Network neuroscience

被引:1558
作者
Bassett, Danielle S. [1 ,2 ]
Sporns, Olaf [3 ,4 ]
机构
[1] Univ Penn, Dept Bioengn, Philadelphia, PA 19104 USA
[2] Univ Penn, Dept Elect & Syst Engn, Philadelphia, PA 19104 USA
[3] Indiana Univ, Dept Psychol & Brain Sci, Bloomington, IN 47405 USA
[4] Indiana Univ, Indiana Univ Network Sci Inst, Bloomington, IN 47405 USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
RICH-CLUB ORGANIZATION; FUNCTIONAL CONNECTIVITY; DYNAMIC RECONFIGURATION; COMMUNITY STRUCTURE; BRAIN NETWORKS; BIG DATA; COMPUTATIONAL MODEL; HUMAN CONNECTOME; SOCIAL-SCIENCE; SCALE;
D O I
10.1038/nn.4502
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Despite substantial recent progress, our understanding of the principles and mechanisms underlying complex brain function and cognition remains incomplete. Network neuroscience proposes to tackle these enduring challenges. Approaching brain structure and function from an explicitly integrative perspective, network neuroscience pursues new ways to map, record, analyze and model the elements and interactions of neurobiological systems. Two parallel trends drive the approach: the availability of new empirical tools to create comprehensive maps and record dynamic patterns among molecules, neurons, brain areas and social systems; and the theoretical framework and computational tools of modern network science. The convergence of empirical and computational advances opens new frontiers of scientific inquiry, including network dynamics, manipulation and control of brain networks, and integration of network processes across spatiotemporal domains. We review emerging trends in network neuroscience and attempt to chart a path toward a better understanding of the brain as a multiscale networked system.
引用
收藏
页码:353 / 364
页数:12
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