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

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Abstract

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.

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References

  • 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 

  • 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.

    PubMed  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • Alexander, A. L., et al. (2007a). Diffusion tensor imaging of the corpus callosum in autism. Neuroimage, 34(1), 61–73.

    PubMed  Google Scholar 

  • Alexander, A. L., et al. (2007b). Diffusion tensor imaging of the brain. Neurotherapeutics, 4(3), 316–329.

    PubMed  PubMed Central  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • Andersson, J.L.R., et al. (2007a). Non-linear optimisation. FMRIB technical report TR07JA1. FMRIB Centre, Oxford, UK.

  • Andersson, J.L.R., et al. (2007b). Non-linear registration, aka spatial normalization. FMRIB Analysis Group Technical Reports. TR07JA2. FMRIB Centre, Oxford, UK.

  • 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.

    CAS  PubMed  Google Scholar 

  • Asato, M. R., et al. (2010). White matter development in adolescence: a DTI study. Cerebral Cortex, 20(9), 2122–2131.

    CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • 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.

    CAS  PubMed  Google Scholar 

  • Bava, S., et al. (2010). Longitudinal characterization of white matter maturation during adolescence. Brain Research, 1327, 38–46.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Beaulieu, C. (2002). The basis of anisotropic water diffusion in the nervous system - a technical review. NMR in Biomedicine, 15(7–8), 435–455.

    PubMed  Google Scholar 

  • 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.

  • 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.

    PubMed  Google Scholar 

  • Bernal, B., & Altman, N. (2010). The connectivity of the superior longitudinal fasciculus: a tractography DTI study. Magnetic Resonance Imaging, 28(2), 217–225.

    PubMed  Google Scholar 

  • Beyer, J. L., et al. (2005). Cortical white matter microstructural abnormalities in bipolar disorder. Neuropsychopharmacology, 30(12), 2225–2229.

    PubMed  Google Scholar 

  • Bonekamp, D., et al. (2007). Diffusion tensor imaging in children and adolescents: reproducibility, hemispheric, and age-related differences. Neuroimage, 34(2), 733–742.

    PubMed  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • Corbetta, M., & Shulman, G. L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Reviews. Neuroscience, 3(3), 201–215.

    CAS  PubMed  Google Scholar 

  • 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.

    PubMed  PubMed Central  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • Dirks, A. (2017). Treatment of the suicidal adolescent: a critical analysis of the cognitive-behavioral approach. Acta Psychopathologica, 3(4):38.

  • 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.

    Google Scholar 

  • Dolcos, F., & McCarthy, G. (2006). Brain systems mediating cognitive interference by emotional distraction. The Journal of Neuroscience, 26(7), 2072–2079.

    CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • 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.

    Google Scholar 

  • Fields, R. D. (2008). White matter in learning, cognition and psychiatric disorders. Trends in Neurosciences, 31(7), 361–370.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Filley, C. M. (2005a). Neurobehavioral aspects of cerebral white matter disorders. The Psychiatric Clinics of North America, 28(3), 685–700 697-688.

    PubMed  Google Scholar 

  • Filley, C. M. (2005b). White matter and behavioral neurology. Annals of the New York Academy of Sciences, 1064, 162–183.

    PubMed  Google Scholar 

  • Filley, C. M. (2011). White matter: beyond focal disconnection. Neurologic Clinics, 29(1), 81–97 viii.

    PubMed  Google Scholar 

  • Fletcher, P. T., et al. (2010). Microstructural connectivity of the arcuate fasciculus in adolescents with high-functioning autism. Neuroimage, 51(3), 1117–1125.

    PubMed  Google Scholar 

  • 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.

    CAS  PubMed  Google Scholar 

  • Frazier, J. A., et al. (2007). White matter abnormalities in children with and at risk for bipolar disorder. Bipolar Disorders, 9(8), 799–809.

    PubMed  Google Scholar 

  • Fuhrmann, D., et al. (2015). Adolescence as a sensitive period of brain development. Trends in Cognitive Sciences, 19(10), 558–566.

    PubMed  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • 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.

    CAS  PubMed  PubMed Central  Google Scholar 

  • 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. https://doi.org/10.1176/ajp.151.5.665.

    Article  CAS  PubMed  Google Scholar 

  • Gilliam, M., et al. (2011). Developmental trajectories of the corpus callosum in attention-deficit/hyperactivity disorder. Biological Psychiatry, 69(9), 839–846.

    PubMed  PubMed Central  Google Scholar 

  • Giorgio, A., et al. (2008). Changes in white matter microstructure during adolescence. Neuroimage, 39(1), 52–61.

    CAS  PubMed  Google Scholar 

  • Greenberg, L. M. (2011). The test of variable of attention (version 8.0). Los Alamitos: The TOVA Company.

    Google Scholar 

  • Heron, M. (2013). Deaths: leading causes for 2010. National Vital Statistics Reports, 62(6), 1–96.

    PubMed  Google Scholar 

  • Hiatt, K. D., & Newman, J. P. (2007). Behavioral evidence of prolonged interhemispheric transfer time among psychopathic offenders. Neuropsychology, 21(3), 313–318.

    PubMed  PubMed Central  Google Scholar 

  • 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.

    CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • Hopfinger, J. B., et al. (2000). The neural mechanisms of top-down attentional control. Nature Neuroscience, 3(3), 284–291.

    CAS  PubMed  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • 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.

    CAS  PubMed  Google Scholar 

  • 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.

    CAS  PubMed  PubMed Central  Google Scholar 

  • Jenkinson, M., & Smith, S. (2001). A global optimisation method for robust affine registration of brain images. Medical Image Analysis, 5(2), 143–156.

    CAS  PubMed  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • Jensen, P. S., et al. (2006). Toward a new diagnositc system for child psychopathology. New York: The Guildford Press.

    Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    CAS  PubMed  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • Kim, S. J., et al. (2006). Asymmetrically altered integrity of cingulum bundle in posttraumatic stress disorder. Neuropsychobiology, 54(2), 120–125.

    PubMed  Google Scholar 

  • Le Bihan, D., et al. (2006). Artifacts and pitfalls in diffusion MRI. Journal of Magnetic Resonance Imaging, 24(3), 478–488.

    PubMed  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • Leark, R. A., et al. (2007). Test of variables of attention: Professional manual. The TOVA Company: Los Alamitos.

    Google Scholar 

  • Lebel, C., & Deoni, S. (2018). The development of brain white matter microstructure. Neuroimage. 182, 207-218.

  • Lebel, C., et al. (2008). Microstructural maturation of the human brain from childhood to adulthood. Neuroimage, 40(3), 1044–1055.

    CAS  PubMed  Google Scholar 

  • 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.

  • Lopez, K. C., et al. (2013). Quantitative morphology of the corpus callosum in obsessive-compulsive disorder. Psychiatry Research, 212(1), 1–6.

    PubMed  PubMed Central  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • Luna, B., et al. (2004). Maturation of cognitive processes from late childhood to adulthood. Child Development, 75(5), 1357–1372.

    PubMed  Google Scholar 

  • 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.

    Google Scholar 

  • Mah, A., et al. (2017). Detailing neuroanatomical development in late childhood and early adolescence using NODDI. PLoS One, 12(8), e0182340.

    PubMed  PubMed Central  Google Scholar 

  • Marrus, N., et al. (2014). Psychotropic medications and their effect on brain volumes in childhood psychopathology. Child & Adolescent Psychopharmacology News, 19(2), 1–8.

    Google Scholar 

  • 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.

    Google Scholar 

  • 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.

    CAS  PubMed  Google Scholar 

  • Mori, S., et al. (2008). Stereotaxic white matter atlas based on diffusion tensor imaging in an ICBM template. Neuroimage, 40(2), 570–582.

    PubMed  Google Scholar 

  • Moscicki, E. K. (2001). Epidemiology of completed and attempted suicide: toward a framework for prevention. Clinical Neuroscience Research, 1(5), 310–323.

    Google Scholar 

  • Mukherjee, P., et al. (2001). Normal brain maturation during childhood: developmental trends characterized with diffusion-tensor MR imaging. Radiology, 221(2), 349–358.

    CAS  PubMed  Google Scholar 

  • 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.

    CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • Olson, I. R., et al. (2015). Development of the uncinate fasciculus: implications for theory and developmental disorders. Developmental Cognitive Neuroscience, 14, 50–61.

    PubMed  PubMed Central  Google Scholar 

  • Pardoe, H. R., et al. (2016). Motion and morphometry in clinical and nonclinical populations. Neuroimage, 135, 177–185.

    PubMed  Google Scholar 

  • 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.

    CAS  PubMed  Google Scholar 

  • Paus, T. (2005). Mapping brain maturation and cognitive development during adolescence. Trends in Cognitive Sciences, 9(2), 60–68.

    PubMed  Google Scholar 

  • Paus, T., et al. (1999). Structural maturation of neural pathways in children and adolescents: in vivo study. Science, 283(5409), 1908–1911.

    CAS  PubMed  Google Scholar 

  • Petersen, S. E., & Posner, M. I. (2012). The attention system of the human brain: 20 years after. Annual Review of Neuroscience, 35, 73–89.

    CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    CAS  PubMed  Google Scholar 

  • 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.

    CAS  PubMed  Google Scholar 

  • Phillips, M. L., et al. (2003). Neurobiology of emotion perception I: the neural basis of normal emotion perception. Biological Psychiatry, 54(5), 504–514.

    PubMed  Google Scholar 

  • 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.

    CAS  PubMed  Google Scholar 

  • Powell, H. W., et al. (2006). Hemispheric asymmetries in language-related pathways: a combined functional MRI and tractography study. Neuroimage, 32(1), 388–399.

    PubMed  Google Scholar 

  • 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 

  • 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.

    PubMed  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • 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.

    CAS  PubMed  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • 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.

    PubMed  PubMed Central  Google Scholar 

  • 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.

  • 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. https://doi.org/10.1162/jocn_a_00206.

    Article  PubMed  PubMed Central  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • 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.

    CAS  PubMed  Google Scholar 

  • 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.

    PubMed  PubMed Central  Google Scholar 

  • Smith, S. M. (2002). Fast robust automated brain extraction. Human Brain Mapping, 17(3), 143–155.

    PubMed  PubMed Central  Google Scholar 

  • Soares, J. M., et al. (2013). A hitchhiker’s guide to diffusion tensor imaging. Frontiers in Neuroscience, 7, 31.

    PubMed  PubMed Central  Google Scholar 

  • Song, S. K., et al. (2002). Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water. Neuroimage, 17(3), 1429–1436.

    PubMed  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • Song, S. K., et al. (2005). Demyelination increases radial diffusivity in corpus callosum of mouse brain. Neuroimage, 26(1), 132–140.

    PubMed  Google Scholar 

  • Spear, L. P. (2000). The adolescent brain and age-related behavioral manifestations. Neuroscience and Biobehavioral Reviews, 24(4), 417–463.

    CAS  PubMed  Google Scholar 

  • Steinberg, L. (2004). Risk taking in adolescence: what changes, and why? Annals of the New York Academy of Sciences, 1021, 51–58.

    PubMed  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • Szeszko, P. R., et al. (2014). White matter changes associated with antipsychotic treatment in first-episode psychosis. Neuropsychopharmacology, 39(6), 1324–1331.

    CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    PubMed  PubMed Central  Google Scholar 

  • Thiebaut de Schotten, M., et al. (2011). A lateralized brain network for visuospatial attention. Nature Neuroscience, 14(10), 1245–1246.

    CAS  PubMed  Google Scholar 

  • Treit, S., et al. (2014). White matter correlates of cognitive inhibition during development: a diffusion tensor imaging study. Neuroscience, 276, 87–97.

    CAS  PubMed  Google Scholar 

  • 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.

    CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • Von Der Heide, R. J., et al. (2013). Dissecting the uncinate fasciculus: disorders, controversies and a hypothesis. Brain, 136(Pt 6), 1692–1707.

    Google Scholar 

  • Wakana, S., et al. (2004). Fiber tract-based atlas of human white matter anatomy. Radiology, 230(1), 77–87.

    PubMed  Google Scholar 

  • Wakana, S., et al. (2007). Reproducibility of quantitative tractography methods applied to cerebral white matter. Neuroimage, 36(3), 630–644.

    PubMed  Google Scholar 

  • Wang, L., et al. (2005). Amygdala activation to sad pictures during high-field (4 tesla) functional magnetic resonance imaging. Emotion, 5(1), 12–22.

    CAS  PubMed  Google Scholar 

  • Wang, L., et al. (2008). Prefrontal mechanisms for executive control over emotional distraction are altered in major depression. Psychiatry Research, 163(2), 143–155.

    PubMed  PubMed Central  Google Scholar 

  • Wang, X., et al. (2016). Subcomponents and connectivity of the superior longitudinal fasciculus in the human brain. Brain Structure & Function, 221(4), 2075–2092.

    Google Scholar 

  • Winkler, A. M., et al. (2014). Permutation inference for the general linear model. Neuroimage, 92, 381–397.

    PubMed  Google Scholar 

  • Xiong, J., et al. (1995). Clustered pixels analysis for functional MRI activation studies of the human brain. Human Brain Mapping, 3(4), 287–301.

    Google Scholar 

  • 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.

    CAS  PubMed  PubMed Central  Google Scholar 

  • 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.

    PubMed  Google Scholar 

  • Zhou, Z., et al. (2012). The risk behaviors and mental health of detained adolescents: a controlled, prospective longitudinal study. PLoS One, 7(5), e37199.

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgments

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.

Funding

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.

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Authors and Affiliations

  1. Laboratory of Behavioral Neuroscience, National Institute on Aging, Baltimore, MD, USA

    Andrea T. Shafer

  2. Department of Psychiatry, University of Alberta, Edmonton, AB, Canada

    James R. Benoit, Matthew R. G. Brown, Andy J. Greenshaw, Sunita Vohra & Florin Dolcos

  3. Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada

    Andy J. Greenshaw, Florin Dolcos & Anthony Singhal

  4. Department of Educational Psychology, University of Alberta, Edmonton, AB, Canada

    K. Jessica Van Vliet

  5. Departments of Pediatrics and Medicine, University of Alberta, Edmonton, AB, Canada

    Sunita Vohra

  6. Psychology Department and Neuroscience Program, University of Illinois, Urbana-Champaign, IL, USA

    Florin Dolcos

  7. Beckman Institute for Advanced Science & Technology, University of Illinois, Urbana-Champaign, IL, USA

    Florin Dolcos

  8. Department of Psychology, University of Alberta, Edmonton, AB, Canada

    Anthony Singhal

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  1. Andrea T. Shafer
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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.

Corresponding authors

Correspondence to Andrea T. Shafer or Anthony Singhal.

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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.

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Andrea T. Shafer and James R. Benoit Shared first authorship.

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Shafer, A.T., Benoit, J.R., Brown, M.R.G. et al. Differences in attentional control and white matter microstructure in adolescents with attentional, affective, and behavioral disorders. Brain Imaging and Behavior 14, 599–614 (2020). https://doi.org/10.1007/s11682-019-00211-7

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