Construction Method and Application of Brain Functional Network Based on Link Prediction

Abstract

Purposes The brain functional network construction method of resting state functional magnetic resonance imaging (rs-fMRI) has been relatively mature, but the fMRI signal acquisition process is affected by acquisition equipment, subjects’ own reasons, noise, and other factors. The traditional rs-fMRI brain network construction method may have false links or missing edges, the network expression accuracy and the stability of repeated measurement needs to be further improved. Methods In order to solve above problems, on the basis of three local information indexes and four node definition strategies, the link prediction algorithm is applied to brain function network reconstruction, and two groups of test data are used to analyze the reliability of the reconstructed network topology index. Findings The experimental results show that the reconstructed network improves the stability of repeated measurement. In addition, the inter group difference of brain network in patients with Alzheimer's disease (AD) is analyzed by using the reconstructed network. The results show that there are significant inter group differences in the reconstructed network, which is consistent with the existing research results. This study provides a certain reference for the technology of constructing a stable brain function network.

Keywords

• brain functional network
• link prediction
• local information index
• repeated measurement stability