Background: Graph theory (GT) is a mathematical field that analyses complex networks that can be applied to neuroimaging to quantify brain's functional systems in Parkinson's disease (PD) and essential tremor (ET).
Objectives: To evaluate the functional connectivity (FC) measured by the global efficiency (GE) of the motor network in PD and compare it to ET and healthy controls (HC), and correlate it to clinical parameters.
Methods: 103 subjects (54PD, 18ET, 31HC) were submitted to structural and functional MRI. A network was designed with regions of interest (ROIs) involved in motor function, and GT was applied to determine its GE. Clinical parameters were analyzed as covariates to estimate the impact of disease severity and medication on GE.
Results: GE of the motor circuit was reduced in PD in comparison with HC (p .042). Areas that most contributed to it were left supplementary motor area (SMA) and bilateral postcentral gyrus. Tremor scores correlated positively with GE of the motor network in PD subgroups. For ET, there was an increase in the connectivity of the anterior cerebellar network to the other ROIs of the motor circuit in comparison with PD.
Conclusions: FC measured by the GE of the motor network is diminished in PD in comparison with HC, especially due to decreased connectivity of left SMA and bilateral postcentral gyrus. This finding supports the theory that there is a global impairment of the motor network in PD, and it does not affect just the basal ganglia, but also areas associated with movement modulation. The ET group presented an increased connectivity of the anterior cerebellar network to the other ROIs of the motor circuit when compared to PD, which reinforces what it is known about its role in this pathology.
Keywords: functional connectivity; functional magnetic resonance imaging; graph theory; movement disorders; tremor physiology.
© 2021 The Authors. Brain and Behavior published by Wiley Periodicals LLC.