title: A framework for quantifying node-level community structure group differences in brain connectivity networks.
abstract: We propose a framework for quantifying node-level community structures between groups using anatomical brain networks derived from DTI-tractography. To construct communities, we computed hierarchical binary trees by maximizing two metrics: the well-known modularity metric (Q), and a novel metric that measures the difference between inter-community and intra-community path lengths. Changes in community structures on the nodal level were assessed between generated trees and a statistical framework was developed to detect local differences between two groups of community structures. We applied this framework to a sample of 42 subjects with major depression and 47 healthy controls. Results showed that several nodes (including the bilateral precuneus, which have been linked to self-awareness) within the default mode network exhibited significant differences between groups. These findings are consistent with those reported in previous literature, suggesting a higher degree of ruminative self-reflections in depression.
authors.affiliation: Electrical and Computer Engineering Department, University of Illinois at Chicago, USA. jgadel2@uic.edu
authors.forename: Johnson J
authors.initials: JJ
authors.lastname: GadElkarim
authors.forename: Dan
authors.initials: D
authors.lastname: Schonfeld
authors.forename: Olusola
authors.initials: O
authors.lastname: Ajilore
authors.forename: Liang
authors.initials: L
authors.lastname: Zhan
authors.forename: Aifeng F
authors.initials: AF
authors.lastname: Zhang
authors.forename: Jamie D
authors.initials: JD
authors.lastname: Feusner
authors.forename: Paul M
authors.initials: PM
authors.lastname: Thompson
authors.forename: Tony J
authors.initials: TJ
authors.lastname: Simon
authors.forename: Anand
authors.initials: A
authors.lastname: Kumar
authors.forename: Alex D
authors.initials: AD
authors.lastname: Leow
mesh_terms: D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D063132:Connectome / Q000379:methods*; D056324:Diffusion Tensor Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009415:Nerve Net / Q000033:anatomy & histology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity