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Conduct disorder symptomatology is associated with an altered functional connectome in a large national youth sample

Published online by Cambridge University Press:  14 April 2021

Scott Tillem Open the ORCID record for Scott Tillem [Opens in a new window] ,
May I. Conley  and
Arielle Baskin-Sommers
Scott Tillem*
Affiliation:
Department of Psychology, Yale University, New Haven, CT, USA
May I. Conley
Affiliation:
Department of Psychology, Yale University, New Haven, CT, USA
Arielle Baskin-Sommers
Affiliation:
Department of Psychology, Yale University, New Haven, CT, USA
*
Author for Correspondence: Scott Tillem, 2 Hillhouse Ave., New Haven, CT 06511, USA. E-mail: scott.tillem@yale.edu
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Abstract

Conduct disorder (CD), characterized by youth antisocial behavior, is associated with a variety of neurocognitive impairments. However, questions remain regarding the neural underpinnings of these impairments. To investigate novel neural mechanisms that may support these neurocognitive abnormalities, the present study applied a graph analysis to resting-state functional magnetic resonance imaging (fMRI) data collected from a national sample of 4,781 youth, ages 9–10, who participated in the baseline session of the Adolescent Brain Cognitive DevelopmentSM Study (ABCD Study®). Analyses were then conducted to examine the relationships among levels of CD symptomatology, metrics of global topology, node-level metrics for subcortical structures, and performance on neurocognitive assessments. Youth higher on CD displayed higher global clustering (β = .039, 95% CIcorrected [.0027 .0771]), but lower Degreesubcortical (β = −.052, 95% CIcorrected [−.0916 −.0152]). Youth higher on CD had worse performance on a general neurocognitive assessment (β = −.104, 95% CI [−.1328 −.0763]) and an emotion recognition memory assessment (β = −.061, 95% CI [−.0919 −.0290]). Finally, global clustering mediated the relationship between CD and general neurocognitive functioning (indirect β = −.002, 95% CI [−.0044 −.0002]), and Degreesubcortical mediated the relationship between CD and emotion recognition memory performance (indirect β = −.002, 95% CI [−.0046 −.0005]). CD appears associated with neuro-topological abnormalities and these abnormalities may represent neural mechanisms supporting CD-related neurocognitive disruptions.

Keywords

conduct disordergraph analysisneural topologyneurocognitive functioningsubcortical structures
Type
Regular Article
Information
Development and Psychopathology , Volume 34 , Issue 4 , October 2022 , pp. 1573 - 1584
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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References

Achard, S., Salvador, R., Whitcher, B., Suckling, J., & Bullmore, E. D. (2006). A resilient, low-frequency, small-world human brain functional network with highly connected association cortical hubs. Journal of Neuroscience, 26, 63–72. doi:10.1523/jneurosci.3874-05.2006.CrossRefGoogle ScholarPubMed
Aghajani, M., Colins, O. F., Klapwijk, E. T., Veer, I. M., Andershed, H., Popma, A., … Vermeiren, R. R. J. M. (2016). Dissociable relations between amygdala subregional networks and psychopathy trait dimensions in conduct-disordered juvenile offenders. Human Brain Mapping, 37, 4017–4033. doi:10.1002/hbm.23292.CrossRefGoogle ScholarPubMed
Akshoomoff, N., Beaumont, J. L., Bauer, P. J., Dikmen, S. S., Gershon, R. C., Mungas, D., … Zelazo, P. D. (2013). VIII. NIH toolbox cognition battery (CB): Composite scores of crystallized, fluid, and overall cognition. Monographs of the Society for Research in Child Development, 78, 119–132. doi:10.1111/mono.12038.CrossRefGoogle ScholarPubMed
Baas, D., Aleman, A., & Kahn, R. S. (2004). Lateralization of amygdala activation: A systematic review of functional neuroimaging studies. Brain Research Reviews, 45, 96–103.CrossRefGoogle ScholarPubMed
Baker, R. H., Clanton, R. L., Rogers, J. C., & De Brito, S. A. (2015). Neuroimaging findings in disruptive behavior disorders. CNS Spectrums, 20, 369–381. doi:10.1017/s1092852914000789.CrossRefGoogle ScholarPubMed
Barch, D. M., Albaugh, M. D., Avenevoli, S., Chang, L., Clark, D. B., Glantz, M. D., … Yurgelun-Todd, D. (2018). Demographic, physical and mental health assessments in the adolescent brain and cognitive development study: Rationale and description. Developmental Cognitive Neuroscience, 32, 55–66. doi:10.1016/j.dcn.2017.10.010.CrossRefGoogle ScholarPubMed
Barch, D. M., Burgess, G. C., Harms, M. P., Petersen, S. E., Schlaggar, B. L., Corbetta, M., … Feldt, C. (2013). Function in the human connectome: Task-fMRI and individual differences in behavior. NeuroImage, 80, 169–189. doi:10.1016/j.neuroimage.2013.05.033.CrossRefGoogle ScholarPubMed
Bauer, P. J., Dikmen, S. S., Heaton, R. K., Mungas, D., Slotkin, J., & Beaumont, J. L. (2013). III. NIH toolbox cognition battery (CB): Measuring episodic memory. Monographs of the Society for Research in Child Development, 78, 34–48. doi:10.1111/mono.12033.CrossRefGoogle ScholarPubMed
Blair, J. (1995). A cognitive developmental approach to morality: Investigating the psychopath. Cognition, 57, 1–29. doi:10.1016/0010-0277(95)00676-p.CrossRefGoogle ScholarPubMed
Blair, J., Leibenluft, E., & Pine, D. S. (2014). Conduct disorder and callous–unemotional traits in youth. New England Journal of Medicine, 371, 2207–2216. doi:10.1056/nejmc1415936.CrossRefGoogle ScholarPubMed
Broulidakis, M. J., Fairchild, G., Sully, K., Blumensath, T., Darekar, A., & Sonuga-Barke, E. J. S. (2016). Reduced default mode connectivity in adolescents with conduct disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 55, 800–808. e801. doi:10.1016/j.jaac.2016.05.021.CrossRefGoogle ScholarPubMed
Brown, R. T., Jaffe, S. L., Silverstein, J., & Magee, H. (1991). Methylphenidate and hospitalized adolescents with conduct disorder: Dose effects on classroom behavior, academic performance, and impulsivity. Journal of Youth and Adolescence, 20, 501–518. doi:10.1007/bf01540634.CrossRefGoogle ScholarPubMed
Bullmore, E., & Sporns, O. (2009). Complex brain networks: Graph theoretical analysis of structural and functional systems. Nature Reviews Neuroscience, 10, 186–198. doi:10.1038/nrn2575.CrossRefGoogle ScholarPubMed
Carlozzi, N. E., Beaumont, J. L., Tulsky, D. S., & Gershon, R. C. (2015). The NIH toolbox pattern comparison processing speed test: Normative data. Archives of Clinical Neuropsychology, 30, 359–368. doi:10.1093/arclin/acv031.CrossRefGoogle ScholarPubMed
Carlozzi, N. E., Tulsky, D. S., Chiaravalloti, N. D., Beaumont, J. L., Weintraub, S., Conway, K., & Gershon, R. C. (2014). NIH toolbox cognitive battery (NIHTB-CB): The NIHTB pattern comparison processing speed test. Journal of the International Neuropsychological Society, 20, 630. doi:10.1093/arclin/acv031.CrossRefGoogle ScholarPubMed
Carlozzi, N. E., Tulsky, D. S., Kail, R. V., & Beaumont, J. L. (2013). VI. NIH toolbox cognition battery (CB): Measuring processing speed. Monographs of the Society for Research in Child Development, 78, 88–102. doi:10.1111/mono.12036.CrossRefGoogle ScholarPubMed
Casey, B. J., Cannonier, T., Conley, M. I., Cohen, A. O., Barch, D. M., Heitzeg, M. M., … Garavan, H. (2018). The adolescent brain cognitive development (ABCD) study: Imaging acquisition across 21 sites. Developmental Cognitive Neuroscience, 32, 43–54. doi:10.1016/j.dcn.2018.03.001.CrossRefGoogle ScholarPubMed
Clark, D. B., Fisher, C. B., Bookheimer, S., Brown, S. A., Evans, J. H., Hopfer, C., … Pfefferbaum, A. (2018). Biomedical ethics and clinical oversight in multisite observational neuroimaging studies with children and adolescents: The ABCD experience. Developmental Cognitive Neuroscience, 32, 143–154. doi:10.1016/j.dcn.2017.06.005.CrossRefGoogle ScholarPubMed
Cohen, A. O., Breiner, K., Steinberg, L., Bonnie, R. J., Scott, E. S., Taylor-Thompson, K., … Heller, A. S. (2016). When is an adolescent an adult? Assessing cognitive control in emotional and nonemotional contexts. Psychological Science, 27, 549–562. doi:10.1177/0956797615627625.CrossRefGoogle ScholarPubMed
Cohn, M. D., Pape, L. E., Schmaal, L., van den Brink, W., van Wingen, G., Vermeiren, R. R., … Popma, A. (2015). Differential relations between juvenile psychopathic traits and resting state network connectivity. Human Brain Mapping, 36, 2396–2405. doi:10.1002/hbm.22779.CrossRefGoogle ScholarPubMed
Dick, A. S., Watts, A. L., Heeringa, S. G., Lopez, D. A., Bartsch, H., Fan, C. C., … Haist, F. (2020). Meaningful effects in the adolescent brain cognitive development study. bioRxiv. doi:10.1101/2020.09.01.276451.Google Scholar
Dikmen, S. S., Bauer, P. J., Weintraub, S., Mungas, D., Slotkin, J., Beaumont, J. L., … Heaton, R. K. (2014). Measuring episodic memory across the lifespan: NIH toolbox picture sequence memory test. Journal of the International Neuropsychological Society, 20, 611. doi:10.1017/s1355617714000460.CrossRefGoogle ScholarPubMed
Dotterer, H. L., Waller, R., Hein, T. C., Pardon, A., Mitchell, C., Lopez-Duran, N., … Hyde, L. W. (2020). Clarifying the link between amygdala functioning during emotion processing and antisocial behaviors versus callous-unemotional traits within a population-based community sample. Clinical Psychological Science, 20, 918–935. doi:10.1177/2167702620922829.CrossRefGoogle Scholar
Eichenbaum, H. (2001). The hippocampus and declarative memory: Cognitive mechanisms and neural codes. Behavioural Brain Research, 127, 199–207. doi:10.1016/s0166-4328(01)00365-5.CrossRefGoogle ScholarPubMed
Estrada, S., Tillem, S., Stuppy-Sullivan, A., & Baskin-Sommers, A. (2019). Specifying the connection between reward processing and antisocial psychopathology across development: Review, integration, and future directions. In Gruber, J. (Ed.), Oxford handbook of positive emotion and psychopathology (pp. 312–332). New York, NY: Oxford University Press. doi:10.1093/oxfordhb/9780190653200.013.21.Google Scholar
Fairchild, G., van Goozen, S. H. M., Stollery, S. J., Aitken, M. R. F., Savage, J., Moore, S. C., & Goodyer, I. M. (2009). Decision making and executive function in male adolescents with early-onset or adolescence-onset conduct disorder and control subjects. Biological Psychiatry, 66, 162–168. doi:10.1016/j.biopsych.2009.02.024.CrossRefGoogle ScholarPubMed
Fan, J., McCandliss, B. D., Sommer, T., Raz, A., & Posner, M. I. (2002). Testing the efficiency and independence of attentional networks. Journal of Cognitive Neuroscience, 14, 340–347. doi:10.1162/089892902317361886.CrossRefGoogle ScholarPubMed
Finger, E. C., Marsh, A., Blair, K. S., Majestic, C., Evangelou, I., Gupta, K., … Blair, R. J. (2012). Impaired functional but preserved structural connectivity in limbic white matter tracts in youth with conduct disorder or oppositional defiant disorder plus psychopathic traits. Psychiatry Research, 202, 239–244. doi:10.1016/j.pscychresns.2011.11.002.CrossRefGoogle ScholarPubMed
Freches, G. B., Haak, K. V., Bryant, K. L., Schurz, M., Beckmann, C. F., & Mars, R. B. (2020). Principles of temporal association cortex organisation as revealed by connectivity gradients. Brain Structure and Function, 1–16. doi:10.1007/s00429-020-02047-0.Google Scholar
Frick, P. J. (2012). Developmental pathways to conduct disorder: Implications for future directions in research, assessment, and treatment. Journal of Clinical Child & Adolescent Psychology, 41, 378–389. doi:10.1080/15374416.2012.664815.CrossRefGoogle Scholar
Garavan, H., Bartsch, H., Conway, K., Decastro, A., Goldstein, R. Z., Heeringa, S., … Zahs, D. (2018). Recruiting the ABCD sample: Design considerations and procedures. Developmental Cognitive Neuroscience, 32, 16–22. doi:10.1016/j.dcn.2018.04.004.CrossRefGoogle ScholarPubMed
Gershon, R. C., Cook, K. F., Mungas, D., Manly, J. J., Slotkin, J., Beaumont, J. L., & Weintraub, S. (2014). Language measures of the NIH toolbox cognition battery. Journal of the International Neuropsychological Society, 20, 642–651. doi:10.1017/s1355617714000411.CrossRefGoogle ScholarPubMed
Gershon, R. C., Slotkin, J., Manly, J. J., Blitz, D. L., Beaumont, J. L., Schnipke, D., … Hirsh-Pasek, K. (2013). IV. NIH toolbox cognition battery (CB): Measuring language (vocabulary comprehension and reading decoding). Monographs of the Society for Research in Child Development, 78, 49–69. doi:10.1111/mono.12034.CrossRefGoogle Scholar
Gershon, R. C., Wagster, M. V., Hendrie, H. C., Fox, N. A., Cook, K. F., & Nowinski, C. J. (2013). NIH toolbox for assessment of neurological and behavioral function. Neurology, 80, S2–S6. doi:10.1212/wnl.0b013e3182872e5f.CrossRefGoogle ScholarPubMed
Ginestet, C. E., Nichols, T. E., Bullmore, T., & Simmons, A. (2011). Brain network analysis: Separating cost from topology using cost-integration. PLoS One, 6, doi:10.1371/journal.pone.0021570.CrossRefGoogle ScholarPubMed
Gonzalez, G. F., Van der Molen, M. J., Zaric, G., Bonte, M., Tijms, J., Blomert, L., … Van der Molen, M. W. (2016). Graph analysis of EEG resting state functional networks in dyslexic readers. Clinical Neurophysiology, 127, 3165–3175. doi:10.1016/j.clinph.2017.09.106.CrossRefGoogle Scholar
Gordon, E. M., Laumann, T. O., Adeyemo, B., Huckins, J. F., Kelley, W. M., & Petersen, S. E. (2016). Generation and evaluation of a cortical area parcellation from resting-state correlations. Cerebral Cortex, 26, 288–303. doi:10.1093/cercor/bhu239.CrossRefGoogle ScholarPubMed
Graziano, P. A., Landis, T., Maharaj, A., Ros-Demarize, R., Hart, K. C., & Garcia, A. (2019). Differentiating preschool children with conduct problems and callous-unemotional behaviors through emotion regulation and executive functioning. Journal of Clinical Child & Adolescent Psychology, 1–13. doi:10.1080/15374416.2019.1666399.Google ScholarPubMed
Hadley, J. A., Kraguljac, N. V., White, D. M., Ver Hoef, L., Tabora, J., & Lahti, A. C. (2016). Change in brain network topology as a function of treatment response in schizophrenia: A longitudinal resting-state fMRI study using graph theory. Schizophrenia, 2, 1–7. doi:10.1038/npjschz.2016.14.CrossRefGoogle ScholarPubMed
Hagler, D. J., Hatton, S., Cornejo, M. D., Makowski, C., Fair, D. A., Dick, A., … Dale, A. M. (2019). Image processing and analysis methods for the adolescent brain cognitive development study. NeuroImage, 202, 116091. doi:10.1016/j.neuroimage.2019.116091.CrossRefGoogle ScholarPubMed
Haney-Caron, E., Caprihan, A., & Stevens, M. C. (2014). DTI-measured white matter abnormalities in adolescents with conduct disorder. Journal of Psychiatric Research, 48, 111–120. doi:10.1016/j.jpsychires.2013.09.015.CrossRefGoogle ScholarPubMed
Hawes, S. W., Waller, R., Thompson, W. K., Hyde, L. W., Byrd, A. L., Burt, S. A., … Gonzalez, R. (2020). Assessing callous-unemotional traits: Development of a brief, reliable measure in a large and diverse sample of preadolescent youth. Psychological Medicine, 50, 456–464. doi:10.1017/S0033291719000278.CrossRefGoogle Scholar
Hayes, A. F. (2013). The PROCESS macro for SPSS and SAS (version 2.15) [Software]. Retrieved from http://www.processmacro.org/index.htmlGoogle Scholar
Hobson, C. W., Scott, S., & Rubia, K. (2011). Investigation of cool and hot executive function in ODD/CD independently of ADHD. Journal of Child Psychology and Psychiatry, 52, 1035–1043. doi:10.1111/j.1469-7610.2011.02454.x.CrossRefGoogle ScholarPubMed
Hosseini, S. M. H., Hoeft, F., & Kesler, S. R. (2012). GAT: A graph-theoretical analysis toolbox for analyzing between-group differences in large-scale structural and functional brain networks. PLoS One, 7, doi:10.1371/journal.pone.0040709.CrossRefGoogle ScholarPubMed
Iacono, W. G., Heath, A. C., Hewitt, J. K., Neale, M. C., Banich, M. T., Luciana, M. M., … Bjork, J. M. (2018). The utility of twins in developmental cognitive neuroscience research: How twins strengthen the ABCD research design. Developmental Cognitive Neuroscience, 32, 30–42. doi:10.1016/j.dcn.2017.09.001.CrossRefGoogle ScholarPubMed
Jiang, Y., Liu, W., Ming, Q., Gao, Y., Ma, R., Zhang, X., … Huang, B. (2016). Disrupted topological patterns of large-scale network in conduct disorder. Scientific Reports, 6, 37053. doi:10.1038/srep37053.CrossRefGoogle ScholarPubMed
Kaufman, J., Birmaher, B., Axelson, D., Perepletchikova, F., Brent, D., & Ryan, N. (2013). Kiddie Schedule for Affective Disorders and Schizophrenia Present and Lifetime Version 2013 (K-SADS-PL). Pittsburgh, PA: Western Psychiatric Institute and Yale University.Google Scholar
Keightley, M. L., Chiew, K. S., Anderson, J. A. E., & Grady, C. L. (2011). Neural correlates of recognition memory for emotional faces and scenes. Social Cognitive and Affective Neuroscience, 6, 24–37. doi:10.1093/scan/nsq003.CrossRefGoogle ScholarPubMed
Knutson, B., & Cooper, J. C. (2005). Functional magnetic resonance imaging of reward prediction. Current Opinion in Neurology, 18, 411–417. doi:10.1097/01.wco.0000173463.24758.f6.CrossRefGoogle ScholarPubMed
Kruskal, J. B. (1956). On the shortest spanning subtree of a graph and the traveling salesman problem. Proceedings of the American Mathematical Society, 7, 48–50. doi:10.1090/s0002-9939-1956-0078686-7.CrossRefGoogle Scholar
Langer, N., Pedroni, A., Gianotti, L. R. R., Hänggi, J., Knoch, D., & Jäncke, L. (2012). Functional brain network efficiency predicts intelligence. Human Brain Mapping, 33, 1393–1406. doi:10.1002/hbm.21297.CrossRefGoogle ScholarPubMed
Liao, X., Vasilakos, A. V., & He, Y. (2017). Small-world human brain networks: Perspectives and challenges. Neuroscience & Biobehavioral Reviews, 77, 286–300. doi:10.1016/j.neubiorev.2017.03.018.CrossRefGoogle ScholarPubMed
Lindner, P., Flodin, P., Budhiraja, M., Savic, I., Jokinen, J., Tiihonen, J., & Hodgins, S. (2018). Associations of psychopathic traits with local and global brain network topology in young adult women. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 3, 1003–1012. doi:10.1016/j.bpsc.2018.04.010.Google ScholarPubMed
Liu, Y., Liang, M., Zhou, Y., He, Y., Hao, Y., Song, M., … Jiang, T. (2008). Disrupted small-world networks in schizophrenia. Brain, 131, 945–961. doi:10.1016/j.neuroimage.2011.09.035.CrossRefGoogle Scholar
Lu, F. M., Zhou, J. S., Zhang, J., Wang, X. P., & Yuan, Z. (2017). Disrupted small-world brain network topology in pure conduct disorder. Oncotarget, 8, 65506. doi:10.18632/oncotarget.19098.CrossRefGoogle ScholarPubMed
Lu, F. M., Zhou, J. S., Zhang, J., Xiang, Y. T., Zhang, J., Liu, Q., … Yuan, Z. (2015). Functional connectivity estimated from resting-state fMRI reveals selective alterations in male adolescents with pure conduct disorder. PLoS One, 10, e0145668. doi:10.1371/journal.pone.0145668.CrossRefGoogle ScholarPubMed
Luciana, M., Bjork, J. M., Nagel, B. J., Barch, D. M., Gonzalez, R., Nixon, S. J., & Banich, M. T. (2018). Adolescent neurocognitive development and impacts of substance use: Overview of the adolescent brain cognitive development (ABCD) baseline neurocognition battery. Developmental Cognitive Neuroscience, 32, 67–79. doi:10.1016/j.dcn.2018.02.006.CrossRefGoogle ScholarPubMed
Menks, W. M., Furger, R., Lenz, C., Fehlbaum, L. V., Stadler, C., & Raschle, N. M. (2017). Microstructural white matter alterations in the corpus callosum of girls with conduct disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 56, 258–265. doi:10.1016/j.jaac.2016.12.006.CrossRefGoogle ScholarPubMed
Merikangas, K. R., He, J. P., Burstein, M., Swanson, S. A., Avenevoli, S., Cui, L., … Swendsen, J. (2010). Lifetime prevalence of mental disorders in US adolescents: Results from the national comorbidity survey replication–adolescent supplement (NCS-A). Journal of the American Academy of Child & Adolescent Psychiatry, 49, 980–989. doi:10.1016/j.jaac.2010.05.017.CrossRefGoogle Scholar
Moffitt, T. E. (1993). The neuropsychology of conduct disorder. Development and Psychopathology, 5, 135–151. doi:10.1017/S0954579400004302.CrossRefGoogle Scholar
Moffitt, T. E. (2006). Life-course-persistent versus adolescence-limited antisocial behavior. In Cicchetti, D. & Cohen, D. J. (Eds.), Developmental psychopathology: Risk, disorder, and adaptation (pp. 570–598). John Wiley & Sons, Inc.Google Scholar
Morgan, A. B., & Lilienfeld, S. O. (2000). A meta-analytic review of the relation between antisocial behavior and neuropsychological measures of executive function. Clinical Psychology Review, 20, 113–136. doi:10.1016/S0272-7358(98)00096-8.CrossRefGoogle ScholarPubMed
Neubauer, A. C., & Fink, A. (2009). Intelligence and neural efficiency. Neuroscience & Biobehavioral Reviews, 33, 1004–1023. doi:10.1016/j.neubiorev.2009.04.001.CrossRefGoogle ScholarPubMed
Nigg, J. T., & Huang-Pollock, C. L. (2003). An early-onset model of the role of executive functions and intelligence in conduct disorder/delinquency. In Lahey, B. B., Moffitt, T. E. & Caspi, A. (Eds.), Causes of conduct disorder and juvenile delinquency (pp. 227–253). The Guildford Press.Google Scholar
Noordermeer, S. D. S., Luman, M., & Oosterlaan, J. (2016). A systematic review and meta-analysis of neuroimaging in oppositional defiant disorder (ODD) and conduct disorder (CD) taking attention-deficit hyperactivity disorder (ADHD) into account. Neuropsychology Review, 26, 44–72. doi:10.1007/s11065-015-9315-8.CrossRefGoogle ScholarPubMed
Offord, D. R., & Bennett, K. J. (1994). Conduct disorder: Long-term outcomes and intervention effectiveness. Journal of the American Academy of Child & Adolescent Psychiatry, 33, 1069–1078. doi:10.1097/00004583-199410000-00001.CrossRefGoogle ScholarPubMed
Ogilvie, J. M., Stewart, A. L., Chan, R. C. K., & Shum, D. H. K. (2011). Neuropsychological measures of executive function and antisocial behavior: A meta-analysis. Criminology, 49, 1063–1107. doi:10.1111/j.1745-9125.2011.00252.x.CrossRefGoogle Scholar
Passamonti, L., Fairchild, G., Fornito, A., Goodyer, I. M., Nimmo-Smith, I., Hagan, C. C., & Calder, A. J. (2012). Abnormal anatomical connectivity between the amygdala and orbitofrontal cortex in conduct disorder. PLoS One, 7, e48789. doi:10.1371/journal.pone.0048789.CrossRefGoogle ScholarPubMed
Rogers, J. C., & De Brito, S. A. (2016). Cortical and subcortical gray matter volume in youths with conduct problems: A meta-analysis. JAMA Psychiatry, 73, 64–72. doi:10.1001/jamapsychiatry.2015.2423.CrossRefGoogle ScholarPubMed
Rubinov, M., & Sporns, O. (2010). Complex network measures of brain connectivity: Uses and interpretations. NeuroImage, 52, 1059–1069. doi:10.1016/j.neuroimage.2009.10.003.CrossRefGoogle ScholarPubMed
Sarkar, S., Craig, M. C., Catani, M., Dell'Acqua, F., Fahy, T., Deeley, Q., & Murphy, D. G. M. (2013). Frontotemporal white-matter microstructural abnormalities in adolescents with conduct disorder: A diffusion tensor imaging study. Psychological Medicine, 43, 401. doi:10.1017/S003329171200116X.CrossRefGoogle ScholarPubMed
Schoonheim, M. M., Geurts, J. J. G., Wiebenga, O. T., De Munck, J. C., Polman, C. H., Stam, C. J., … Wink, A. M. (2014). Changes in functional network centrality underlie cognitive dysfunction and physical disability in multiple sclerosis. Multiple Sclerosis Journal, 20, 1058–1065. doi:10.1177/1352458513516892.CrossRefGoogle ScholarPubMed
Schoorl, J., van Rijn, S., de Wied, M., Van Goozen, S. H., & Swaab, H. (2018). Boys with oppositional defiant disorder/conduct disorder show impaired adaptation during stress: An executive functioning study. Child Psychiatry & Human Development, 49, 298–307. doi:10.1007/s10578-017-0749-5.CrossRefGoogle ScholarPubMed
Shu, N., Duan, Y., Xia, M., Schoonheim, M. M., Huang, J., Ren, Z., … Shi, F. D. (2016). Disrupted topological organization of structural and functional brain connectomes in clinically isolated syndrome and multiple sclerosis. Scientific Reports, 6, 1–11. doi:10.1038/srep29383.CrossRefGoogle ScholarPubMed
Smit, D. J., de Geus, E. J., Boersma, M., Boomsma, D. I., & Stam, C. J. (2016). Life-span development of brain network integration assessed with phase lag index connectivity and minimum spanning tree graphs. Brain Connectivity, 6, 312–325. doi:10.1089/brain.2015.0359.CrossRefGoogle ScholarPubMed
Stam, C. J., & Reijneveld, J. C. (2007). Graph theoretical analysis of complex networks in the brain. Nonlinear Biomedical Physics, 1, 3. doi:10.1186/1753-4631-1-3.CrossRefGoogle Scholar
Suprano, I., Delon-Martin, C., Kocevar, G., Stamile, C., Hannoun, S., Achard, S., … Nusbaum, F. (2019). Topological modification of brain networks organization in children with high intelligence quotient: A resting-state fMRI study. Frontiers in Human Neuroscience, 13, 241. doi:10.3389/fnhum.2019.00241.CrossRefGoogle ScholarPubMed
Teichner, G., & Golden, C. J. (2000). The relationship of neuropsychological impairment to conduct disorder in adolescence: A conceptual review. Aggression and Violent Behavior, 5, 509–528. doi:10.1016/S1359-1789(98)00035-4.CrossRefGoogle Scholar
Tewarie, P., Hillebrand, A., Schoonheim, M. M., van Dijk, B. W., Geurts, J., Barkhof, F., … Stam, C. J. (2014). Functional brain network analysis using minimum spanning trees in multiple sclerosis: An MEG source-space study. NeuroImage, 88, 308–318. doi:10.1016/j.neuroimage.2013.10.022.CrossRefGoogle ScholarPubMed
Tillem, S., Harenski, K., Harenski, C., Decety, J., Kosson, D., Kiehl, K. A., & Baskin-Sommers, A. (2019). Psychopathy is associated with shifts in the organization of neural networks in a large incarcerated male sample. NeuroImage: Clinical, 24, 102083. doi:10.1016/j.nicl.2019.102083.CrossRefGoogle Scholar
Tillem, S., van Dongen, J., Brazil, I. A., & Baskin-Sommers, A. (2018). Psychopathic traits are differentially associated with efficiency of neural communication. Psychophysiology, 55, e13194. doi:10.1111/psyp.13194.CrossRefGoogle ScholarPubMed
Tulsky, D. S., Carlozzi, N., Chiaravalloti, N. D., Beaumont, J. L., Kisala, P. A., Mungas, D., … Gershon, R. C. (2014). NIH toolbox cognition battery (NIHTB-CB): The list sorting test to measure working memory. Journal of the International Neuropsychological Society, 20, 599. doi:10.1017/S135561771400040X.CrossRefGoogle ScholarPubMed
van den Heuvel, M. P., Mandl, R. C. W., Stam, C. J., Kahn, R. S., & Hulshoff Pol, H. E. (2010). Aberrant frontal and temporal complex network structure in schizophrenia: A graph theoretical analysis. Journal of Neuroscience, 30, 15915–15926. doi:10.1523/JNEUROSCI.2874-10.2010.CrossRefGoogle ScholarPubMed
Viding, E., & Jones, A. P. (2008). Cognition to genes via the brain in the study of conduct disorder. Quarterly Journal of Experimental Psychology, 61, 171–181. doi:10.1080/17470210701508889.CrossRefGoogle Scholar
Viding, E., Sebastian, C. L., Dadds, M. R., Lockwood, P. L., Cecil, C. A. M., De Brito, S. A., & McCrory, E. J. (2012). Amygdala response to preattentive masked fear in children with conduct problems: The role of callous-unemotional traits. American Journal of Psychiatry, 169, 1109–1116. doi:10.1176/appi.ajp.2012.12020191.CrossRefGoogle ScholarPubMed
Waller, R., Hawes, S. W., Byrd, A. L., Dick, A. S., Sutherland, M. T., Riedel, M. C., … Gonzalez, R. (2020). Disruptive behavior problems, callous-unemotional traits, and regional gray matter volume in the ABCD study. Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 5, 470–472. doi:10.1016/j.bpsc.2020.01.002.Google Scholar
Wang, J., Wang, L., Zang, Y., Yang, H., Tang, H., Gong, Q., … He, Y. (2009). Parcellation-dependent small-world brain functional networks: A resting-state fMRI study. Human Brain Mapping, 30, 1511–1523. doi:10.1002/hbm.20623.CrossRefGoogle ScholarPubMed
Woolfenden, S. R., Williams, K., & Peat, J. K. (2002). Family and parenting interventions for conduct disorder and delinquency: A meta-analysis of randomised controlled trials. Archives of Disease in Childhood, 86, 251–256. doi:10.1136/adc.86.4.251.CrossRefGoogle ScholarPubMed
Zelazo, P. D. (2006). The dimensional change card sort (DCCS): A method of assessing executive function in children. Nature Protocols, 1, 297–301. doi:10.1038/nprot.2006.46.CrossRefGoogle ScholarPubMed
Zhang, J., Zhu, X., Wang, X., Gao, J., Shi, H., Huang, B., … Yao, S. (2014). Increased structural connectivity in corpus callosum in adolescent males with conduct disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 53, 466–475. e461. doi:10.1016/j.jaac.2013.12.015.CrossRefGoogle ScholarPubMed
Zhou, J., Yao, N., Fairchild, G., Cao, X., Zhang, Y., Xiang, Y. T., … Wang, X. (2016). Disrupted default mode network connectivity in male adolescents with conduct disorder. Brain Imaging and Behavior, 10, 995–1003. doi:10.1007/s11682-015-9465-6.CrossRefGoogle ScholarPubMed
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