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Impaired attentional and socio-affective networks in subjects with antisocial behaviors: a meta-analysis of resting-state functional connectivity studies

Published online by Cambridge University Press:  27 April 2021

Jules Roger Dugré Open the ORCID record for Jules Roger Dugré [Opens in a new window]  and
Stéphane Potvin Open the ORCID record for Stéphane Potvin [Opens in a new window]
Jules Roger Dugré
Affiliation:
Research Center of the Institut Universitaire en Santé Mentale de Montréal, Montreal, Quebec, Canada Department of Psychiatry and Addictology, Faculty of Medicine, University of Montreal, Montreal, Quebec, Canada
Stéphane Potvin*
Affiliation:
Research Center of the Institut Universitaire en Santé Mentale de Montréal, Montreal, Quebec, Canada Department of Psychiatry and Addictology, Faculty of Medicine, University of Montreal, Montreal, Quebec, Canada
*
Author for correspondence: Jules Roger Dugré, E-mail: jules.dugre@umontreal.ca; Stéphane Potvin, E-mail: stephane.potvin@umontreal.ca
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Abstract

In the past decade, there has been a growing interest in examining resting-state functional connectivity deficits in subjects with conduct and antisocial personality disorder. Through meta-analyses and literature reviews, extensive work has been done to characterize their abnormalities in brain activation during a wide range of functional magnetic resonance imaging (fMRI) tasks. However, there is currently no meta-analytical evidence regarding neural connectivity patterns during resting-state fMRI. Therefore, we conducted a coordinate-based meta-analysis of resting-state fMRI studies on individuals exhibiting antisocial behaviors. Of the retrieved studies, 18 used a seed-based connectivity approach (513 cases v. 488 controls), 20 employed a non-seed-based approach (453 cases v. 460 controls) and 20 included a correlational analysis between the severity of antisocial behaviors and connectivity patterns (3462 subjects). Meta-analysis on seed-based studies revealed significant connectivity deficits in the amygdala, middle cingulate cortex, ventral posterior cingulate cortex-precuneus, ventromedial and dorsomedial prefrontal cortex, premotor cortex, and superior parietal lobule. Additionally, non-seed-based meta-analysis showed increased connectivity in the ventral posterior cingulate cortex and decreased connectivity in the parietal operculum, calcarine cortex, and cuneus. Finally, we found meta-analytical evidence for negative relationship between the severity of antisocial behaviors and connectivity with the ventromedial prefrontal cortex. Functional characterization and meta-analytical connectivity modeling indicated that these findings overlapped with socio-affective and attentional processes. This further underscores the importance of these functions in the pathophysiology of conduct and antisocial personality disorders.

Keywords

Functional connectivityantisocial behaviorsconduct disorderdefault mode networkventral attention networkdorsal attention network

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Type
Review Article
Information
Psychological Medicine , Volume 51 , Issue 8 , June 2021 , pp. 1249 - 1259
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Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

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References

American Psychiatric Association (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Association.Google Scholar
Amft, M., Bzdok, D., Laird, A. R., Fox, P. T., Schilbach, L., & Eickhoff, S. B. (2015). Definition and characterization of an extended social-affective default network. Brain Structure and Function, 220(2), 1031–1049.CrossRefGoogle ScholarPubMed
Aoki, Y., Inokuchi, R., Nakao, T., & Yamasue, H. (2013). Neural bases of antisocial behavior: A voxel-based meta-analysis. Social Cognitive and Affective Neuroscience, 9(8), 1223–1231.CrossRefGoogle ScholarPubMed
Bevilacqua, L., Hale, D., Barker, E. D., & Viner, R. (2018). Conduct problems trajectories and psychosocial outcomes: A systematic review and meta-analysis. European Child & Adolescent Psychiatry, 27(10), 1239–1260.CrossRefGoogle ScholarPubMed
Black, D. W., Gunter, T., Loveless, P., Allen, J., & Sieleni, B. (2010). Antisocial personality disorder in incarcerated offenders: Psychiatric comorbidity and quality of life. Annals of Clinical Psychiatry, 22(2), 113–120.Google ScholarPubMed
Bzdok, D., Schilbach, L., Vogeley, K., Schneider, K., Laird, A. R., Langner, R., & Eickhoff, S. B. (2012). Parsing the neural correlates of moral cognition: ALE meta-analysis on morality, theory of mind, and empathy. Brain Structure and Function, 217(4), 783–796.CrossRefGoogle ScholarPubMed
Cantor, J., Lafaille, S., Hannah, J., Kucyi, A., Soh, D., Girard, T., & Mikulis, D. (2016). Independent component analysis of resting-state functional magnetic resonance imaging in pedophiles. The Journal of Sexual Medicine, 13(10), 1546–1554.CrossRefGoogle ScholarPubMed
Cao, W., Li, C., Zhang, J., Dong, D., Sun, X., Yao, S., … Liu, J. (2019). Regional homogeneity abnormalities in early-onset and adolescent-onset conduct disorder in boys: A resting-state fMRI study. Frontiers in Human Neuroscience, 13, 26.CrossRefGoogle ScholarPubMed
Chen, C., Zhou, J., Liu, C., Witt, K., Zhang, Y., Jing, B., … Li, L. (2015). Regional homogeneity of resting-state brain abnormalities in violent juvenile offenders: A biomarker of brain immaturity? The Journal of Neuropsychiatry and Clinical Neurosciences, 27(1), 27–32.CrossRefGoogle ScholarPubMed
Cole, D. M., Smith, S. M., & Beckmann, C. F. (2010). Advances and pitfalls in the analysis and interpretation of resting-state FMRI data. Frontiers in Systems Neuroscience, 4, 8.Google ScholarPubMed
Colman, I., Murray, J., Abbott, R. A., Maughan, B., Kuh, D., Croudace, T. J., & Jones, P. B. (2009). Outcomes of conduct problems in adolescence: 40 year follow-up of national cohort. BMJ, 338, a2981.CrossRefGoogle ScholarPubMed
Corbetta, M., Patel, G., & Shulman, G. L. (2008). The reorienting system of the human brain: From environment to theory of mind. Neuron, 58(3), 306–324.CrossRefGoogle ScholarPubMed
Cortese, S., Aoki, Y. Y., Itahashi, T., Castellanos, F. X., & Eickhoff, S. B. (2020). Systematic review and meta-analysis: Resting state functional magnetic resonance imaging studies of attention-deficit/hyperactivity disorder. Journal of the American Academy of Child & Adolescent Psychiatry, 60(1), 61–75.CrossRefGoogle ScholarPubMed
Decety, J., Michalska, K. J., Akitsuki, Y., & Lahey, B. B. (2009). Atypical empathic responses in adolescents with aggressive conduct disorder: A functional MRI investigation. Biological Psychology, 80(2), 203–211. http://dx.doi.org/10.1016/j.biopsycho.2008.09.004.CrossRefGoogle ScholarPubMed
Deming, P., & Koenigs, M. (2020). Functional neural correlates of psychopathy: A meta-analysis of MRI data. Translational Psychiatry, 10(1), 1–8.CrossRefGoogle ScholarPubMed
Dong, D., Wang, Y., Chang, X., Luo, C., & Yao, D. (2018). Dysfunction of large-scale brain networks in schizophrenia: A meta-analysis of resting-state functional connectivity. Schizophrenia Bulletin, 44(1), 168–181.CrossRefGoogle ScholarPubMed
Dotterer, H. L., Hyde, L. W., Shaw, D. S., Rodgers, E. L., Forbes, E. E., & Beltz, A. M. (2020). Connections that characterize callousness: Affective features of psychopathy are associated with personalized patterns of resting-state network connectivity. NeuroImage: Clinical, 28, 102402.CrossRefGoogle ScholarPubMed
Doucet, G. E., Janiri, D., Howard, R., O'Brien, M., Andrews-Hanna, J. R., & Frangou, S. (2020). Transdiagnostic and disease-specific abnormalities in the default-mode network hubs in psychiatric disorders: A meta-analysis of resting-state functional imaging studies. European Psychiatry, 63(1), 1–7.CrossRefGoogle ScholarPubMed
Dugré, J. R., Radua, J., Carignan-Allard, M., Dumais, A., Rubia, K., & Potvin, S. (2020). Neurofunctional abnormalities in antisocial spectrum: A meta-analysis of fMRI studies on five distinct neurocognitive research domains. Neuroscience & Biobehavioral Reviews, 119, 168–183.CrossRefGoogle ScholarPubMed
Eickhoff, S. B., Laird, A. R., Grefkes, C., Wang, L. E., Zilles, K., & Fox, P. T. (2009). Coordinate-based activation likelihood estimation meta-analysis of neuroimaging data: A random-effects approach based on empirical estimates of spatial uncertainty. Human Brain Mapping, 30(9), 2907–2926.CrossRefGoogle ScholarPubMed
Eickhoff, S. B., Nichols, T. E., Laird, A. R., Hoffstaedter, F., Amunts, K., Fox, P. T., … Eickhoff, C. R. (2016). Behavior, sensitivity, and power of activation likelihood estimation characterized by massive empirical simulation. Neuroimage, 137, 70–85.CrossRefGoogle ScholarPubMed
Erskine, H. E., Norman, R. E., Ferrari, A. J., Chan, G. C., Copeland, W. E., Whiteford, H. A., & Scott, J. G. (2016). Long-term outcomes of attention-deficit/hyperactivity disorder and conduct disorder: A systematic review and meta-analysis. Journal of the American Academy of Child & Adolescent Psychiatry, 55(10), 841–850.CrossRefGoogle ScholarPubMed
Fazel, S., & Danesh, J. (2002). Serious mental disorder in 23 000 prisoners: A systematic review of 62 surveys. The Lancet, 359(9306), 545–550.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(1), 288–303.CrossRefGoogle ScholarPubMed
Gürsel, D. A., Avram, M., Sorg, C., Brandl, F., & Koch, K. (2018). Frontoparietal areas link impairments of large-scale intrinsic brain networks with aberrant fronto-striatal interactions in OCD: A meta-analysis of resting-state functional connectivity. Neuroscience & Biobehavioral Reviews, 87, 151–160.CrossRefGoogle ScholarPubMed
Hamilton, R. K., Hiatt Racer, K., & Newman, J. P. (2015). Impaired integration in psychopathy: A unified theory of psychopathic dysfunction. Psychological Review, 122(4), 770.10.1037/a0039703CrossRefGoogle ScholarPubMed
Hare, R. D. (2003). The psychopathy checklist–revised. Toronto, ON: Multi-Health Systems.Google Scholar
Janiri, D., Moser, D. A., Doucet, G. E., Luber, M. J., Rasgon, A., Lee, W. H., … Frangou, S. (2020). Shared neural phenotypes for mood and anxiety disorders: A Meta-analysis of 226 Task-Related Functional Imaging Studies. JAMA Psychiatry, 77(2), 172–179. http://dx.doi.org/10.1001/jamapsychiatry.2019.3351.CrossRefGoogle ScholarPubMed
Kaiser, R. H., Andrews-Hanna, J. R., Wager, T. D., & Pizzagalli, D. A. (2015). Large-scale network dysfunction in major depressive disorder: A meta-analysis of resting-state functional connectivity. JAMA Psychiatry, 72(6), 603–611.CrossRefGoogle ScholarPubMed
Kärgel, C., Massau, C., Weiß, S., Walter, M., Kruger, T. H., & Schiffer, B. (2015). Diminished functional connectivity on the road to child sexual abuse in pedophilia. The Journal of Sexual Medicine, 12(3), 783–795.CrossRefGoogle ScholarPubMed
Kim, H. (2014). Involvement of the dorsal and ventral attention networks in oddball stimulus processing: A meta-analysis. Human Brain Mapping, 35(5), 2265–2284.CrossRefGoogle ScholarPubMed
Kim, J. I., Kang, Y.-H., Lee, J.-M., Cha, J., Park, Y.-H., Kweon, K.-J., & Kim, B.-N. (2018). Resting-state functional magnetic resonance imaging investigation of the neural correlates of cognitive-behavioral therapy for externalizing behavior problems in adolescent bullies. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 86, 193–202.CrossRefGoogle ScholarPubMed
Langner, R., & Eickhoff, S. B. (2013). Sustaining attention to simple tasks: A meta-analytic review of the neural mechanisms of vigilant attention. Psychological Bulletin, 139(4), 870.CrossRefGoogle ScholarPubMed
Li, S., Hu, N., Zhang, W., Tao, B., Dai, J., Gong, Y., … Lui, S. (2019). Dysconnectivity of multiple brain networks in schizophrenia: A meta-analysis of resting-state functional connectivity. Frontiers in Psychiatry, 10, 482.CrossRefGoogle ScholarPubMed
Liberati, A., Altman, D. G., Tetzlaff, J., Mulrow, C., Gøtzsche, P. C., Ioannidis, J. P., … Moher, D. (2009). The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate health care interventions: Explanation and elaboration. Journal of Clinical Epidemiology, 62(10), e1–e34.10.1016/j.jclinepi.2009.06.006CrossRefGoogle ScholarPubMed
Marsh, A. A., Finger, E. C., Fowler, K. A., Jurkowitz, I. T., Schechter, J. C., Henry, H. Y., … Blair, R. (2011). Reduced amygdala–orbitofrontal connectivity during moral judgments in youths with disruptive behavior disorders and psychopathic traits. Psychiatry Research: Neuroimaging, 194(3), 279–286.CrossRefGoogle ScholarPubMed
Marsh, A. A., Finger, E. C., Mitchell, D. G., Reid, M. E., Sims, C., Kosson, D. S., … Blair, R. (2008). Reduced amygdala response to fearful expressions in children and adolescents with callous-unemotional traits and disruptive behavior disorders. American Journal of Psychiatry, 165(6), 712–720.CrossRefGoogle ScholarPubMed
McTeague, L. M., Huemer, J., Carreon, D. M., Jiang, Y., Eickhoff, S. B., & Etkin, A. (2017). Identification of common neural circuit disruptions in cognitive control across psychiatric disorders. American Journal of Psychiatry, 174(7), 676–685.CrossRefGoogle ScholarPubMed
McTeague, L. M., Rosenberg, B. M., Lopez, J. W., Carreon, D. M., Huemer, J., Jiang, Y., … Etkin, A. (2020). Identification of common neural circuit disruptions in emotional processing across psychiatric disorders. American Journal of Psychiatry, 177(5), 411–421. http://dx.doi.org/10.1176/appi.ajp.2019.18111271.CrossRefGoogle ScholarPubMed
Moffitt, T. E.. (2003). Life-course-persistent and adolescence-limited antisocial behavior: A 10-year research review and a research agenda. In Lahey, B. B., Moffitt, T. E., & Caspi, A. (Eds.), Causes of conduct disorder and juvenile delinquency (pp. 49–75). New York: The Guilford Press.Google 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). New York: John Wiley & Sons.Google Scholar
Motzkin, J. C., Newman, J. P., Kiehl, K. A., & Koenigs, M. (2011). Reduced prefrontal connectivity in psychopathy. Journal of Neuroscience, 31(48), 17348–17357.CrossRefGoogle ScholarPubMed
Müller, V. I., Cieslik, E. C., Laird, A. R., Fox, P. T., Radua, J., Mataix-Cols, D., … Turkeltaub, P. E. (2018). Ten simple rules for neuroimaging meta-analysis. Neuroscience & Biobehavioral Reviews, 84, 151–161.CrossRefGoogle ScholarPubMed
Poeppl, T. B., Donges, M. R., Mokros, A., Rupprecht, R., Fox, P. T., Laird, A. R., … Eickhoff, S. B. (2019). A view behind the mask of sanity: Meta-analysis of aberrant brain activity in psychopaths. Molecular Psychiatry, 24(3), 463.CrossRefGoogle ScholarPubMed
Pondé, M. P., Freire, A. C., & Mendonça, M. S. (2011). The prevalence of mental disorders in prisoners in the city of Salvador, Bahia, Brazil. Journal of Forensic Sciences, 56(3), 679–682.CrossRefGoogle ScholarPubMed
Pu, W., Luo, Q., Jiang, Y., Gao, Y., Ming, Q., & Yao, S. (2017). Alterations of brain functional architecture associated with psychopathic traits in male adolescents with conduct disorder. Scientific Reports, 7(1), 1–11.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(1), 64–72.CrossRefGoogle ScholarPubMed
Rottschy, C., Langner, R., Dogan, I., Reetz, K., Laird, A. R., Schulz, J. B., … Eickhoff, S. B. (2012). Modelling neural correlates of working memory: A coordinate-based meta-analysis. Neuroimage, 60(1), 830–846.CrossRefGoogle ScholarPubMed
Salimi-Khorshidi, G., Smith, S. M., Keltner, J. R., Wager, T. D., & Nichols, T. E. (2009). Meta-analysis of neuroimaging data: A comparison of image-based and coordinate-based pooling of studies. Neuroimage, 45(3), 810–823.CrossRefGoogle ScholarPubMed
Schaefer, A., Kong, R., Gordon, E. M., Laumann, T. O., Zuo, X.-N., Holmes, A. J., … Yeo, B. T. (2018). Local-global parcellation of the human cerebral cortex from intrinsic functional connectivity MRI. Cerebral Cortex, 28(9), 3095–3114.CrossRefGoogle ScholarPubMed
Siep, N., Tonnaer, F., van de Ven, V., Arntz, A., Raine, A., & Cima, M. (2019). Anger provocation increases limbic and decreases medial prefrontal cortex connectivity with the left amygdala in reactive aggressive violent offenders. Brain Imaging and Behavior, 13(5), 1311–1323.CrossRefGoogle ScholarPubMed
Sprooten, E., Rasgon, A., Goodman, M., Carlin, A., Leibu, E., Lee, W. H., … Frangou, S. (2017). Addressing reverse inference in psychiatric neuroimaging: Meta-analyses of task-related brain activation in common mental disorders. Human Brain Mapping, 38(4), 1846–1864. http://dx.doi.org/10.1002/hbm.23486.CrossRefGoogle ScholarPubMed
Sutcubasi, B., Metin, B., Kurban, M. K., Metin, Z. E., Beser, B., & Sonuga-Barke, E. (2020). Resting-state network dysconnectivity in ADHD: A system-neuroscience-based meta-analysis. The World Journal of Biological Psychiatry, 21(9), 662–672.10.1080/15622975.2020.1775889CrossRefGoogle ScholarPubMed
Sylvester, C. M., Yu, Q., Srivastava, A. B., Marek, S., Zheng, A., Alexopoulos, D., … Dierker, D. L. (2020). Individual-specific functional connectivity of the amygdala: A substrate for precision psychiatry. Proceedings of the National Academy of Sciences, 117(7), 3808–3818.CrossRefGoogle ScholarPubMed
Uddin, L. Q., Yeo, B. T., & Spreng, R. N. (2019). Towards a universal taxonomy of macro-scale functional human brain networks. Brain Topography, 32(6), 926–942.CrossRefGoogle ScholarPubMed
Umbach, R. H., & Tottenham, N. (2020). Callous-unemotional traits and reduced default mode network connectivity within a community sample of children. Development and Psychopathology. Advance online publication. DOI:10.1017/S0954579420000401.CrossRefGoogle ScholarPubMed
Vossel, S., Geng, J. J., & Fink, G. R. (2014). Dorsal and ventral attention systems: Distinct neural circuits but collaborative roles. The Neuroscientist, 20(2), 150–159.CrossRefGoogle ScholarPubMed
Wager, T. D., Jonides, J., & Reading, S. (2004). Neuroimaging studies of shifting attention: A meta-analysis. Neuroimage, 22(4), 1679–1693.CrossRefGoogle ScholarPubMed
Weathersby, F. L., King, J. B., Fox, J. C., Loret, A., & Anderson, J. S. (2019). Functional connectivity of emotional well-being: Overconnectivity between default and attentional networks is associated with attitudes of anger and aggression. Psychiatry Research: Neuroimaging, 291, 52–62.CrossRefGoogle ScholarPubMed
Xu, J., Van Dam, N. T., Feng, C., Luo, Y., Ai, H., Gu, R., & Xu, P. (2019). Anxious brain networks: A coordinate-based activation likelihood estimation meta-analysis of resting-state functional connectivity studies in anxiety. Neuroscience & Biobehavioral Reviews, 96, 21–30.CrossRefGoogle ScholarPubMed
Yeo, B. T., Krienen, F. M., Sepulcre, J., Sabuncu, M. R., Lashkari, D., Hollinshead, M., … Polimeni, J. R. (2011). The organization of the human cerebral cortex estimated by intrinsic functional connectivity. Journal of Neurophysiology, 106(3), 1125–1165.Google ScholarPubMed
Yoder, K., Harenski, C., Kiehl, K., & Decety, J. (2015). Neural networks underlying implicit and explicit moral evaluations in psychopathy. Translational Psychiatry, 5(8), e625.CrossRefGoogle ScholarPubMed
Yu-Feng, Z., Yong, H., Chao-Zhe, Z., Qing-Jiu, C., Man-Qiu, S., Meng, L., … Yu-Feng, W. (2007). Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI. Brain and Development, 29(2), 83–91.CrossRefGoogle Scholar
Zang, Y., Jiang, T., Lu, Y., He, Y., & Tian, L. (2004). Regional homogeneity approach to fMRI data analysis. Neuroimage, 22(1), 394–400.CrossRefGoogle ScholarPubMed
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