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Adolescent brain development in normality and psychopathology

Published online by Cambridge University Press:  17 December 2013

Monica Luciana*
Affiliation:
University of Minnesota
*
Address correspondence and reprint requests to: Monica Luciana, Department of Psychology, University of Minnesota, 75 East River Parkway, N218 Elliott Hall, Minneapolis, MN 55455; E-mail: [email protected].

Abstract

Since this journal's inception, the field of adolescent brain development has flourished, as researchers have investigated the underpinnings of adolescent risk-taking behaviors. Explanations based on translational models initially attributed such behaviors to executive control deficiencies and poor frontal lobe function. This conclusion was bolstered by evidence that the prefrontal cortex and its interconnections are among the last brain regions to structurally and functionally mature. As substantial heterogeneity of prefrontal function was revealed, applications of neuroeconomic theory to adolescent development led to dual systems models of behavior. Current epidemiological trends, behavioral observations, and functional magnetic resonance imaging based brain activity patterns suggest a quadratic increase in limbically mediated incentive motivation from childhood to adolescence and a decline thereafter. This elevation occurs in the context of immature prefrontal function, so motivational strivings may be difficult to regulate. Theoretical models explain this patterning through brain-based accounts of subcortical–cortical integration, puberty-based models of adolescent sensation seeking, and neurochemical dynamics. Empirically sound tests of these mechanisms, as well as investigations of biology–context interactions, represent the field's most challenging future goals, so that applications to psychopathology can be refined and so that developmental cascades that incorporate neurobiological variables can be modeled.

Type
Regular Articles
Copyright
Copyright © Cambridge University Press 2013 

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References

Abelson, R. P. (1963). Computer simulation of “hot cognition.” In Tomkins, S. S. & Messick, S. (Eds.), Computer simulation of personality (pp. 277302). New York: Wiley.Google Scholar
Alexander, G. E., DeLong, M. R., & Strick, P. L. (1986). Parallel organization of functionally segregated circuits linking basal ganglia and cortex. Annual Review of Neuroscience, 9, 357381.CrossRefGoogle ScholarPubMed
Alvarez, J. A., & Emory, E. (2006). Executive function and the frontal lobes: A meta-analytic review. Neuropsychology Review, 16, 1742.CrossRefGoogle ScholarPubMed
Arnett, J. J. (1999). Adolescent storm and stress, reconsidered. American Psychologist, 54, 317326.CrossRefGoogle ScholarPubMed
Arnett, J. J. (2007). Emerging adulthood: What is it, and what is it good for? Child Development Perspectives, 1, 6873.Google Scholar
Arnsten, A. F., & Rubia, K. (2012). Neurobiological circuits regulating attention, cognitive control, motivation, and emotion: Disruptions in neurodevelopmental psychiatric disorders. Journal of the American Academy of Child & Adolescent Psychiatry, 51, 356367.Google Scholar
Asato, M. R., Terwilliger, R., Woo, J., & Luna, B. (2010). White matter development in adolescence: A DTI study. Cerebral Cortex, 20, 21222131.CrossRefGoogle ScholarPubMed
Ashtari, M., Cervellione, K. L., Hasan, K. M., Wu, J., McIlree, C., Kester, H., et al. (2007). White matter development during late adolescence in healthy males: A cross-sectional diffusion tensor imaging study. NeuroImage, 35, 501510.CrossRefGoogle Scholar
Baddeley, A. D. (1996). The fractionation of working memory. Proceedings of the National Academy of Sciences, 9, 1346813472.CrossRefGoogle Scholar
Bandettini, P. A. (2013). Twenty years of MRI: The science and the stories. NeuroImage, 62, 575588.Google Scholar
Barkley, R. A. (1997). Behavioral inhibition, sustained attention and executive functions: Constructing a unifying theory of ADHD. Psychological Bulletin, 121, 6594.Google Scholar
Barnea-Goraly, N., Menon, V., Eckert, M., Tamm, L., Bammer, R., Karchemskiy, A., et al. (2005). White matter development during childhood and adolescence: A cross-sectional diffusion tensor imaging study. Cerebral Cortex, 15, 18481854.CrossRefGoogle ScholarPubMed
Basser, P. J., & Jones, D. K. (2002). Diffusion-tensor MRI: Theory, experimental design and data analysis: A technical review. NMR in Biomedicine, 15, 456467.Google Scholar
Bava, S., Frank, L., McQueeny, T., Schweinsburg, B., Schweinsburg, A., & Tapert, S. (2009). Altered white matter microstructure in adolescent substance users. Psychiatry Research: Neuroimaging, 173, 228237.CrossRefGoogle ScholarPubMed
Beauchaine, T. P., Neuhaus, E., Brenner, S. L., & Gatzke-Kopp, L. (2008). Ten good reasons to consider biological processes in prevention and intervention research. Development and Psychopathology, 20, 745774.Google Scholar
Beauchaine, T. P., Neuhaus, E., Zalewski, M., Crowell, S. E., & Potopova, N. (2011). The effects of allostatic load on neural systems subserving motivation, mood regulation, and social affiliation. Development and Psychopathology, 23, 975999.Google Scholar
Bechara, A., Damasio, H., & Damasio, A. R. (2000). Emotion, decision making and the orbitofrontal cortex. Cerebral Cortex, 10, 295307.CrossRefGoogle ScholarPubMed
Bechara, A., Damasio, A. R., Damasio, H., & Anderson, S. W. (1994). Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50, 715.Google Scholar
Bechara, A., Damasio, H., Damasio, A. R., & Lee, G. P. (1999). Different contributions of the human amygdala and ventromedial prefrontal cortex to decision-making. Journal of Neuroscience, 19, 54735481.Google Scholar
Best, J. R., & Miller, P. H. (2010). A developmental perspective on executive function. Child Development, 81, 16411660.Google Scholar
Bjork, J. M., Knutson, B., Fong, G. W., Caggiano, D. M., Bennett, S. M., & Homer, D. W. (2004). Incentive-elicited brain activation in adolescents: Similarities and differences from young adults. Journal of Neuroscience, 24, 17931802.CrossRefGoogle ScholarPubMed
Bjork, J. M., Lynne-Landsman, S. D., Sirocco, K., & Boyce, C. A. (2012). Brain maturation and risky behavior: The promise and the challenges of neuroimaging-based accounts. Child Development Perspectives, 6, 385391.Google Scholar
Bjork, J. M., Smith, A. R., Chen, G., & Hommer, D. W. (2010). Adolescents, adults and rewards: Comparing motivational neurocircuitry recruitment using fMRI. PLoS ONE, 5, e11440.Google Scholar
Blakemore, S. J., Burnett, S., & Dahl, R. (2010). The role of puberty in the developing adolescent brain, Human Brain Mapping, 31, 926933.Google Scholar
Bonekamp, D., Nagae, L. M., Degaonkar, M., Matson, M., Abdalla, W. M., Barker, P. B., et al. (2007). Diffusion tensor imaging in children and adolescents: Reproducibility, hemispheric, and age-related differences. NeuroImage, 34, 733742.Google Scholar
Bourgeois, J. P., Goldman-Rakic, P. S., & Rakic, P., 1994. Synaptogenesis in the prefrontal cortex of rhesus monkeys. Cerebral Cortex 4, 7896.Google Scholar
Bowlby, J. (1999). Attachment and loss: Vol. 1. Attachment (2nd ed.). New York: Basic Books.Google Scholar
Bramen, J. E., Hranilovich, J. A., Dahl, R. E., Forbes, E. E., Chen, J., Toga, A. W., et al. (2011). Puberty influences medial temporal lobe and cortical gray matter maturation differently in boys than girls matched for sexual maturity. Cerebral Cortex, 21, 636646.Google Scholar
Braver, T. S., Barch, D. M., Gray, J. R., Molfese, D. L., & Snyder, A. (2001) Anterior cingulate cortex and response conflict: Effects of frequency, inhibition and errors. Cerebral Cortex, 11, 825836.Google Scholar
Buchanan, C. M., & Holmbeck, G. (1998). Measuring beliefs about adolescent personality and behavior. Journal of Youth and Adolescence, 27, 609629.CrossRefGoogle Scholar
Bunge, S. A., Dudukovic, M. M., Thomason, M. M., Vaidya, C. J., & Gabrieli, J. D. E. (2002). Immature frontal lobe contributions to cognitive control in children: Evidence from fMRI. Neuron, 32, 301311.CrossRefGoogle Scholar
Burnett, S., & Blakemore, S. J. (2009). The development of adolescent social cognition. Annals of the New York Academy of Sciences, 1167, 5156.CrossRefGoogle ScholarPubMed
Bush, G., Luu, P., & Posner, M. I. (2000). Cognitive and emotional influences in anterior cingulate cortex. Trends in Cognitive Science, 4, 215222.Google Scholar
Carskadon, M., (2011). Sleep in adolescents: The perfect storm. Pediatric Clinics of North America, 58, 637647.Google Scholar
Casey, B. J., & Caudle, K. (2013). The teenage brain: Self-control. Current Directions in Psychological Science, 22, 8287.CrossRefGoogle ScholarPubMed
Casey, B. J., Cohen, J. D., Jezzard, P., Turner, R., Noll, D. C., Trainor, R. J., et al. (1995). Activation of prefrontal cortex in children during a nonspatial working memory task with functional MRI. NeuroImage, 2, 221229.CrossRefGoogle ScholarPubMed
Casey, B. J., Jones, R. M., & Hare, T. A. (2008). The adolescent brain. Annals of the New York Academy of Sciences, 1124, 111126.Google Scholar
Casey, B. J., Trainor, R. J., Orendi, J. L., Schubert, A. B., Nystrom, L. E., Giedd, J. N., et al. (1997). A developmental functional MRI study of prefrontal activation during performance of a go-no-go task. Journal of Cognitive Neuroscience, 9, 835847.Google Scholar
Centers for Disease Control. (2011). Youth risk behavior surveillance—United States. Morbidity and Mortality Weekly Report, 61(SS04), 1162.Google Scholar
Chein, J., Albert, D., O'Brien, L., Uckert, K., & Steinberg, L. (2011). Peers increase adolescent risk-taking by enhancing activity in the brain's reward circuitry. Developmental Science, 14, F1F10.Google Scholar
Cho, Y. T., Fromm, S., Guyer, A. E., Detloff, A., Pine, D. S., Fudge, J. L., et al. (2013). Nucleus accumbens, thalamus and insula connectivity during incentive anticipation in typical adults and adolescents. NeuroImage, 66, 508521.Google Scholar
Cicchetti, D. (1989). Developmental psychopathology: Some thoughts on its evolution. Development and Psychopathology, 1, 14.CrossRefGoogle Scholar
Cicchetti, D., & Rogosch, F. A. (1996). Equifinality and multifinality in developmental psychopathology. Developmental Psychopathology, 8, 597600.Google Scholar
Cicchetti, D., & Rogosch, F. A. (2002). A developmental psychopathology perspective on adolescence. Journal of Consulting and Clinical Psychology, 70, 620.Google Scholar
Cohen, J. R., Asarnow, R. F., Sabb, F. W., Bilder, R. M., Bookheimer, S. Y., Knowlton, B. J., et al. (2010). A unique adolescent response to reward prediction errors. Nature Neuroscience, 13, 669671.Google Scholar
Crockett, L. J., Brown, J. R., Shen, Y-L, & Russell, R. T. (2007). The meaning of good parent–child relationships for Mexican American adolescents. Journal of Research on Adolescence, 17, 639668.CrossRefGoogle Scholar
Crone, E. A., & van der Molen, M. W. (2004). Developmental changes in real-life decision making: Performance on a gambling task previously shown to depend on the ventromedial prefrontal cortex. Developmental Neuropsychology, 25, 251279.Google Scholar
Dahl, R. E. (1996). The regulation of sleep and arousal: Development and psychopathology. Development and Psychopathology, 8, 327.Google Scholar
Dahl, R. E. (2004). Adolescent brain development: A period of vulnerabilities and opportunities. Annals of the New York Academy of Sciences, 1021, 122.Google Scholar
DeBellis, M. D., Clark, D. B., Beers, S. R., Soloff, P. H., Boring, A. M., Hall, J., et al. (2000). Hippocampal volume in adolescent-onset alcohol use disorders. American Journal of Psychiatry, 137, 737744.Google Scholar
Depue, R. A., & Collins, P. F. (1999). Neurobiology of the structure of personality: Dopamine, facilitation of incentive motivation, and extraversion. Behavioral and Brain Sciences, 22, 491517.Google Scholar
Diamond, A. (1990). The development and neural bases of memory functions as indexed by the AB and delayed response tasks in human infants and infant monkeys. Annals of the New York Academy of Sciences, 608, 267317.Google Scholar
Diamond, A. (2013). Executive functions. Annual Review of Psychology, 64, 135168.Google Scholar
Diamond, A., & Goldman-Rakic, P. S. (1989). Comparison of human infants and rhesus monkeys on Piaget's AB task: Evidence for dependence on dorsolateral prefrontal cortex. Experimental Brain Research, 74, 2440.CrossRefGoogle ScholarPubMed
Diamond, A., Zola-Morgan, S., & Squire, L. R. (1989). Successful performance by monkeys with lesions of the hippocampal formation on AB and object retrieval, two tasks that mark developmental changes in human infants. Behavioral Neuroscience, 103, 526–37.Google Scholar
Di Martino, A., Scheres, A., Margulies, D. S., Kelly, A. M. C, Uddin, L. Q., Shehzad, Z. et al. (2008). Functional connectivity of human striatum: A resting state fMRI study, Cerebral Cortex, 18, 27352747.CrossRefGoogle ScholarPubMed
Dishion, T. J., Capaldi, D., Spracklen, K. M., & Li, F. (1995). Peer ecology of male adolescent drug use. Development and Psychopathology, 7, 803824.Google Scholar
Duncan, J. (1995). Attention, intelligence, and the frontal lobes. In Gazzaniga, M. S. (Ed.), The cognitive neurosciences (pp. 721733). Cambridge, MA: MIT Press.Google Scholar
Durston, S., Thomas, K. M., Yang, Y., Ulug, A. M., Zimmerman, R. D., & Casey, B. J. (2002). A neural basis for the development of inhibitory control. Developmental Science, 5, F9F16.Google Scholar
Ellis, B. J., Del Giudice, M., Dishion, T. J., Figueredo, A. J., Gray, P., Griskevicius, V., et al. (2012). The evolutionary basis of risky adolescent behavior: Implications for science, policy, and practice. Developmental Psychology, 48, 598623.CrossRefGoogle ScholarPubMed
Eluvathingal, T. J., Hasan, K. M., Kramer, L., Fletcher, J. M., & Ewing-Cobbs, L. (2007). Quantitative diffusion tensor tractography of association and projection fibers in normally developing children and adolescents. Cerebral Cortex, 17, 27602768.Google Scholar
Ernst, M., Nelson, E. E., Jazbec, S. P., McClure, E. B., Monk, C. S., & Leibenluft, E., et al. (2005). Amygdala and nucleus accumbens in responses to receipt and omission of gains in adults and adolescents. NeuroImage, 25, 12791291.Google Scholar
Ernst, M., Pine, D. S., & Hardin, M. (2006). Triadic model of the neurobiology of motivated behavior in adolescence. Psychological Medicine, 36, 299312.Google Scholar
Eshel, N., Nelson, E. E., Blair, R. J., Dine, D. S., & Ernst, M. (2007). Neural substrates of choices selection in adults and adolescents: Development of the ventrolateral prefrontal and anterior cingulate cortices. Neuropsychologia, 45, 12701279.Google Scholar
Farah, M. J., Noble, K. G., & Hurt, H. (2007) The developing adolescent brain in socioeconomic context. In Romer, D. & Walker, E. (Eds.), Adolescent psychopathology and the developing brain (pp. 373387). New York: Oxford University Press.Google Scholar
Fareri, D. S., Martin, L. N., & Delgado, M. R. (2008). Reward-related processing in the human brain: Developmental considerations. Development and Psychopathology, 20, 11911211.Google Scholar
Figner, B., Mackinlay, R. J., Wilkening, F., & Weber, E. U. (2009). Affective and deliberative processes in risky choice: Age differences in risk taking in the Columbia Card Task. Journal of Experimental Psychology: Learning, Memory, and Cognition, 35, 709730.Google ScholarPubMed
Forbes, E. E., & Dahl, R. E. (2010). Pubertal development and behavior: Hormonal activation of social and motivational tendencies. Brain and Cognition. 72, 6672.Google Scholar
Fryer, S. L., Frank, L. R., Spadoni, A. D., Theilmann, R. J., Nagel, B. J., Schweinsburg, A. D., et al. (2008). Microstructural integrity of the corpus callosum linked with neuropsychological performance in adolescents. Brain and Cognition, 67, 225233.Google Scholar
Galván, A., (2013). The teenage brain: Sensitivity to rewards. Current Directions in Psychological Science, 22, 8893.Google Scholar
Galván, A., Hare, T. A., Parra, C. E., Penn, J., Voss, H., Glover, G., & Casey, B. J. (2006). Earlier development of the accumbens relative to orbitofrontal cortex might underlie risk- taking behavior in adolescents. Journal of Neuroscience, 26, 68856892.Google Scholar
Galván, A., Hare, T. A., Voss, H., Glover, G., & Casey, B. J. (2007). Risk-taking and adolescent brain: Who is at risk? Developmental Science, 10, F8F14.Google Scholar
Ganzel, B. L., & Morris, P. A. (2011) Allostatis and the developing brain: Explicit consideration of implicit models. Development and Psychopathology, 23, 955974.Google Scholar
Gardner, M., & Steinberg, L. (2005). Peer influence on risk taking, risk preference, and risky decision making in adolescence and adulthood: An experimental study. Developmental Psychology, 41, 625635.Google Scholar
Geier, C. F., Terwilliger, R., Teslovich, T., Velanova, K., & Luna, B. (2010). Immaturities in reward processing and its influence on inhibitory control in adolescence. Cerebral Cortex, 20, 16131629.Google Scholar
Giedd, J. N., Blumenthal, J., Jeffries, N. O., Castellanos, F. X., Liu, H., Zijdenbos, A., et al. (1999). Brain development during childhood and adolescence: A longitudinal MRI study. Nature Neuroscience, 2, 861863.Google Scholar
Giedd, J. N., Snell, J. W., Lange, N., Rajapakse, J. C., Casey, B. J., Kozuch, P. I., et al. (1996). Quantitative magnetic resonance imaging of human brain development: Ages 4–18. Cerebral Cortex, 6, 551560.Google Scholar
Giorgio, A., Watkins, K. E., Douaud, G., James, A. C., James, S., De Stefano, N., et al. (2008). Changes in white matter microstructure during adolescence. NeuroImage, 39, 5261.Google Scholar
Goel, V., & Dolan, R. J., 2003. Reciprocal neural response within lateral and ventral medial prefrontal cortex during hot and cold reasoning. NeuroImage, 20, 23142321.Google Scholar
Gogtay, N., Giedd, J. N., Lusk, L., Hayashi, K. M., Greenstein, D., Vaituzis, A. C., et al. (2004). Dynamic mapping of human cortical development during childhood through early adulthood. Proceedings of the National Academy of Sciences, 101, 81748179.Google Scholar
Gogtay, N., & Thompson, P. M. (2010). Mapping gray matter development: Implications for typical development and vulnerability to psychopathology. Brain & Cognition, 72, 618.Google Scholar
Goldman-Rakic, P. S. (1987a). Circuitry of primate prefrontal cortex and regulation of behavior by representational memory. In Plum, F. & Mountcastle, V. (Eds.), Handbook of physiology: The nervous system (Vol. 5, pp. 373417). Bethesda, MD: American Physiological Society.Google Scholar
Goldman-Rakic, P. S. (1987b). Development of cortical circuitry and cognitive function. Child Development, 58, 601622.Google Scholar
Grace, A. A., & Bunney, B. S. (1984a). The control of firing pattern in nigral dopamine neurons: single spike firing. Journal of Neuroscience, 4, 28662876.Google Scholar
Grace, A. A., & Bunney, B. S. (1984b). The control of firing pattern in nigral dopamine neurons: Burst firing. Journal of Neuroscience, 4, 28772890.Google Scholar
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.Google Scholar
Hagmann, P., Grant, P. E., & Fair, D. E. (2012). MR connectomics: A conceptual framework for studying the developing brain. Frontiers in Systems Neuroscience, 6, 43.Google Scholar
Hall, G. S. (1904). Adolescence: Its psychology and its relations to physiology, anthropology, sociology, sex, crime, religion, and education. New York: Appleton.Google Scholar
Hamilton, B. E., Martin, J. A., & Ventura, S. J. (2010). Births: Preliminary data for 2009. National Vital Statistics Reports, 59(3).Google Scholar
Hanson, D. R., & Gottesman, I. I. (2012). Biologically flavored perspectives on Garmezian resilience. Development and Psychopathology, 24, 363369.Google Scholar
Harden, K. P., & Tucker-Drob, E. M. (2011). Individual differences in the development of sensation seeking and impulsivity during adolescence: Further evidence for a dual systems model. Developmental Psychology, 47, 739746.Google Scholar
Harter, S., Bresnick, S., Bouchey, H. A., & Whitesell, N. R. (1997). The development of multiple role-related selves during adolescence. Development and Psychopathology, 9, 835853.Google Scholar
Hasan, K. M., Kamali, A., Kramer, L. A., Papnicolaou, A. C., Fletcher, J. M., & Ewing-Cobbs, L. (2008). Diffusion tensor quantification of the human midsagittal corpus callosum subdivisions across the lifespan. Brain Research, 1227, 5267.CrossRefGoogle ScholarPubMed
Hooper, C., Luciana, M., Conklin, H. M., Yarger, R. (2004). Adolescents' performance on the Iowa Gambling Task: Implications for the development of decision making and ventromedial prefrontal cortex. Developmental Psychology, 40, 11481158.Google Scholar
Huizinga, M., Dolan, C. V., & van der Molen, M. W. (2006). Age-related change in executive function: Developmental trends and a latent variable analysis. Neuropsychologia, 44, 20172036.Google Scholar
Hunt, R. H., & Thomas, K. M. (2008). Magnetic resonance imaging methods in developmental science: A primer. Development and Psychopathology, 20, 10291051.Google Scholar
Huttenlocher, P. R. (1990). Morphometric study of human cerebral cortex development. Neuropsychologia, 28, 517527.CrossRefGoogle ScholarPubMed
Hwang, K., Hallquist, M., & Luna, B. (2013). The development of hub architecture in the human functional brain network. Cerebral Cortex, 23, 23802393.Google Scholar
Hwang, K., Velanova, K., & Luna, B. (2010). Strengthening of top-down frontal cognitive control networks underlying the development of inhibitory control: A functional magnetic resonance imaging effective connectivity study. Journal of Neuroscience, 30, 1553515545.Google Scholar
Iacono, W. G., Malone, S. M., & McGue, M. M. (2003). Substance use disorders, externalizing psychopathology, and P300 event-related potential amplitude. International Journal of Psychophysiology, 48, 147178.Google Scholar
Janve, V. A, Zu, Z., Yao, S. Y., Li, K., Zhang, F. L., Wilson, K. J., et al. (2013). The radial diffusivity and magnetization transfer pool size ratio are sensitive markers for demyelination in a rat model of type III multiple sclerosis (MS) lesions. NeuroImage, 74, 298305.Google Scholar
Klimes-Dougan, B., Hastings, P., Granger, D. A., Usher, B., & Zahn-Waxler, C. (2001). Adrenocortical activity in at-risk and normally developing adolescents: Individual differences in salivary cortisol response to social challenges, basal levels, and diurnal variation. Development and Psychopathology, 13, 695719.Google Scholar
Koob, G. F., & LeMoal, M. (1997). Drug abuse: Hedonic homeostatic dysregulation. Science, 278, 5258.Google Scholar
Koob, G. F., & Volkow, N. (2010). Neurocircuitry of addiction. Neuropsychopharmacology, 35, 217238.Google Scholar
Lebel, C., Walker, L., Leemans, A., Phillips, L., & Beaulieu, C. (2008). Microstructural maturation of the human brain from childhood to adulthood. NeuroImage, 40, 10441055.Google Scholar
Lenroot, R. K., & Giedd, J. N. (2010). Sex differences in the adolescent brain. Brain, & Cognition, 72, 4655.Google Scholar
Lewin-Bizan, S., Bowers, E. P., & Lerner, R. M. (2010). One good thing leads to another: Cascades of positive youth development among American adolescents. Development and Psychopathology, 22, 759770.Google Scholar
Li, T. Q., & Noseworthy, M. D. (2002). Mapping the development of white matter tracts with diffusion tensor imaging. Developmental Science, 5, 293300.Google Scholar
Loewenstein, G., Rick, S., & Cohen, J. D. (2008). Neuroeconomics. Annual Review of Psychology, 59, 647672.Google Scholar
Luciana, M., & Collins, P. F. (2012). Incentive motivation, cognitive control, and the adolescent brain: Is it time for a paradigm shift? Child Development Perspectives. doi:10.1111/j.750–8606.2012.00252. xGoogle Scholar
Luciana, M., & Nelson, C. A. (1998). The functional emergence of prefrontally guided working memory systems in four-to-eight year-old children. Neuropsychologia, 36, 273293.Google Scholar
Luciana, M., & Nelson, C. A. (2002). Assessment of neuropsychological function in children using the Cambridge Neuropsychological Testing Automated Battery (CANTAB): Performance in 4- to 12-year-olds. Developmental Neuropsychology, 22, 595623.Google Scholar
Luciana, M., Conklin, H., Hooper, C., & Yarger, R. (2005). The development of nonverbal working memory processes in adolescents: Different maturational trajectories for recall versus executive control. Child Development, 76, 697712.Google Scholar
Luciana, M., Collins, P. F., Muetzel, R. L., & Lim, K. O. (in press). Effects of alcohol use initiation on brain structure in typically developing adolescents. American Journal of Drug and Alcohol Abuse.Google Scholar
Luciana, M., Collins, P. F., Olson, E. A., & Schissel, A. M. (2009). Tower of London performance in healthy adolescents: The development of planning skills and associations with self- reported inattention and impulsivity. Developmental Neuropsychology, 34, 461475.Google Scholar
Luciana, M., Wahlstrom, D., Collins, P. F., & Porter, J. N. (2012). Dopaminergic modulation of incentive motivation in adolescence: Age-related changes in signaling, individual differences, and implications for the development of self-regulation. Developmental Psychology, 48, 844861.Google Scholar
Luna, B., Garver, K. E., Urban, T. A., Lazar, N. A., & Sweeney, J. A. (2004). Maturation of cognitive from late childhood to adulthood. Child Development, 75, 13571372.CrossRefGoogle ScholarPubMed
Luna, B., Padmanabhan, A., O'Hearn, K. (2010). What has fMRI told us about the development of cognitive control through adolescence? Brain, & Cognition, 72, 101113.Google Scholar
Luna, B., Thulborn, K. R., Munoz, D. P., Merriam, E. P., Garver, K. E., Minshew, N. J., et al. (2001). Maturation of widely distributed brain function subserves cognitive development. NeuroImage, 13, 786793.Google Scholar
Manoach, D. S., Gollub, R. L., Benson, E. S., Searl, M. M., Golf, D. C.Halpern, E., Saper, C. B., & Rauch, S. L., et al. (2000). Schizophrenia subjects show aberrant fMRI activation of dorsolateral prefrontal cortex and basal ganglia during working memory performance, Biological Psychiatry, 48, 99109.Google Scholar
Mars, R. B., & Grol, M. J. (2007). Dorsolateral prefrontal cortex, working memory, and prospective coding for action Journal of Neuroscience, 27, 18011802.Google Scholar
Maslowsky, J., Keating, D. P., Monk, C. S., & Schulenberg, J. S. (2011). Planned versus unplanned risks: Neurocognitive predictors of subtypes of adolescents' risk behavior. International Journal of Behavioral Development, 35, 152160.Google Scholar
Masten, A. S., Best, K. M., & Garmezy, (1990). Resilience and development: Contributions from the study of children who overcome adversity. Development and Psychopathology, 2, 425444.Google Scholar
Masten, A. S., Roisman, G. L., Long, J. B., Burt, K. B., Obradović, J., Riley, J. R., et al. (2005). Developmental cascades: Linking academic achievement and externalizing and internalizing symptoms over 20 years. Developmental Psychology, 41, 733746.CrossRefGoogle ScholarPubMed
May, J. C., Delgado, M. R., Dahl, R. E., Stenger, V. A., Ryan, N. D., Fiez, J. A., & Carter, C. S. (2004). Event-related functional magnetic resonance imaging of reward-related brain circuitry in children and adolescents. Biological Psychiatry, 55, 359366.Google Scholar
McQueeny, T., Schweinsburg, B. C., Schweinsburg, A. D, Jacobus, J., Bava, S., Frank, L. R., & Tapert, S. F. (2009). Altered white matter integrity in adolescent binge drinkers. Alcoholism: Clinical and Experimental Research, 33, 12781285.Google Scholar
Meisel, R. L., & Mullins, A. J. (2006). Sexual experience in female rodents: Cellular mechanisms and functional consequences. Brain Research, 1126, 6675.Google Scholar
Metcalfe, J., & Mischel, W. (1999). A hot/cool system analysis of delay of gratification: Dynamics of willpower. Psychological Review, 106, 319.Google Scholar
Milner, B. (1963). Effects of different brain lesions on card sorting: The role of the frontal lobe. Archives of Neurology, 9, 90100.Google Scholar
Miniño, A. M. (2010, May). Mortality among teenagers aged 12–19 years: United States, 1999–2006. NCHS Data Brief, 37, 18.Google Scholar
Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. (2000). The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive Psychology, 41, 49100.CrossRefGoogle ScholarPubMed
Niv, Y., Daw, N. D., Joel, D., & Dayan, P. (2007). Tonic dopamine: Opportunity costs and the control of response vigor. Psychopharmacology (Berlin), 191, 507520.Google Scholar
Niv, Y., Joel, D., & Dayan, P. (2006). A normative perspective on motivation. Trends in Cognitive Sciences, 10, 375381.Google Scholar
Ochsner, K. N., & Gross, J. J. (2005). The cognitive control of emotion. Trends in Cognitive Sciences, 9, 242249.Google Scholar
Oscar-Berman, M., & Marinkovic, K. (2007). Alcohol: Effects on neurobehavioral functions and the brain. Neuropsychology Review, 17, 239257.Google Scholar
Owen, A. M. (1997). The functional organization of working memory processes within human lateral frontal cortex: The contribution of functional neuroimaging. European Journal of Neuroscience, 9, 13291339.Google Scholar
Paus, T. (2010). Growth of white matter in the adolescent brain: Myelin or axon? Brain & Cognition, 72, 2635.Google Scholar
Paus, T. (2013). How environment and genes shape the adolescent brain. Hormones and Behavior, 64, 195202.Google Scholar
Paus, T., Keshavan, M., & Giedd, J. N. (2008). Why do many psychiatric disorders emerge during adolescence? Nature Reviews Neuroscience, 9, 947957.Google Scholar
Pennington, B. F., & Ozonoff, S. (2006). Executive functions in development and psychopathology. Journal of Child Psychology and Psychiatry, 37, 5187.Google Scholar
Peper, J. S., Brouwer, R. M., Schnack, H. G., van Baal, G. C., van Leeuwen, M., van den Berg, S. M., et al. (2009). Sex steroids and brain structure in pubertal boys and girls. Psychoneuroendocrinology, 34, 332342.Google Scholar
Perrin, J. S., Herve, P. Y., Leonard, G., Perron, M., Pike, G. B., Pitiot, A. et al. (2008). Growth of white matter in the adolescent brain: Role of testosterone and androgen receptor. Journal of Neuroscience, 28, 95199524.Google Scholar
Petrides, M. (2000). The role of the mid-dorsolateral prefrontal cortex in working memory. Experimental Brain Research, 133, 4454.Google Scholar
Pfeifer, J. H., & Blakemore, S.-J. (2012). Adolescent social cognitive and affective neuroscience: Past, present, and future. Social Cognitive and Affective Neuroscience, 7, 110.Google Scholar
Piaget, J. (1936). The construction of reality in the child (Cook, M., Trans.). New York: Basic Books.Google Scholar
Piazza, P., Rougé-Pont, F., Deminière, J. M., Kharoubi, M., Le Moal, M., & Simon, H. (1991) Dopamine activity is reduced in the prefrontal cortex and increased in the nucleus acumbens of rats predisposed to develop amphetamine self-administration. Brain Research, 567, 169174.Google Scholar
Platt, M. L., & Huettel, S. A. (2008) Risky business: The neuroeconomics of decision making under uncertainty. Nature Neuroscience, 11, 398403.Google Scholar
Porter, J. N., Roy, A. K., Benson, B., Carlisi, C., Pine, D., Luciana, M., et al. (2013). Instrinsic connectivity of ventral vs. dorsal striatum from a developmental perspective. Unpublished data.Google Scholar
Prencipe, A., Kesek, A., Cohen, J., Lamm, C., Lewis, M. D., & Zelazo, P. D. (2011). Development of hot and cool executive function during the transition to adolescence. Journal of Experimental Child Psychology, 108, 621637.Google Scholar
Quinn, P. R., & Harden, K. P. (2013). Differential changes in impulsivity and sensation seeking and the escalation of substance abuse from adolescence to early adulthood. Development and Psychopathology, 25, 223239.Google Scholar
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.CrossRefGoogle ScholarPubMed
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.Google Scholar
Robinson, D. L, Zitzman, D. L., Smith, K. J., & Spear, L. P. (2011). Fast dopamine release events in the nucleus accumbens of early adolescent rats. Neuroscience, 176, 296307.Google Scholar
Rustichini, A. (2009). Neuroeconomics: What have we found, and what should we search for? Current Opinion in Neurobiology, 19, 672677.Google Scholar
Sameroff, A. J. (2000). Developmental systems and psychopathology. Development and Psychopathology, 12, 297312.Google Scholar
Schissel, A., Olson, E. A., Collins, P. F., & Luciana, M. (2011). Age-independent effects of pubertal status on behavioral constraint in healthy adolescents. Personality and Individual Differences, 58, 975980.Google Scholar
Schmithorst, V. J., & Yuan, W. (2010). White matter development in adolescence as shown by diffusion MRI. Brain, & Cognition, 72, 1625.Google Scholar
Schultz, W. (2000). Multiple reward signals in the brain. Nature Reviews Neuroscience, 1, 199207.Google Scholar
Schultz, W., Tremblay, L., & Hollerman, J. R. (2000). Reward processing in primate orbitofrontal cortex and basal ganglia. Cerebral Cortex, 10, 272283.Google Scholar
Seguin, J. R., Arseneault, L., & Tremblay, R. A. (2007). The contribution of “cool” and “hot” components of decision-making in adolescence: Implications for developmental psychopathology. Cognitive Development, 22, 530543.Google Scholar
Selemon, L. D., & Goldman-Rakic, P. S. (1988). Common cortical and subcortical target areas of the dorsolateral prefrontal and posterior parietal cortices in the rhesus monkey: A double-labeled study of distributed networks. Journal of Neuroscience, 8, 40494068.Google Scholar
Sheridan, M. A., Hinshaw, S., and D'Esposito, M. (2007). Efficiency of the prefrontal cortex during working memory in attention-deficit/hyperactivity disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 46, 13571366.Google Scholar
Shields, A. N., Cicchetti, D., & Ryan, R. M. (1994). The development of emotional and behavioral self-regulation and social competence among maltreated school-age children. Development and Psychopathology, 6, 5775.Google Scholar
Shirtcliff, E. A., Dahl, R. E., & Pollak, S. D. (2009). Pubertal development: Correspondence between hormonal and physical development. Child Development, 80, 310311.Google Scholar
Shors, T. J., Anderson, M. L., Curlik, D. M., & Nokia, M. S. (2012). Use it or lose it: How neurogenesis keeps the brain fit for learning. Behavioral Brain Research, 227, 450458.Google Scholar
Shulman, E. P., & Cauffman, E. (2013). Deciding in the dark: Age differences in intuitive risk judgment. Developmental Psychology. Advance online publication. doi:10.1037/a0032778Google Scholar
Smith, E. E., & Jonides, J. (1999). Storage and executive processes in the frontal lobe, Science, 283, 16571661.Google Scholar
Somerville, L. H., Hare, T. A., & Casey, B. J. (2010). Frontostriatal maturation predicts behavioral regulation failures to appetitive cues in adolescence. Journal of Cognitive Neuroscience, 23, 21032114.Google Scholar
Song, S. K., Sun, S. W., Ramsbottom, M. J., Chang, C., Russell, J., & Cross, A. H. (2002). Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water. NeuroImage, 17, 14291436.Google Scholar
Sowell, E. R., Peterson, B. S., Thompson, P. M., Welcome, S. E., Henkenius, A. L., & Toga, A. W. (2003). Mapping cortical change across the human life span. Nature Neuroscience, 6, 309315.Google Scholar
Sowell, E. R., Thompson, P. M., Leonard, C. M., Welcome, S. E., Kan, E., & Toga, A. W. (2004). Longitudinal mapping of cortical thickness and brain growth in normal children. Journal of Neuroscience, 24, 82238231.Google Scholar
Spear, L. P. (2011). Reward, aversions and affect in adolescence: Emerging controversies across laboratory, animal and human data. Developmental Cognitive Neuroscience, 1, 390403.Google Scholar
Staff, J., Schulenberg, J. E., Maslowsky, J., Bachman, J. G., O'Malley, P. M., Maggs, J. L., et al. (2010). Substance use changes and social role transitions: Proximal developmental effects on ongoing trajectories from late adolescence through early adulthood. Development and Psychopathology, 22, 917932.Google Scholar
Staffend, N. A., Loftus, C. M., & Meisel, R. L. (2011). Estradiol reduces dendritic spine density in the ventral striatum of female Syrian hamsters. Brain Structure and Function, 215, 187194.Google Scholar
Stang, N. M., Chein, J. M., & Steinberg, L. (2013). The value of the dual systems model of adolescent risk-taking. Frontiers in Human Neuroscience, 7, 233.Google Scholar
Steinberg, L. (2010). A dual systems model of adolescent risk-taking. Developmental Psychobiology, 52, 216224.Google Scholar
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.Google Scholar
Steinberg, L., Cauffman, E., Woolard, J., Graham, S., & Banich, M. (2009). Are adolescents less mature than adults? Minors' access to abortion, the juvenile death penalty, and the alleged APA “flip-flop.” American Psychologist, 64, 583594.Google Scholar
Steinberg, L., Graham, S., O'Brien, L., Woolard, J., Cauffman, E., & Banich, M. (2009). Age differences in future orientation and delay discounting. Child Development, 80, 2844.Google Scholar
Stevens, M. C., Pearlson, G. D., & Calhoun, V. D. (2009). Changes in the interaction of resting state neural networks from adolescence to adulthood. Human Brain Mapping, 30, 23562366.Google Scholar
Stuss, D. T., & Alexander, M. P. (2000). Executive functions and the frontal lobes: A conceptual view. Psychological Research, 63, 289298.Google Scholar
Stuss, D. T., & Benson, D. F. (1986). The frontal lobes. New York: Raven Press.Google Scholar
Substance Abuse and Mental Health Services Administration. (2012). Results from the 2011 National Survey on Drug Use and Health: Summary of national findings (NSDUH Series H-44, HHS Publication No. (SMA) 12-4713). Rockville, MD: Author.Google Scholar
Suo, L., Zhao, L., Si, J., Liu, J., Zhu, W., Chai, B. et al. (2013). Predictable chronic mild stress in adolescence increases resilience in adulthood. Neuropsychopharmacology, 38, 13871400.Google Scholar
Tanner, J. M. (1962). Growth at adolescence. Springfield, IL: Charles C. Thomas.Google Scholar
Telzer, E., Fuligni, A. J., Lieberman, M. J., & Galván, A. (2013a). The effects of poor quality sleep on brain function and risk taking in adolescence, NeuroImage, 71, 275–83.Google Scholar
Telzer, E. H., Fuligni, A. J., Lieberman, M. D., Galván, A., (2013b). Meaningful family relationships: Neurocognitive buffers of adolescent risk taking. Journal of Cognitive Neuroscience, 25, 374387.Google Scholar
Thelen, E. (1989). Self-organization in developmental processes: Can systems approaches work? In Gunnar, M. R. & Thelen, E. (Eds.), The Minnesota symposia on child psychology: Vol. 22. Systems and development (pp. 77117). Hillsdale, NJ: Erlbaum.Google Scholar
Thornberry, T. P., Ireland, T. O., & Smith, C. A. (2001). The importance of timing: The varying impact of childhood and adolescent maltreatment on multiple problem outcomes. Development and Psychopathology, 13, 957979.Google Scholar
Tobler, P. N., O'Doherty, J. P., Dolan, R. J., & Schulz, W. (2007). Reward value coding distinct from risk attitude-related uncertainty coding in human reward systems. Journal of Neurophysiology, 97, 16211632.Google Scholar
Urosevic, S., Collins, P. F., Muetzel, R., & Luciana, M. (2012). Longitudinal changes in adolescent behavioral approach system and behavioral inhibition system sensitivities: Associations with OFC and nucleus accumbens volumes. Developmental Psychology. doi:10.1037/a0028203Google Scholar
Urosevic, S., Collins, P. F., Muetzel, R., Lim, K. O., & Luciana, M. (2013a). Pubertal status associations with reward and threat sensitivities and subcortical brain volumes. Manuscript submitted for publication.Google Scholar
Urosevic, S., Collins, P. F., Muetzel, R., Lim, K. O., & Luciana, M. (2013b). Effects of reward sensitivity and regional brain volumes on substance use initiation in adolescence. Manuscript submitted for publication.Google Scholar
van Leijenhorst, L., Gunther Moor, B., Op de Macks, Z. A., Rombouts, S. A. R. B., Westenberg, P. M. & Crone, E. A. (2010). Adolescent risky decision making: Neurocognitive development of reward and control regions. NeuroImage, 51, 345355.Google Scholar
van Leijenhorst, L.Zanolie, K., Van Meel, C. S., Westenberg, P. M., Rombouts, S. A. R. B. & Crone, E. A. (2010). What motivates the adolescent? Brain regions mediating reward sensitivity across adolescence, Cerebral Cortex, 20, 6169.Google Scholar
Wahlstrom, D., Collins, P. F., White, T., & Luciana, M. (2010). Developmental changes in dopamine neurotransmission in adolescence: Behavioral implications and issues in assessment. Brain & Cognition, 72, 146159.Google Scholar
Wahlstrom, D., White, T., & Luciana, M. (2010). Neurobehavioral evidence for changes in dopamine system activity during adolescence. Neuroscience & Biobehavioral Reviews, 34, 631648.Google Scholar
Walker, E. F. (2002). Adolescent neurodevelopment and psychopathology. Current Directions in Psychological Sciences, 11, 2428.Google Scholar
Walsh, D. (2004). Why do they act that way? A survival guide to the adolescent brain for you and your teen. New York: Free Press.Google Scholar
Wanat, M. J., Willuhn, I., Clark, J. J., & Phillips, P. E. (2009). Phasic dopamine release in appetitive behaviors and drug addiction. Current Drug Abuse Reviews, 2, 195213.Google Scholar
Weinberger, D. R., Elvevag, B., & Giedd, J. N. (2005). The adolescent brain. Washington, DC: National Campaign to Prevent Teen Pregnancy.Google Scholar
Weiner, I,., & Joel, D. (2002). Dopamine in schizophrenia: Dysfunctional information processing in basal ganglia–thalamocortical split circuits. In Chiara, G. Di (Ed.), Handbook of experimental pharmacology: Vol. 154/II. Dopamine in the CNS II (pp. 417472). Berlin: Springer–Verlag.Google Scholar
Welsh, M. C., & Pennington, B. F. (1998). Assessing frontal lobe functioning in children: Views from developmental psychology. Developmental Neuropsychology, 4, 199230.Google Scholar
Welsh, M. C., Pennington, B. F., & Groisser, D. B. (1991). A normative-developmental study of executive function: A window of prefrontal function in children. Developmental Neuropsychology, 7, 131149.Google Scholar
Willuhn, I., Wanat, M. J., Clark, M. J., & Phillips, P. E. M. (2010). Dopamine signaling in the nucleus accumbens of animals self-administering drugs of abuse. In Self, D. W. & Staley, J. K. (Eds.), Behavioral neuroscience of drug addiction: Current topics in behavioral neurosciences (pp. 2971). New York: Springer.Google Scholar
Zuckerman, M. (1994). Behavioral expressions and biosocial bases of sensation seeking. Cambridge: Cambridge University Press.Google Scholar
Zuckerman, M., Eysenck, S. B. J., & Eysenck, H. J. (1978). Sensation seeking in England and America: Cross-cultural, age, and sex comparisons. Journal of Consulting and Clinical Psychology, 46, 139149.Google Scholar