A Comparative Study of Theoretical Graph Models for Characterizing Structural Networks of Human Brain
Joint Authors
Li, Xiaojin
Hu, Xintao
Liu, Tianming
Hao, Wei
Guo, Lei
Han, Junwei
Li, Lingjiang
Jin, Changfeng
Source
International Journal of Biomedical Imaging
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-11-27
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Previous studies have investigated both structural and functional brain networks via graph-theoretical methods.
However, there is an important issue that has not been adequately discussed before: what is the optimal theoretical graph model for describing the structural networks of human brain? In this paper, we perform a comparative study to address this problem.
Firstly, large-scale cortical regions of interest (ROIs) are localized by recently developed and validated brain reference system named Dense Individualized Common Connectivity-based Cortical Landmarks (DICCCOL) to address the limitations in the identification of the brain network ROIs in previous studies.
Then, we construct structural brain networks based on diffusion tensor imaging (DTI) data.
Afterwards, the global and local graph properties of the constructed structural brain networks are measured using the state-of-the-art graph analysis algorithms and tools and are further compared with seven popular theoretical graph models.
In addition, we compare the topological properties between two graph models, namely, stickiness-index-based model (STICKY) and scale-free gene duplication model (SF-GD), that have higher similarity with the real structural brain networks in terms of global and local graph properties.
Our experimental results suggest that among the seven theoretical graph models compared in this study, STICKY and SF-GD models have better performances in characterizing the structural human brain network.
American Psychological Association (APA)
Li, Xiaojin& Hu, Xintao& Jin, Changfeng& Han, Junwei& Liu, Tianming& Guo, Lei…[et al.]. 2013. A Comparative Study of Theoretical Graph Models for Characterizing Structural Networks of Human Brain. International Journal of Biomedical Imaging،Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-454015
Modern Language Association (MLA)
Li, Xiaojin…[et al.]. A Comparative Study of Theoretical Graph Models for Characterizing Structural Networks of Human Brain. International Journal of Biomedical Imaging No. 2013 (2013), pp.1-8.
https://search.emarefa.net/detail/BIM-454015
American Medical Association (AMA)
Li, Xiaojin& Hu, Xintao& Jin, Changfeng& Han, Junwei& Liu, Tianming& Guo, Lei…[et al.]. A Comparative Study of Theoretical Graph Models for Characterizing Structural Networks of Human Brain. International Journal of Biomedical Imaging. 2013. Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-454015
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-454015