Multivariate approaches improve the reliability and validity of functional connectivity and prediction of individual behaviors.

ABSTRACT: Brain functional connectivity features can predict cognition and behavior at the level of the individual. Most studies measure univariate signals, correlating timecourses from the average of constituent voxels in each node. While straightforward, this approach overlooks the spatial patterns of voxel-wise signals within individual nodes. Given that multivariate spatial activity patterns across voxels can improve fMRI measures of mental representations, here we asked whether using voxel-wise timecourses can better characterize region-by-region interactions relative to univariate approaches. Using two fMRI datasets, the Human Connectome Project sample and a local test-retest sample, we measured multivariate functional connectivity with multivariate distance correlation and univariate connecti

SUBMITTER: Yoo K 

PROVIDER: S-EPMC6591084 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature