AUTHOR=Wang Donglin , Wu Qiang , Hong Don 

TITLE=Extracting default mode network based on graph neural network for resting state fMRI study

JOURNAL=Frontiers in Neuroimaging

VOLUME=Volume 1 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/neuroimaging/articles/10.3389/fnimg.2022.963125

DOI=10.3389/fnimg.2022.963125

ISSN=2813-1193

ABSTRACT=Functional magnetic resonance imaging (fMRI)-based study for the functional connections in
the brain has been highlighted by numerous human and animal studies recently, which have provided
significant information to explain a wide range of pathological conditions and behavioral characteristics.
In this paper, we propose the use of graph neural network, a deep learning technique called graphSAGE,
to investigate resting state fMRI (rs-fMRI) and extract the default mode network (DMN). Comparing
typical methods such as seed-based correlation, the independent component analysis, and the dictionary learning, the real data experiment results showed that the graphSAGE is more robust, reliable
and defines more clear region of interests. In addition, the graphSAGE requires less and more
relaxing assumptions, as well as considers the single subject analysis and group subjects analysis
simultaneously.