PSYCH OpenIR  > 中国科学院行为科学重点实验室
Weighted Stochastic Block Models of the Human Connectome across the Life Span
Faskowitz, Joshua1,2; Yan, Xiaoran3; Zuo, Xi-Nian4,5,6; Sporns, Olaf1,2,3

The human brain can be described as a complex network of anatomical connections between distinct areas, referred to as the human connectome. Fundamental characteristics of connectome organization can be revealed using the tools of network science and graph theory. Of particular interest is the network's community structure, commonly identified by modularity maximization, where communities are conceptualized as densely intra-connected and sparsely inter-connected. Here we adopt a generative modeling approach called weighted stochastic block models (WSBM) that can describe a wider range of community structure topologies by explicitly considering patterned interactions between communities. We apply this method to the study of changes in the human connectome that occur across the life span (between 6-85 years old). We find that WSBM communities exhibit greater hemispheric symmetry and are spatially less compact than those derived from modularity maximization. We identify several network blocks that exhibit significant linear and non-linear changes across age, with the most significant changes involving subregions of prefrontal cortex. Overall, we show that the WSBM generative modeling approach can be an effective tool for describing types of community structure in brain networks that go beyond modularity.

Funding ProjectNational Institutes of Health[R01 AT009036-01] ; National Science Foundation Graduate Research Fellowship[1342962] ; National Basic Research Program[2015CB351702] ; National Natural Science Foundation of China[81220108014] ; Beijing Municipal Science & Technology Commission[Z161100002616023] ; Beijing Municipal Science & Technology Commission[Z171100000117012] ; National R&D Infrastructure and Facility Development Program of China -
WOS KeywordHuman Cerebral-cortex ; Age-related-changes ; Diffusion Mri Data ; Brain Networks ; Functional Connectivity ; Spherical Deconvolution ; Structural Connectivity ; Community Detection ; Cortical Thickness ; Sex-differences
WOS Research AreaScience & Technology - Other Topics
WOS SubjectMultidisciplinary Sciences
WOS IDWOS:000443003800004
Citation statistics
Cited Times:11[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Corresponding AuthorSporns, Olaf
Affiliation1.Indiana Univ, Program Neurosci, Bloomington, IN 47405 USA
2.Indiana Univ, Dept Psychol & Brain Sci, Bloomington, IN 47405 USA
3.Indiana Univ, Indiana Univ Network Sci Inst, Bloomington, IN 47405 USA
4.Inst Psychol, CAS Key Lab Behav Sci, Beijing, Peoples R China
5.Inst Psychol, Res Ctr Lifespan Dev Mind & Brain CLIMB, Beijing, Peoples R China
6.Nanning Normal Univ, Key Lab Brain & Educ Sci, Nanning 530001, Guangxi, Peoples R China
Recommended Citation
GB/T 7714
Faskowitz, Joshua,Yan, Xiaoran,Zuo, Xi-Nian,et al. Weighted Stochastic Block Models of the Human Connectome across the Life Span[J]. SCIENTIFIC REPORTS,2018,8:16.
APA Faskowitz, Joshua,Yan, Xiaoran,Zuo, Xi-Nian,&Sporns, Olaf.(2018).Weighted Stochastic Block Models of the Human Connectome across the Life Span.SCIENTIFIC REPORTS,8,16.
MLA Faskowitz, Joshua,et al."Weighted Stochastic Block Models of the Human Connectome across the Life Span".SCIENTIFIC REPORTS 8(2018):16.
Files in This Item:
File Name/Size DocType Version Access License
Weighted Stochastic (3233KB)期刊论文出版稿限制开放CC BY-NC-SAApplication Full Text
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Faskowitz, Joshua]'s Articles
[Yan, Xiaoran]'s Articles
[Zuo, Xi-Nian]'s Articles
Baidu academic
Similar articles in Baidu academic
[Faskowitz, Joshua]'s Articles
[Yan, Xiaoran]'s Articles
[Zuo, Xi-Nian]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Faskowitz, Joshua]'s Articles
[Yan, Xiaoran]'s Articles
[Zuo, Xi-Nian]'s Articles
Terms of Use
No data!
Social Bookmark/Share
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.