Using graph theory to identify aberrant hierarchical patterns in parkinsonian brain networks

Abstract

The topology of complex brain networks allows efficient dynamic interactions between spatially distinct regions. Neuroimaging studies have provided consistent evidence of dysfunctional connectivity among the cortical circuitry in Parkinson's disease; however, little is known about the topological properties of brain networks underlying these alterations. This paper introduces a methodology to explore aberrant changes in hierarchical patterns of nodal centrality through cortical networks, combining graph theoretical analysis and morphometric connectivity. The edges in graph were estimated by correlation analysis and thresholding between 148 nodes defined by cortical regions. Our findings demonstrated that the networks organization was disrupted in the patients with PD. We found a reconfiguration in hierarchical weighting of high degree hubs in structural networks associated with levels of cognitive decline, probably related to a system-wide compensatory mechanism. Simulated targeted attack on the network's nodes as measures of network resilience showed greater effects on information flow in advanced stages of disease. © Springer-Verlag 2013.