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Reward-related neural activity and structure predict future substance use in dysregulated youth

Published online by Cambridge University Press:  21 December 2016

M. A. Bertocci
Affiliation:
Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, PA, USA
G. Bebko
Affiliation:
Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, PA, USA
A. Versace
Affiliation:
Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, PA, USA
S. Iyengar
Affiliation:
Department of Statistics, University of Pittsburgh, Pittsburgh, PA, USA
L. Bonar
Affiliation:
Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, PA, USA
E. E. Forbes
Affiliation:
Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, PA, USA
J. R. C. Almeida
Affiliation:
Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, PA, USA
S. B. Perlman
Affiliation:
Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, PA, USA
C. Schirda
Affiliation:
Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, PA, USA
M. J. Travis
Affiliation:
Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, PA, USA
M. K. Gill
Affiliation:
Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, PA, USA
V. A. Diwadkar
Affiliation:
Department of Psychiatry and Behavioral Neuroscience, Wayne State University, Detroit, MI, USA
J. L. Sunshine
Affiliation:
Department of Radiology, University Hospitals Case Medical Center/Case Western Reserve University, Cleveland, OH, USA
S. K. Holland
Affiliation:
Cincinnati Children's Hospital Medical Center, University of Cincinnati, Cincinnati, OH, USA
R. A. Kowatch
Affiliation:
Department of Psychiatry and Behavioral Health, Ohio State University, Columbus, OH, USA
B. Birmaher
Affiliation:
Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, PA, USA
D. A. Axelson
Affiliation:
Department of Psychiatry and Behavioral Health, Ohio State University, Columbus, OH, USA
T. W. Frazier
Affiliation:
Pediatric Institute, Cleveland Clinic, Cleveland, OH, USA
L. E. Arnold
Affiliation:
Department of Psychiatry and Behavioral Health, Ohio State University, Columbus, OH, USA
M. A. Fristad
Affiliation:
Department of Psychiatry and Behavioral Health, Ohio State University, Columbus, OH, USA
E. A. Youngstrom
Affiliation:
Department of Psychology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
S. M. Horwitz
Affiliation:
Department of Child and Adolescent Psychiatry, New York University School of Medicine, New York, NY, USA
R. L. Findling
Affiliation:
Department of Psychiatry, Johns Hopkins University, Baltimore, MD, USA
M. L. Phillips
Affiliation:
Department of Psychiatry, Western Psychiatric Institute and Clinic, University of Pittsburgh Medical Center, University of Pittsburgh, Pittsburgh, PA, USA
Corresponding
E-mail address:

Abstract

Background

Identifying youth who may engage in future substance use could facilitate early identification of substance use disorder vulnerability. We aimed to identify biomarkers that predicted future substance use in psychiatrically un-well youth.

Method

LASSO regression for variable selection was used to predict substance use 24.3 months after neuroimaging assessment in 73 behaviorally and emotionally dysregulated youth aged 13.9 (s.d. = 2.0) years, 30 female, from three clinical sites in the Longitudinal Assessment of Manic Symptoms (LAMS) study. Predictor variables included neural activity during a reward task, cortical thickness, and clinical and demographic variables.

Results

Future substance use was associated with higher left middle prefrontal cortex activity, lower left ventral anterior insula activity, thicker caudal anterior cingulate cortex, higher depression and lower mania scores, not using antipsychotic medication, more parental stress, older age. This combination of variables explained 60.4% of the variance in future substance use, and accurately classified 83.6%.

Conclusions

These variables explained a large proportion of the variance, were useful classifiers of future substance use, and showed the value of combining multiple domains to provide a comprehensive understanding of substance use development. This may be a step toward identifying neural measures that can identify future substance use disorder risk, and act as targets for therapeutic interventions.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2016 

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References

Amrock, SM, Weitzman, M (2014). Parental psychological distress and children's mental health: results of a national survey. Academic Pediatrics 14, 375381.CrossRefGoogle ScholarPubMed
Axelson, D, Birmaher, BJ, Brent, D, Wassick, S, Hoover, C, Bridge, J, Ryan, N (2003). A preliminary study of the Kiddie Schedule for Affective Disorders and Schizophrenia for School-Age Children mania rating scale for children and adolescents. Journal of Child Adolescent Psychopharmacology 13, 463470.CrossRefGoogle ScholarPubMed
Bebko, G, Bertocci, MA, Fournier, JC, Hinze, AK, Bonar, L, Almeida, JR, Perlman, SB, Versace, A, Schirda, C, Travis, M, Gill, MK, Demeter, C, Diwadkar, VA, Ciuffetelli, G, Rodriguez, E, Olino, T, Forbes, E, Sunshine, JL, Holland, SK, Kowatch, RA, Birmaher, B, Axelson, D, Horwitz, SM, Arnold, LE, Fristad, MA, Youngstrom, EA, Findling, RL, Phillips, ML (2014). Parsing dimensional vs diagnostic category-related patterns of reward circuitry function in behaviorally and emotionally dysregulated youth in the Longitudinal Assessment of Manic Symptoms study. Journal of the American Medical Association Psychiatry 71, 7180.Google ScholarPubMed
Becker, B, Wagner, D, Koester, P, Tittgemeyer, M, Mercer-Chalmers-Bender, K, Hurlemann, R, Zhang, J, Gouzoulis-Mayfrank, E, Kendrick, KM, Daumann, J (2015). Smaller amygdala and medial prefrontal cortex predict escalating stimulant use. Brain 138, 20742086.CrossRefGoogle Scholar
Berkman, ET, Falk, EB (2013). Beyond brain mapping using neural measures to predict real-world outcomes. Current Directions in Psychological Science 22, 4550.CrossRefGoogle ScholarPubMed
Bertocci, MA, Bebko, G, Versace, A, Fournier, JC, Iyengar, S, Olino, T, Bonar, L, Almeida, JRC, Perlman, SB, Schirda, C, Travis, MJ, Gill, MK, Diwadkar, VA, Forbes, EE, Sunshine, JL, Holland, SK, Kowatch, RA, Birmaher, B, Axelson, D, Horwitz, SM, Frazier, TW, Arnold, LE, Fristad, MA, Youngstrom, EA, Findling, RL, Phillips, ML (2016). Predicting clinical outcome from reward circuitry function and white matter structure in behaviorally and emotionally dysregulated youth. Molecular Psychiatry 21, 11941201.CrossRefGoogle ScholarPubMed
Birmaher, B, Khetarpal, S, Brent, D, Cully, M, Balach, L, Kaufman, J, Neer, SM (1997). The Screen for Child Anxiety Related Emotional Disorders (SCARED): scale construction and psychometric characteristics. Journal of the American Academy of Child and Adolescent Psychiatry 36, 545553.CrossRefGoogle ScholarPubMed
Brett, M, Anton, J-L, Valabregue, R, Poline, J-B (2002). Region of interest analysis using an SPM toolbox [abstract]. Presented at the 8th International Conference on Functional Mapping of the Human Brain, June 2-6, 2002, Sendai, Japan. NeuroImage 16, Abstract 497.Google Scholar
Caseras, X, Lawrence, NS, Murphy, K, Wise, RG, Phillips, ML (2013). Ventral striatum activity in response to reward: differences between bipolar I and II disorders. American Journal of Psychiatry 170, 533541.CrossRefGoogle ScholarPubMed
Christensen, JA, Zoetmulder, M, Koch, H, Frandsen, R, Arvastson, L, Christensen, SR, Jennum, P, Sorensen, HB (2014). Data-driven modeling of sleep EEG and EOG reveals characteristics indicative of pre-Parkinson's and Parkinson's disease. Journal of Neuroscience Methods 235, 262276.CrossRefGoogle ScholarPubMed
Clark, L, Bechara, A, Damasio, H, Aitken, MR, Sahakian, BJ, Robbins, TW (2008). Differential effects of insular and ventromedial prefrontal cortex lesions on risky decision-making. Brain 131, 13111322.CrossRefGoogle ScholarPubMed
Davidson, RJ (1992). Anterior cerebral asymmetry and the nature of emotion. Brain and Cognition 20, 125151.CrossRefGoogle ScholarPubMed
Davidson, RJ, Ekman, P, Saron, CD, Senulis, JA, Friesen, WV (1990). Approach–withdrawal and cerebral asymmetry: emotional expression and brain physiology: I. Journal of Personality and Social Psychology 58, 330341.CrossRefGoogle Scholar
Deen, B, Pitskel, NB, Pelphrey, KA (2011). Three systems of insular functional connectivity identified with cluster analysis. Cerebral Cortex 21, 14981506.CrossRefGoogle ScholarPubMed
Deykin, EY, Levy, JC, Wells, V (1987). Adolescent depression, alcohol and drug abuse. American Journal of Public Health 77, 178182.CrossRefGoogle Scholar
Di Martino, A, Scheres, A, Margulies, DS, Kelly, AM, Uddin, LQ, Shehzad, Z, Biswal, B, Walters, JR, Castellanos, FX, Milham, MP (2008). Functional connectivity of human striatum: a resting state fMRI study. Cerebral Cortex 18, 27352747.CrossRefGoogle ScholarPubMed
Findling, RL, Youngstrom, EA, Fristad, MA, Birmaher, B, Kowatch, RA, Arnold, LE, Frazier, TW, Axelson, D, Ryan, N, Demeter, C, Gill, MK, Fields, B, Depew, J, Kennedy, SM, Marsh, L, Rowles, BM, Horwitz, SM (2010). Characteristics of children with elevated symptoms of mania: the Longitudinal Assessment of Manic Symptoms (LAMS) Study. Journal of Clinical Psychiatry 71, 16641672.CrossRefGoogle ScholarPubMed
Fischl, B (2012). FreeSurfer. NeuroImage 62, 774781.CrossRefGoogle ScholarPubMed
Forbes, EE, Hariri, AR, Martin, SL, Silk, JS, Moyles, DL, Fisher, PM, Brown, SM, Ryan, ND, Birmaher, B, Axelson, DA, Dahl, RE (2009). Altered striatal activation predicting real-world positive affect in adolescent major depressive disorder. American Journal of Psychiatry 166, 6473.CrossRefGoogle ScholarPubMed
Forbes, EE, Olino, TM, Ryan, ND, Birmaher, B, Axelson, D, Moyles, DL, Dahl, RE (2010). Reward-related brain function as a predictor of treatment response in adolescents with major depressive disorder. Cognitive, Affective, and Behavioral Neuroscience 10, 107118.CrossRefGoogle ScholarPubMed
Friedman, J, Hastie, T, Simon, N, Tibshirani, R (2014). GLMNET. CRAN (http://www.jstatsoft.org/v33/i01/).Google Scholar
Friedman, J, Hastie, T, Tibshirani, R (2010). Regularization paths for generalized linear models via coordinate descent. Journal of Statistical Software 33, 122.CrossRefGoogle ScholarPubMed
Fu, CH, Steiner, H, Costafreda, SG (2013). Predictive neural biomarkers of clinical response in depression: a meta-analysis of functional and structural neuroimaging studies of pharmacological and psychological therapies. Neurobiology of Disease 52, 7583.CrossRefGoogle ScholarPubMed
Gerson, AC, Gerring, JP, Freund, L, Joshi, PT, Capozzoli, J, Brady, K, Denckla, MB (1996). The Children's Affective Lability Scale: a psychometric evaluation of reliability. Psychiatry Research 65, 189198.CrossRefGoogle ScholarPubMed
Gowin, JL, Harle, KM, Stewart, JL, Wittmann, M, Tapert, SF, Paulus, MP (2014). Attenuated insular processing during risk predicts relapse in early abstinent methamphetamine-dependent individuals. Neuropsychopharmacology 39, 13791387.CrossRefGoogle ScholarPubMed
Grant, BF, Dawson, DA (1997). Age at onset of alcohol use and its association with DSM-IV alcohol abuse and dependence: results from the National Longitudinal Alcohol Epidemiologic Survey. Journal of Substance Abuse 9, 103110.CrossRefGoogle ScholarPubMed
Grigsby, TJ, Forster, M, Unger, JB, Sussman, S (2016). Predictors of alcohol-related negative consequences in adolescents: a systematic review of the literature and implications for future research. Journal of Adolescence 48, 1835.CrossRefGoogle ScholarPubMed
Heinrich, A, Muller, KU, Banaschewski, T, Barker, GJ, Bokde, AL, Bromberg, U, Buchel, C, Conrod, P, Fauth-Buhler, M, Papadopoulos, D, Gallinat, J, Garavan, H, Gowland, P, Heinz, A, Ittermann, B, Mann, K, Martinot, JL, Paus, T, Pausova, Z, Smolka, M, Strohle, A, Rietschel, M, Flor, H, Schumann, G, Nees, F (2016). Prediction of alcohol drinking in adolescents: personality-traits, behavior, brain responses, and genetic variations in the context of reward sensitivity. Biological Psychology 118, 7987.CrossRefGoogle ScholarPubMed
Helfinstein, SM, Schonberg, T, Congdon, E, Karlsgodt, KH, Mumford, JA, Sabb, FW, Cannon, TD, London, ED, Bilder, RM, Poldrack, RA (2014). Predicting risky choices from brain activity patterns. Proceedings of the National Academy of Sciences USA 111, 24702475.CrossRefGoogle ScholarPubMed
Horwitz, SM, Demeter, C, Pagano, ME, Youngstrom, EA, Fristad, MA, Arnold, LE, Birmaher, B, Gill, MK, Axelson, D, Kowatch, RA (2010). Longitudinal Assessment of Manic Symptoms (LAMS) Study: background, design and initial screening results. Journal of Clinical Psychiatry 71, 1511.CrossRefGoogle ScholarPubMed
Hum, KM, Manassis, K, Lewis, MD (2013). Neurophysiological markers that predict and track treatment outcomes in childhood anxiety. Journal of Abnormal Child Psychology 41, 12431255.CrossRefGoogle ScholarPubMed
Kandel, DB, Logan, JA (1984). Patterns of drug use from adolescence to young adulthood: I. Periods of risk for initiation, continued use, and discontinuation. American Journal of Public Health 74, 660666.CrossRefGoogle ScholarPubMed
Kaufman, J, Birmaher, B, Brent, D, Rao, U, Flynn, C, Moreci, P, Williamson, D, Ryan, N (1997). Schedule for Affective Disorders and Schizophrenia for School-Age Children-Present and Lifetime version (K-SADS-PL): initial reliability and validity data. Journal of the American Academy of Child and Adolescent Psychiatry 36, 980988.CrossRefGoogle ScholarPubMed
Kohannim, O, Hibar, DP, Jahanshad, N, Stein, JL, Hua, X, Toga, AW, Jack, CR Jr., Weiner, MW, Thompson, PM; the Alzheimer's Disease Neuroimaging Initiative (2012 a). Predicting temporal lobe volume on MRI from genotypes using L1–L2 regularized regression. Proceedings. IEEE International Symposium on Biomedical Imaging 2012, 11601163.Google Scholar
Kohannim, O, Hibar, DP, Stein, JL, Jahanshad, N, Hua, X, Rajagopalan, P, Toga, AW, Jack, CR Jr., Weiner, MW, de Zubicaray, GI, McMahon, KL, Hansell, NK, Martin, NG, Wright, MJ, Thompson, PM; Alzheimer's Disease Neuroimaging Initiative (2012 b). Discovery and replication of gene influences on brain structure using LASSO regression. Frontiers in Neuroscience 6, 115.CrossRefGoogle ScholarPubMed
Kokkevi, A, Richardson, C, Florescu, S, Kuzman, M, Stergar, E (2007 a). Psychosocial correlates of substance use in adolescence: a cross-national study in six European countries. Drug and Alcohol Dependence 86, 6774.CrossRefGoogle ScholarPubMed
Kokkevi, AE, Arapaki, AA, Richardson, C, Florescu, S, Kuzman, M, Stergar, E (2007 b). Further investigation of psychological and environmental correlates of substance use in adolescence in six European countries. Drug and Alcohol Dependence 88, 308312.CrossRefGoogle ScholarPubMed
Kuhnen, CM, Knutson, B (2005). The neural basis of financial risk taking. Neuron 47, 763770.CrossRefGoogle ScholarPubMed
Lavigne, JV, Cromley, T, Sprafkin, J, Gadow, KD (2009). The Child and Adolescent Symptom Inventory-Progress Monitor: a brief Diagnostic and Statistical Manual of Mental Disorders, 4th edition-referenced parent-report scale for children and adolescents. Journal of Child and Adolescent Psychopharmacology 19, 241252.CrossRefGoogle Scholar
Lockhart, R, Taylor, J, Tibshirani, RJ, Tibshirani, R (2014). A significance test for the lasso. Annals of Statistics 42, 413468.CrossRefGoogle ScholarPubMed
Lopez-Larson, MP, Bogorodzki, P, Rogowska, J, McGlade, E, King, JB, Terry, J, Yurgelun-Todd, D (2011). Altered prefrontal and insular cortical thickness in adolescent marijuana users. Behavioural Brain Research 220, 164172.CrossRefGoogle ScholarPubMed
Luo, Y, McShan, D, Kong, F, Schipper, M, Haken, RT (2015). TH-AB-304–07: a two-stage signature-based data fusion mechanism to predict radiation pneumonitis in patients with non-small-cell lung cancer (NSCLC). Medical Physics 42, 4926122.CrossRefGoogle Scholar
Maldjian, JA, Laurienti, PJ, Kraft, RA, Burdette, JH (2003). An automated method for neuroanatomic and cytoarchitectonic atlas-based interrogation of fMRI data sets. NeuroImage 19, 12331239.CrossRefGoogle ScholarPubMed
Mashhoon, Y, Czerkawski, C, Crowley, DJ, Cohen-Gilbert, JE, Sneider, JT, Silveri, MM (2014). Binge alcohol consumption in emerging adults: anterior cingulate cortical ‘thinness’ is associated with alcohol use patterns. Alcoholism: Clinical and Experimental Research 38, 19551964.CrossRefGoogle ScholarPubMed
Masten, CL, Eisenberger, NI, Borofsky, LA, McNealy, K, Pfeifer, JH, Dapretto, M (2011). Subgenual anterior cingulate responses to peer rejection: a marker of adolescents’ risk for depression. Development and Psychopathology 23, 283292.CrossRefGoogle ScholarPubMed
McClure, EB, Adler, A, Monk, CS, Cameron, J, Smith, S, Nelson, EE, Leibenluft, E, Ernst, M, Pine, DS (2007). fMRI predictors of treatment outcome in pediatric anxiety disorders. Psychopharmacology 191, 97105.CrossRefGoogle ScholarPubMed
Morgan, JK, Olino, TM, McMakin, DL, Ryan, ND, Forbes, EE (2013). Neural response to reward as a predictor of increases in depressive symptoms in adolescence. Neurobiology of Disease 52, 6674.CrossRefGoogle ScholarPubMed
Naqvi, NH, Bechara, A (2009). The hidden island of addiction: the insula. Trends in Neurosciences 32, 5667.CrossRefGoogle ScholarPubMed
Nees, F, Tzschoppe, J, Patrick, CJ, Vollstadt-Klein, S, Steiner, S, Poustka, L, Banaschewski, T, Barker, GJ, Buchel, C, Conrod, PJ, Garavan, H, Heinz, A, Gallinat, J, Lathrop, M, Mann, K, Artiges, E, Paus, T, Poline, JB, Robbins, TW, Rietschel, M, Smolka, MN, Spanagel, R, Struve, M, Loth, E, Schumann, G, Flor, H (2012). Determinants of early alcohol use in healthy adolescents: the differential contribution of neuroimaging and psychological factors. Neuropsychopharmacology 37, 986995.CrossRefGoogle ScholarPubMed
Nusslock, R, Almeida, JR, Forbes, EE, Versace, A, Frank, E, LaBarbara, EJ, Klein, CR, Phillips, ML (2012). Waiting to win: elevated striatal and orbitofrontal cortical activity during reward anticipation in euthymic bipolar disorder adults. Bipolar Disorders 14, 249260.CrossRefGoogle ScholarPubMed
Pizzagalli, DA (2010). Frontocingulate dysfunction in depression: toward biomarkers of treatment response. Neuropsychopharmacology 36, 183206.CrossRefGoogle ScholarPubMed
Pochon, JB, Levy, R, Fossati, P, Lehericy, S, Poline, JB, Pillon, B, Le Bihan, D, Dubois, B (2002). The neural system that bridges reward and cognition in humans: an fMRI study. Proceedings of the National Academy of Sciences 99, 56695674.CrossRefGoogle ScholarPubMed
Postuma, RB, Dagher, A (2006). Basal ganglia functional connectivity based on a meta-analysis of 126 positron emission tomography and functional magnetic resonance imaging publications. Cerebral Cortex 16, 15081521.CrossRefGoogle ScholarPubMed
Reeb, BT, Wu, EY, Martin, MJ, Gelardi, KL, Shirley Chan, SY, Conger, KJ (2015). Long-term effects of fathers’ depressed mood on youth internalizing symptoms in early adulthood. Journal of Research on Adolescence 25, 151162.CrossRefGoogle ScholarPubMed
Ricket J (2013). Trevor Hastie presents glmnet: lasso and elastic-net regularization in R (http://blog.revolutionanalytics.com/2013/05/hastie-glmnet.html).Google Scholar
Schneider, S, Peters, J, Bromberg, U, Brassen, S, Miedl, SF, Banaschewski, T, Barker, GJ, Conrod, P, Flor, H, Garavan, H, Heinz, A, Ittermann, B, Lathrop, M, Loth, E, Mann, K, Martinot, JL, Nees, F, Paus, T, Rietschel, M, Robbins, TW, Smolka, MN, Spanagel, R, Strohle, A, Struve, M, Schumann, G, Buchel, C (2012). Risk taking and the adolescent reward system: a potential common link to substance abuse. American Journal of Psychiatry 169, 3946.CrossRefGoogle ScholarPubMed
Shaw, P, Kabani, NJ, Lerch, JP, Eckstrand, K, Lenroot, R, Gogtay, N, Greenstein, D, Clasen, L, Evans, A, Rapoport, JL, Giedd, JN, Wise, SP (2008). Neurodevelopmental trajectories of the human cerebral cortex. Journal of Neuroscience 28, 35863594.CrossRefGoogle ScholarPubMed
Shin, LM, Davis, FC, VanElzakker, MB, Dahlgren, MK, Dubois, SJ (2013). Neuroimaging predictors of treatment response in anxiety disorders. Biology of Mood and Anxiety Disorders 3, 15.CrossRefGoogle ScholarPubMed
Steinberg, L, Albert, D, Cauffman, E, Banich, M, Graham, S, Woolard, J (2008). Age differences in sensation seeking and impulsivity as indexed by behavior and self-report: evidence for a dual systems model. Developmental Psychology 44, 17641778.CrossRefGoogle Scholar
Stewart, JL, Connolly, CG, May, AC, Tapert, SF, Wittmann, M, Paulus, MP (2014 a). Striatum and insula dysfunction during reinforcement learning differentiates abstinent and relapsed methamphetamine-dependent individuals. Addiction 109, 460471.CrossRefGoogle ScholarPubMed
Stewart, JL, May, AC, Poppa, T, Davenport, PW, Tapert, SF, Paulus, MP (2014 b). You are the danger: attenuated insula response in methamphetamine users during aversive interoceptive decision-making. Drug and Alcohol Dependence 142, 110119.CrossRefGoogle ScholarPubMed
Substance Abuse and Mental Health Services Administration (2013). Results from the 2012 National Survey on Drug Use and Health: Summary of National Findings, NSDUH Series H-46, HHS Publication No. (SMA) 13-4795. Substance Abuse and Mental Health Services Administration: Rockville, MD.Google Scholar
Tibshirani, R (1996). Regression shrinkage and selection via the Lasso. Journal of the Royal Statistical Society. Series B (Methodological) 58, 267288.Google Scholar
Vetreno, RP, Yaxley, R, Paniagua, B, Johnson, GA, Crews, FT (2016). Adult rat cortical thickness changes across age and following adolescent intermittent ethanol treatment. Addiction Biology. Published online 1 February 2016. doi:10.1111/adb.12364.Google ScholarPubMed
Wang, Z, Xu, W, Liu, Y (2015). Integrating full spectrum of sequence features into predicting functional microRNA–mRNA interactions. Bioinformatics 31, 35293536.CrossRefGoogle ScholarPubMed
Wu, TT, Lange, K (2008). Coordinate decent algorithms for lasso penalized regression. Annals of Applied Statistics 2, 224244.CrossRefGoogle Scholar
Yan, S, Tsurumi, A, Que, YA, Ryan, CM, Bandyopadhaya, A, Morgan, AA, Flaherty, PJ, Tompkins, RG, Rahme, LG (2015). Prediction of multiple infections after severe burn trauma: a prospective cohort study. Annals of Surgery 261, 781792.CrossRefGoogle ScholarPubMed
Youngstrom, E, Meyers, O, Demeter, C, Youngstrom, J, Morello, L, Piiparinen, R, Feeny, N, Calabrese, JR, Findling, RL (2005). Comparing diagnostic checklists for pediatric bipolar disorder in academic and community mental health settings. Bipolar Disorders 7, 507517.CrossRefGoogle ScholarPubMed
Youngstrom, EA, Frazier, TW, Demeter, C, Calabrese, JR, Findling, RL (2008). Developing a 10-item mania scale from the Parent General Behavior Inventory for children and adolescents. Journal of Clinical Psychiatry 69, 831839.CrossRefGoogle Scholar
Zemmour, C, Bertucci, F, Finetti, P, Chetrit, B, Birnbaum, D, Filleron, T, Boher, JM (2015). Prediction of early breast cancer metastasis from DNA microarray data using high-dimensional Cox regression models. Cancer Informatics 14, 129138.Google ScholarPubMed
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Reward-related neural activity and structure predict future substance use in dysregulated youth
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