Visual Analysis To Explore The Differences Of Functional Brain Networks

In the field of neuroscience,researchers use statistical models and other methods to find out the differences between functional brain networks in different states and understand the working mechanism within the brain.However,due to the complexity of the brain network and the limitation of human eye observation,the current research in the field of neuroscience is mainly focused on the analysis of the differences between two or more groups of average functional brain networks.A large number of hidden differences between individuals or groups have not been fully excavated and quantified.In order to solve the above problems,this paper designs a visual analysis system to explore the differences between functional brain networks,which can analyze large brain network data sets and intuitively present the difference size and overall distribution among multiple functional brain networks.and mining the basic topological attribute differences between functional brain networks in different states to find the details of brain changes in a specific state.The work of this paper is reflected in the following three aspects:1.Several dimensionality reduction algorithms of functional brain networks based on MDS are proposed.In order to solve the problem that the existing methods can not describe the differences between multiple functional brain networks,firstly,the similarity between functional brain networks is calculated from two aspects of functional brain network connectivity weight and topology,and then combined with MDS dimensionality reduction algorithm,the difference of functional brain network in high dimensional space is transformed into the visual distance between data mapping points in low dimensional space.Assist neurologists to observe the size and overall distribution of differences among multiple functional brain networks.2.By mining the basic topological attribute information of the functional brain network,we can find the detailed changes of the brain in a particular state.In order to find out what changes have taken place in the brain caused by a specific state,graph theory and visualization technology are combined to visually present a variety of network topological attributes such as functional connectivity,network characteristic parameters and modular structure of functional brain networks.assist neuroscientists to find the differences in topological attributes between brain networks in different states and speculate whether diseases or tasks lead to brain changes.3.A visual analysis system for exploring functional brain network differences is designed and implemented,which is used for multiple functional brain network difference analysis and functional brain network topology attribute analysis.Through the exploration from the whole to the detail,the system obtains useful information from high-dimensional and large data sets,looks for the differences between the functional brain networks of the subjects in different states,and finds the changes of the brain in a specific state.Finally,three cases and user evaluation are used to prove the practicability and innovation of this system,which is of great help to assist neuroscientists to put forward new hypotheses and research ideas.