Dynamics of functional connectivity at high spatial resolution reveal long-range interactions and fine-scale organization.

ABSTRACT: Dynamic functional connectivity (dFC) derived from resting-state functional magnetic resonance imaging sheds light onto moment-to-moment reconfigurations of large-scale functional brain networks. Due to computational limits, connectivity is typically computed using pre-defined atlases, a non-trivial choice that might influence results. Here, we leverage new computational methods to retrieve dFC at the voxel level in terms of dominant patterns of fluctuations, and demonstrate that this new representation is informative to derive meaningful brain parcellations, capturing both long-range interactions and fine-scale local organization. Specifically, voxelwise dFC dominant patterns were captured through eigenvector centrality followed by clustering across time/subjects to yield most representat

SUBMITTER: Preti MG 

PROVIDER: S-EPMC5630612 | biostudies-literature | 2017 Oct

REPOSITORIES: biostudies-literature