Журнал высшей нервной деятельности им. И.П. Павлова, 2020, T. 70, № 6, стр. 723-737

Resting-state networks in adolescents with poor behavior regulation. An analysis of effective cortical connectivity in eeg source space

A. V. Kurgansky 1*, D. I. Lomakin 1, R. I. Machinskaya 1

1 Institute of developmental physiology, Russian academy of education
Moscow, Russia

* E-mail: akurg@yandex.ru

Поступила в редакцию 12.09.2019
После доработки 10.12.2019
Принята к публикации 16.12.2019

Аннотация

The general direction of this study is the search for possible neurophysiological causes of deviant behavior. The specific goal of the work was to assess to what extent the effective connectivity that was estimated in the EEG source space at rest is sensitive to the non-optimal state of several most relevant resting-state networks (RSN) that are closely associated with emotional and motivational control and executive functions in adolescents. Individual records of the background EEG of two groups of adolescents 13–14 years of both sexes (24 girls and 28 boys, 52 in total): control group (30 adolescents) and group of adolescents showing signs of deviant behavior (22 adolescents) were used to assess the strength of effective (directed) connections between the nodes of three resting-state networks: the default mode network (DMN), the salience network (SN) and the central executive network (CEN). It was found that the pattern of effective connectivity between cortical regions belonging to the three CEN, SN and DMN neural networks differed in adolescents from the control group and those in the group with signs of deviant behavior. It was also found that the differences between these two groups were not the same for two sexes and were frequency-specific in nature.

Keywords: adolescence, deviant behavior, cognitive control, emotional-motivational regulation, resting-state networks, EEG source space, effective connectivity, vector autoregressive modeling

DOI: 10.31857/S0044467720060064

Список литературы

  1. Arain M., Haque M., Johal L., Mathur P., Nel W., Rais A., Sandhu R., Sharma S. Maturation of the adolescent brain. Neuropsychiatr Dis Treat. 2013. 9: 449–461.

  2. Baccala L.A., Sameshima K., Ballester G., Do Valle A.C., Timo-Iaria C. Studying the interaction between brain structures via directed coherence and Granger causality. Appl. Signal Processing. 1998. 5: 40–48.

  3. Baeken C., Marinazzo D., Van Schuerbeek P., Wu G.R., De Mey J., Luypaert R., De Raedt R. Left and right amygdala – mediofrontal cortical functional connectivity is differentially modulated by harm avoidance. PLoS One. 2014. 9 (4): e95740.

  4. Bernhardt B.C., Singer T. The neural basis of empathy. Annu Rev Neurosci. 2012. 35: 1–23.

  5. Berns G.S., Moore S., Capra C.M. Adolescent engagement in dangerous behaviors is associated with increased white matter maturity of frontal cortex. PLoS One. 2009. 4 (8): e6773.

  6. Botdorf M., Rosenbaum G.M., Patrianakos J., Steinberg L., Chein J.M. Adolescent risk-taking is predicted by individual differences in cognitive control over emotional, but not non-emotional, response conflict. Cogn Emot. 2017. 31 (5): 972–979.

  7. Bradley K.A., Colcombe S., Henderson S.E., Alonso C.M., Milham M.P., Gabbay V. Neural correlates of self-perceptions in adolescents with major depressive disorder. Dev Cogn Neurosci. 2016. 19: 87–97.

  8. Brenhouse H.C., Andersen S.L. Developmental trajectories during adolescence in males and females: a cross-species understanding of underlying brain changes. Neurosci Biobehav Rev. 2011. 35 (8): 1687–1703.

  9. Bressler S.L., Menon V. Large-scale brain networks in cognition: emerging methods and principles. Trends Cogn Sci. 2010. 14 (6): 277–290.

  10. Cai W., Chen T., Ryali S., Kochalka J., Li C.S., Menon V. Causal Interactions Within a Frontal-Cingulate-Parietal Network During Cognitive Control: Convergent Evidence from a Multisite-Multitask Investigation. Cereb Cortex. 2016. 26 (5): 2140–2153.

  11. Caouette J.D., Feldstein Ewing S.W. Four Mechanistic Models of Peer Influence on Adolescent Cannabis Use. Curr Addict Rep. 2017. 4 (2): 90–99.

  12. Casey B.J. Beyond simple models of self-control to circuit-based accounts of adolescent behavior. Annu Rev Psychol. 2015. 66: 295–319.

  13. Casey B.J., Getz S., Galvan A. The adolescent brain. Dev Rev. 2008. 28 1): 62–77.

  14. Catani M., Dell’acqua F., Thiebaut de Schotten M. A revised limbic system model for memory, emotion and behaviour. Neurosci Biobehav Rev. 2013. 37 (8): 1724–1737.

  15. Che D., Hu J., Zhen S., Yu C., Li B., Chang X., Zhang W. Dimensions of Emotional Intelligence and Online Gaming Addiction in Adolescence: The Indirect Effects of Two Facets of Perceived Stress. Front Psychol. 2017. 8: 1206.

  16. Chen A.C., Oathes D.J., Chang C., Bradley T., Zhou Z.W., Williams L.M., Glover G.H., Deisseroth K., Etkin A. Causal interactions between fronto-parietal central executive and default-mode networks in humans. Proc Natl Acad Sci U S A. 2013. 110 (49): 19944–19949.

  17. Cole M.W., Reynolds J.R., Power J.D., Repovs G., Anticevic A., Braver T.S. Multi-task connectivity reveals flexible hubs for adaptive task control. Nat Neurosci. 2013. 16 (9): 1348–1355.

  18. Cui J., Xu L., Bressler S.L., Ding M., Liang H. BSMART: A Matlab/C toolbox for analysis of multichannel neural time series. Neural Networks. 2008. 21 (8): 1094–1104.

  19. Darvas F., Pantazis D., Kucukaltun-Yildirim E., Leahy R.M. Mapping human brain function with MEG and EEG: methods and validation. Neuroimage. 2004. 23 Suppl 1: S289–299.

  20. Davey C.G., Breakspear M., Pujol J., Harrison B.J. A brain model of disturbed self-appraisal in depression. Am J Psychiatry. 2017. 174 (9): 895–903.

  21. de Lacy N., McCauley E., Kutz J.N., Calhoun V.D. Multilevel mapping of sexual dimorphism in intrinsic functional brain networks. Front Neurosci. 2019. 13: 332.

  22. Diamond A. Executive functions. Annu Rev Psychol. 2013. 64: 135–168.

  23. Ernst M., Pine D.S., Hardin M. Triadic model of the neurobiology of motivated behavior in adolescence. Psychol Med. 2006. 36 (3): 299–312.

  24. Esménio S., Soares J.M., Oliveira-Silva P., Zeidman P., Razi A., Gonçalves Ó.F., Friston K., Coutinho J. Using resting-state DMN effective connectivity to characterize the neurofunctional architecture of empathy. Sci Rep. 2019. 9: 2603.

  25. Fox M.D., Raichle M.E. Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci. 2007. 8 (9): 700–711.

  26. Franzmeier N., Göttler J., Grimmer T., Drzezga A., Áraque-Caballero M.A., Simon-Vermot L., Taylor A.N.W., Bürger K., Catak C., Janowitz D., Müller C., Duering M., Sorg C., Ewers M. Resting-state connectivity of the left frontal cortex to the default mode and dorsal attention network supports reserve in mild cognitive impairment. Front Aging Neurosci. 2017. 9: 264.

  27. Ham T., Leff A., de Boissezon X., Joffe A., Sharp D.J. Cognitive control and the salience network: an investigation of error processing and effective connectivity. J Neurosci. 2013. 33 (16): 7091–7098.

  28. Ho T.C., Connolly C.G., Henje Blom E., LeWinn K.Z., Strigo I.A., Paulus M.P., Frank G., Max J.E., Wu J., Chan M., Tapert S.F., Simmons A.N., Yang T.T. Emotion-Dependent Functional Connectivity of the Default Mode Network in Adolescent Depression. Biol Psychiatry. 2015. 78 (9): 635–646.

  29. Kogler L., Müller V.I., Seidel E.M., Boubela R., Kalcher K., Moser E., Habel U., Gur R.C., Eickhoff S.B., Derntl B. Sex differences in the functional connectivity of the amygdalae in association with cortisol. Neuroimage. 2016. 134: 410–423.

  30. Kurgansky A.V. Study of cortico-cortical functional connectivity with vector autoregressive model of multichannel EEG. Zh Vyssh Nerv Deiat Im I P Pavlova. 2010. 60(6): 740–759. < Курганский А.В. Некоторые вопросы исследования кортико-кортикальных функциональных связей с помощью векторной авторегрессионной модели многоканальной ЭЭГ. Журн. высш. нервн. деят. им. И.П. Павлова. 2010. 60 (6): 740–759.

  31. Litvak V., Mattout J., Kiebel S., Phillips C., Henson R., Kilner J., Barnes G., Oostenveld R., Daunizeau J., Flandin G., Penny W., Friston K. EEG and MEG data analysis in SPM8. Comput Intell Neurosci. 2011. 2011: 852961.

  32. Machinskaya R.I., Kurgansky A.V., Lomakin D.I. Age-related trends in functional organization of cortical parts of regulatory brain systems in adolescents: an analysis of resting-state networks in the EEG source space. Human Physiology. 2019. 45 (5): 461–473. Russian Text © The Author(s), 2019, published in Fiziologiya Cheloveka, 2019, Vol. 45, No. 5, pp. 5–19.

  33. McCormick E.M., Perino M.T., Telzer E.H. Not just social sensitivity: Adolescent neural suppression of social feedback during risk taking. Dev Cogn Neurosci. 2018. 30: 134–141.

  34. McClure S.M., Laibson D.I., Loewenstein G., Cohen J.D. Separate neural systems value immediate and delayed monetary rewards. Science. 2004. 306 (5695): 503–507.

  35. Menon V. Salience Network. In: Arthur W. Toga, editor. Brain Mapping: An Encyclopedic Reference. 2015. vol. 2. pp. 597–611. Academic Press: Elsevier.

  36. Mills K.L., Goddings A.L., Clasen L.S., Giedd J.N., Blakemore S.J. The developmental mismatch in structural brain maturation during adolescence. Dev Neurosci. 2014. 36 (3–4): 147–160.

  37. Mišić B., Betzel R.F., de Reus M.A., van den Heuvel M.P., Berman M.G., McIntosh A.R., Sporns O. Network-Level Structure-Function Relationships in Human Neocortex. Cereb Cortex. 2016. 26 (7): 3285–3296.

  38. Oldham S., Fornito A. The development of brain network hubs. Dev Cogn Neurosci. 2019. 36: 100607.

  39. Pannekoek J.N., van der Werff S.J., Meens P.H., van den Bulk B.G., Jolles D.D., Veer I.M., van Lang N.D., Rombouts S.A., van der Wee N.J., Vermeiren R.R. Aberrant resting-state functional connectivity in limbic and salience networks in treatment–naïve clinically depressed adolescents. J Child Psychol Psychiatry. 2014. 55 (12): 1317–1327.

  40. Pascual-Marqui R.D., Lehmann D., Koukkou M., Kochi K., Anderer P., Saletu B., Tanaka H., Hirata K., John E.R., Prichep L., Biscay-Lirio R., Kinoshita T. Assessing interactions in the brain with exact low-resolution electromagnetic tomography. Philos Trans A Math Phys Eng Sci. 2011. 369 (1952): 3768–3784.

  41. Pessoa L. Understanding emotion with brain networks. Curr Opin Behav Sci. 2018. 19: 19–25.

  42. Qu Y., Galvan A., Fuligni A.J., Lieberman M.D., Telzer E.H. Longitudinal Changes in Prefrontal Cortex Activation Underlie Declines in Adolescent Risk Taking. J Neurosci. 2015. 35 (32): 11308–11314.

  43. Sato J.R., Biazoli C.E. Jr., Salum G.A., Gadelha A., Crossley N., Vieira G., Zugman A., Picon F.A., Pan P.M., Hoexter M.Q., Anés M., Moura L.M., Del’Aquilla M.A., Junior E.A., Mcguire P., Rohde L.A., Miguel E.C., Bressan R.A., Jackowski A.P. Connectome hubs at resting state in children and adolescents: Reproducibility and psychopathological correlation. Dev Cogn Neurosci. 2016. 20: 2–11.

  44. Satterthwaite T.D., Wolf D.H., Roalf D.R., Ruparel K., Erus G., Vandekar S., Gennatas E.D., Elliott M.A., Smith A., Hakonarson H., Verma R., Davatzikos C., Gur R.E., Gur R.C. Linked Sex Differences in Cognition and Functional Connectivity in Youth. Cereb Cortex. 2015. 25 (9): 2383–2394.

  45. Sherman L.E., Rudie J.D., Pfeifer J.H., Masten C.L., McNealy K., Dapretto M. Development of the default mode and central executive networks across early adolescence: a longitudinal study. Dev Cogn Neurosci. 2014. 10: 148–159.

  46. Shulman E.P., Smith A.R., Silva K., Icenogle G., Duell N., Chein J., Steinberg L. The dual systems model: Review, reappraisal, and reaffirmation. Dev Cogn Neurosci. 2016. 17: 103–117.

  47. Shura R.D., Hurley R.A., Taber K.H. Insular cortex: structural and functional neuroanatomy. J Neuropsychiatry Clin Neurosci. 2014. 26 (4): 276–282.

  48. Sockeel S., Schwartz D., Pélégrini-Issac M., Benali H. Large-Scale Functional Networks Identified from Resting-State EEG Using Spatial ICA. PLoS One. 2016. 11 (1): e0146845.

  49. Solé-Padullés C., Castro-Fornieles J., de la Serna E., Calvo R., Baeza I., Moya J., Lázaro L., Rosa M., Bargalló N., Sugranyes G. Intrinsic connectivity networks from childhood to late adolescence: Effects of age and sex. Dev Cogn Neurosci. 2016. 17: 35–44.

  50. Sporns O. Graph theory methods: applications in brain networks. Dialogues Clin Neurosci. 2018. 20 (2): 111–121.

  51. Sridharan D., Levitin D.J., Menon V. A critical role for the right fronto-insular cortex in switching between central-executive and default-mode networks. Proc Natl Acad Sci U S A. 2008. 105(34): 12569–12574.

  52. Steinberg L., Chein J.M. Multiple accounts of adolescent impulsivity. Proc Natl Acad Sci U S A. 2015. 112 (29): 8807–8808.

  53. Uchida M., Biederman J., Gabrieli J.D., Micco J., de Los Angeles C., Brown A., Kenworthy T., Kagan E., Whitfield-Gabrieli S. Emotion regulation ability varies in relation to intrinsic functional brain architecture. Soc Cogn Affect Neurosci. 2015. 10 (12): 1738–1748.

  54. Uddin L.Q., Nomi J.S., Hébert-Seropian B., Ghaziri J., Boucher O. Structure and Function of the Human Insula. J Clin Neurophysiol. 2017. 34 (4): 300–306.

  55. van den Heuvel M.P., Mandl R.C., Kahn R.S., Hulshoff Pol H.E. Functionally linked resting-state networks reflect the underlying structural connectivity architecture of the human brain. Hum Brain Mapp. 2009. 30 (10): 3127–3141.

  56. Whitaker K.J., Vértes P.E., Romero-Garcia R., Váša F., Moutoussis M., Prabhu G., Weiskopf N., Callaghan M.F., Wagstyl K., Rittman T., Tait R., Ooi C., Suckling J., Inkster B., Fonagy P., Dolan R.J., Jones P.B., Goodyer I.M.; NSPN Consortium, Bullmore E.T. Adolescence is associated with genomically patterned consolidation of the hubs of the human brain connectome. Proc Natl Acad Sci U S A. 2016. 113 (32): 9105–9110.

  57. Wilcox C.E., Pommy J.M., Adinoff B. Neural Circuitry of Impaired Emotion Regulation in Substance Use Disorders. Am J Psychiatry. 2016. 173 (4): 344–361.

  58. Yuan H., Ding L., Zhu M., Zotev V., Phillips R., Bodurka J. Reconstructing Large-Scale Brain Resting-State Networks from High-Resolution EEG: Spatial and Temporal Comparisons with fMRI. Brain Connect. 2016. 6 (2): 122–135.

  59. Zhao J., Tomasi D., Wiers C.E., Shokri-Kojori E., Demiral S.B., Zhang Y., Volkow N.D., Wang G.J. Correlation between traits of emotion-based impulsivity and intrinsic default-mode network activity. Neural Plast. 2017. 2017: 9297621.

Дополнительные материалы отсутствуют.