Your browser doesn't support javascript.
loading
Brain-behaviour modes of covariation in healthy and clinically depressed young people.
Mihalik, Agoston; Ferreira, Fabio S; Rosa, Maria J; Moutoussis, Michael; Ziegler, Gabriel; Monteiro, Joao M; Portugal, Liana; Adams, Rick A; Romero-Garcia, Rafael; Vértes, Petra E; Kitzbichler, Manfred G; Vása, Frantisek; Vaghi, Matilde M; Bullmore, Edward T; Fonagy, Peter; Goodyer, Ian M; Jones, Peter B; Dolan, Raymond; Mourão-Miranda, Janaina.
Affiliation
  • Mihalik A; Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom. a.mihalik@ucl.ac.uk.
  • Ferreira FS; Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom. a.mihalik@ucl.ac.uk.
  • Rosa MJ; Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom.
  • Moutoussis M; Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom.
  • Ziegler G; Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom.
  • Monteiro JM; Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom.
  • Portugal L; Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom.
  • Adams RA; Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom.
  • Romero-Garcia R; Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany.
  • Vértes PE; German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.
  • Kitzbichler MG; Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom.
  • Vása F; Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom.
  • Vaghi MM; Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom.
  • Bullmore ET; Department of Physiology and Pharmacology, Federal Fluminense University, Niteroi, Brazil.
  • Fonagy P; Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom.
  • Goodyer IM; Max Planck University College London Centre for Computational Psychiatry and Ageing Research, University College London, London, United Kingdom.
  • Jones PB; Wellcome Centre for Human Neuroimaging, University College London, London, United Kingdom.
  • Dolan R; Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, United Kingdom.
  • Mourão-Miranda J; Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom.
Sci Rep ; 9(1): 11536, 2019 08 08.
Article in En | MEDLINE | ID: mdl-31395894
Understanding how variations in dimensions of psychometrics, IQ and demographics relate to changes in brain connectivity during the critical developmental period of adolescence and early adulthood is a major challenge. This has particular relevance for mental health disorders where a failure to understand these links might hinder the development of better diagnostic approaches and therapeutics. Here, we investigated this question in 306 adolescents and young adults (14-24 y, 25 clinically depressed) using a multivariate statistical framework, based on canonical correlation analysis (CCA). By linking individual functional brain connectivity profiles to self-report questionnaires, IQ and demographic data we identified two distinct modes of covariation. The first mode mapped onto an externalization/internalization axis and showed a strong association with sex. The second mode mapped onto a well-being/distress axis independent of sex. Interestingly, both modes showed an association with age. Crucially, the changes in functional brain connectivity associated with changes in these phenotypes showed marked developmental effects. The findings point to a role for the default mode, frontoparietal and limbic networks in psychopathology and depression.
Subject(s)

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Psychometrics / Brain / Depression / Mental Disorders Type of study: Diagnostic_studies / Prognostic_studies Limits: Adolescent / Adult / Female / Humans / Male Language: En Journal: Sci Rep Year: 2019 Document type: Article Affiliation country: United kingdom Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Psychometrics / Brain / Depression / Mental Disorders Type of study: Diagnostic_studies / Prognostic_studies Limits: Adolescent / Adult / Female / Humans / Male Language: En Journal: Sci Rep Year: 2019 Document type: Article Affiliation country: United kingdom Country of publication: United kingdom