人脑
神经科学
连接组学
网络科学
认知
人类连接体项目
神经影像学
认知科学
计算机科学
多学科方法
数据科学
连接体
心理学
人工智能
复杂网络
功能连接
社会学
万维网
社会科学
作者
Xuhong Liao,Athanasios V. Vasilakos,Yong He
标识
DOI:10.1016/j.neubiorev.2017.03.018
摘要
Modelling the human brain as a complex network has provided a powerful mathematical framework to characterize the structural and functional architectures of the brain. In the past decade, the combination of non-invasive neuroimaging techniques and graph theoretical approaches enable us to map human structural and functional connectivity patterns (i.e., connectome) at the macroscopic level. One of the most influential findings is that human brain networks exhibit prominent small-world organization. Such a network architecture in the human brain facilitates efficient information segregation and integration at low wiring and energy costs, which presumably results from natural selection under the pressure of a cost-efficiency balance. Moreover, the small-world organization undergoes continuous changes during normal development and ageing and exhibits dramatic alterations in neurological and psychiatric disorders. In this review, we survey recent advances regarding the small-world architecture in human brain networks and highlight the potential implications and applications in multidisciplinary fields, including cognitive neuroscience, medicine and engineering. Finally, we highlight several challenging issues and areas for future research in this rapidly growing field.
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