Skip to main content Accessibility help
×
Home

Brains of a feather flocking together? Peer and individual neurobehavioral risks for substance use across adolescence

  • Jungmeen Kim-Spoon (a1), Kirby Deater-Deckard (a2), Alexis Brieant (a1), Nina Lauharatanahirun (a3) (a4), Jacob Lee (a5) and Brooks King-Casas (a1) (a5)...

Abstract

Adolescence is a period of heightened susceptibility to peer influences, and deviant peer affiliation has well-established implications for the development of psychopathology. However, little is known about the role of brain functions in pathways connecting peer contexts and health risk behaviors. We tested developmental cascade models to evaluate contributions of adolescent risk taking, peer influences, and neurobehavioral variables of risk processing and cognitive control to substance use among 167 adolescents who were assessed annually for four years. Risk taking at Time 1 was related to substance use at Time 4 indirectly through peer substance use at Time 2 and insular activation during risk processing at Time 3. Furthermore, neural cognitive control moderated these effects. Greater insular activation during risk processing was related to higher substance use for those with greater medial prefrontal cortex activation during cognitive control, but it was related to lower substance use among those with lower medial prefrontal cortex activation during cognitive control. Neural processes related to risk processing and cognitive control play a crucial role in the processes linking risk taking, peer substance use, and adolescents’ own substance use.

Copyright

Corresponding author

Author for Correspondence: Jungmeen Kim-Spoon, Ph.D., Department of Psychology (MC 0436), Virginia Tech, Blacksburg, Virginia, 24061, USA E-mail: jungmeen@vt.edu.

Footnotes

Hide All
*

Indicates equal contribution.

Footnotes

References

Hide All
Albert, D., Chein, J., & Steinberg, L. (2013). The teenage brain: Peer influences on adolescent decision making. Current Directions in Psychological Science, 22, 114120. doi:10.1177/0963721412471347
Allen, J. P., Chango, J., Szwedo, D., Schad, M., & Marston, E. (2012). Predictors of susceptibility to peer influence regarding substance use in adolescence. Child Development, 83, 337350. doi:10.1111/j.1467-8624.2011.01682.x
Aron, A. R., Robbins, T. W., & Poldrack, R. A. (2014). Inhibition and the right inferior frontal cortex: One decade on. Trends in Cognitive Sciences, 18, 177185. doi:10.1016/j.tics.2013.12.003
Arrow, K. (1965). Aspects of the theory of risk bearing. Helsinki: Yrjö Jahnssonin Säätiö.
Bach, D. R., Symmonds, M., Barnes, G., & Dolan, R. J. (2017). Whole-brain neural dynamics of probabilistic reward prediction. Journal of Neuroscience, 37, 37893798. doi:10.1523/JNEUROSCI.2943-16.2017
Bechara, A., & Damasio, A. R. (2005). The somatic marker hypothesis: A neural theory of economic decision. Games and Economic Behavior, 52, 336372. doi:10.1016/j.geb.2004.06.010
Blakemore, S.-J. (2008). The social brain in adolescence. Nature Reviews Neuroscience, 9, 267277. doi:10.1038/nrn2353
Bray, J. H., Adams, G. J., Getz, J. G., & McQueen, A. (2003). Individuation, peers, and adolescent alcohol use: A latent growth analysis. Journal of Consulting and Clinical Psychology, 71, 553564. doi:10.1037/0022-006X.71.3.553
Buchmann, A. F., Schmid, B., Blomeyer, D., Becker, K., Treutlein, J., Zimmermann, U. S., … Laucht, M. (2009). Impact of age at first drink on vulnerability to alcohol-related problems: Testing the marker hypothesis in a prospective study of young adults. Journal of Psychiatric Research, 43, 12051212. doi:10.1016/j.jpsychires.2009.02.006
Bush, G., Shin, L. M., Holmes, J., Rosen, B. R., & Vogt, B. A. (2003). The Multi-Source Interference Task: Validation study with fMRI in individual subjects. Molecular Psychiatry, 8, 6070. doi:10.1038/sj.mp.4001217
Casey, B. J., Durston, S., & Fossella, J. A. (2001). Evidence for a mechanistic model of cognitive control. Clinical Neuroscience Research, 1, 267282. doi:10.1016/S1566-2772(01)00013-5
Casey, B. J., Getz, S., & Galvan, A. (2008). The adolescent brain. Developmental Review, 28, 6277. doi:10.1016/j.dr.2007.08.003
Cavalca, E., Kong, G., Liss, T., Reynolds, E. K., Schepis, T. S., Lejuez, C. W., & Krishnan-Sarin, S. (2013). A preliminary experimental investigation of peer influence on risk-taking among adolescent smokers and non-smokers. Drug and Alcohol Dependence, 129, 163166. doi:10.1016/j.drugalcdep.2012.09.020
Chung, D., Christopoulos, G. I., King-Casas, B., Ball, S. B., & Chiu, P. H. (2015). Social signals of safety and risk confer utility and have asymmetric effects on observers’ choices. Nature Neuroscience, 18, 912916. doi:10.1038/nn.4022
Conger, R. D., Elder, G. H. Jr., Lorenz, F. O., Simons, R. L., & Whitbeck, L. B. (1994). Social institutions and social change. Families in troubled times: Adapting to change in rural America. Hawthorne, NY, US: Aldine de Gruyter.
d'Acremont, M., & Bossaerts, P. (2008). Neurobiological studies of risk assessment: A comparison of expected utility and mean-variance approaches. Cognitive, Affective, & Behavioral Neuroscience, 8, 363374. doi:10.3758/CABN.8.4.363
Deater-Deckard, K. (2001). Annotation: Recent research examining the role of peer relationships in the development of psychopathology. Journal of Child Psychology and Psychiatry, 42, 565579. doi:10.1017/S0021963001007272
Deng, Y., Wang, X., Wang, Y., & Zhou, C. (2018). Neural correlates of interference resolution in the multi-source interference task: a meta-analysis of functional neuroimaging studies. Behavioral and Brain Functions, 1–9. doi:10.1186/s12993-018-0140-0
Dishion, T. J., Capaldi, D., Spracklen, K. M., & Li, F. (1995). Peer ecology of male adolescent drug use. Development and Psychopathology, 7, 803824. doi:10.1017/S0954579400006854
Dishion, T. J., McCord, J., & Poulin, F. (1999). When interventions harm: Peer groups and problem behavior. American Psychologist, 54, 755764. doi:10.1037/0003-066X.54.9.755
Dishion, T. J., & Owen, L. D. (2002). A longitudinal analysis of friendships and substance use: Bidirectional influence from adolescence to adulthood. Developmental Psychology, 38, 480491. doi:10.1037/0012-1649.38.4.480
Dishion, T. J., & Patterson, G. R. (2016). The development and ecology of antisocial behavior: Linking etiology, prevention, and treatment. In Cicchetti, D. (Ed.), Developmental psychopathology: Maladaptation and psychopathology (pp. 647678). Hoboken, NJ, US: John Wiley & Sons.
Dishion, T. J., Spracklen, K. M., Andrews, D. W., & Patterson, G. R. (1996). Deviancy training in male adolescent friendships. Behavior Therapy, 27, 373390. doi:10.1016/S0005-7894(96)80023-2
Dishion, T. J., & Tipsord, J. M. (2011). Peer contagion in child and adolescent social and emotional development. Annual Review of Psychology, 62, 189214. doi:10.1146/annurev.psych.093008.100412
Dishion, T. J., Véronneau, M.-H., & Myers, M. W. (2010). Cascading peer dynamics underlying the progression from problem behavior to violence in early to late adolescence. Development and Psychopathology, 22, 603619. doi:10.1017/S0954579410000313
Dodge, K. A., Malone, P. S., Lansford, J. E., Miller, S., Pettit, G. S., Bates, J. E., … Maslowsky, J. (2009). A dynamic cascade model of the development of substance-use onset. Monographs of the Society for Research in Child Development, 74, i–134. doi:10.1111/j.1540-5834.2009.00528.x
Ernst, M., Pine, D. S., & Hardin, M. (2006). Triadic model of the neurobiology of motivated behavior in adolescence. Psychological Medicine, 36, 299312. doi:10.1017/S0033291705005891
Farley, J. P., & Kim-Spoon, J. (2015). Longitudinal associations among impulsivity, friend substance use, and adolescent substance use. Journal of Addiction Research & Therapy, 6, 1000220. doi:10.4172/2155-6105.1000220
Farrell, A. D., & Danish, S. J. (1993). Peer drug associations and emotional restraint: Causes or consequences of adolescents’ drug use? Journal of Consulting and Clinical Psychology, 61, 327334.
Farrell, Albert D., Kung, E. M., White, K. S., & Valois, R. F. (2000). The structure of self-reported aggression, drug use, and delinquent behaviors during early adolescence. Journal of Clinical Child Psychology, 29, 282292. doi:10.1207/S15374424jccp2902_13
Foulkes, L., & Blakemore, S. J. (2018). Studying individual differences in human adolescent brain development. Nature Neuroscience, 21, 315323. doi:10.1038/s41593-018-0078-4
Gardner, T. W., Dishion, T. J., & Connell, A. M. (2008). Adolescent self-regulation as resilience: Resistance to antisocial behavior within the deviant peer context. Journal of Abnormal Child Psychology, 36, 273284. doi:10.1007/s10802-007-9176-6
Grant, B. F., & Dawson, D. A. (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.
Guillaume, B., Hua, X., Thompson, P. M., Waldorp, L., & Nichols, T. E. (2014). Fast and accurate modelling of longitudinal and repeated measures neuroimaging data. NeuroImage, 94, 287302. doi:10.1016/j.neuroimage.2014.03.029
Haller, M., Handley, E., Chassin, L., & Bountress, K. (2010). Developmental cascades: Linking adolescent substance use, affiliation with substance use promoting peers, and academic achievement to adult substance use disorders. Development and Psychopathology, 22, 899916. doi:10.1017/S0954579410000532
Hawkins, J. D., Catalano, R. F., & Miller, J. Y. (1992). Risk and protective factors for alcohol and other drug problems in adolescence and early adulthood: Implications for substance abuse prevention. Psychological Bulletin, 112, 64105. doi:10.1037/0033-2909.112.1.64
Hinnant, J. B., & Forman-Alberti, A. B. (2018). Deviant peer behavior and adolescent delinquency: Protective effects of inhibitory control, planning, or decision making? Journal of Research on Adolescence. Advance online publication. doi:10.1111/jora.12405
Holt, C. A., & Laury, S. K. (2002). Risk aversion and incentive effects. The American Economic Review, 92, 16441655. doi:10.1257/000282802762024700
Hussong, A. M. (2002). Differentiating peer contexts and risk for adolescent substance use. Journal of Youth and Adolescence, 31, 207220. doi:10.1023/A:1015085203097
Kandel, D. B. (1978). Homophily, selection, and socialization in adolescent friendships. American Journal of Sociology, 84, 427436.
Kann, L., Kinchen, S., Shanklin, S. L., Flint, K. H., Hawkins, J., Harris, W. A., … Zaza, S. (2014). Youth risk behavior surveillance—United States, 2013. Morbidity and Mortality Weekly Report: Surveillance Summaries, 63, 1168.
Kann, L., McManus, T., Harris, W. A., Shanklin, S. L., Flint, K. H., Hawkins, J., … Zaza, S. (2016). Youth risk behavior surveillance-United States, 2015. Morbidity and Mortality Weekly Report: Surveillance Summaries, 65, 1174.
Kim-Spoon, J., Deater-Deckard, K., Holmes, C. J., Lee, J., Chiu, P., & King-Casas, B. (2016). Behavioral and neural inhibitory control moderates the effects of reward sensitivity on adolescent substance use. Neuropsychologia, 91, 318326. doi:10.1016/j.jep.2015.07.033
Kim-Spoon, J., Deater-Deckard, K., Lauharatanahirun, N., Farley, J. P., Chiu, P. H., Bickel, W. K., & King-Casas, B. (2016). Neural interaction between risk sensitivity and cognitive control predicting health risk behaviors among late adolescents. Journal of Research on Adolescence, 27, 674682. doi:10.1111/jora.12295
Kim-Spoon, J., Maciejewski, D., Lee, J., Deater-Deckard, K., & King-Casas, B. (2017). Longitudinal associations among family environment, neural cognitive control, and social competence among adolescents. Developmental Cognitive Neuroscience, 26, 6976. doi:10.1016/j.dcn.2017.04.009
Kuhnen, C. M., & Knutson, B. (2005). The neural basis of financial risk taking. Neuron, 47, 763770. doi:10.1016/j.neuron.2005.08.008
Martel, M. M., Pierce, L., Nigg, J. T., Jester, J. M., Adams, K., Puttler, L. I., … Zucker, R. A. (2008). Temperament pathways to childhood disruptive behavior and adolescent substance abuse: Testing a cascade model. Journal of Abnormal Child Psychology, 37, 363373. doi:10.1007/s10802-008-9269-x
Maslowsky, J., Keating, D. P., Monk, C. S., & Schulenberg, J. (2011). Planned versus unplanned risks: Neurocognitive predictors of subtypes of adolescents’ risk behavior. International Journal of Behavioral Development, 35, 152160. doi:10.1177/0165025410378069
Mohr, P. N. C., Biele, G., & Heekeren, H. R. (2010). Neural processing of risk. Journal of Neuroscience, 30, 66136619. doi:10.1523/JNEUROSCI.0003-10.2010
Muthén, L. K., & Muthén, B. O. (1998). Mplus User's Guide. Seventh Edition. Los Angeles, CA: Muthén & Muthén.
Nigg, J. (2017). Annual Research Review: On the relations among self-regulation, self-control, executive functioning, effortful control, cognitive control, impulsivity, risk-taking, and inhibition for developmental psychopathology. Journal of Child Psychology and Psychiatry, 58, 361383. doi:10.1111/jcpp.12675
Otten, R., Mun, C. J., & Dishion, T. J. (2017). The social exigencies of the gateway progression to the use of illicit drugs from adolescence into adulthood. Addictive Behaviors, 73, 144150. doi:10.1016/j.addbeh.2017.05.011
Paulsen, D., Carter, R. M., Platt, M., Huettel, S. A., & Brannon, E. M. (2012). Neurocognitive development of risk aversion from early childhood to adulthood. Frontiers in Human Neuroscience, 5. doi:10.3389/fnhum.2011.00178
Paulus, M. P., Rogalsky, C., Simmons, A., Feinstein, J. S., & Stein, M. B. (2003). Increased activation in the right insula during risk-taking decision making is related to harm avoidance and neuroticism. NeuroImage, 19, 14391448. doi:10.1016/S1053-8119(03)00251-9
Peake, S. J., Dishion, T. J., Stormshak, E. A., Moore, W. E., & Pfeifer, J. H. (2013). Risk-taking and social exclusion in adolescence: Neural mechanisms underlying peer influences on decision-making. NeuroImage, 82, 2334. doi:10.1016/j.neuroimage.2013.05.061
Piehler, T., Véronneau, M.-H., & Dishion, T. (2012). Substance use progression from adolescence to early adulthood: Effortful control in the context of friendship influence and early-onset use. Journal of Abnormal Child Psychology, 40, 10451058. doi:10.1007/s10802-012-9626-7
Platt, M. L., & Huettel, S. A. (2008). Risky business: the neuroeconomics of decision making under uncertainty. Nature Neuroscience, 11, 398403. doi:10.1038/nn2062
Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2012). Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. NeuroImage, 59, 21422154. doi:10.1016/j.neuroimage.2011.10.018
Pratt, J. W. (1964). Risk aversion in the small and in the large. Econometrica, 32, 122136. doi: 10.1016/B978-0-12-214850-7.50010-3
Preuschoff, K., Quartz, S. R., & Bossaerts, P. (2008). Human insula activation reflects risk prediction errors as well as risk. Journal of Neuroscience, 28, 27452752. doi:10.1523/JNEUROSCI.4286-07.2008
Reyna, V. F., & Farley, F. (2006). Risk and rationality in adolescent decision making: implications for theory, practice, and public policy. Psychological Science in the Public Interest, 7, 144. doi:10.1111/j.1529-1006.2006.00026.x
Richards, J. M., Plate, R. C., & Ernst, M. (2013). A systematic review of fMRI reward paradigms used in studies of adolescents vs. adults: The impact of task design and implications for understanding neurodevelopment. Neuroscience & Biobehavioral Reviews, 37, 976991. doi:10.1016/j.neubiorev.2013.03.004
Rogosch, F. A., Oshri, A., & Cicchetti, D. (2010). From child maltreatment to adolescent cannabis abuse and dependence: A developmental cascade model. Development and Psychopathology, 22, 883897. doi:10.1017/S0954579410000520
Satterthwaite, T. D., Wolf, D. H., Loughead, J., Ruparel, K., Elliott, M. A., Hakonarson, H., … Gur, R. E. (2012). Impact of in-scanner head motion on multiple measures of functional connectivity: Relevance for studies of neurodevelopment in youth. NeuroImage, 60, 623632. doi:10.1016/j.neuroimage.2011.12.063
Saxbe, D., Del Piero, L., Immordino-Yang, M. H., Kaplan, J., & Margolin, G. (2015). Neural correlates of adolescents’ viewing of parents’ and peers’ emotions: Associations with risk-taking behavior and risky peer affiliations. Social Neuroscience, 10, 592604. doi:10.1080/17470919.2015.1022216
Schriber, R. A., & Guyer, A. E. (2016). Adolescent neurobiological susceptibility to social context. Developmental Cognitive Neuroscience, 19, 118. doi:10.1016/j.dcn.2015.12.009
Siegel, J. S., Power, J. D., Dubis, J. W., Vogel, A. C., Church, J. A., Schlaggar, B. L., & Petersen, S. E. (2014). Statistical improvements in functional magnetic resonance imaging analyses produced by censoring high-motion data points. Human Brain Mapping, 35, 19811996. doi:10.1002/hbm.22307
Simons-Morton, B., & Chen, R. S. (2006). Over time relationships between early adolescent and peer substance use. Addictive Behaviors, 31, 12111223. doi:10.1016/j.addbeh.2005.09.006
Steinberg, L. (2008). A social neuroscience perspective on adolescent risk-taking. Developmental Review, 28, 78106. doi:10.1016/j.dr.2007.08.002
Stride, C. B., Gardner, S., Catley, N., & Thomas, F. (2015). Mplus code for the mediation, moderation, and moderated mediation model templates from Andrew Hayes’ PROCESS analysis examples. Retrieved from http://www.offbeat.group.shef.ac.uk/FIO/mplusmedmod.htm
van den Bos, W., Vahl, P., Güroğlu, B., van Nunspeet, F., Colins, O., Markus, M., … Crone, E. A. (2014). Neural correlates of social decision-making in severely antisocial adolescents. Social Cognitive and Affective Neuroscience, 9, 20592066. doi:10.1093/scan/nsu003
van Duijvenvoorde, A. C. K., Huizenga, H. M., Somerville, L. H., Delgado, M. R., Powers, A., Weeda, W. D., … Figner, B. (2015). Neural correlates of expected risks and returns in risky choice across development. Journal of Neuroscience, 35, 15491560. doi:10.1523/JNEUROSCI.1924-14.2015
Van Ryzin, M. J., & Dishion, T. J. (2013). From antisocial behavior to violence: a model for the amplifying role of coercive joining in adolescent friendships: Coercive joining and young adult violence. Journal of Child Psychology and Psychiatry, 54, 661669. doi:10.1111/jcpp.12017
Van Ryzin, M. J., Fosco, G. M., & Dishion, T. J. (2012). Family and peer predictors of substance use from early adolescence to early adulthood: An 11-year prospective analysis. Addictive Behaviors, 37, 13141324. doi:10.1016/j.addbeh.2012.06.020
Weber, E. U., Shafir, S., & Blais, A.-R. (2004). Predicting risk sensitivity in humans and lower animals: Risk as variance or coefficient of variation. Psychological Review, 111, 430445. doi:10.1037/0033-295X.111.2.430

Keywords

Type Description Title
WORD
Supplementary materials

Kim-Spoon et al. supplementary material
Appendices A-F

 Word (68 KB)
68 KB

Brains of a feather flocking together? Peer and individual neurobehavioral risks for substance use across adolescence

  • Jungmeen Kim-Spoon (a1), Kirby Deater-Deckard (a2), Alexis Brieant (a1), Nina Lauharatanahirun (a3) (a4), Jacob Lee (a5) and Brooks King-Casas (a1) (a5)...

Metrics

Altmetric attention score

Full text views

Total number of HTML views: 0
Total number of PDF views: 0 *
Loading metrics...

Abstract views

Total abstract views: 0 *
Loading metrics...

* Views captured on Cambridge Core between <date>. This data will be updated every 24 hours.

Usage data cannot currently be displayed