Identification of community structure-based brain states and transitions using functional MRI.

ABSTRACT: Brain function relies on a precisely coordinated and dynamic balance between the functional integration and segregation of distinct networks. Characterizing the way in which brain regions reconfigure their interactions to give rise to distinct but hidden brain states remains an open challenge. In this paper, we propose a Bayesian method for characterizing community structure-based latent brain states and showcase a novel strategy based on posterior predictive discrepancy using the latent block model to detect transitions between community structures in blood oxygen level-dependent (BOLD) time series. The set of estimated parameters in the model includes a latent label vector that assigns network nodes to communities, and also block model parameters that reflect the weighted connectivity wi

SUBMITTER: Bian L 

PROVIDER: S-EPMC8905300 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature