Activity flow mapping over probabilistic functional connectivity.

ABSTRACT: Emerging evidence indicates that activity flow over resting-state network topology allows the prediction of task activations. However, previous studies have mainly adopted static, linear functional connectivity (FC) estimates as activity flow routes. It is unclear whether an intrinsic network topology that captures the dynamic nature of FC can be a better representation of activity flow routes. Moreover, the effects of between- versus within-network connections and tight versus loose (using rest baseline) task contrasts on the prediction of task-evoked activity across brain systems remain largely unknown. In this study, we first propose a probabilistic FC estimation derived from a dynamic framework as a new activity flow route. Subsequently, activity flow mapping was tested using between-

SUBMITTER: Zhu H 

PROVIDER: S-EPMC9842909 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature