Understanding principles of integration and segregation using whole-brain computational connectomics: implications for neuropsychiatric disorders

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  • Louis-David Lord, Department of Psychiatry, University of Oxford, Oxford
  • ,
  • Angus B Stevner
  • Gustavo Deco, Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; Institució Catalana de la Recerca i Estudis Avançats (ICREA), Passeig Lluís Companys 23, Barcelona 08010, Spain; Department of Neuropsychology, Max Planck Institute for Human Cognitive and Brain Sciences, 04103 Leipzig, Germany; School of Psychological Sciences, Monash University, Melbourne, Clayton VIC 3800, Australia.
  • ,
  • Morten L Kringelbach

To survive in an ever-changing environment, the brain must seamlessly integrate a rich stream of incoming information into coherent internal representations that can then be used to efficiently plan for action. The brain must, however, balance its ability to integrate information from various sources with a complementary capacity to segregate information into modules which perform specialized computations in local circuits. Importantly, evidence suggests that imbalances in the brain's ability to bind together and/or segregate information over both space and time is a common feature of several neuropsychiatric disorders. Most studies have, however, until recently strictly attempted to characterize the principles of integration and segregation in static (i.e. time-invariant) representations of human brain networks, hence disregarding the complex spatio-temporal nature of these processes. In the present Review, we describe how the emerging discipline of whole-brain computational connectomics may be used to study the causal mechanisms of the integration and segregation of information on behaviourally relevant timescales. We emphasize how novel methods from network science and whole-brain computational modelling can expand beyond traditional neuroimaging paradigms and help to uncover the neurobiological determinants of the abnormal integration and segregation of information in neuropsychiatric disorders.This article is part of the themed issue 'Mathematical methods in medicine: neuroscience, cardiology and pathology'.

Original languageEnglish
Article number20160283
JournalPhilosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
Volume375
Issue2096
Number of pages21
ISSN1364-503X
DOIs
Publication statusPublished - 28 Jun 2017

    Research areas

  • Journal Article, Review

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