Differences in attentional control and white matter microstructure in adolescents with attentional, affective, and behavioral disorders

  • Andrea T. ShaferEmail author
  • James R. Benoit
  • Matthew R. G. Brown
  • Andy J. Greenshaw
  • K. Jessica Van Vliet
  • Sunita Vohra
  • Florin Dolcos
  • Anthony SinghalEmail author
Original Research


Adolescence is a critical time of physiological, cognitive, and social development. It is also a time of increased risk-taking and vulnerability for psychopathology. White matter (WM) changes during adolescence have been better elucidated in the last decade, but how WM is impacted by psychopathology during this time remains unclear. Here, we examined the link between WM microstructure and psychopathology during adolescence. Twenty youth diagnosed with affective, attentional, and behavioral disorders (clinical sample), and 20 age-matched controls were recruited to examine group differences in WM microstructure, attentional control, and the link between them. The main results showed that clinical sample had relatively lower attentional control and fractional anisotropy (FA) in WM throughout the brain: two association tracts were identified, and many differences were found in areas rich in callosal and projection fibers. Moreover, increased FA was positively associated with attention performance in the clinical sample in structures supporting ventral WM pathways, whereas a similar link was identified in controls in dorsal WM association fibers. Overall, these results support a model of general impairment in WM microstructure combined with reliance on altered, perhaps less efficient, pathways for attentional control in youth with affective, attentional, and behavioral disorders.


DTI Imaging ADHD Emotion Adolescent Cognition Mental health 



During the preparation of this manuscript, A.T.S. was supported by the Intramural Research Program, National Institute on Aging, National Institutes of Health (NIH). F.D. was supported by a Helen Corley Petit Scholarship in Liberal Arts and Sciences and an Emanuel Donchin Professorial Scholarship in Psychology from the University of Illinois. The authors wish to thank Denise Adams, Dylan Lampan, and Gerald Trach for assistance with data collection, and Matt Moore and Yifan Hu for assistance with data analyses. The authors thank Cindy Clark, NIH Library Writing Center, for manuscript editing assistance.

Authors’ contributions

FD, AS, SV, and KJVV designed the study; ATS collected the data; ATS and JRB constructed the preprocessing pipeline; ATS, AS, and FD contributed to the analytical approach, with input from JRB; ATS performed the analyses; ATS, AS, and FD wrote the manuscript. All authors provided feedback and approved the content of the article.


This research was supported by an Emerging Team Grant from the Faculty of Medicine and Dentistry at the University Alberta (RES0002614), and by funding from the Lotte & John Hecht Memorial Foundation (RES0006762) awarded to S.V., J. VV., F.D., and A.S.

Compliance and ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

“All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.”

Informed consent

Informed consent was obtained from the parents of all individual adolescent participants included in the study, and informed assent was obtained from all adolescents included in the study.

Supplementary material

11682_2019_211_MOESM1_ESM.docx (175 kb)
ESM 1 (DOCX 175 kb)


  1. Abdi, H. (2003). Least squares. In M. Lewis-Beck, A. Bryman, & T. Futing (Eds.), Encyclopedia of social sciences research methods. Thousand Oaks: Sage.Google Scholar
  2. Abe, O., et al. (2006). Voxel-based diffusion tensor analysis reveals aberrant anterior cingulum integrity in posttraumatic stress disorder due to terrorism. Psychiatry Research, 146(3), 231–242.PubMedCrossRefPubMedCentralGoogle Scholar
  3. Adler, C. M., et al. (2004). Abnormal frontal white matter tracts in bipolar disorder: a diffusion tensor imaging study. Bipolar Disorders, 6(3), 197–203.PubMedCrossRefPubMedCentralGoogle Scholar
  4. Alexander, A. L., et al. (2007a). Diffusion tensor imaging of the corpus callosum in autism. Neuroimage, 34(1), 61–73.PubMedCrossRefPubMedCentralGoogle Scholar
  5. Alexander, A. L., et al. (2007b). Diffusion tensor imaging of the brain. Neurotherapeutics, 4(3), 316–329.PubMedPubMedCentralCrossRefGoogle Scholar
  6. Alexopoulos, G. S., et al. (2002). Frontal white matter microstructure and treatment response of late-life depression: a preliminary study. The American Journal of Psychiatry, 159(11), 1929–1932.PubMedCrossRefPubMedCentralGoogle Scholar
  7. Andersson, J.L.R., et al. (2007a). Non-linear optimisation. FMRIB technical report TR07JA1. FMRIB Centre, Oxford, UK.Google Scholar
  8. Andersson, J.L.R., et al. (2007b). Non-linear registration, aka spatial normalization. FMRIB Analysis Group Technical Reports. TR07JA2. FMRIB Centre, Oxford, UK.Google Scholar
  9. Arshad, M., et al. (2016). Adult age differences in subcortical myelin content are consistent with protracted myelination and unrelated to diffusion tensor imaging indices. Neuroimage, 143, 26–39.PubMedPubMedCentralCrossRefGoogle Scholar
  10. Asato, M. R., et al. (2010). White matter development in adolescence: a DTI study. Cerebral Cortex, 20(9), 2122–2131.PubMedCrossRefPubMedCentralGoogle Scholar
  11. Bae, J. N., et al. (2006). Dorsolateral prefrontal cortex and anterior cingulate cortex white matter alterations in late-life depression. Biological Psychiatry, 60(12), 1356–1363.PubMedCrossRefPubMedCentralGoogle Scholar
  12. Barnea-Goraly, N., et al. (2005). White matter development during childhood and adolescence: a cross-sectional diffusion tensor imaging study. Cerebral Cortex, 15(12), 1848–1854.PubMedCrossRefPubMedCentralGoogle Scholar
  13. Basser, P. J., & Pierpaoli, C. (1996). Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. Journal of Magnetic Resonance. Series B, 111(3), 209–219.PubMedCrossRefPubMedCentralGoogle Scholar
  14. Bava, S., et al. (2010). Longitudinal characterization of white matter maturation during adolescence. Brain Research, 1327, 38–46.PubMedPubMedCentralCrossRefGoogle Scholar
  15. Beaulieu, C. (2002). The basis of anisotropic water diffusion in the nervous system - a technical review. NMR in Biomedicine, 15(7–8), 435–455.PubMedCrossRefPubMedCentralGoogle Scholar
  16. Beaulieu, C. (2013). Chapter 8 - the biological basis of diffusion anisotropy. Diffusion MRI: from quantitative measurements to in vivo Neuroanatomy (2nd ed.).  London, UK: Academic Press.Google Scholar
  17. Ben Bashat, D., et al. (2005). Normal white matter development from infancy to adulthood: comparing diffusion tensor and high b value diffusion weighted MR images. Journal of Magnetic Resonance Imaging, 21(5), 503–511.PubMedCrossRefPubMedCentralGoogle Scholar
  18. Bernal, B., & Altman, N. (2010). The connectivity of the superior longitudinal fasciculus: a tractography DTI study. Magnetic Resonance Imaging, 28(2), 217–225.PubMedCrossRefPubMedCentralGoogle Scholar
  19. Beyer, J. L., et al. (2005). Cortical white matter microstructural abnormalities in bipolar disorder. Neuropsychopharmacology, 30(12), 2225–2229.PubMedCrossRefPubMedCentralGoogle Scholar
  20. Bonekamp, D., et al. (2007). Diffusion tensor imaging in children and adolescents: reproducibility, hemispheric, and age-related differences. Neuroimage, 34(2), 733–742.PubMedCrossRefPubMedCentralGoogle Scholar
  21. Cannistraro, P. A., et al. (2007). A diffusion tensor imaging study of white matter in obsessive-compulsive disorder. Depression and Anxiety, 24(6), 440–446.PubMedCrossRefPubMedCentralGoogle Scholar
  22. Chiang, H. L., et al. (2015). Altered white matter tract property related to impaired focused attention, sustained attention, cognitive impulsivity and vigilance in attention-deficit/ hyperactivity disorder. Journal of Psychiatry & Neuroscience, 40(5), 325–335.CrossRefGoogle Scholar
  23. Chiang, H. L., et al. (2016). Different neural substrates for executive functions in youths with ADHD: a diffusion spectrum imaging tractography study. Psychological Medicine, 46(6), 1225–1238.PubMedCrossRefPubMedCentralGoogle Scholar
  24. Corbetta, M., & Shulman, G. L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews. Neuroscience, 3(3), 201–215.PubMedCrossRefPubMedCentralGoogle Scholar
  25. Couvy-Duchesne, B., et al. (2016). Head motion and inattention/hyperactivity share common genetic influences: implications for fMRI studies of ADHD. PLoS One, 11(1), e0146271.PubMedPubMedCentralCrossRefGoogle Scholar
  26. Deoni, S. C., et al. (2012). Investigating white matter development in infancy and early childhood using myelin water faction and relaxation time mapping. Neuroimage, 63(3), 1038–1053.PubMedPubMedCentralCrossRefGoogle Scholar
  27. Dirks, A. (2017). Treatment of the suicidal adolescent: a critical analysis of the cognitive-behavioral approach. Acta Psychopathologica, 3(4):38.Google Scholar
  28. Diwadkar, V. A., et al. (2006). Genetically predisposed offspring with schizotypal features: an ultra high-risk group for schizophrenia? Progress in Neuro-Psychopharmacology & Biological Psychiatry, 30(2), 230–238.CrossRefGoogle Scholar
  29. Dolcos, F., & McCarthy, G. (2006). Brain systems mediating cognitive interference by emotional distraction. The Journal of Neuroscience, 26(7), 2072–2079.PubMedPubMedCentralCrossRefGoogle Scholar
  30. Dolcos, F., et al. (2008). Opposing influences of emotional and non-emotional distracters upon sustained prefrontal cortex activity during a delayed-response working memory task. Neuropsychologia, 46(1), 326–335.PubMedCrossRefGoogle Scholar
  31. Dolcos, F., et al. (2011). Neural correlates of emotion-cognition interactions: a review of evidence from brain imaging investigations. Journal of Cognitive Psychology (Hove, England), 23(6), 669–694.CrossRefGoogle Scholar
  32. Fields, R. D. (2008). White matter in learning, cognition and psychiatric disorders. Trends in Neurosciences, 31(7), 361–370.PubMedPubMedCentralCrossRefGoogle Scholar
  33. Filley, C. M. (2005a). Neurobehavioral aspects of cerebral white matter disorders. The Psychiatric Clinics of North America, 28(3), 685–700 697-688.PubMedCrossRefGoogle Scholar
  34. Filley, C. M. (2005b). White matter and behavioral neurology. Annals of the New York Academy of Sciences, 1064, 162–183.PubMedCrossRefPubMedCentralGoogle Scholar
  35. Filley, C. M. (2011). White matter: beyond focal disconnection. Neurologic Clinics, 29(1), 81–97 viii.PubMedCrossRefPubMedCentralGoogle Scholar
  36. Fletcher, P. T., et al. (2010). Microstructural connectivity of the arcuate fasciculus in adolescents with high-functioning autism. Neuroimage, 51(3), 1117–1125.PubMedPubMedCentralCrossRefGoogle Scholar
  37. Forman, S. D., et al. (1995). Improved assessment of significant activation in functional magnetic resonance imaging (fMRI): use of a cluster-size threshold. Magnetic Resonance in Medicine, 33(5), 636–647.PubMedCrossRefPubMedCentralGoogle Scholar
  38. Frazier, J. A., et al. (2007). White matter abnormalities in children with and at risk for bipolar disorder. Bipolar Disorders, 9(8), 799–809.PubMedCrossRefPubMedCentralGoogle Scholar
  39. Fuhrmann, D., et al. (2015). Adolescence as a sensitive period of brain development. Trends in Cognitive Sciences, 19(10), 558–566.PubMedCrossRefPubMedCentralGoogle Scholar
  40. Gabard-Durnam, L. J., et al. (2014). The development of human amygdala functional connectivity at rest from 4 to 23 years: a cross-sectional study. Neuroimage, 95, 193–207.PubMedPubMedCentralCrossRefGoogle Scholar
  41. Gee, D. G., et al. (2013). A developmental shift from positive to negative connectivity in human amygdala-prefrontal circuitry. The Journal of Neuroscience, 33(10), 4584–4593.PubMedPubMedCentralCrossRefGoogle Scholar
  42. Giedd, J. N., et al. (1994). Quantitative morphology of the corpus callosum in attention deficit hyperactivity disorder. The American Journal of Psychiatry, 151(5), 665–669. Scholar
  43. Gilliam, M., et al. (2011). Developmental trajectories of the corpus callosum in attention-deficit/hyperactivity disorder. Biological Psychiatry, 69(9), 839–846.PubMedPubMedCentralCrossRefGoogle Scholar
  44. Giorgio, A., et al. (2008). Changes in white matter microstructure during adolescence. Neuroimage, 39(1), 52–61.PubMedCrossRefPubMedCentralGoogle Scholar
  45. Greenberg, L. M. (2011). The test of variable of attention (version 8.0). Los Alamitos: The TOVA Company.Google Scholar
  46. Heron, M. (2013). Deaths: leading causes for 2010. National Vital Statistics Reports, 62(6), 1–96.PubMedPubMedCentralGoogle Scholar
  47. Hiatt, K. D., & Newman, J. P. (2007). Behavioral evidence of prolonged interhemispheric transfer time among psychopathic offenders. Neuropsychology, 21(3), 313–318.PubMedPubMedCentralCrossRefGoogle Scholar
  48. Hoeft, F., et al. (2007). More is not always better: increased fractional anisotropy of superior longitudinal fasciculus associated with poor visuospatial abilities in Williams syndrome. The Journal of Neuroscience, 27(44), 11960–11965.PubMedPubMedCentralCrossRefGoogle Scholar
  49. Hofer, S., & Frahm, J. (2006). Topography of the human corpus callosum revisited--comprehensive fiber tractography using diffusion tensor magnetic resonance imaging. Neuroimage, 32(3), 989–994.PubMedCrossRefGoogle Scholar
  50. Hopfinger, J. B., et al. (2000). The neural mechanisms of top-down attentional control. Nature Neuroscience, 3(3), 284–291.PubMedCrossRefPubMedCentralGoogle Scholar
  51. Hua, K., et al. (2008). Tract probability maps in stereotaxic spaces: analyses of white matter anatomy and tract-specific quantification. Neuroimage, 39(1), 336–347.PubMedCrossRefPubMedCentralGoogle Scholar
  52. Hynd, G. W., et al. (1991). Corpus callosum morphology in attention deficit-hyperactivity disorder: morphometric analysis of MRI. Journal of Learning Disabilities, 24(3), 141–146.PubMedCrossRefPubMedCentralGoogle Scholar
  53. Iordan, A. D., et al. (2013). Neural signatures of the response to emotional distraction: a review of evidence from brain imaging investigations. Frontiers in Human Neuroscience, 7, 200.PubMedPubMedCentralCrossRefGoogle Scholar
  54. Jenkinson, M., & Smith, S. (2001). A global optimisation method for robust affine registration of brain images. Medical Image Analysis, 5(2), 143–156.PubMedCrossRefPubMedCentralGoogle Scholar
  55. Jenkinson, M., et al. (2002). Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage, 17(2), 825–841.PubMedCrossRefPubMedCentralGoogle Scholar
  56. Jensen, P. S., et al. (2006). Toward a new diagnositc system for child psychopathology. New York: The Guildford Press.Google Scholar
  57. Jones, D. K., et al. (2013). White matter integrity, fiber count, and other fallacies: the do’s and don’ts of diffusion MRI. Neuroimage, 73, 239–254.CrossRefGoogle Scholar
  58. Kaess, M., et al. (2014). Risk-behaviour screening for identifying adolescents with mental health problems in Europe. European Child & Adolescent Psychiatry, 23(7), 611–620.CrossRefGoogle Scholar
  59. Kamali, A., et al. (2014a). Tracing superior longitudinal fasciculus connectivity in the human brain using high resolution diffusion tensor tractography. Brain Structure & Function, 219(1), 269–281.CrossRefGoogle Scholar
  60. Kamali, A., et al. (2014b). Decoding the superior parietal lobule connections of the superior longitudinal fasciculus/arcuate fasciculus in the human brain. Neuroscience, 277, 577–583.PubMedCrossRefPubMedCentralGoogle Scholar
  61. Karlsgodt, K. H., et al. (2008). Diffusion tensor imaging of the superior longitudinal fasciculus and working memory in recent-onset schizophrenia. Biological Psychiatry, 63(5), 512–518.PubMedCrossRefPubMedCentralGoogle Scholar
  62. Kim, S. J., et al. (2006). Asymmetrically altered integrity of cingulum bundle in posttraumatic stress disorder. Neuropsychobiology, 54(2), 120–125.PubMedCrossRefPubMedCentralGoogle Scholar
  63. Le Bihan, D., et al. (2006). Artifacts and pitfalls in diffusion MRI. Journal of Magnetic Resonance Imaging, 24(3), 478–488.PubMedCrossRefPubMedCentralGoogle Scholar
  64. Leark, R. A., et al. (2004). Test-retest reliability and standard error of measurement for the test of variables of attention (T.O.V.A.) with healthy school-age children. Assessment, 11(4), 285–289.PubMedCrossRefPubMedCentralGoogle Scholar
  65. Leark, R. A., et al. (2007). Test of variables of attention: Professional manual. The TOVA Company: Los Alamitos.Google Scholar
  66. Lebel, C., & Deoni, S. (2018). The development of brain white matter microstructure. Neuroimage. 182, 207-218.Google Scholar
  67. Lebel, C., et al. (2008). Microstructural maturation of the human brain from childhood to adulthood. Neuroimage, 40(3), 1044–1055.PubMedCrossRefPubMedCentralGoogle Scholar
  68. Lebel C., et al. (2017) A review of diffusion MRI of typical white matter development from early childhood to young adulthood. NMR in Biomedicine 32(4):e3778.PubMedCrossRefPubMedCentralGoogle Scholar
  69. Lopez, K. C., et al. (2013). Quantitative morphology of the corpus callosum in obsessive-compulsive disorder. Psychiatry Research, 212(1), 1–6.PubMedPubMedCentralCrossRefGoogle Scholar
  70. Luna, B., & Sweeney, J. A. (2004). The emergence of collaborative brain function: FMRI studies of the development of response inhibition. Annals of the New York Academy of Sciences, 1021, 296–309.PubMedCrossRefPubMedCentralGoogle Scholar
  71. Luna, B., et al. (2004). Maturation of cognitive processes from late childhood to adulthood. Child Development, 75(5), 1357–1372.PubMedCrossRefPubMedCentralGoogle Scholar
  72. Maggs, J. L., et al. (1995). Risky Buisness: the paradoxical meaning of problem behavior for young adolescents. The Journal of Early Adolescence, 15(3), 344–362.CrossRefGoogle Scholar
  73. Mah, A., et al. (2017). Detailing neuroanatomical development in late childhood and early adolescence using NODDI. PLoS One, 12(8), e0182340.PubMedPubMedCentralCrossRefGoogle Scholar
  74. Marrus, N., et al. (2014). Psychotropic medications and their effect on brain volumes in childhood psychopathology. Child & Adolescent Psychopharmacology News, 19(2), 1–8.CrossRefGoogle Scholar
  75. Martino, J., et al. (2013). Analysis of the subcomponents and cortical terminations of the perisylvian superior longitudinal fasciculus: a fiber dissection and DTI tractography study. Brain Structure & Function, 218(1), 105–121.CrossRefGoogle Scholar
  76. Moeller, F. G., et al. (2005). Reduced anterior corpus callosum white matter integrity is related to increased impulsivity and reduced discriminability in cocaine-dependent subjects: diffusion tensor imaging. Neuropsychopharmacology, 30(3), 610–617.PubMedCrossRefPubMedCentralGoogle Scholar
  77. Mori, S., et al. (2008). Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template. Neuroimage, 40(2), 570–582.PubMedPubMedCentralCrossRefGoogle Scholar
  78. Moscicki, E. K. (2001). Epidemiology of completed and attempted suicide: toward a framework for prevention. Clinical Neuroscience Research, 1(5), 310–323.CrossRefGoogle Scholar
  79. Mukherjee, P., et al. (2001). Normal brain maturation during childhood: developmental trends characterized with diffusion-tensor MR imaging. Radiology, 221(2), 349–358.PubMedCrossRefPubMedCentralGoogle Scholar
  80. Nagae, L. M., et al. (2012). Elevated mean diffusivity in the left hemisphere superior longitudinal fasciculus in autism spectrum disorders increases with more profound language impairment. AJNR. American Journal of Neuroradiology, 33(9), 1720–1725.PubMedCrossRefPubMedCentralGoogle Scholar
  81. Oh, J., et al. (2004). Mechanisms of normal appearing corpus callosum injury related to pericallosal T1 lesions in multiple sclerosis using directional diffusion tensor and 1H MRS imaging. Journal of Neurology, Neurosurgery, and Psychiatry, 75(9), 1281–1286.PubMedPubMedCentralCrossRefGoogle Scholar
  82. Oishi, K., et al. (2008). Human brain white matter atlas: identification and assignment of common anatomical structures in superficial white matter. Neuroimage, 43(3), 447–457.PubMedPubMedCentralCrossRefGoogle Scholar
  83. Olson, I. R., et al. (2015). Development of the uncinate fasciculus: implications for theory and developmental disorders. Developmental Cognitive Neuroscience, 14, 50–61.PubMedPubMedCentralCrossRefGoogle Scholar
  84. Pardoe, H. R., et al. (2016). Motion and morphometry in clinical and nonclinical populations. Neuroimage, 135, 177–185.PubMedCrossRefPubMedCentralGoogle Scholar
  85. Paul, L. K., et al. (2007). Agenesis of the corpus callosum: genetic, developmental and functional aspects of connectivity. Nature Reviews. Neuroscience, 8(4), 287–299.PubMedCrossRefPubMedCentralGoogle Scholar
  86. Paus, T. (2005). Mapping brain maturation and cognitive development during adolescence. Trends in Cognitive Sciences, 9(2), 60–68.PubMedCrossRefPubMedCentralGoogle Scholar
  87. Paus, T., et al. (1999). Structural maturation of neural pathways in children and adolescents: in vivo study. Science, 283(5409), 1908–1911.PubMedCrossRefPubMedCentralGoogle Scholar
  88. Petersen, S. E., & Posner, M. I. (2012). The attention system of the human brain: 20 years after. Annual Review of Neuroscience, 35, 73–89.PubMedPubMedCentralCrossRefGoogle Scholar
  89. Petrides, M., & Pandya, D. N. (1984). Projections to the frontal cortex from the posterior parietal region in the rhesus monkey. The Journal of Comparative Neurology, 228(1), 105–116.PubMedCrossRefPubMedCentralGoogle Scholar
  90. Petrides, M., & Pandya, D. N. (1988). Association fiber pathways to the frontal cortex from the superior temporal region in the rhesus monkey. The Journal of Comparative Neurology, 273(1), 52–66.PubMedCrossRefPubMedCentralGoogle Scholar
  91. Phillips, M. L., et al. (2003). Neurobiology of emotion perception I: the neural basis of normal emotion perception. Biological Psychiatry, 54(5), 504–514.PubMedCrossRefPubMedCentralGoogle Scholar
  92. Pierpaoli, C., et al. (2001). Water diffusion changes in Wallerian degeneration and their dependence on white matter architecture. Neuroimage, 13(6 Pt 1), 1174–1185.PubMedCrossRefPubMedCentralGoogle Scholar
  93. Powell, H. W., et al. (2006). Hemispheric asymmetries in language-related pathways: a combined functional MRI and tractography study. Neuroimage, 32(1), 388–399.PubMedCrossRefPubMedCentralGoogle Scholar
  94. Price, J. M., & Zwolinski, J. (2010). The nature of child and adolescent vulnerability: History and definitions. In R. E. Ingram & J. M. Price (Eds.), Vulnerability to Psychopathology: Risk across the lifespan (pp. 18–38). New York: Guilford Press.Google Scholar
  95. Price, G., et al. (2008). White matter tracts in first-episode psychosis: a DTI tractography study of the uncinate fasciculus. Neuroimage, 39(3), 949–955.PubMedPubMedCentralCrossRefGoogle Scholar
  96. Putnam, M. C., et al. (2010). Cortical projection topography of the human splenium: hemispheric asymmetry and individual differences. Journal of Cognitive Neuroscience, 22(8), 1662–1669.PubMedCrossRefPubMedCentralGoogle Scholar
  97. Rose, J., et al. (2014). Brain microstructural development at near-term age in very-low-birth-weight preterm infants: an atlas-based diffusion imaging study. Neuroimage, 86, 244–256.PubMedCrossRefPubMedCentralGoogle Scholar
  98. Rosso, I. M., et al. (2004). Cognitive and emotional components of frontal lobe functioning in childhood and adolescence. Annals of the New York Academy of Sciences, 1021, 355–362.PubMedCrossRefPubMedCentralGoogle Scholar
  99. Rueckert, D., et al. (1999). Nonrigid registration using free-form deformations: application to breast MR images. IEEE Transactions on Medical Imaging, 18(8), 712–721.PubMedCrossRefPubMedCentralGoogle Scholar
  100. Rusch, N., et al. (2007). Inferior frontal white matter microstructure and patterns of psychopathology in women with borderline personality disorder and comorbid attention-deficit hyperactivity disorder. Neuroimage, 35(2), 738–747.PubMedCrossRefPubMedCentralGoogle Scholar
  101. Sauder, C. L., et al. (2012). Neuroanatomical correlates of heterotypic comorbidity in externalizing male adolescents. Journal of Clinical Child and Adolescent Psychology, 41(3), 346–352.PubMedCrossRefPubMedCentralGoogle Scholar
  102. Schmithorst, V. J., et al. (2002). Correlation of white matter diffusivity and anisotropy with age during childhood and adolescence: a cross-sectional diffusion-tensor MR imaging study. Radiology, 222(1), 212–218.PubMedPubMedCentralCrossRefGoogle Scholar
  103. Schrantee, A., et al. (2016). Age-dependent effects of methylphenidate on the human dopaminergic system in young vs adult patients with attention-deficit/hyperactivity disorder: a randomized clinical trial. JAMA Psychiatry, 73(9), 955–962.PubMedPubMedCentralCrossRefGoogle Scholar
  104. Shafer, A., & Dolcos, F. (2010). Functional MRI investigation of the role of processing load, emotional content, distraction time, and individual differences in the impact of distraction on a visual perceptual task. Paper presented at the fourth annual meeting of the Social and Affective Neuroscience Society, Chicago, IL.Google Scholar
  105. Shafer, A. T., et al. (2012). Processing of emotional distraction is both automatic and modulated by attention: evidence from an event-related fMRI investigation. Journal of Cognitive Neuroscience, 24(5), 1233–1252. Scholar
  106. Sheehan, D. V., et al. (1998). The Mini-International Neuropsychiatric Interview (M.I.N.I.): the development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. The Journal of Clinical Psychiatry, 59(Suppl 20), 22–33 quiz 34-57.PubMedPubMedCentralGoogle Scholar
  107. Sheehan, D. V., et al. (2010). Reliability and validity of the mini international neuropsychiatric interview for children and adolescents (MINI-KID). The Journal of Clinical Psychiatry, 71(3), 313–326.PubMedCrossRefPubMedCentralGoogle Scholar
  108. Shinoura, N., et al. (2009). Damage to the right superior longitudinal fasciculus in the inferior parietal lobe plays a role in spatial neglect. Neuropsychologia, 47(12), 2600–2603.PubMedCrossRefPubMedCentralGoogle Scholar
  109. Singhal, A., et al. (2012). Electrophysiological correlates of fearful and sad distraction on target processing in adolescents with attention deficit-hyperactivity symptoms and affective disorders. Frontiers in Integrative Neuroscience, 6, 119.PubMedPubMedCentralCrossRefGoogle Scholar
  110. Smith, S. M. (2002). Fast robust automated brain extraction. Human Brain Mapping, 17(3), 143–155.PubMedCrossRefPubMedCentralGoogle Scholar
  111. Soares, J. M., et al. (2013). A hitchhiker’s guide to diffusion tensor imaging. Frontiers in Neuroscience, 7, 31.PubMedPubMedCentralCrossRefGoogle Scholar
  112. Song, S. K., et al. (2002). Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water. Neuroimage, 17(3), 1429–1436.PubMedCrossRefPubMedCentralGoogle Scholar
  113. Song, S. K., et al. (2003). Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia. Neuroimage, 20(3), 1714–1722.PubMedCrossRefGoogle Scholar
  114. Song, S. K., et al. (2005). Demyelination increases radial diffusivity in corpus callosum of mouse brain. Neuroimage, 26(1), 132–140.PubMedCrossRefGoogle Scholar
  115. Spear, L. P. (2000). The adolescent brain and age-related behavioral manifestations. Neuroscience and Biobehavioral Reviews, 24(4), 417–463.PubMedCrossRefPubMedCentralGoogle Scholar
  116. Steinberg, L. (2004). Risk taking in adolescence: what changes, and why? Annals of the New York Academy of Sciences, 1021, 51–58.PubMedCrossRefGoogle Scholar
  117. Szeszko, P. R., et al. (2005). White matter abnormalities in obsessive-compulsive disorder: a diffusion tensor imaging study. Archives of General Psychiatry, 62(7), 782–790.PubMedCrossRefPubMedCentralGoogle Scholar
  118. Szeszko, P. R., et al. (2014). White matter changes associated with antipsychotic treatment in first-episode psychosis. Neuropsychopharmacology, 39(6), 1324–1331.PubMedPubMedCentralCrossRefGoogle Scholar
  119. Taoka, T., et al. (2009). Fractional anisotropy--threshold dependence in tract-based diffusion tensor analysis: evaluation of the uncinate fasciculus in Alzheimer disease. AJNR. American Journal of Neuroradiology, 30(9), 1700–1703.PubMedCrossRefPubMedCentralGoogle Scholar
  120. Taylor, W. D., et al. (2007). Structural integrity of the uncinate fasciculus in geriatric depression: relationship with age of onset. Neuropsychiatric Disease and Treatment, 3(5), 669–674.PubMedPubMedCentralGoogle Scholar
  121. Thiebaut de Schotten, M., et al. (2011). A lateralized brain network for visuospatial attention. Nature Neuroscience, 14(10), 1245–1246.PubMedCrossRefPubMedCentralGoogle Scholar
  122. Treit, S., et al. (2014). White matter correlates of cognitive inhibition during development: a diffusion tensor imaging study. Neuroscience, 276, 87–97.PubMedCrossRefPubMedCentralGoogle Scholar
  123. Urry, H. L., et al. (2006). Amygdala and ventromedial prefrontal cortex are inversely coupled during regulation of negative affect and predict the diurnal pattern of cortisol secretion among older adults. The Journal of Neuroscience, 26(16), 4415–4425.PubMedPubMedCentralCrossRefGoogle Scholar
  124. Van Vliet, K. J., et al. (2017). Impact of a mindfulness-based stress reduction program frmo the perspective of adolescents with serious mental health concerns. Child and Adolescent Mental Health, 22(1), 16–22.CrossRefGoogle Scholar
  125. Vestergaard, M., et al. (2011). White matter microstructure in superior longitudinal fasciculus associated with spatial working memory performance in children. Journal of Cognitive Neuroscience, 23(9), 2135–2146.PubMedCrossRefPubMedCentralGoogle Scholar
  126. Von Der Heide, R. J., et al. (2013). Dissecting the uncinate fasciculus: disorders, controversies and a hypothesis. Brain, 136(Pt 6), 1692–1707.CrossRefGoogle Scholar
  127. Wakana, S., et al. (2004). Fiber tract-based atlas of human white matter anatomy. Radiology, 230(1), 77–87.PubMedCrossRefPubMedCentralGoogle Scholar
  128. Wakana, S., et al. (2007). Reproducibility of quantitative tractography methods applied to cerebral white matter. Neuroimage, 36(3), 630–644.PubMedPubMedCentralCrossRefGoogle Scholar
  129. Wang, L., et al. (2005). Amygdala activation to sad pictures during high-field (4 tesla) functional magnetic resonance imaging. Emotion, 5(1), 12–22.PubMedCrossRefPubMedCentralGoogle Scholar
  130. Wang, L., et al. (2008). Prefrontal mechanisms for executive control over emotional distraction are altered in major depression. Psychiatry Research, 163(2), 143–155.PubMedPubMedCentralCrossRefGoogle Scholar
  131. Wang, X., et al. (2016). Subcomponents and connectivity of the superior longitudinal fasciculus in the human brain. Brain Structure & Function, 221(4), 2075–2092.CrossRefGoogle Scholar
  132. Winkler, A. M., et al. (2014). Permutation inference for the general linear model. Neuroimage, 92, 381–397.PubMedPubMedCentralCrossRefGoogle Scholar
  133. Xiong, J., et al. (1995). Clustered pixels analysis for functional MRI activation studies of the human brain. Human Brain Mapping, 3(4), 287–301.CrossRefGoogle Scholar
  134. Yamasaki, H., et al. (2002). Dissociable prefrontal brain systems for attention and emotion. Proceedings of the National Academy of Sciences of the United States of America, 99(17), 11447–11451.PubMedPubMedCentralCrossRefGoogle Scholar
  135. Zhang, J., et al. (2007). Evidence of slow maturation of the superior longitudinal fasciculus in early childhood by diffusion tensor imaging. Neuroimage, 38(2), 239–247.PubMedPubMedCentralCrossRefGoogle Scholar
  136. Zhou, Z., et al. (2012). The risk behaviors and mental health of detained adolescents: a controlled, prospective longitudinal study. PLoS One, 7(5), e37199.PubMedPubMedCentralCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Laboratory of Behavioral NeuroscienceNational Institute on AgingBaltimoreUSA
  2. 2.Department of PsychiatryUniversity of AlbertaEdmontonCanada
  3. 3.Neuroscience and Mental Health InstituteUniversity of AlbertaEdmontonCanada
  4. 4.Department of Educational PsychologyUniversity of AlbertaEdmontonCanada
  5. 5.Departments of Pediatrics and MedicineUniversity of AlbertaEdmontonCanada
  6. 6.Psychology Department and Neuroscience ProgramUniversity of IllinoisUrbana-ChampaignUSA
  7. 7.Beckman Institute for Advanced Science & TechnologyUniversity of IllinoisUrbana-ChampaignUSA
  8. 8.Department of PsychologyUniversity of AlbertaEdmontonCanada

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