Data-driven brain network models differentiate variability across language tasks.

ABSTRACT: The relationship between brain structure and function has been probed using a variety of approaches, but how the underlying structural connectivity of the human brain drives behavior is far from understood. To investigate the effect of anatomical brain organization on human task performance, we use a data-driven computational modeling approach and explore the functional effects of naturally occurring structural differences in brain networks. We construct personalized brain network models by combining anatomical connectivity estimated from diffusion spectrum imaging of individual subjects with a nonlinear model of brain dynamics. By performing computational experiments in which we measure the excitability of the global brain network and spread of synchronization following a targeted computa

SUBMITTER: Bansal K 

PROVIDER: S-EPMC6192563 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature