Functional brain networks and cognitive deficits in Parkinson's disease

Abstract

Graph-theoretical analyses of functional networks obtained with resting-state functional magnetic resonance imaging (fMRI) have recently proven to be a useful approach for the study of the substrates underlying cognitive deficits in different diseases. We used this technique to investigate whether cognitive deficits in Parkinson's disease (PD) are associated with changes in global and local network measures. Thirty-six healthy controls (HC) and 66 PD patients matched for age, sex, and education were classified as having mild cognitive impairment (MCI) or not based on performance in the three mainly affected cognitive domains in PD: attention/executive, visuospatial/visuoperceptual (VS/VP), and declarative memory. Resting-state fMRI and graph theory analyses were used to evaluate network measures. We have found that patients with MCI had connectivity reductions predominantly affecting long-range connections as well as increased local interconnectedness manifested as higher measures of clustering, small-worldness, and modularity. The latter measures also tended to correlate negatively with cognitive performance in VS/VP and memory functions. Hub structure was also reorganized: normal hubs displayed reduced centrality and degree in MCI PD patients. Our study indicates that the topological properties of brain networks are changed in PD patients with cognitive deficits. Our findings provide novel data regarding the functional substrate of cognitive impairment in PD, which may prove to have value as a prognostic marker.