Using Low-Dimensional Manifolds to Map Relationships Between Dynamic Brain Networks.

ABSTRACT: As the field of dynamic brain networks continues to expand, new methods are needed to allow for optimal handling and understanding of this explosion in data. We propose here a novel approach that embeds dynamic brain networks onto a two-dimensional (2D) manifold based on similarities and differences in network organization. Each brain network is represented as a single point on the low dimensional manifold with networks of similar topology being located in close proximity. The rich spatio-temporal information has great potential for visualization, analysis, and interpretation of dynamic brain networks. The fact that each network is represented by a single point makes it possible to switch between the low-dimensional space and the full connectivity of any given brain network. Thus, networks

SUBMITTER: Bahrami M 

PROVIDER: S-EPMC6914694 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature