Functional connectivity metrics for wavelet clustering of rs-fMRI data

Functional connectivity (FC) in the brain reflects the time-varying cognitive demands imposed by our changing environment. Researchers have advanced methods towards evaluating such changes but no single dynamic FC method has emerged. This plurality of methodologies challenges the research community to implement efficient means for evaluating the results of each method. Brain connectivity exists in a high-dimensional space where changing connectivity between regions is assessed across hundreds of time points. The present research address this challenge by embedding network dynamics in a 2D manifold. Findings suggest the ability of the proposed manifold embedding technique to highlight dynamic brain state transitions.