Turbulent-like Dynamics in the Human Brain

被引:57
|
作者
Deco, Gustavo [1 ,2 ,3 ,4 ]
Kringelbach, Morten L. [5 ,6 ,7 ]
机构
[1] Univ Pompeu Fabra, Ctr Brain & Cognit, Computat Neurosci Grp, Dept Informat & Commun Technol, Roc Boronat 138, Barcelona 08018, Spain
[2] Inst Catalana Recerca & Estudis Avancats ICREA, Passeig Lluis Companys 23, Barcelona 08010, Spain
[3] Max Planck Inst Human Cognit & Brain Sci, Dept Neuropsychol, D-04103 Leipzig, Germany
[4] Monash Univ, Sch Psychol Sci, Clayton, Vic 3800, Australia
[5] Univ Oxford, Ctr Eudaimonia & Human Flourishing, Oxford, England
[6] Univ Oxford, Dept Psychiat, Oxford, England
[7] Aarhus Univ, Ctr Mus Brain, Dept Clin Med, Aarhus, Denmark
来源
CELL REPORTS | 2020年 / 33卷 / 10期
基金
欧盟地平线“2020”; 新加坡国家研究基金会;
关键词
STATE FUNCTIONAL CONNECTIVITY; CEREBRAL-CORTEX; DEFAULT-MODE; CONNECTOME; NETWORK; CRITICALITY; FMRI; MULTISTABILITY; MECHANISMS; CHAOS;
D O I
10.1016/j.celrep.2020.108471
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
Turbulence facilitates fast energy/information transfer across scales in physical systems. These qualities are important for brain function, but it is currently unknown if the dynamic intrinsic backbone of the brain also exhibits turbulence. Using large-scale neuroimaging empirical data from 1,003 healthy participants, we demonstrate turbulent-like human brain dynamics. Furthermore, we build a whole-brain model with coupled oscillators to demonstrate that the best fit to the data corresponds to a region of maximally developed turbulent-like dynamics, which also corresponds to maximal sensitivity to the processing of external stimulations (information capability). The model shows the economy of anatomy by following the exponential distance rule of anatomical connections as a cost-of-wiring principle. This establishes a firm link between turbulent-like brain activity and optimal brain function. Overall, our results reveal a way of analyzing and modeling whole-brain dynamics that suggests a turbulent-like dynamic intrinsic backbone facilitating large-scale network communication.
引用
收藏
页数:20
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