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Nat Rev Neurosci. 2015 Jul;16(7):430-9. doi: 10.1038/nrn3963. Epub 2015 Jun 17.

Rethinking segregation and integration: contributions of whole-brain modelling.

Author information

1
Center for Brain and Cognition, Computational Neuroscience Group, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Roc Boronat 138, Barcelona 08018, Spain; and the Instituci Catalana de la Recerca i Estudis Avanats (ICREA), Universitat Pompeu Fabra, Passeig Llus Companys 23, Barcelona 08010, Spain.
2
Department of Psychiatry, University of Wisconsin-Madison, Wisconsin 53719, USA.
3
1] Department of Psychiatry, University of Wisconsin-Madison, Wisconsin 53719, USA. [2] Department of Neurology, University of Wisconsin-Madison, Wisconsin 53702, USA.
4
Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK; and the Center of Functionally Integrative Neuroscience (CFIN), Aarhus University, 8000 Aarhus C, Denmark.

Abstract

The brain regulates information flow by balancing the segregation and integration of incoming stimuli to facilitate flexible cognition and behaviour. The topological features of brain networks--in particular, network communities and hubs--support this segregation and integration but do not provide information about how external inputs are processed dynamically (that is, over time). Experiments in which the consequences of selective inputs on brain activity are controlled and traced with great precision could provide such information. However, such strategies have thus far had limited success. By contrast, recent whole-brain computational modelling approaches have enabled us to start assessing the effect of input perturbations on brain dynamics in silico.

PMID:
26081790
DOI:
10.1038/nrn3963
[Indexed for MEDLINE]

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