Research on Modeling Approach of Brain Function Network Based on Anatomical Distance

doi:10.1007/s12204-015-1687-7

Journal of Shanghai Jiao Tong University(Science) ›› 2015, Vol. 20 ›› Issue (6): 758-762.doi: 10.1007/s12204-015-1687-7

• Research article • Previous Articles

Research on Modeling Approach of Brain Function Network Based on Anatomical Distance

Yan-li YANG, Hao GUO, Jun-jie CHEN, Hai-fang LI^*

College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan 030024, China

Received:2015-09-30 Online:2015-12-20 Published:2020-10-09
Contact: Hai-fang LI
Supported by:
Foundation item: the National Natural Science Foundation of China (Nos. 61170136, 61373101, 61472270 and 61402318);The Natural Science Foundation of Shanxi (No. 2014021022-5);The Special/Youth Foundation of Taiyuan University of Technology (No.2012L014);The Youth Team Fund of Taiyuan University of Technology (Nos.2013T047 and 2013T048)

Abstract

Abstract:

The number of common neighbor between nodes is applied to the modeling of resting-state brain function network in order to analyze the effect of anatomical distance on the modeling of resting-state brain function network. Three models based on anatomical distance, the number of common neighbor, or anatomical distance and the number of common neighbor are designed. Basing on residuals creates the evaluation criteria for selecting the optimal brain function model network in each class model. The model is selected to simulate the human real brain function network by comparison with real data functional magnetic resonance imaging (fMRI) network. Finally, the result shows that the best model only is based on anatomical distance.

CLC Number:

TP 391.41

Yan-li YANG, Hao GUO, Jun-jie CHEN, Hai-fang LI. Research on Modeling Approach of Brain Function Network Based on Anatomical Distance[J]. Journal of Shanghai Jiao Tong University(Science), 2015, 20(6): 758-762.

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Research on Modeling Approach of Brain Function Network Based on Anatomical Distance

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