Rethinking segregation and integration: contributions of whole-brain modelling

被引：368

作者：

Deco, Gustavo ^{[1
,2
]}

Tononi, Giulio ^{[3
]}

Boly, Melanie ^{[3
,4
]}

Kringelbach, Morten L. ^{[5
,6
]}

机构：

[1] Univ Pompeu Fabra, Dept Informat & Commun Technol, Computat Neurosci Grp, Ctr Brain & Cognit, Barcelona 08018, Spain

[2] Univ Pompeu Fabra, ICREA, Barcelona 08010, Spain

[3] Univ Wisconsin, Dept Psychiat, Madison, WI 53719 USA

[4] Univ Wisconsin, Dept Neurol, Madison, WI 53702 USA

[5] Univ Oxford, Dept Psychiat, Oxford OX3 7JX, England

[6] Aarhus Univ, CFIN, DK-8000 Aarhus C, Denmark

来源：

NATURE REVIEWS NEUROSCIENCE | 2015年 / 16卷 / 07期

基金：

欧洲研究理事会;

关键词：

STATE FUNCTIONAL CONNECTIVITY; GRAPH-THEORETICAL ANALYSIS; RESTING-STATE; INFORMATION INTEGRATION; NETWORK OSCILLATIONS; CEREBRAL-CORTEX; SMALL-WORLD; DIFFUSION; DYNAMICS; MULTISTABILITY;

D O I：

10.1038/nrn3963

中图分类号：

Q189 [神经科学];

学科分类号：

071006 ;

摘要：

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.

引用

页码：430 / U81

页数：10

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