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Author:

Zhang, Xiaofei (Zhang, Xiaofei.) | Yang, Yang (Yang, Yang.) | Liu, Ruohao (Liu, Ruohao.) | Zhong, Ning (Zhong, Ning.)

Indexed by:

EI

Abstract:

A large number of studies on altered functional brain network tend to focus only on the alternation in topological metric of functional connectivity, rather than on the details of graph adjustment that cause topological metric changes, such as significant adjusted route and the nodes on it. In this paper, we first used the brain atlas of Dosenbach to generate the functional brain networks of the 21 participants recruited in the mental arithmetic experiment. Then, the nodal efficiency of each brain region in the network were calculated and statistically compared between mental arithmetic cognitive states. The brain regions with significant alternation in nodal efficiency were taken as seeds for searching adjusted routes. The brain regions that have significant changes in network efficiency with the seed nodes were considered as destined nodes of the relative seed nodes. Finally, the details of two adopted indicators on altered functional brain network by comparing the adjusted route between the two endpoints of the adjusted route were given and used as clues for the better understanding of the cognitive pattern of mental arithmetic. In this paper, the average number of adjusted routes contributed by brain region is used to indicate the degree of contribution of the brain region to the route adjustment, and the interaction degree within specific network is indicated by the density of adjusted routes. The results show that both indicators of fronto-parietal network is significantly higher than that of other networks, which indicates the brain regions and the routes within fronto-parietal network are the most active. In summary, the method proposed in this paper provides a new perspective to study the causes of functional brain network alternation in mental arithmetic. However, due to the participants’ variation of adjusted routes and the nodes on it, a better understanding of these functional brain network alternation for individual participant with the proposed method needs more in-depth research. © 2019, Springer Nature Switzerland AG.

Keyword:

Efficiency Calculations Topology Brain

Author Community:

  • [ 1 ] [Zhang, Xiaofei]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Zhang, Xiaofei]School of Computer, Jiangsu University of Science and Technology, Zhenjiang; 212003, China
  • [ 3 ] [Zhang, Xiaofei]Beijing International Collaboration Base on Brain Informatics and Wisdom Services, Beijing; 100124, China
  • [ 4 ] [Zhang, Xiaofei]Beijing Key Laboratory of MRI and Brain Informatics, Beijing; 100124, China
  • [ 5 ] [Yang, Yang]Department of Psychology, Beijing Forestry University, Beijing; 100083, China
  • [ 6 ] [Yang, Yang]Beijing International Collaboration Base on Brain Informatics and Wisdom Services, Beijing; 100124, China
  • [ 7 ] [Yang, Yang]Beijing Key Laboratory of MRI and Brain Informatics, Beijing; 100124, China
  • [ 8 ] [Yang, Yang]Department of Life Science and Informatics, Maebashi Institute of Technology, Maebashi; Gunma; 371-0816, Japan
  • [ 9 ] [Liu, Ruohao]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 10 ] [Liu, Ruohao]Beijing International Collaboration Base on Brain Informatics and Wisdom Services, Beijing; 100124, China
  • [ 11 ] [Liu, Ruohao]Beijing Key Laboratory of MRI and Brain Informatics, Beijing; 100124, China
  • [ 12 ] [Zhong, Ning]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 13 ] [Zhong, Ning]Beijing International Collaboration Base on Brain Informatics and Wisdom Services, Beijing; 100124, China
  • [ 14 ] [Zhong, Ning]Beijing Key Laboratory of MRI and Brain Informatics, Beijing; 100124, China
  • [ 15 ] [Zhong, Ning]Department of Life Science and Informatics, Maebashi Institute of Technology, Maebashi; Gunma; 371-0816, Japan

Reprint Author's Address:

  • 钟宁

    [zhong, ning]faculty of information technology, beijing university of technology, beijing; 100124, china;;[zhong, ning]beijing key laboratory of mri and brain informatics, beijing; 100124, china;;[zhong, ning]beijing international collaboration base on brain informatics and wisdom services, beijing; 100124, china;;[zhong, ning]department of life science and informatics, maebashi institute of technology, maebashi; gunma; 371-0816, japan

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Source :

ISSN: 0302-9743

Year: 2019

Volume: 11976 LNAI

Page: 51-61

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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