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Research of Hubs Location Method for Weighted Brain Network Based on NoS-FA

As a complex network of many interlinked brain regions, there are some central hub regions which play key roles in the structural human brain network based on T1 and diffusion tensor imaging (DTI) technology. Since most studies about hubs location method in the whole human brain network are mainly c...

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Autores principales: Weng, Zhengkui, Wang, Bin, Xue, Jie, Yang, Baojie, Liu, Hui, Xiong, Xin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5499242/
https://www.ncbi.nlm.nih.gov/pubmed/28717361
http://dx.doi.org/10.1155/2017/6174090
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author Weng, Zhengkui
Wang, Bin
Xue, Jie
Yang, Baojie
Liu, Hui
Xiong, Xin
author_facet Weng, Zhengkui
Wang, Bin
Xue, Jie
Yang, Baojie
Liu, Hui
Xiong, Xin
author_sort Weng, Zhengkui
collection PubMed
description As a complex network of many interlinked brain regions, there are some central hub regions which play key roles in the structural human brain network based on T1 and diffusion tensor imaging (DTI) technology. Since most studies about hubs location method in the whole human brain network are mainly concerned with the local properties of each single node but not the global properties of all the directly connected nodes, a novel hubs location method based on global importance contribution evaluation index is proposed in this study. The number of streamlines (NoS) is fused with normalized fractional anisotropy (FA) for more comprehensive brain bioinformation. The brain region importance contribution matrix and information transfer efficiency value are constructed, respectively, and then by combining these two factors together we can calculate the importance value of each node and locate the hubs. Profiting from both local and global features of the nodes and the multi-information fusion of human brain biosignals, the experiment results show that this method can detect the brain hubs more accurately and reasonably compared with other methods. Furthermore, the proposed location method is used in impaired brain hubs connectivity analysis of schizophrenia patients and the results are in agreement with previous studies.
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spelling pubmed-54992422017-07-17 Research of Hubs Location Method for Weighted Brain Network Based on NoS-FA Weng, Zhengkui Wang, Bin Xue, Jie Yang, Baojie Liu, Hui Xiong, Xin Comput Intell Neurosci Research Article As a complex network of many interlinked brain regions, there are some central hub regions which play key roles in the structural human brain network based on T1 and diffusion tensor imaging (DTI) technology. Since most studies about hubs location method in the whole human brain network are mainly concerned with the local properties of each single node but not the global properties of all the directly connected nodes, a novel hubs location method based on global importance contribution evaluation index is proposed in this study. The number of streamlines (NoS) is fused with normalized fractional anisotropy (FA) for more comprehensive brain bioinformation. The brain region importance contribution matrix and information transfer efficiency value are constructed, respectively, and then by combining these two factors together we can calculate the importance value of each node and locate the hubs. Profiting from both local and global features of the nodes and the multi-information fusion of human brain biosignals, the experiment results show that this method can detect the brain hubs more accurately and reasonably compared with other methods. Furthermore, the proposed location method is used in impaired brain hubs connectivity analysis of schizophrenia patients and the results are in agreement with previous studies. Hindawi 2017 2017-06-21 /pmc/articles/PMC5499242/ /pubmed/28717361 http://dx.doi.org/10.1155/2017/6174090 Text en Copyright © 2017 Zhengkui Weng et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Weng, Zhengkui
Wang, Bin
Xue, Jie
Yang, Baojie
Liu, Hui
Xiong, Xin
Research of Hubs Location Method for Weighted Brain Network Based on NoS-FA
title Research of Hubs Location Method for Weighted Brain Network Based on NoS-FA
title_full Research of Hubs Location Method for Weighted Brain Network Based on NoS-FA
title_fullStr Research of Hubs Location Method for Weighted Brain Network Based on NoS-FA
title_full_unstemmed Research of Hubs Location Method for Weighted Brain Network Based on NoS-FA
title_short Research of Hubs Location Method for Weighted Brain Network Based on NoS-FA
title_sort research of hubs location method for weighted brain network based on nos-fa
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5499242/
https://www.ncbi.nlm.nih.gov/pubmed/28717361
http://dx.doi.org/10.1155/2017/6174090
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