title: WHOLE BRAIN GROUP NETWORK ANALYSIS USING NETWORK BIAS AND VARIANCE PARAMETERS.
abstract: The disruption of normal function and connectivity of neural circuits is common across many diseases and disorders of the brain. This disruptive effect can be studied and analyzed using the brain's complex functional and structural connectivity network. Complex network measures from the field of graph theory have been used for this purpose in the literature. In this paper we have introduced a new approach for analyzing the brain connectivity network. In our approach the true connectivity network and each subject's bias and variance are estimated using a population of patients and healthy controls. These parameters can then be used to compare two groups of brain networks. We have used this approach for the comparison of the resting state functional MRI network of pediatric Tuberous Sclerosis Complex (TSC) patients and healthy subjects. We have shown that a significant difference between the two groups can be found. For validation, we have compared our findings with three well known complex network measures.
authors.affiliation: Computational Radiology Laboratory, Childrens Hospital Boston, and Harvard Medical School 300 Longwood Ave. Boston MA 02115 USA.
authors.forename: Alireza
authors.initials: A
authors.lastname: Akhondi-Asl
authors.affiliation: Computational Radiology Laboratory, Childrens Hospital Boston, and Harvard Medical School 300 Longwood Ave. Boston MA 02115 USA.
authors.forename: Arne
authors.initials: A
authors.lastname: Hans
authors.affiliation: Computational Radiology Laboratory, Childrens Hospital Boston, and Harvard Medical School 300 Longwood Ave. Boston MA 02115 USA.
authors.forename: Benoit
authors.initials: B
authors.lastname: Scherrer
authors.affiliation: Computational Radiology Laboratory, Childrens Hospital Boston, and Harvard Medical School 300 Longwood Ave. Boston MA 02115 USA.
authors.forename: Jurriaan M
authors.initials: JM
authors.lastname: Peters
authors.affiliation: Computational Radiology Laboratory, Childrens Hospital Boston, and Harvard Medical School 300 Longwood Ave. Boston MA 02115 USA.
authors.forename: Simon K
authors.initials: SK
authors.lastname: Warfield
keywords: Connectivity graph; Functional connectivity; Parcellation; Resting state fMRI; Tuberous Sclerosis Complex