, Gainesville, FL, USA
| | - O D Williams
- Florida International University, Miami, FL, USA
| | - A Wilbur
- SRI International, Menlo Park, CA, USA
| | - D Wing
- University of California, San Diego, La Jolla, CA, USA
| | - D Wolff-Hughes
- NIH Office of Behavioral and Social Sciences Research, Bethesda, MD, USA
| | - R Yang
- University of California, San Diego, La Jolla, CA, USA
| | | | - R A Zucker
- University of Michigan, Ann Arbor, MI, USA
| | - A Potter
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - H P Garavan
- Department of Psychiatry, University of Vermont, Burlington, VT, USA.
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11
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Hahn S, Yuan DK, Thompson WK, Owens M, Allgaier N, Garavan H. Brain Predictability toolbox: a Python library for neuroimaging-based machine learning. Bioinformatics 2021; 37:1637-1638. [PMID: 33216147 DOI: 10.1093/bioinformatics/btaa974] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 08/17/2020] [Accepted: 11/10/2020] [Indexed: 11/13/2022] Open
Abstract
SUMMARY Brain Predictability toolbox (BPt) represents a unified framework of machine learning (ML) tools designed to work with both tabulated data (e.g. brain derived, psychiatric, behavioral and physiological variables) and neuroimaging specific data (e.g. brain volumes and surfaces). This package is suitable for investigating a wide range of different neuroimaging-based ML questions, in particular, those queried from large human datasets. AVAILABILITY AND IMPLEMENTATION BPt has been developed as an open-source Python 3.6+ package hosted at https://github.com/sahahn/BPt under MIT License, with documentation provided at https://bpt.readthedocs.io/en/latest/, and continues to be actively developed. The project can be downloaded through the github link provided. A web GUI interface based on the same code is currently under development and can be set up through docker with instructions at https://github.com/sahahn/BPt_app.
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Affiliation(s)
- Sage Hahn
- Department of Psychiatry and Complex Systems, University of Vermont, Burlington, VT 05401, USA
| | - De Kang Yuan
- Department of Psychiatry and Complex Systems, University of Vermont, Burlington, VT 05401, USA
| | - Wesley K Thompson
- Division of Biostatistics, Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA 92093, USA
| | - Max Owens
- Department of Psychiatry and Complex Systems, University of Vermont, Burlington, VT 05401, USA
| | - Nicholas Allgaier
- Department of Psychiatry and Complex Systems, University of Vermont, Burlington, VT 05401, USA
| | - Hugh Garavan
- Department of Psychiatry and Complex Systems, University of Vermont, Burlington, VT 05401, USA
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12
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Adise S, Allgaier N, Laurent J, Hahn S, Chaarani B, Owens M, Yuan D, Nyugen P, Mackey S, Potter A, Garavan HP. Multimodal brain predictors of current weight and weight gain in children enrolled in the ABCD study ®. Dev Cogn Neurosci 2021; 49:100948. [PMID: 33862325 PMCID: PMC8066422 DOI: 10.1016/j.dcn.2021.100948] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2020] [Revised: 12/20/2020] [Accepted: 03/22/2021] [Indexed: 02/02/2023] Open
Abstract
Multimodal neuroimaging assessments were utilized to identify generalizable brain correlates of current body mass index (BMI) and predictors of pathological weight gain (i.e., beyond normative development) one year later. Multimodal data from children enrolled in the Adolescent Brain Cognitive Development Study® at 9-to-10-years-old, consisted of structural magnetic resonance imaging (MRI), diffusion tensor imaging (DTI), resting state (rs), and three task-based functional (f) MRI scans assessing reward processing, inhibitory control, and working memory. Cross-validated elastic-net regression revealed widespread structural associations with BMI (e.g., cortical thickness, surface area, subcortical volume, and DTI), which explained 35% of the variance in the training set and generalized well to the test set (R2 = 0.27). Widespread rsfMRI inter- and intra-network correlations were related to BMI (R2train = 0.21; R2test = 0.14), as were regional activations on the working memory task (R2train = 0.20; (R2test = 0.16). However, reward and inhibitory control tasks were unrelated to BMI. Further, pathological weight gain was predicted by structural features (Area Under the Curve (AUC)train = 0.83; AUCtest = 0.83, p < 0.001), but not by fMRI nor rsfMRI. These results establish generalizable brain correlates of current weight and future pathological weight gain. These results also suggest that sMRI may have particular value for identifying children at risk for pathological weight gain.
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Affiliation(s)
- Shana Adise
- Department of Psychiatry, University of Vermont, Burlington, VT, USA.
| | - Nicholas Allgaier
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Jennifer Laurent
- Department of Nursing, University of Vermont, Burlington, VT, USA
| | - Sage Hahn
- Department of Complex Systems, University of Vermont, Burlington, VT, USA
| | - Bader Chaarani
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Max Owens
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - DeKang Yuan
- Department of Complex Systems, University of Vermont, Burlington, VT, USA
| | - Philip Nyugen
- Department of Psychiatry, University of Vermont, Burlington, VT, USA; Department of Complex Systems, University of Vermont, Burlington, VT, USA; Department of Nursing, University of Vermont, Burlington, VT, USA; Department of Psychological Science, University of Vermont, Burlington, VT, USA
| | - Scott Mackey
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Alexandra Potter
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Hugh P Garavan
- Department of Psychiatry, University of Vermont, Burlington, VT, USA; Department of Psychological Science, University of Vermont, Burlington, VT, USA
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13
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Li Y, Thompson WK, Reuter C, Nillo R, Jernigan T, Dale A, Sugrue LP, Brown J, Dougherty RF, Rauschecker A, Rudie J, Barch DM, Calhoun V, Hagler D, Hatton S, Tanabe J, Marshall A, Sher KJ, Heeringa S, Hermosillo R, Banich MT, Squeglia L, Bjork J, Zucker R, Neale M, Herting M, Sheth C, Huber R, Reeves G, Hettema JM, Howlett KD, Cloak C, Baskin-Sommers A, Rapuano K, Gonzalez R, Karcher N, Laird A, Baker F, James R, Sowell E, Dick A, Hawes S, Sutherland M, Bagot K, Bodurka J, Breslin F, Morris A, Paulus M, Gray K, Hoffman E, Weiss S, Rajapakse N, Glantz M, Nagel B, Ewing SF, Goldstone A, Pfefferbaum A, Prouty D, Rosenberg M, Bookheimer S, Tapert S, Infante M, Jacobus J, Giedd J, Shilling P, Wade N, Uban K, Haist F, Heyser C, Palmer C, Kuperman J, Hewitt J, Cottler L, Isaiah A, Chang L, Edwards S, Ernst T, Heitzeg M, Puttler L, Sripada C, Iacono W, Luciana M, Clark D, Luna B, Schirda C, Foxe J, Freedman E, Mason M, McGlade E, Renshaw P, Yurgelun-Todd D, Albaugh M, Allgaier N, Chaarani B, Potter A, Ivanova M, Lisdahl K, Do E, Maes H, Bogdan R, Anokhin A, Dosenbach N, Glaser P, Heath A, Casey BJ, Gee D, Garavan HP, Dowling G, Brown S. Rates of Incidental Findings in Brain Magnetic Resonance Imaging in Children. JAMA Neurol 2021; 78:578-587. [PMID: 33749724 PMCID: PMC7985817 DOI: 10.1001/jamaneurol.2021.0306] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Importance Incidental findings (IFs) are unexpected abnormalities discovered during imaging and can range from normal anatomic variants to findings requiring urgent medical intervention. In the case of brain magnetic resonance imaging (MRI), reliable data about the prevalence and significance of IFs in the general population are limited, making it difficult to anticipate, communicate, and manage these findings. Objectives To determine the overall prevalence of IFs in brain MRI in the nonclinical pediatric population as well as the rates of specific findings and findings for which clinical referral is recommended. Design, Setting, and Participants This cohort study was based on the April 2019 release of baseline data from 11 810 children aged 9 to 10 years who were enrolled and completed baseline neuroimaging in the Adolescent Brain Cognitive Development (ABCD) study, the largest US population-based longitudinal observational study of brain development and child health, between September 1, 2016, and November 15, 2018. Participants were enrolled at 21 sites across the US designed to mirror the demographic characteristics of the US population. Baseline structural MRIs were centrally reviewed for IFs by board-certified neuroradiologists and findings were described and categorized (category 1, no abnormal findings; 2, no referral recommended; 3; consider referral; and 4, consider immediate referral). Children were enrolled through a broad school-based recruitment process in which all children of eligible age at selected schools were invited to participate. Exclusion criteria were severe sensory, intellectual, medical, or neurologic disorders that would preclude or interfere with study participation. During the enrollment process, demographic data were monitored to ensure that the study met targets for sex, socioeconomic, ethnic, and racial diversity. Data were analyzed from March 15, 2018, to November 20, 2020. Main Outcomes and Measures Percentage of children with IFs in each category and prevalence of specific IFs. Results A total of 11 679 children (52.1% boys, mean [SD] age, 9.9 [0.62] years) had interpretable baseline structural MRI results. Of these, 2464 participants (21.1%) had IFs, including 2013 children (17.2%) assigned to category 2, 431 (3.7%) assigned to category 3, and 20 (0.2%) assigned to category 4. Overall rates of IFs did not differ significantly between singleton and twin gestations or between monozygotic and dizygotic twins, but heritability analysis showed heritability for the presence or absence of IFs (h2 = 0.260; 95% CI, 0.135-0.387). Conclusions and Relevance Incidental findings in brain MRI and findings with potential clinical significance are both common in the general pediatric population. By assessing IFs and concurrent developmental and health measures and following these findings over the longitudinal study course, the ABCD study has the potential to determine the significance of many common IFs.
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Affiliation(s)
- Yi Li
- Department of Radiology and Biomedical Imaging, University of California, San Francisco
| | - Wesley K. Thompson
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla
| | - Chase Reuter
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla
| | - Ryan Nillo
- Department of Radiology and Biomedical Imaging, University of California, San Francisco
| | - Terry Jernigan
- Center for Human Development, University of California, San Diego, La Jolla
| | - Anders Dale
- Center for Human Development, University of California, San Diego, La Jolla
| | - Leo P. Sugrue
- Department of Radiology and Biomedical Imaging, University of California, San Francisco
| | | | - Julian Brown
- Department of Radiology and Biomedical Imaging, University of California, San Francisco
| | - Robert F Dougherty
- Center for Cognitive and Neurobiological Imaging, Stanford University, Stanford, California
| | - Andreas Rauschecker
- Department of Radiology and Biomedical Imaging, University of California, San Francisco
| | - Jeffrey Rudie
- Department of Radiology and Biomedical Imaging, University of California, San Francisco
| | - Deanna M Barch
- Department of Psychological & Brain Sciences, Psychiatry, Radiology, Washington University in St Louis, St Louis, Missouri
| | - Vince Calhoun
- Tri-institutional Center for Translational Research in Neuroimaging and Data Science, Georgia State University, Georgia Tech, Emory University, Atlanta
| | - Donald Hagler
- Department of Radiology, University of California, San Diego, La Jolla
| | - Sean Hatton
- Department of Neurosciences, University of California, San Diego, La Jolla
| | - Jody Tanabe
- Department of Radiology, University of Colorado Anschutz Medical Center, Aurora
| | - Andrew Marshall
- Department of Pediatrics, Children's Hospital Los Angeles/University of Southern California, Los Angeles
| | - Kenneth J Sher
- Department of Psychological Sciences, University of Missouri, Columbia
| | - Steven Heeringa
- Institute for Social Research, University of Michigan, Ann Arbor
| | - Robert Hermosillo
- Department of Behavioral Neuroscience, Oregon Health Sciences University, Portland
| | - Marie T Banich
- Institute of Cognitive Science, Department of Psychology and Neuroscience, University of Colorado, Boulder
| | - Lindsay Squeglia
- Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston
| | - James Bjork
- Department of Psychiatry, Virginia Commonwealth University, Richmond
| | - Robert Zucker
- Department of Psychiatry and Psychology, University of Michigan, Ann Arbor
| | - Michael Neale
- Department of Psychiatry, Virginia Commonwealth University, Richmond
| | - Megan Herting
- Department of Preventive Medicine, University of Southern California, Los Angeles
| | - Chandni Sheth
- Department of Psychiatry, University of Utah School of Medicine, Salt Lake City
| | - Rebeka Huber
- Department of Psychiatry, University of Utah School of Medicine, Salt Lake City
| | - Gloria Reeves
- Department of Psychiatry, University of Maryland, Baltimore
| | - John M Hettema
- Department of Psychiatry, Texas A&M Health Science Center, Bryan
| | - Katia Delrahim Howlett
- Division of Extramural Research, National Institute on Drug Abuse/National Institutes of Health, Bethesda, Maryland
| | - Christine Cloak
- Department of Radiology and Nuclear Medicine, University of Maryland, Baltimore
| | | | - Kristina Rapuano
- Department of Psychology, Yale University, New Haven, Connecticut
| | - Raul Gonzalez
- Department of Psychology, Florida International University, Miami
| | - Nicole Karcher
- Department of Psychiatry, Washington University in St Louis, St Louis, Missouri
| | - Angela Laird
- Department of Physics, Florida International University, Miami
| | | | - Regina James
- Department of Clinical Research, 2M Research Services, Arlington, Virginia
| | - Elizabeth Sowell
- Department of Pediatrics, Children's Hospital Los Angeles/University of Southern California, Los Angeles
| | - Anthony Dick
- Department of Psychology, Florida International University, Miami
| | - Samuel Hawes
- Department of Psychology, Florida International University, Miami
| | | | - Kara Bagot
- Department of Psychiatry, Icahn School of Medicine at Mt Sinai, New York, New York
| | - Jerzy Bodurka
- Laureate Institute for Brain Research, Tulsa, Oklahoma
| | | | - Amanda Morris
- Laureate Institute for Brain Research, Tulsa, Oklahoma
| | - Martin Paulus
- Laureate Institute for Brain Research, Tulsa, Oklahoma
| | - Kevin Gray
- Department of Psychiatry and Behavioral Sciences, Medical University of South Carolina, Charleston
| | - Elizabeth Hoffman
- Division of Extramural Research, National Institute on Drug Abuse/National Institutes of Health, Bethesda, Maryland
| | - Susan Weiss
- Division of Extramural Research, National Institute on Drug Abuse/National Institutes of Health, Bethesda, Maryland
| | - Nishadi Rajapakse
- Department of Scientific Programs, National Institute on Minority Health and Health Disparities, Bethesda, Maryland
| | - Meyer Glantz
- Department of Psychology, National Institute on Drug Abuse/National Institutes of Health, Bethesda, Maryland
| | - Bonnie Nagel
- Department of Psychiatry, Oregon Health and Science University, Portland
| | | | | | | | | | - Monica Rosenberg
- Department of Psychology, University of Chicago, Chicago, Illinois
| | - Susan Bookheimer
- Department of Psychiatry and Biobehavioral Sciences, School of Medicine, University of California, Los Angeles
| | - Susan Tapert
- Department of Psychiatry, University of California, San Diego, La Jolla
| | - Maria Infante
- Department of Psychiatry, University of California, San Diego, La Jolla
| | - Joanna Jacobus
- Department of Psychiatry, University of California, San Diego, La Jolla
| | - Jay Giedd
- Department of Psychiatry, University of California, San Diego, La Jolla
| | - Paul Shilling
- Department of Psychiatry, University of California, San Diego, La Jolla
| | - Natasha Wade
- Department of Psychiatry, University of California, San Diego, La Jolla
| | - Kristina Uban
- Department of Public Health, University of California, Irvine
| | - Frank Haist
- Department of Psychiatry and Center for Human Development, University of California, San Diego, La Jolla
| | - Charles Heyser
- Center for Human Development, University of California, San Diego, La Jolla
| | - Clare Palmer
- Center for Human Development, University of California, San Diego, La Jolla
| | - Joshua Kuperman
- Department of Radiology, University of California, San Diego, La Jolla
| | - John Hewitt
- Institute for Behavioral Genetics, University of Colorado, Boulder
| | - Linda Cottler
- Department of Epidemiology, University of Florida, Gainesville
| | - Amal Isaiah
- Department of Otorhinolaryngology/Head and Neck Surgery and Pediatrics, University of Maryland School of Medicine, Baltimore
| | - Linda Chang
- Departments of Radiology and Neurology, University of Maryland, Baltimore
| | - Sarah Edwards
- Department of Psychiatry, University of Maryland, Baltimore
| | - Thomas Ernst
- Department of Radiology, University of Maryland, Baltimore
| | - Mary Heitzeg
- Department of Psychiatry, University of Michigan, Ann Arbor
| | - Leon Puttler
- Department of Psychiatry, University of Michigan, Ann Arbor
| | | | - William Iacono
- Department of Psychology, University of Minnesota, Minneapolis
| | - Monica Luciana
- Department of Psychology, University of Minnesota, Minneapolis
| | - Duncan Clark
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Beatriz Luna
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Claudiu Schirda
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - John Foxe
- Department of Neuroscience, University of Rochester Medical Center, Rochester, New York
| | - Edward Freedman
- Department of Neuroscience, University of Rochester Medical Center, Rochester, New York
| | - Michael Mason
- Center for Behavioral Health Research, University of Tennessee, Knoxville
| | - Erin McGlade
- Department of Psychiatry, University of Utah School of Medicine, Salt Lake City
| | - Perry Renshaw
- Department of Psychiatry, University of Utah School of Medicine, Salt Lake City
| | | | | | | | - Bader Chaarani
- Department of Psychiatry, University of Vermont, Burlington
| | | | - Masha Ivanova
- Department of Psychiatry, University of Vermont, Burlington
| | - Krista Lisdahl
- Department of Psychiatry, University of Vermont, Burlington
| | - Elizabeth Do
- Department of Health Behavior and Policy, Virginia Commonwealth University, Richmond
| | - Hermine Maes
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond
| | - Ryan Bogdan
- Department of Psychological and Brain Sciences, Washington University in St Louis, St Louis, Missouri
| | - Andrey Anokhin
- Department of Psychiatry, Washington University in St Louis, St Louis, Missouri
| | - Nico Dosenbach
- Department of Neurology, Washington University in St Louis, St Louis, Missouri
| | - Paul Glaser
- Department of Psychiatry, Washington University in St Louis, St Louis, Missouri
| | - Andrew Heath
- Department of Psychiatry, Washington University in St Louis, St Louis, Missouri
| | - Betty J Casey
- Department of Psychology, Yale University, New Haven, Connecticut
| | - Dylan Gee
- Department of Psychology, Yale University, New Haven, Connecticut
| | - Hugh P Garavan
- Department of Psychiatry, University of Vermont, Burlington
| | - Gaya Dowling
- Division of Extramural Research, National Institute on Drug Abuse/National Institutes of Health, Bethesda, Maryland
| | - Sandra Brown
- Department of Psychiatry and Psychology, University of California, San Diego, La Jolla
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14
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Potter A, Dube S, Allgaier N, Loso H, Ivanova M, Barrios LC, Bookheimer S, Chaarani B, Dumas J, Feldstein-Ewing S, Freedman E, Garavan H, Hoffman E, McGlade E, Robin L, Johns MM. Early adolescent gender diversity and mental health in the Adolescent Brain Cognitive Development study. J Child Psychol Psychiatry 2021; 62:171-179. [PMID: 32463952 PMCID: PMC7704539 DOI: 10.1111/jcpp.13248] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2019] [Revised: 03/27/2020] [Accepted: 03/30/2020] [Indexed: 12/14/2022]
Abstract
BACKGROUND There are known associations between mental health symptoms and transgender identity among adults. Whether this relationship extends to early adolescents and to gender domains other than identity is unclear. This study measured dimensions of gender in a large, diverse, sample of youth, and examined associations between diverse gender experiences and mental health. METHODS The ABCD study is an ongoing, longitudinal, US cohort study. Baseline data (release 2.0) include 11,873 youth age 9/10 (48% female); and the 4,951 1-year follow-up visits (age 10/11; 48% female) completed prior to data release. A novel gender survey at the 1-year visit assessed felt-gender, gender noncontentedness, and gender nonconformity using a 5-point scale. Mental health measures included youth- and parent-reports. RESULTS Roughly half a percent of 9/10-year-olds (n = 58) responded 'yes' or 'maybe' when asked, 'Are you transgender' at baseline. Recurrent thoughts of death were more prevalent among these youth compared to the rest of the cohort (19.6% vs. 6.4%, χ2 = 16.0, p < .001). At the 1-year visit, when asked about the three dimensions of gender on a 5-point scale, 33.2% (n = 1,605) provided responses that were not exclusively and totally aligned with one gender. Significant relationships were observed between mental health symptoms and gender diversity for all dimensions assessed. CONCLUSIONS Similar to adult studies, early adolescents identifying as transgender reported increased mental health symptoms. Results also point to considerable diversity in other dimensions of gender (felt-gender, gender noncontentedness, gender nonconformity) among 10/11-year-olds, and find this diversity to be related to critical mental health symptoms. These findings add to our limited understanding of the relationship between dimensions of gender and wellness for youth.
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Affiliation(s)
- Alexandra Potter
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Sarahjane Dube
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Nicholas Allgaier
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Hannah Loso
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Masha Ivanova
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Lisa C. Barrios
- Division of Adolescent and School Health, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Susan Bookheimer
- Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, USA
| | - Bader Chaarani
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Julie Dumas
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Sarah Feldstein-Ewing
- Department of Child and Adolescent Psychiatry, Oregon Health and Science University, Portland, OR, USA
| | - Ed Freedman
- Department of Neuroscience, University of Rochester Medical Center, Rochester, NY, USA
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Elizabeth Hoffman
- National Institute on Drug Abuse, National Institutes of Health, Bethesda, MD, USA
| | - Erin McGlade
- Department of Psychiatry, University of Utah, Salt Lake City, UT, USA
| | - Leah Robin
- Division of Adolescent and School Health, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Michelle M. Johns
- Division of Adolescent and School Health, Centers for Disease Control and Prevention, Atlanta, GA, USA
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15
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Owens MM, Allgaier N, Hahn S, Yuan D, Albaugh M, Adise S, Chaarani B, Ortigara J, Juliano A, Potter A, Garavan H. Multimethod investigation of the neurobiological basis of ADHD symptomatology in children aged 9-10: baseline data from the ABCD study. Transl Psychiatry 2021; 11:64. [PMID: 33462190 PMCID: PMC7813832 DOI: 10.1038/s41398-020-01192-8] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 11/30/2020] [Accepted: 12/04/2020] [Indexed: 12/18/2022] Open
Abstract
Attention deficit/hyperactivity disorder is associated with numerous neurocognitive deficits, including poor working memory and difficulty inhibiting undesirable behaviors that cause academic and behavioral problems in children. Prior work has attempted to determine how these differences are instantiated in the structure and function of the brain, but much of that work has been done in small samples, focused on older adolescents or adults, and used statistical approaches that were not robust to model overfitting. The current study used cross-validated elastic net regression to predict a continuous measure of ADHD symptomatology using brain morphometry and activation during tasks of working memory, inhibitory control, and reward processing, with separate models for each MRI measure. The best model using activation during the working memory task to predict ADHD symptomatology had an out-of-sample R2 = 2% and was robust to residualizing the effects of age, sex, race, parental income and education, handedness, pubertal status, and internalizing symptoms from ADHD symptomatology. This model used reduced activation in task positive regions and reduced deactivation in task negative regions to predict ADHD symptomatology. The best model with morphometry alone predicted ADHD symptomatology with an R2 = 1% but this effect dissipated when including covariates. The inhibitory control and reward tasks did not yield generalizable models. In summary, these analyses show, with a large and well-characterized sample, that the brain correlates of ADHD symptomatology are modest in effect size and captured best by brain morphometry and activation during a working memory task.
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Affiliation(s)
- Max M. Owens
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
| | - Nicholas Allgaier
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
| | - Sage Hahn
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
| | - DeKang Yuan
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
| | - Matthew Albaugh
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
| | - Shana Adise
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
| | - Bader Chaarani
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
| | - Joseph Ortigara
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
| | - Anthony Juliano
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
| | - Alexandra Potter
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
| | - Hugh Garavan
- grid.59062.380000 0004 1936 7689Department of Psychiatry, University of Vermont, Burlington, VT 05401 USA
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16
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Owens MM, Hyatt CS, Gray JC, Miller JD, Lynam DR, Hahn S, Allgaier N, Potter A, Garavan H. Neuroanatomical correlates of impulsive traits in children aged 9 to 10. J Abnorm Psychol 2020; 129:831-844. [PMID: 32897083 PMCID: PMC7606639 DOI: 10.1037/abn0000627] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Impulsivity refers to a set of traits that are generally negatively related to critical domains of adaptive functioning and are core features of numerous psychiatric disorders. The current study examined the gray and white matter correlates of five impulsive traits measured using an abbreviated version of the UPPS-P (Urgency, (lack of) Premeditation, (lack of) Perseverance, Sensation-Seeking, Positive Urgency) impulsivity scale in children aged 9 to 10 (N = 11,052) from the Adolescent Brain and Cognitive Development (ABCD) study. Linear mixed effect models and elastic net regression were used to examine features of regional gray matter and white matter tractography most associated with each UPPS-P scale; intraclass correlations were computed to examine the similarity of the neuroanatomical correlates among the scales. Positive Urgency showed the most robust association with neuroanatomy, with similar but less robust associations found for Negative Urgency. Perseverance showed little association with neuroanatomy. Premeditation and Sensation Seeking showed intermediate associations with neuroanatomy. Critical regions across measures include the dorsolateral prefrontal cortex, lateral temporal cortex, and orbitofrontal cortex; critical tracts included the superior longitudinal fasciculus and inferior fronto-occipital fasciculus. Negative Urgency and Positive Urgency showed the greatest neuroanatomical similarity. Some UPPS-P traits share neuroanatomical correlates, while others have distinct correlates or essentially no relation to neuroanatomy. Neuroanatomy tended to account for relatively little variance in UPPS-P traits (i.e., Model R2 < 1%) and effects were spread throughout the brain, highlighting the importance of well powered samples. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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Affiliation(s)
| | | | - Joshua C. Gray
- Uniformed Services University, Department of Medical and Clinical Psychology
| | | | | | - Sage Hahn
- University of Vermont, Department of Psychiatry
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17
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Hahn S, Mackey S, Cousijn J, Foxe JJ, Heinz A, Hester R, Hutchinson K, Kiefer F, Korucuoglu O, Lett T, Li CSR, London E, Lorenzetti V, Maartje L, Momenan R, Orr C, Paulus M, Schmaal L, Sinha R, Sjoerds Z, Stein DJ, Stein E, van Holst RJ, Veltman D, Walter H, Wiers RW, Yucel M, Thompson PM, Conrod P, Allgaier N, Garavan H. Predicting alcohol dependence from multi-site brain structural measures. Hum Brain Mapp 2020; 43:555-565. [PMID: 33064342 PMCID: PMC8675424 DOI: 10.1002/hbm.25248] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 09/21/2020] [Accepted: 10/06/2020] [Indexed: 12/16/2022] Open
Abstract
To identify neuroimaging biomarkers of alcohol dependence (AD) from structural magnetic resonance imaging, it may be useful to develop classification models that are explicitly generalizable to unseen sites and populations. This problem was explored in a mega‐analysis of previously published datasets from 2,034 AD and comparison participants spanning 27 sites curated by the ENIGMA Addiction Working Group. Data were grouped into a training set used for internal validation including 1,652 participants (692 AD, 24 sites), and a test set used for external validation with 382 participants (146 AD, 3 sites). An exploratory data analysis was first conducted, followed by an evolutionary search based feature selection to site generalizable and high performing subsets of brain measurements. Exploratory data analysis revealed that inclusion of case‐ and control‐only sites led to the inadvertent learning of site‐effects. Cross validation methods that do not properly account for site can drastically overestimate results. Evolutionary‐based feature selection leveraging leave‐one‐site‐out cross‐validation, to combat unintentional learning, identified cortical thickness in the left superior frontal gyrus and right lateral orbitofrontal cortex, cortical surface area in the right transverse temporal gyrus, and left putamen volume as final features. Ridge regression restricted to these features yielded a test‐set area under the receiver operating characteristic curve of 0.768. These findings evaluate strategies for handling multi‐site data with varied underlying class distributions and identify potential biomarkers for individuals with current AD.
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Affiliation(s)
- Sage Hahn
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, Vermont, USA
| | - Scott Mackey
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, Vermont, USA
| | - Janna Cousijn
- Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands
| | - John J Foxe
- Department of Neuroscience & The Ernest J. Del Monte Institute for Neuroscience, University of Rochester School of Medicine and Dentistry, Rochester, New York, USA
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Robert Hester
- Melbourne School of Psychological Sciences, University of Melbourne, Melbourne, Australia
| | - Kent Hutchinson
- Department of Psychology and Neuroscience, University of Colorado, Boulder, Colorado, USA
| | - Falk Kiefer
- Department of Addictive Behaviour and Addiction Medicine, Central Institute of Mental Health, Heidelberg University, Mannheim, Germany
| | - Ozlem Korucuoglu
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Tristram Lett
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Chiang-Shan R Li
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Edythe London
- David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California, USA
| | - Valentina Lorenzetti
- Monash Institute of Cognitive and Clinical Neurosciences & School of Psychological Sciences, Monash University, Melbourne, Australia.,School of Psychology, Faculty of Health Sciences, Australian Catholic University, Melbourne, Australia.,Department of Psychological Sciences, the University of Liverpool, Liverpool, UK
| | - Luijten Maartje
- Behavioural Science Institute, Radboud University, Nijmegen, the Netherlands
| | - Reza Momenan
- Clinical NeuroImaging Research Core, Division of Intramural Clinical and Biological Research, National Institute on Alcohol Abuse and Alcoholism, Bethesda, Maryland, USA
| | - Catherine Orr
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, Vermont, USA
| | - Martin Paulus
- VA San Diego Healthcare System and Department of Psychiatry, University of California San Diego, La Jolla, California, USA.,Laureate Institute for Brain Research, Tulsa, Oklahoma, USA
| | - Lianne Schmaal
- Orygen, The National Centre of Excellence in Youth Mental Health, Parkville, Australia.,Centre for Youth Mental Health, The University of Melbourne, Melbourne, Australia
| | - Rajita Sinha
- Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Zsuzsika Sjoerds
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany.,Institute of Psychology, Cognitive Psychology Unit & Leiden Institute for Brain and Cognition, Leiden University, Leiden, the Netherlands
| | - Dan J Stein
- SA MRC Unit on Risk & Resilience in Mental Disorders, Department of Psychiatry & Neuroscience Institute, University of Cape Town, Cape Town, South Africa
| | - Elliot Stein
- Neuroimaging Research Branch, Intramural Research Program, National Institute on Drug Abuse, Baltimore, Maryland, USA
| | - Ruth J van Holst
- Department of Psychiatry, Amsterdam UMC, Location AMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Dick Veltman
- Department of Psychiatry, VU University Medical Center, Amsterdam, the Netherlands
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Reinout W Wiers
- Department of Psychology, University of Amsterdam, Amsterdam, the Netherlands
| | - Murat Yucel
- David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California, USA.,Melbourne Neuropsychiatry Centre, Department of Psychiatry, The University of Melbourne and Melbourne Health, Melbourne, Australia
| | - Paul M Thompson
- Imaging Genetics Center, Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, California, USA
| | - Patricia Conrod
- Department of Psychiatry, Université de Montreal, CHU Ste Justine Hospital, Montreal, Quebec, Canada
| | - Nicholas Allgaier
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, Vermont, USA
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, Vermont, USA
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18
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Owens MM, Yuan D, Hahn S, Albaugh M, Allgaier N, Chaarani B, Potter A, Garavan H. Investigation of Psychiatric and Neuropsychological Correlates of Default Mode Network and Dorsal Attention Network Anticorrelation in Children. Cereb Cortex 2020; 30:6083-6096. [PMID: 32591777 DOI: 10.1093/cercor/bhaa143] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Revised: 05/05/2020] [Accepted: 05/07/2020] [Indexed: 12/31/2022] Open
Abstract
The default mode network (DMN) and dorsal attention network (DAN) demonstrate an intrinsic "anticorrelation" in healthy adults, which is thought to represent the functional segregation between internally and externally directed thought. Reduced segregation of these networks has been proposed as a mechanism for cognitive deficits that occurs in many psychiatric disorders, but this association has rarely been tested in pre-adolescent children. The current analysis used data from the Adolescent Brain Cognitive Development study to examine the relationship between the strength of DMN/DAN anticorrelation and psychiatric symptoms in the largest sample to date of 9- to 10-year-old children (N = 6543). The relationship of DMN/DAN anticorrelation to a battery of neuropsychological tests was also assessed. DMN/DAN anticorrelation was robustly linked to attention problems, as well as age, sex, and socioeconomic factors. Other psychiatric correlates identified in prior reports were not robustly linked to DMN/DAN anticorrelation after controlling for demographic covariates. Among neuropsychological measures, the clearest correlates of DMN/DAN anticorrelation were the Card Sort task of executive function and cognitive flexibility and the NIH Toolbox Total Cognitive Score, although these did not survive correction for socioeconomic factors. These findings indicate a complicated relationship between DMN/DAN anticorrelation and demographics, neuropsychological function, and psychiatric problems.
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Affiliation(s)
- Max M Owens
- Department of Psychiatry, University of Vermont, Burlington, VT 05401, USA
| | - DeKang Yuan
- Department of Psychiatry, University of Vermont, Burlington, VT 05401, USA
| | - Sage Hahn
- Department of Psychiatry, University of Vermont, Burlington, VT 05401, USA
| | - Matthew Albaugh
- Department of Psychiatry, University of Vermont, Burlington, VT 05401, USA
| | - Nicholas Allgaier
- Department of Psychiatry, University of Vermont, Burlington, VT 05401, USA
| | - Bader Chaarani
- Department of Psychiatry, University of Vermont, Burlington, VT 05401, USA
| | - Alexandra Potter
- Department of Psychiatry, University of Vermont, Burlington, VT 05401, USA
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont, Burlington, VT 05401, USA
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19
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Albaugh MD, Ivanova M, Chaarani B, Orr C, Allgaier N, Althoff RR, D' Alberto N, Hudson K, Mackey S, Spechler PA, Banaschewski T, Brühl R, Bokde ALW, Bromberg U, Büchel C, Cattrell A, Conrod PJ, Desrivières S, Flor H, Frouin V, Gallinat J, Goodman R, Gowland P, Grimmer Y, Heinz A, Kappel V, Martinot JL, Martinot MLP, Nees F, Papadopoulos Orfanos D, Penttilä J, Poustka L, Paus T, Smolka MN, Struve M, Walter H, Whelan R, Schumann G, Garavan H, Potter AS. Ventromedial Prefrontal Volume in Adolescence Predicts Hyperactive/Inattentive Symptoms in Adulthood. Cereb Cortex 2020; 29:1866-1874. [PMID: 29912404 DOI: 10.1093/cercor/bhy066] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2017] [Revised: 02/27/2018] [Accepted: 02/28/2018] [Indexed: 11/14/2022] Open
Abstract
Youths with attention-deficit/hyperactivity disorder symptomatology often exhibit residual inattention and/or hyperactivity in adulthood; however, this is not true for all individuals. We recently reported that dimensional, multi-informant ratings of hyperactive/inattentive symptoms are associated with ventromedial prefrontal cortex (vmPFC) structure. Herein, we investigate the degree to which vmPFC structure during adolescence predicts hyperactive/inattentive symptomatology at 5-year follow-up. Structural equation modeling was used to test the extent to which adolescent vmPFC volume predicts hyperactive/inattentive symptomatology 5 years later in early adulthood. 1104 participants (M = 14.52 years, standard deviation = 0.42; 583 females) possessed hyperactive/inattentive symptom data at 5-year follow-up, as well as quality controlled neuroimaging data and complete psychometric data at baseline. Self-reports of hyperactive/inattentive symptomatology were obtained during adolescence and at 5-year follow-up using the Strengths and Difficulties Questionnaire (SDQ). At baseline and 5-year follow-up, a hyperactive/inattentive latent variable was derived from items on the SDQ. Baseline vmPFC volume predicted adult hyperactive/inattentive symptomatology (standardized coefficient = -0.274, P < 0.001) while controlling for baseline hyperactive/inattentive symptomatology. These results are the first to reveal relations between adolescent brain structure and adult hyperactive/inattentive symptomatology, and suggest that early structural development of the vmPFC may be consequential for the subsequent expression of hyperactive/inattentive symptoms.
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Affiliation(s)
- Matthew D Albaugh
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Masha Ivanova
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Bader Chaarani
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Catherine Orr
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Nicholas Allgaier
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Robert R Althoff
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Nicholas D' Alberto
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Kelsey Hudson
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Scott Mackey
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Philip A Spechler
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt [PTB], Abbestr. 2-12, Berlin-Charlottenburg, Germany
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neurosciences, Trinity College Dublin, Dublin 2, Ireland
| | - Uli Bromberg
- University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | | | - Anna Cattrell
- Medical Research Council-Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Patricia J Conrod
- Department of Psychiatry, Universite de Montreal, CHU Ste Justine Hospital, QC, Canada.,Department of Psychological Medicine and Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Sylvane Desrivières
- Medical Research Council-Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Herta Flor
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | - Vincent Frouin
- Neurospin, Commissariat à l'Energie Atomique, CEA-Saclay Center, Paris, France
| | - Jürgen Gallinat
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Robert Goodman
- King's College London Institute of Psychiatry, Psychology & Neuroscience, London, UK
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
| | - Yvonne Grimmer
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité, Universitätsmedizin Berlin, Charitéplatz 1, Berlin, Germany
| | - Viola Kappel
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Charité-Universitätsmedizin, Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 "Neuroimaging & Psychiatry", University Paris Sud, University Paris Descartes-Sorbonne Paris Cité.,Maison de Solenn, Paris, France
| | - Marie-Laure Paillère Martinot
- INSERM, UMR 1000, Research Unit NeuroImaging and Psychiatry, Service Hospitalier Frédéric Joliot, Orsay, University Paris-Sud, University Paris Saclay, Orsay, France.,University Paris Descartes, Paris, France AP-HP, Department of Adolescent Psychopathology and Medicine, Maison De Solenn, Cochin Hospital, Paris, France
| | - Frauke Nees
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | | | - Jani Penttilä
- University of Tampere, Medical School, Tampere, Finland
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | - Tomáš Paus
- Rotman Research Institute, Baycrest and Departments of Psychology and Psychiatry, University of Toronto, Toronto, Ontario, Canada
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Maren Struve
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité, Universitätsmedizin Berlin, Charitéplatz 1, Berlin, Germany
| | - Robert Whelan
- Department of Psychology, University College Dublin, Dublin 4, Ireland
| | - Gunter Schumann
- Medical Research Council-Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Alexandra S Potter
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
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20
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Laurent JS, Watts R, Adise S, Allgaier N, Chaarani B, Garavan H, Potter A, Mackey S. Associations Among Body Mass Index, Cortical Thickness, and Executive Function in Children. JAMA Pediatr 2020; 174:170-177. [PMID: 31816020 PMCID: PMC6902097 DOI: 10.1001/jamapediatrics.2019.4708] [Citation(s) in RCA: 78] [Impact Index Per Article: 19.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
IMPORTANCE A total of 25.7 million children in the United States are classified as overweight or obese. Obesity is associated with deficits in executive function, which may contribute to poor dietary decision-making. Less is known about the associations between being overweight or obese and brain development. OBJECTIVE To examine whether body mass index (BMI) is associated with thickness of the cerebral cortex and whether cortical thickness mediates the association between BMI and executive function in children. DESIGN, SETTING, AND PARTICIPANTS In this cross-sectional study, cortical thickness maps were derived from T1-weighted structural magnetic resonance images of a large, diverse sample of 9 and 10-year-old children from 21 US sites. List sorting, flanker, matrix reasoning, and Wisconsin card sorting tasks were used to assess executive function. MAIN OUTCOMES AND MEASURES A 10-fold nested cross-validation general linear model was used to assess mean cortical thickness from BMI across cortical brain regions. Associations between BMI and executive function were explored with Pearson partial correlations. Mediation analysis examined whether mean prefrontal cortex thickness mediated the association between BMI and executive function. RESULTS Among 3190 individuals (mean [SD] age, 10.0 [0.61] years; 1627 [51.0%] male), those with higher BMI exhibited lower cortical thickness. Eighteen cortical regions were significantly inversely associated with BMI. The greatest correlations were observed in the prefrontal cortex. The BMI was inversely correlated with dimensional card sorting (r = -0.088, P < .001), list sorting (r = -0.061, P < .003), and matrix reasoning (r = -0.095, P < .001) but not the flanker task. Mean prefrontal cortex thickness mediated the association between BMI and list sorting (mean [SE] indirect effect, 0.014 [0.008]; 95% CI, 0.001-0.031) but not the matrix reasoning or card sorting task. CONCLUSIONS AND RELEVANCE These results suggest that BMI is associated with prefrontal cortex development and diminished executive functions, such as working memory.
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Affiliation(s)
- Jennifer S. Laurent
- Department of Nursing, College of Nursing and Health Sciences, University of Vermont, Burlington
| | - Richard Watts
- Magnetic Resonance Imaging Facility, Yale University, New Haven, Connecticut
| | - Shana Adise
- Department of Psychiatry, Larner College of Medicine, University of Vermont, Burlington
| | - Nicholas Allgaier
- Department of Psychiatry, Larner College of Medicine, University of Vermont, Burlington
| | - Bader Chaarani
- Department of Psychiatry, Larner College of Medicine, University of Vermont, Burlington
| | - Hugh Garavan
- Department of Psychiatry, Larner College of Medicine, University of Vermont, Burlington
| | - Alexandra Potter
- Department of Psychiatry, Larner College of Medicine, University of Vermont, Burlington
| | - Scott Mackey
- Department of Psychiatry, Larner College of Medicine, University of Vermont, Burlington
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21
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Spechler PA, Allgaier N, Chaarani B, Whelan R, Watts R, Orr C, Albaugh MD, D'Alberto N, Higgins ST, Hudson KE, Mackey S, Potter A, Banaschewski T, Bokde ALW, Bromberg U, Büchel C, Cattrell A, Conrod PJ, Desrivières S, Flor H, Frouin V, Gallinat J, Gowland P, Heinz A, Ittermann B, Martinot JL, Paillère Martinot ML, Nees F, Papadopoulos Orfanos D, Paus T, Poustka L, Smolka MN, Walter H, Schumann G, Althoff RR, Garavan H. The initiation of cannabis use in adolescence is predicted by sex-specific psychosocial and neurobiological features. Eur J Neurosci 2018; 50:2346-2356. [PMID: 29889330 DOI: 10.1111/ejn.13989] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2018] [Revised: 05/03/2018] [Accepted: 05/21/2018] [Indexed: 12/14/2022]
Abstract
Cannabis use initiated during adolescence might precipitate negative consequences in adulthood. Thus, predicting adolescent cannabis use prior to any exposure will inform the aetiology of substance abuse by disentangling predictors from consequences of use. In this prediction study, data were drawn from the IMAGEN sample, a longitudinal study of adolescence. All selected participants (n = 1,581) were cannabis-naïve at age 14. Those reporting any cannabis use (out of six ordinal use levels) by age 16 were included in the outcome group (N = 365, males n = 207). Cannabis-naïve participants at age 14 and 16 were included in the comparison group (N = 1,216, males n = 538). Psychosocial, brain and genetic features were measured at age 14 prior to any exposure. Cross-validated regularized logistic regressions for each use level by sex were used to perform feature selection and obtain prediction error statistics on independent observations. Predictors were probed for sex- and drug-specificity using post-hoc logistic regressions. Models reliably predicted use as indicated by satisfactory prediction error statistics, and contained psychosocial features common to both sexes. However, males and females exhibited distinct brain predictors that failed to predict use in the opposite sex or predict binge drinking in independent samples of same-sex participants. Collapsed across sex, genetic variation on catecholamine and opioid receptors marginally predicted use. Using machine learning techniques applied to a large multimodal dataset, we identified a risk profile containing psychosocial and sex-specific brain prognostic markers, which were likely to precede and influence cannabis initiation.
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Affiliation(s)
- Philip A Spechler
- Vermont Center on Behavior and Health, University of Vermont, Burlington, VT, USA.,Department of Psychological Science, University of Vermont, Burlington, VT, 05401, USA.,Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Nicholas Allgaier
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Bader Chaarani
- Vermont Center on Behavior and Health, University of Vermont, Burlington, VT, USA.,Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Richard Watts
- Department of Radiology, University of Vermont, Burlington, VT, USA
| | - Catherine Orr
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Matthew D Albaugh
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | | | - Stephen T Higgins
- Vermont Center on Behavior and Health, University of Vermont, Burlington, VT, USA.,Department of Psychological Science, University of Vermont, Burlington, VT, 05401, USA.,Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Kelsey E Hudson
- Department of Psychological Science, University of Vermont, Burlington, VT, 05401, USA
| | - Scott Mackey
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Alexandra Potter
- Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Tobias Banaschewski
- Medical Faculty Mannheim, Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Heidelberg University, Mannheim, Germany
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neurosciences, Trinity College Dublin, Dublin, Ireland
| | - Uli Bromberg
- University Medical Centre Hamburg-Eppendorf, Hamburg, Germany
| | | | - Anna Cattrell
- Centre for Population Neuroscience and Stratified Medicine (PONS) and MRC-SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Patricia J Conrod
- Department of Psychiatry, Universite de Montreal, CHU Ste Justine Hospital, Montreal, Canada
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Stratified Medicine (PONS) and MRC-SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Herta Flor
- Medical Faculty Mannheim, Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Heidelberg University, Mannheim, Germany.,Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany
| | - Vincent Frouin
- NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Jürgen Gallinat
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, UK
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Charité, Universitätsmedizin Berlin, Campus Charité Mitte, Berlin, Germany
| | - Bernd Ittermann
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig, Germany
| | - Jean-Luc Martinot
- DIGITEO Labs, Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 "Neuroimaging & Psychiatry", University Paris Sud - University Paris Saclay, Gif sur Yvette, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 "Neuroimaging & Psychiatry", University Paris Sud - Paris Saclay, University Paris Descartes, Paris, France.,Department of Adolescent Psychopathology and Medicine, AP-HP, Maison de Solenn, Cochin Hospital, Paris, France
| | - Frauke Nees
- Medical Faculty Mannheim, Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Heidelberg University, Mannheim, Germany.,Medical Faculty Mannheim, Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Heidelberg University, Mannheim, Germany
| | | | - Tomáš Paus
- Baycrest and Departments of Psychology and Psychiatry, Rotman Research Institute, University of Toronto, Toronto, ON, M6A 2E1, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, 37075, Göttingen, Germany.,Clinic for Child and Adolescent Psychiatry, Medical University of Vienna, Vienna, Austria
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy, Charité, Universitätsmedizin Berlin, Campus Charité Mitte, Berlin, Germany
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine (PONS) and MRC-SGDP Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Robert R Althoff
- Department of Psychological Science, University of Vermont, Burlington, VT, 05401, USA.,Department of Psychiatry, University of Vermont, Burlington, VT, USA
| | - Hugh Garavan
- Vermont Center on Behavior and Health, University of Vermont, Burlington, VT, USA.,Department of Psychological Science, University of Vermont, Burlington, VT, 05401, USA.,Department of Psychiatry, University of Vermont, Burlington, VT, USA
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22
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D'Alberto N, Chaarani B, Orr CA, Spechler PA, Albaugh MD, Allgaier N, Wonnell A, Banaschewski T, Bokde AL, Bromberg U, Büchel C, Quinlan EB, Conrod PJ, Desrivières S, Flor H, Fröhner JH, Frouin V, Gowland P, Heinz A, Itterman B, Martinot J, Paillère Martinot M, Artiges E, Nees F, Papadopoulos Orfanos D, Poustka L, Robbins TW, Smolka MN, Walter H, Whelan R, Schumann G, Potter AS, Garavan H. Individual differences in stop-related activity are inflated by the adaptive algorithm in the stop signal task. Hum Brain Mapp 2018; 39:3263-3276. [PMID: 29656430 PMCID: PMC6045976 DOI: 10.1002/hbm.24075] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2017] [Revised: 03/13/2018] [Accepted: 03/26/2018] [Indexed: 11/12/2022] Open
Abstract
Research using the Stop Signal Task employing an adaptive algorithm to accommodate individual differences often report inferior performance on the task in individuals with ADHD, OCD, and substance use disorders compared to non-clinical controls. Furthermore, individuals with deficits in inhibitory control tend to show reduced neural activity in key inhibitory regions during successful stopping. However, the adaptive algorithm systematically introduces performance-related differences in objective task difficulty that may influence the estimation of individual differences in stop-related neural activity. This report examines the effect that these algorithm-related differences have on the measurement of neural activity during the stop signal task. We compared two groups of subjects (n = 210) who differed in inhibitory ability using both a standard fMRI analysis and an analysis that resampled trials to remove the objective task difficulty confound. The results show that objective task difficulty influences the magnitude of between-group differences and that controlling for difficulty attenuates stop-related activity differences between superior and poor inhibitors. Specifically, group differences in the right inferior frontal gyrus, right middle occipital gyrus, and left inferior frontal gyrus are diminished when differences in objective task difficulty are controlled for. Also, when objective task difficulty effects are exaggerated, group differences in stop related activity emerge in other regions of the stopping network. The implications of these effects for how we interpret individual differences in activity levels are discussed.
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Affiliation(s)
- Nicholas D'Alberto
- Department of PsychiatryUniversity of Vermont College of MedicineBurlingtonVermont
| | - Bader Chaarani
- Department of PsychiatryUniversity of Vermont College of MedicineBurlingtonVermont
| | - Catherine A. Orr
- Department of PsychiatryUniversity of Vermont College of MedicineBurlingtonVermont
| | - Philip A. Spechler
- Department of PsychiatryUniversity of Vermont College of MedicineBurlingtonVermont
| | - Matthew D. Albaugh
- Department of PsychiatryUniversity of Vermont College of MedicineBurlingtonVermont
| | - Nicholas Allgaier
- Department of PsychiatryUniversity of Vermont College of MedicineBurlingtonVermont
| | - Alexander Wonnell
- Department of PsychiatryUniversity of Vermont College of MedicineBurlingtonVermont
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and PsychotherapyCentral Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5Mannheim68159Germany
| | - Arun L.W. Bokde
- Discipline of PsychiatrySchool of Medicine and Trinity College Institute of Neurosciences, Trinity CollegeDublin, Ireland
| | - Uli Bromberg
- University Medical Centre Hamburg‐Eppendorf, House W34, 3.OG, Martinistr. 52Hamburg20246Germany
| | - Christian Büchel
- University Medical Centre Hamburg‐Eppendorf, House W34, 3.OG, Martinistr. 52Hamburg20246Germany
| | - Erin Burke Quinlan
- Medical Research Council – Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology & Neuroscience, King's College LondonUnited Kingdom
| | - Patricia J. Conrod
- Department of PsychiatryUniversite de Montreal, CHU Ste Justine HospitalMontrealQuebecCanada
- Department of Psychological Medicine and PsychiatryInstitute of Psychiatry, Psychology & Neuroscience, King's College LondonLondonUnited Kingdom
| | - Sylvane Desrivières
- Medical Research Council – Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology & Neuroscience, King's College LondonUnited Kingdom
| | - Herta Flor
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty MannheimHeidelberg University, Square J5MannheimGermany
- Department of Psychology, School of Social SciencesUniversity of MannheimMannheim68131Germany
| | - Juliane H. Fröhner
- Department of Psychiatry and Neuroimaging CenterTechnische Universität DresdenDresdenGermany
| | - Vincent Frouin
- Neurospin, Commissariat à l'Energie Atomique, CEA‐Saclay CenterParisFrance
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and AstronomyUniversity of Nottingham, University ParkNottinghamUnited Kingdom
| | - Andreas Heinz
- Department of Psychiatry and PsychotherapyCampus Charité Mitte, Charité, Universitätsmedizin Berlin, Charitéplatz 1BerlinGermany
| | - Bernd Itterman
- Physikalisch‐Technische Bundesanstalt (PTB), Abbestr. 2 – 12BerlinGermany
| | - Jean‐Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 “Neuroimaging & Psychiatry”, University Paris Sud, University Paris Descartes – Sorbonne Paris Cité and Maison de SolennParisFrance
| | - Marie‐Laure Paillère Martinot
- Department of Adolescent Psychopathology and Medicine, Maison de Solenn, Cochin HospitalInstitut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 “Neuroimaging & Psychiatry”, University Paris Sud, University Paris Descartes – Sorbonne Paris Cité and AP‐HPParisFrance
| | - Eric Artiges
- Department 91G16, Orsay HospitalInstitut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 “Neuroimaging & Psychiatry”, University Paris Sud, University Paris Descartes – Sorbonne Paris Cité and PsychiatryParisFrance
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and PsychotherapyCentral Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5Mannheim68159Germany
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty MannheimHeidelberg University, Square J5MannheimGermany
| | | | - Luise Poustka
- Department of Child and Adolescent Psychiatry and PsychotherapyUniversity Medical Centre Göttingen, von‐Siebold‐Str. 5Göttingen37075Germany
- Clinic for Child and Adolescent Psychiatry, Medical University of Vienna, Währinger Gürtel 18‐20Vienna1090Austria
| | - Trevor W. Robbins
- Department of Psychology and Behavioural and Clinical Neuroscience InstituteUniversity of CambridgeCambridgeUnited Kingdom
| | - Michael N. Smolka
- Department of Psychiatry and Neuroimaging CenterTechnische Universität DresdenDresdenGermany
| | - Henrik Walter
- Department of Psychiatry and PsychotherapyCampus Charité Mitte, Charité, Universitätsmedizin Berlin, Charitéplatz 1BerlinGermany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College DublinDublinIreland
| | - Gunter Schumann
- Medical Research Council – Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology & Neuroscience, King's College LondonUnited Kingdom
| | - Alexandra S. Potter
- Department of PsychiatryUniversity of Vermont College of MedicineBurlingtonVermont
| | - Hugh Garavan
- Department of PsychiatryUniversity of Vermont College of MedicineBurlingtonVermont
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23
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Albaugh MD, Orr C, Chaarani B, Althoff RR, Allgaier N, Alberto ND, Hudson K, Mackey S, Spechler PA, Banaschewski T, Brühl R, Bokde AL, Bromberg U, Büchel C, Cattrell A, Conrod PJ, Desrivières S, Flor H, Frouin V, Gallinat J, Goodman R, Gowland P, Grimmer Y, Heinz A, Kappel V, Martinot JL, Martinot MLP, Nees F, Orfanos DP, Penttilä J, Poustka L, Paus T, Smolka MN, Struve M, Walter H, Whelan R, Schumann G, Garavan H, Potter AS. Inattention and Reaction Time Variability Are Linked to Ventromedial Prefrontal Volume in Adolescents. Biol Psychiatry 2017; 82:660-668. [PMID: 28237458 PMCID: PMC5509516 DOI: 10.1016/j.biopsych.2017.01.003] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2016] [Revised: 12/13/2016] [Accepted: 01/04/2017] [Indexed: 12/12/2022]
Abstract
BACKGROUND Neuroimaging studies of attention-deficit/hyperactivity disorder (ADHD) have most commonly reported volumetric abnormalities in the basal ganglia, cerebellum, and prefrontal cortices. Few studies have examined the relationship between ADHD symptomatology and brain structure in population-based samples. We investigated the relationship between dimensional measures of ADHD symptomatology, brain structure, and reaction time variability-an index of lapses in attention. We also tested for associations between brain structural correlates of ADHD symptomatology and maps of dopaminergic gene expression. METHODS Psychopathology and imaging data were available for 1538 youths. Parent ratings of ADHD symptoms were obtained using the Development and Well-Being Assessment and the Strengths and Difficulties Questionnaire (SDQ). Self-reports of ADHD symptoms were assessed using the youth version of the SDQ. Reaction time variability was available in a subset of participants. For each measure, whole-brain voxelwise regressions with gray matter volume were calculated. RESULTS Parent ratings of ADHD symptoms (Development and Well-Being Assessment and SDQ), adolescent self-reports of ADHD symptoms on the SDQ, and reaction time variability were each negatively associated with gray matter volume in an overlapping region of the ventromedial prefrontal cortex. Maps of DRD1 and DRD2 gene expression were associated with brain structural correlates of ADHD symptomatology. CONCLUSIONS This is the first study to reveal relationships between ventromedial prefrontal cortex structure and multi-informant measures of ADHD symptoms in a large population-based sample of adolescents. Our results indicate that ventromedial prefrontal cortex structure is a biomarker for ADHD symptomatology. These findings extend previous research implicating the default mode network and dopaminergic dysfunction in ADHD.
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Affiliation(s)
- Matthew D. Albaugh
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Catherine Orr
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Bader Chaarani
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Robert R. Althoff
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Nicholas Allgaier
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Nicholas D’ Alberto
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Kelsey Hudson
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Scott Mackey
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Philip A. Spechler
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany [or depending on journal requirements can be: Physikalisch-Technische Bundesanstalt (PTB), Abbestr. 2 - 12, Berlin, Germany
| | - Arun L.W. Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neurosciences, Trinity College Dublin
| | - Uli Bromberg
- University Medical Centre Hamburg-Eppendorf, House W34, 3.OG, Martinistr. 52, 20246, Hamburg, Germany
| | - Christian Büchel
- University Medical Centre Hamburg-Eppendorf, House W34, 3.OG, Martinistr. 52, 20246, Hamburg, Germany
| | - Anna Cattrell
- Medical Research Council - Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, United Kingdom
| | - Patricia J. Conrod
- Department of Psychiatry, Universite de Montreal, CHU Ste Justine Hospital, Canada;,Department of Psychological Medicine and Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King’s College London
| | - Sylvane Desrivières
- Medical Research Council - Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, United Kingdom
| | - Herta Flor
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | - Vincent Frouin
- Neurospin, Commissariat à l’Energie Atomique, CEA-Saclay Center, Paris, France
| | - Jürgen Gallinat
- Department of Psychiatry and Psychotherapy, University Medical Center Hamburg-Eppendorf (UKE), Martinistrasse 52, 20246 Hamburg
| | - Robert Goodman
- King’s College London Institute of Psychiatry, Psychology & Neuroscience, London, United Kingdom
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, United Kingdom
| | - Yvonne Grimmer
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité, Universitätsmedizin Berlin, Charitéplatz 1, Berlin, Germany
| | - Viola Kappel
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Charité-Universitätsmedizin, Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM Unit 1000 “Neuroimaging & Psychiatry”, University Paris Sud, University Paris Descartes - Sorbonne Paris Cité; and Maison de Solenn, Paris, France
| | - Marie-Laure Paillère Martinot
- INSERM, UMR 1000, Research Unit NeuroImaging and Psychiatry, Service Hospitalier Frédéric Joliot, Orsay, University Paris-Sud, University Paris Saclay, Orsay, and Maison De Solenn, University Paris Descartes, Paris, France AP-HP, Department of Adolescent Psychopathology and Medicine, Maison De Solenn, Cochin Hospital, Paris, France
| | - Frauke Nees
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | | | - Jani Penttilä
- University of Tampere, Medical School, Tampere, Finland
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, 68159 Mannheim, Germany
| | - Tomáš Paus
- Rotman Research Institute, Baycrest and Departments of Psychology and Psychiatry, University of Toronto, Toronto, Ontario, M6A 2E1, Canada
| | - Michael N. Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Maren Struve
- Department of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Square J5, Mannheim, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy, Campus Charité Mitte, Charité, Universitätsmedizin Berlin, Charitéplatz 1, Berlin, Germany
| | | | - Gunter Schumann
- Medical Research Council - Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, United Kingdom
| | - Hugh Garavan
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
| | - Alexandra S. Potter
- Department of Psychiatry, University of Vermont College of Medicine, Burlington, VT, USA
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