title: Small-world human brain networks: Perspectives and challenges.
abstract: 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.
authors.affiliation: National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China.
authors.forename: Xuhong
authors.initials: X
authors.lastname: Liao
authors.affiliation: Department of Computer Science, Electrical and Space Engineering, Lulea University of Technology, 97187 Lulea, Sweden.
authors.forename: Athanasios V
authors.initials: AV
authors.lastname: Vasilakos
authors.affiliation: National Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing 100875, China; IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China; Beijing Key Laboratory of Brain Imaging and Connectomics, Beijing Normal University, Beijing 100875, China. Electronic address: yong.he@bnu.edu.cn.
authors.forename: Yong
authors.initials: Y
authors.lastname: He
mesh_terms: D000375:Aging; D001921:Brain; D063132:Connectome; D006801:Humans; D059906:Neuroimaging; D012641:Selection, Genetic
keywords: Brain modelling; Connectome; Graph theory; Modularity; Small-world