Journal
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
Volume 375, Issue 2096, Pages -Publisher
ROYAL SOC
DOI: 10.1098/rsta.2016.0283
Keywords
brain connectivity; network analysis; integration and segregation; neuropsychiatric disorders; computational modelling
Categories
Funding
- Canadian Institutes of Health Research (CIHR)
- Canadian Centennial Scholarship Fund
- Mann Senior Scholarship from Hertford College (University of Oxford)
- European Research Council (ERC) [CAREGIVING (615539)]
- ERC advanced grant [DYSTRUCTURE (295129)]
- Spanish Research Project [PSI2013-42091-P]
- ICREA Funding Source: Custom
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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'.
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