Spatio-temporal modeling of connectome-scale brain network interactions via time-evolving graphs.

ABSTRACT: Many recent literature studies have revealed interesting dynamics patterns of functional brain networks derived from fMRI data. However, it has been rarely explored how functional networks spatially overlap (or interact) and how such connectome-scale network interactions temporally evolve. To explore these unanswered questions, this paper presents a novel framework for spatio-temporal modeling of connectome-scale functional brain network interactions via two main effective computational methodologies. First, to integrate, pool and compare brain networks across individuals and their cognitive states under task performances, we designed a novel group-wise dictionary learning scheme to derive connectome-scale consistent brain network templates that can be used to define the common reference s

SUBMITTER: Yuan J 

PROVIDER: S-EPMC5943195 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature