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Brain Imaging and Behavior

, Volume 11, Issue 1, pp 113–128 | Cite as

Impaired topological architecture of brain structural networks in idiopathic Parkinson’s disease: a DTI study

  • Changhong Li
  • Biao Huang
  • Ruibin Zhang
  • Qing Ma
  • Wanqun Yang
  • Lijuan Wang
  • Limin Wang
  • Qin Xu
  • Jieying Feng
  • Liqing Liu
  • Yuhu Zhang
  • Ruiwang Huang
Original Research

Abstract

Parkinson’s disease (PD) is considered as a neurodegenerative disorder of the brain central nervous system. But, to date, few studies adopted the network model to reveal topological changes in brain structural networks in PD patients. Additionally, although the concept of rich club organization has been widely used to study brain networks in various brain disorders, there is no study to report the changed rich club organization of brain networks in PD patients. Thus, we collected diffusion tensor imaging (DTI) data from 35 PD patients and 26 healthy controls and adopted deterministic tractography to construct brain structural networks. During the network analysis, we calculated their topological properties, and built the rich club organization of brain structural networks for both subject groups. By comparing the between-group differences in topological properties and rich club organizations, we found that the connectivity strength of the feeder and local connections are lower in PD patients compared to those of the healthy controls. Furthermore, using a network-based statistic (NBS) approach, we identified uniformly significantly decreased connections in two modules, the limbic/paralimbic/subcortical module and the cognitive control/attention module, in patients compared to controls. In addition, for the topological properties of brain network topology in the PD patients, we found statistically increased shortest path length and decreased global efficiency. Statistical comparisons of nodal properties were also widespread in the frontal and parietal regions for the PD patients. These findings may provide useful information to better understand the abnormalities of brain structural networks in PD patients.

Keywords

Rich club organization Diffusion tensor imaging Edge architecture Network-based statistic 

Notes

Acknowledgments

We appreciate English editing assistance of Drs. Rhoda E. and Edmund F. Perozzi.

Compliance with ethical standards

Funding

This work was supported by the funding from the National Natural Science Foundation of China (Grant numbers: 81271548, 81271560, 81371535, 81428013, and 81471654).

Conflict of interest

The authors declare that they have no competing financial interests. We declare that our work described here has not been submitted elsewhere for publication, neither in whole or in part, and all the authors listed have approved the manuscript that is enclosed. All authors of this research paper have directly participated in the planning, execution, or analysis of this study. All authors of this paper have also read and approved the final submitted version.

Ethical approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study.

Supplementary material

11682_2015_9501_MOESM1_ESM.doc (903 kb)
ESM 1 (DOC 903 kb)

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Changhong Li
    • 1
  • Biao Huang
    • 2
  • Ruibin Zhang
    • 1
  • Qing Ma
    • 1
  • Wanqun Yang
    • 2
  • Lijuan Wang
    • 3
  • Limin Wang
    • 3
  • Qin Xu
    • 1
  • Jieying Feng
    • 2
  • Liqing Liu
    • 1
  • Yuhu Zhang
    • 3
  • Ruiwang Huang
    • 1
  1. 1.Center for the Study of Applied Psychology, Key Laboratory of Mental Health and Cognitive Science of Guangdong Province, School of Psychology, Brain Study InstituteSouth China Normal UniversityGuangzhouChina
  2. 2.Department of Radiology, Guangdong Academy of Medical SciencesGuangdong General HospitalGuangzhouChina
  3. 3.Department of Neurology, Guangdong Academy of Medical SciencesGuangdong General HospitalGuangzhouChina

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