Graph Laplacian learning based Fourier Transform for brain network analysis with resting state fMRI

In recent decades, the graph signal processing techniques have demonstrated their effectiveness in tackling neuroimaging problems. However, most of these tools rely on predefined graphs to conduct spectral analysis, which can not be always satisfied due to the complexity of the brain structure. We, therefore, propose a data-driven signal processing framework (or namely, graph Laplacian learning based Fourier transform) that can effectively...