Parkinson’s disease speech production network as determined by graph-theoretical network analysis

Abstract

Parkinson’s disease (PD) can affect speech as well as emotion processing. We employ wholebrain graph-theoretical network analysis to determine how the speech-processing network (SPN) changes in PD, and assess its susceptibility to emotional distraction. Functional magnetic resonance images of 14 patients (aged 59.6 ± 10.1 years, 5 female) and 23 healthy controls (aged 64.1 ± 6.5 years, 12 female) were obtained during a picture-naming task. Pictures were supraliminally primed by face pictures showing either a neutral or an emotional expression. PD network metrics were significantly decreased (mean nodal degree, p < 0.0001; mean nodal strength, p < 0.0001; global network efficiency, p < 0.002; mean clustering coefficient, p < 0.0001), indicating an impairment of network integration and segregation. There was an absence of connector hubs in PD. Controls exhibited key network hubs located in the associative cortices, of which most were insusceptible to emotional distraction. The PD SPN had more key network hubs, which were more disorganized and shifted into auditory, sensory, and motor cortices after emotional distraction. The whole-brain SPN in PD undergoes changes that result in (a) decreased network integration and segregation, (b) amodularization of information flow within the network, and (c) the inclusion of primary and secondary cortical areas after emotional distraction.