title: Identifying the brain's most globally connected regions.
abstract: Recent advances in brain connectivity methods have made it possible to identify hubs-the brain's most globally connected regions. Such regions are essential for coordinating brain functions due to their connectivity with numerous regions with a variety of specializations. Current structural and functional connectivity methods generally agree that default mode network (DMN) regions have among the highest global brain connectivity (GBC). We developed two novel statistical approaches using resting state functional connectivity MRI-weighted and unweighted GBC (wGBC and uGBC)-to test the hypothesis that the highest global connectivity also occurs in the cognitive control network (CCN), a network anti-correlated with the DMN across a variety of tasks. High global connectivity was found in both CCN and DMN. The newly developed wGBC approach improves upon existing methods by quantifying inter-subject consistency, quantifying the highest GBC values by percentage, and avoiding arbitrarily connection strength thresholding. The uGBC approach is based on graph theory and includes many of these improvements, but still requires an arbitrary connection threshold. We found high GBC in several subcortical regions (e.g., hippocampus, basal ganglia) only with wGBC despite the regions' extensive anatomical connectivity. These results demonstrate the complementary utility of wGBC and uGBC analyses for the characterization of the most highly connected, and thus most functionally important, regions of the brain. Additionally, the high connectivity of both the CCN and the DMN demonstrates that brain regions outside primary sensory-motor networks are highly involved in coordinating information throughout the brain.
authors.affiliation: Department of Psychology, Washington University, St. Louis, MO 63130, USA. mwcole@mwcole.net
authors.forename: Michael W
authors.initials: MW
authors.lastname: Cole
authors.forename: Sudhir
authors.initials: S
authors.lastname: Pathak
authors.forename: Walter
authors.initials: W
authors.lastname: Schneider
mesh_terms: D000328:Adult; D001921:Brain / Q000033:anatomy & histology*; D003198:Computer Simulation; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008953:Models, Anatomic; D008959:Models, Neurological; D009415:Nerve Net / Q000033:anatomy & histology*; D009434:Neural Pathways / Q000033:anatomy & histology*; D055815:Young Adult