Abstract
Adolescence is a transitional period between childhood and adulthood. The definition of this period varies, but it is commonly anchored to the start of puberty (~ 9–11 years in girls and 11–13 in boys) and ends at the age of legal adulthood (Adkins, 2011). Adolescence is characterized by considerable changes in multiple domains (i.e., physical, cognitive, emotional, motivational, and social). For example, goal-directed behaviors are executed with shorter reaction times than adults, motoric and cognitive inhibition are facilitated, and working memory is improved (Williams et al., 1999; Bedard et al., 2002; Munoz & Istvan, 1998; Gathercole et al., 2004; Ernst & Mueller, 2008). Concurrently, impulsivity, emotional lability, and risk taking are increased (Arnett, 1999; Dahl, 2004; Ernst, Pine, & Hardin, 2006; Hardin & Ernst, 2009; Buchanan, Eccles, & Becker, 1992), which, when extreme, can have dramatic life-changing consequences, such as drug addiction, serious car accidents, sexually transmitted infections, or unplanned pregnancies (Kann et al., 2014). In addition, these changes are concomitant with the adolescent peak incidence of many psychiatric disorders, including mood and anxiety disorders (Kessler et al., 2005; Angold & Costello, 2006).
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References
Adkins, D. (2013, October 01). ‘When is puberty too early?’. Retrieved from http://www.dukemedicine.org/
Anderson, J. S., Ferguson, M. A., Lopez-Larson, M., & Yurgelun-Todd, D. (2011). ‘Connectivity gradients between the default mode and attention control networks’, Brain Connectivity, 1, 147–57.
Angold, A., & Costello, E.J. (2006). ‘Puberty and depression’, Child and Adolescent Psychiatric Clinics of North America, 15, 919–37.
Arnett, J. J. (1999). ‘Adolescent storm and stress, reconsidered’, American Psychologist, 54, 317–26.
Beckmann, C. F., DeLuca, M., Devlin, J. T., & Smith, S. M. (2005). ‘Investigations into resting-state connectivity using independent component analysis’, Philosophical Transactions of The Royal Society B-Biological Sciences, 360, 1001–13.
Bedard, A. C., Nichols, S., Barbosa, J. A., Schachar, R., Logan, G. D., & Tannock, R. (2002). ‘The development of selective inhibitory control across the life span’, Developmental Neuropsychology, 21, 93–111.
Biswal, B., Yetkin, F. Z., Haughton, V. M., & Hyde, J. S. (1995). ‘Functional connectivity in the motor cortex of resting human brain using echo-planar MRI’, Magnetic Resonance in Medicine, 34, 537–41.
Blanton, R. E., Levitt, J. G., Thompson, P. M., Narr, K. L., Capetillo-Cunliffe, L., Nobel, A., … Toga, A. W. (2001). ‘Mapping cortical asymmetry and complexity patterns in normal children’, Psychiatry Research, 107, 29–43.
Bourgeois, J. P., & Rakic, P. (1993). ‘Changes of synaptic density in the primary visual cortex of the macaque monkey from fetal to adult stage’, Journal of Neuroscience, 13, 2801–20.
Buchanan, C. M., Eccles, J. S., & Becker, J. B. (1992). ‘Are adolescents the victims of raging hormones: Evidence for activational effects of hormones on moods and behavior at adolescence’, Psychological Bulletin, 111, 62–107.
Bulfmore, E., & Sporns, O. (2009). ‘Complex brain networks: Graph theoretical analysis of structural and functional systems’, Nature Reviews Neuroscience, 10, 186–98.
Casey, B., Jones, R. M., & Somerville, L. H. (2011). ‘Braking and accelerating of the adolescent brain’, Journal of Research on Adolescence, 21, 21–33.
Chambers, R. A., Taylor, J. R., & Potenza, M. N. (2003). ‘Developmental neurocircuitry of motivation in adolescence: A critical period of addiction vulnerability’, American Journal of Psychiatry, 160, 1041–52.
Dahl, R. E. (2004). ‘Adolescent brain development: A period of vulnerabilities and opportunities. Keynote address’, Annals of the New York Academy of Sciences, 1021, 1–22.
Das, P., Kemp, A. H., Liddell, B. J., Brown, K. J., Olivieri, G., Peduto, A., … Williams, L. M. (2005). ‘Pathways for fear perception: Modulation of amygdala activity by thalamo-cortical systems’, Neuroimage, 26, 141–8.
David, O., Guillemain, I., Saillet, S., Reyt, S., Deransart, C., Segebarth, C., & Depaulis A. (2008). ‘Identifying neural drivers with functional MRI: An electrophysiological validation’, PLoS Biology, 6, 2683–97.
Ernst, M., & Fudge, J. L. (2009). ‘A developmental neurobiological model of motivated behavior: Anatomy, connectivity and ontogeny of the triadic nodes’, Neuroscience and Biobehavioral Reviews, 33, 367–82.
Ernst, M., & Mueller, S. C. (2008). ‘The adolescent brain: Insights from functional neuroimaging research’, Developmental Neurobiology, 68, 729–43.
Ernst, M., Pine, D. S., & Hardin, M. (2006). ‘Triadic model of the neurobiology of motivated behavior in adolescence’, Psychological Medicine, 36, 299–312.
Fair, D. A., Bathula, D., Mills, K. L., Dias, T. G., Blythe, M. S., Zhang, D., … Nagel, B. J. (2010). ‘Maturing thalamocortical functional connectivity across development’, Frontiers in Systems Neuroscience, 4, 10.
Fair, D. A., Cohen, A. L., Dosenbach, N. U., Church, J. A., Miezin, F. M., Barch, D. M., … Schlaggar, B. L. (2008). ‘The maturing architecture of the brain’s default network’, Proceedings of the National Academy of Sciences of the United States of America, 105, 4028–32.
Fair, D. A., Cohen, A. L., Power, J. D., Dosenbach, N. U., Church, J. A., Miezin, F. M., … Petersen, S. E. (2009). ‘Functional brain networks develop from a “local to distributed” organization’, PLoS Computational Biology, 5, el000381.
Fair, D. A., Dosenbach, N. U., Church, J. A., Cohen, A. L., Brahmbhatt, S., Miezin, F. M., … Schlaggar, B. L. (2007). ‘Development of distinct control networks through segregation and integration’, Proceedings of the National Academy of Sciences of the United States of America, 104, 13507–12.
Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005). ‘The human brain is intrinsically organized into dynamic, anticorrelated functional networks’, Proceedings of the National Academy of Sciences of the United States of America, 102, 9673–9678.
Friston, K. J., Buechel, C., Fink, G. R., Morris, J., Rolls, E., & Dolan, R. J. (1997). ‘Psychophysiological and modulatory interactions in neuroimaging’, Neuroimage, 6, 218–29.
Friston, K.J., Harrison, L., & Penny, W. (2003). ‘Dynamic causal modelling’, Neuroimage, 19, 1273–1302.
Friston, K. J., Kahan, J., Biswal, B., & Razi, A. (2014). ‘A DCM for resting state fMRI’, Neuroimage, 94, 396–407
Gathercole, S. E., Pickering, S. J., Ambridge, B., & Wearing, H. (2004). ‘The structure of working memory from 4 to 15 years of age’, Developmental Psychology, 40, 177–90.
Giedd, J. N., Blumenthal, J., Jeffries, N. O., Castellanos, F. X., Liu, H., Zijdenbos, A., … Rapoport, J. L. (1999). ‘Brain development during childhood and adolescence: A longitudinal MRI study’, Nature Neuroscience, 2, 861–3.
Gogtay N., & Thompson, P. M. (2010). ‘Mapping gray matter development: Implications for typical development and vulnerability to psychopathology’, Brain and Cognition, 72, 6–15.
Hardin, M. G., & Ernst, M. (2009). ‘Functional brain imaging of development-related risk and vulnerability for substance use in adolescents’, Journal of Addiction Medicine, 3, 47–54.
Hoff, G. E. A.-J., Van den Heuvel, M. P., Benders, M. J. N. L., Kersbergen, K. J., & De Vries, L. S. (2013). ‘On development of functional brain connectivity in the young brain’, Frontiers in Human Neuroscience, 7.
Hwang, K., Hallquist, M. N., & Luna, B. (2013). ‘The development of hub architecture in the human functional brain network’, Cerebral Cortex, 23, 2380–93.
Jo, H. J., Saad, Z. S., Simmons, W. K., Milbury L. A., & Cox, R. W. (2010). ‘Mapping sources of correlation in resting state FMRI, with artifact detection and removal’, Neuroimage, 52, 571–82.
Kahan, J., & Foltynie, T. (2013). ‘Understanding DCM: Ten simple rules for the clinician’, Neuroimage, 83, 542–9.
Kann, L., Kinchen, S., Shanklin, S. L., Flint, K. H., Kawkins, J., Harris, W. A., … Zaza, S. (2014). ‘Youth risk behavior surveillance — United States, 2014’, Morbidity and Mortality Weekly Report (MMWR), 63.
Kessler, R. C., Berglund, P., Dernier, O., Jin, R., Merikangas, K. R., & Walters, E. E. (2005). ‘Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication’, Archives of General Psychiatry, 62, 593–602.
Knutson, B., Adams, C. M., Fong, G. W., & Hommer, D. (2001). ‘Anticipation of increasing monetary reward selectively recruits nucleus accumbens’, Journal of Neuroscience, 21, RC159.
Lenroot, R. K., Gogtay N., Greenstein, D. K., Wells, E. M., Wallace, G. L., Clasen, L. S., … Giedd, J. N. (2007). ‘Sexual dimorphism of brain developmental trajectories during childhood and adolescence’, Neuroimage, 36, 1065–73.
Liao, W., Mantini, D., Zhang, Z., Pan, Z., Ding, J., Gong, Q., … Chen, H. (2010). ‘Evaluating the effective connectivity of resting state networks using conditional Granger causality’, Biological Cybernetics, 102, 57–69.
Liu, X., Hairston, J., Schrier, M., & Fan, J. (2011). ‘Common and distinct networks underlying reward valence and processing stages: A meta-analysis of functional neuroimaging studies’, Neuroscience and Biobehavioral Reviews, 35, 1219–36.
Lohmann, G., Erfurth, K., Muller, K., & Turner, R. (2012). ‘Critical comments on dynamic causal modelling’, Neuroimage, 59, 2322–9.
Madler, B., Drabycz, S. A., Kolind, S. H., Whittall, K. P., & MacKay A. L. (2008). ‘Is diffusion anisotropy an accurate monitor of myelination? Correlation of multicomponent T2 relaxation and diffusion tensor anisotropy in human brain’, Magnetic Resonance Imaging, 26, 874–88.
McKeown, M. J., Hansen, L. K., & Sejnowsk, T. J. (2003). ‘Independent component analysis of functional MRI: What is signal and what is noise?’, Current Opinion In Neurobiology, 13, 620–9.
Munoz, D. P., & Istvan, P. J. (1998). ‘Lateral inhibitory interactions in the intermediate layers of the monkey superior colliculus’, Journal of Neurophysiology, 79, 1193–209.
O’Muircheartaigh, J., Dean 3rd, D. C., Dirks, H., Waskiewicz, N., Lehman, K., Jerskey B. A., & Deoni, S. C. (2013). ‘Interactions between white matter asymmetry and language during neurodevelopment’, Journal of Neuroscience, 33, 16170–7.
Patel, R. S., Bowman, F. D., & Rilling, J. K. (2006). ‘A Bayesian approach to determining connectivity of the human brain’, Human Brain Mapping, 27, 267–76.
Paus, T. (2005). ‘Mapping brain maturation and cognitive development during adolescence’, Trends In Cognitive Sciences, 9, 60–8.
Power, J. D., Mitra, A., Laumann, T. O., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2014). ‘Methods to detect, characterize, and remove motion artifact in resting state fMRI’, Neuroimage, 84, 320–41.
Raichle, M. E., MacLeod, A. M., Snyder, A. Z., Powers, W. J., Gusnard, D. A., & Shulman, G. L. (2001). ‘A default mode of brain function’, Proceedings of the National Academy of Sciences of The United States of America, 98, 676–82.
Ramsey, J. D., Hanson, S. J., Hanson, C., Halchenko, Y. O., Poldrack, R. A., & Glymour, C. (2010). ‘Six problems for causal inference from fMRI’, Neuroimage, 49, 1545–58.
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 and Biobehavioral Reviews, 37, 976–91.
Roebroeck, A., Formisano, E., & Goebel, R. (2005). ‘Mapping directed influence over the brain using Granger causality and fMRI’, Neuroimage, 25, 230–42.
Rosazza, C., & Minati, L. (2011). ‘Resting-state brain networks: Literature review and clinical applications’, Neurological Sciences, 32, 773–85.
Rubia, K. (2013). ‘Functional brain imaging across development’, European Child & Adolescent Psychiatry, 22, 719–31.
Smith, A. B., Halari, R., Giampetro, V., Brammer, M., & Rubia, K. (2011). ‘Developmental effects of reward on sustained attention networks’, Neuroimage, 56, 1693–704.
Smith, S. M., Fox, P. T., Miller, K. L., Glahn, D. C., Fox, P. M., Mackay, C. E., … Beckman, C. F. (2009). ‘Correspondence of the brain’s functional architecture during activation and rest’, Proceedings of the National Academy of Sciences of the United States of America, 106, 13040–5.
Smith, S. M., Miller, K. L., Moeller, S., Xu, J., Auerbach, E. J., Woolrich, M. W., … Uqurbil, K. (2012). ‘Temporally-independent functional modes of spontaneous brain activity’, Proceedings of the National Academy of Sciences of the United States of America, 109, 3131–6.
Snook, L., Paulson, L. A., Roy D., Phillips, L., & Beaulieu, C. (2005). ‘Diffusion tensor imaging of neurodevelopment in children and young adults’, Neuroimage, 26, 1164–73.
Sporns, O. (2013). ‘Structure and function of complex brain networks’, Dialogues in Clinical Neuroscience, 15, 247–62.
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, 2356–66.
Supekar, K., Musen, M., & Menon, V. (2009). ‘Development of large-scale functional brain networks in children’, PLoS Biology, 7, el000157.
Thomason, M. E., Dassanayake, M. T, Shen, S., Katkuri, Y., Alexis, M., Anderson, A. L., … Romero, R. (2013). ‘Cross-hemispheric functional connectivity in the human fetal brain’, Science Translational Medicine, 5, 173ra24.
Uddin, L. Q., Supekar, K. S., Ryali, S., & Menon, V. (2011). ‘Dynamic reconfiguration of structural and functional connectivity across core neurocognitive brain networks with development’, Journal of Neuroscience, 31, 18578–89.
van den Heuvel, M. P., & Hulshoff Pol, H. E. (2010). ‘Exploring the brain network: A review on resting-state fMRI functional connectivity’, European Neuropsychopharmacology 20, 519–34.
van der Marel, K., Klomp, A., Meerhoff, G. F., Schipper, P., Lucassen, P. J., Homberg, J. R., … Reneman, L. (2014). ‘Long-term oral methylphenidate treatment in adolescent and adult rats: Differential effects on brain morphology and function’, Neuropsychopharmacology 39, 263–73.
Webb, J. T., Ferguson, M. A., Nielsen, J. A., & Anderson, J. S. (2013). ‘BOLD Granger causality reflects vascular anatomy’, PLoS One, 8, e84279.
Williams, B. R., Ponesse, J. S., Schachar, R. J., Logan, G. D., & Tannock, R. (1999). ‘Development of inhibitory control across the life span’, Developmental Psychology, 35, 205–13.
Zhang, D., & Raichle, M. E. (2010). ‘Disease and the brain’s dark energy’, Nature Reviews Neurology, 6, 15–28.
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© 2015 Monique Ernst, Elizabeth A. Hale, Nicholas Balderston, and Salvatore Torrisi
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Ernst, M., Hale, E.A., Balderston, N., Torrisi, S. (2015). Introduction to Functional Brain Connectivity: Potential Contributions to Understanding Adolescent Vulnerability to Substance Abuse. In: Ewing, S.W.F., Witkiewitz, K., Filbey, F.M. (eds) Neuroimaging and Psychosocial Addiction Treatment. Palgrave Macmillan, London. https://doi.org/10.1057/9781137362650_12
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DOI: https://doi.org/10.1057/9781137362650_12
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