Comparing functional connectivity matrices: A geometry-aware approach applied to participant identification.

ABSTRACT: Understanding the correlation structure associated with multiple brain measurements informs about potential "functional groupings" and network organization. The correlation structure can be conveniently captured in a matrix format that summarizes the relationships among a set of brain measurements involving two regions, for example. Such functional connectivity matrix is an important component of many types of investigation focusing on network-level properties of the brain, including clustering brain states, characterizing dynamic functional states, performing participant identification (so-called "fingerprinting") understanding how tasks reconfigure brain networks, and inter-subject correlation analysis. In these investigations, some notion of proximity or similarity of functional connect

SUBMITTER: Venkatesh M 

PROVIDER: S-EPMC6995445 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature