Research On Mathematics Modeling Approach Of Resting-state Brain Function Network

In recent years, scholars focus on the study of brain network and theresearch on the structure and function of brain network has made greatachievements. Research shows that the brain network has some unique topologicattributes and characteristics. The results are fully utilized in the field of braindisease diagnosis. But the brain network traditional research methods also havesome defects, such as: the brain network according to fMRI time series lack oftime resolution, the brain network in a large number of node has too muchcomputation. So the research on brain function network based on the methods ofmathematical modeling has received attention of scholars. Scholars used to useanatomical distance between nodes as the only parameter, construct the brainmodel network of cats and monkeys in Ganges RIver. Some scholars usedanatomical distance and node common neighbor as the parameter of modelnetwork. They use it to analysis topological properties of brain network ofmental disorders and achieved good results. There are the two basicassumptions on the study of network modeling. The closer the anatomicaldistance between the nodes, the greater the connection possibility between thenodes. The more similarity between the nodes, the greater the connection possibility between the nodes.In this paper, design three different brain model network based onanatomical distance or node similarity and evaluation. Compare the two networksimilarity judge standard in the levels of structure. Specific work and mainresults are as follows:First, analyzes network model based on anatomical distance andnode similarity, the anatomical distance by AAL template to calculate. For thefirst time will be used to similarity node index in complex network modeling isintroduced into the brain network modeling. This paper introduces the variousnodes similarity index, design experiments proved that the number of commonneighbor of nodes is the most suitable for network modeling of the brain. Thispaper design new comparison method about network similarity—the methodbased on the network metrics. And the paper describes two kinds of comparisonmethod about network similarity. They are Pearson method and Jaccard method.Specifically, the method based on the network metrics is analyze the similaritybetween two network topological properties. Pearson comparison method is toanalyze the relevance of the two network. Jaccard comparison method is toanalyze the coincidence rate of the edges of the two network. Constructeconomic cluster through different kinds of nodes similarity metrics. Analysisthe distribution of the optimal model of the economic cluster model by the threecomparison method. The result shows that the distribution of the optimal modelis same when we use same method. And the most suitable method used to compare brain network is the method based on the network metrics.Second, in order to analysis the contribution of anatomical distance andnode similarity in brain network modeling, this paper design two different brainmodel network—network model based on anatomical distance，network modelbased on node similarity. Create the evaluation criteria for select theoptimal brain function model network in each class model based on residuals.Select the model that can simulate the real brain function network bycomparison with real network. The results show the best model only is based onanatomical distance.Third, build the visual aid research software—Brain NetworkConstruction&Analysis Platform. It have many function, include constructionand analysis brain function network, construction and analysis brain modelnetwork, compare the similarity of network and so on.