Discovering prominent differences in structural and functional connectomes using a multinomial stochastic block model.

ABSTRACT: Understanding the differences between functional and structural human brain connectivity has been a focus of an extensive amount of neuroscience research. We employ a novel approach using the multinomial stochastic block model (MSBM) to explicitly extract components that characterize prominent differences across graphs. We analyze structural and functional connectomes derived from high-resolution diffusion-weighted MRI and fMRI scans of 250 Human Connectome Project subjects, analyzed at group connectivity level across 50 subjects. The inferred brain partitions revealed consistent, spatially homogeneous clustering patterns across inferred resolutions demonstrating the MSBM's reliability in identifying brain areas with prominent structure-function differences. Prominent differences in low-re

SUBMITTER: Iskov NB 

PROVIDER: S-EPMC11674489 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature