title: Influence of choice of null network on small-world parameters of structural correlation networks.
abstract: In recent years, coordinated variations in brain morphology (e.g., volume, thickness) have been employed as a measure of structural association between brain regions to infer large-scale structural correlation networks. Recent evidence suggests that brain networks constructed in this manner are inherently more clustered than random networks of the same size and degree. Thus, null networks constructed by randomizing topology are not a good choice for benchmarking small-world parameters of these networks. In the present report, we investigated the influence of choice of null networks on small-world parameters of gray matter correlation networks in healthy individuals and survivors of acute lymphoblastic leukemia. Three types of null networks were studied: 1) networks constructed by topology randomization (TOP), 2) networks matched to the distributional properties of the observed covariance matrix (HQS), and 3) networks generated from correlation of randomized input data (COR). The results revealed that the choice of null network not only influences the estimated small-world parameters, it also influences the results of between-group differences in small-world parameters. In addition, at higher network densities, the choice of null network influences the direction of group differences in network measures. Our data suggest that the choice of null network is quite crucial for interpretation of group differences in small-world parameters of structural correlation networks. We argue that none of the available null models is perfect for estimation of small-world parameters for correlation networks and the relative strengths and weaknesses of the selected model should be carefully considered with respect to obtained network measures.
authors.affiliation: Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California, United States of America. hosseiny@stanford.edu
authors.forename: S M Hadi
authors.initials: SM
authors.lastname: Hosseini
authors.forename: Shelli R
authors.initials: SR
authors.lastname: Kesler
mesh_terms: D000293:Adolescent; D001921:Brain / Q000473:pathology / Q000503:physiopathology*; D016022:Case-Control Studies; D002648:Child; D002675:Child, Preschool; D016000:Cluster Analysis; D059907:Functional Neuroimaging; D006801:Humans; D008954:Models, Biological; D009415:Nerve Net / Q000473:pathology*; D054198:Precursor Cell Lymphoblastic Leukemia-Lymphoma / Q000473:pathology / Q000503:physiopathology; D055815:Young Adult