Differences in the intra-cerebellar connections and graph theoretical measures between Parkinson's disease and multiple system atrophy

J Neurol Sci. 2019 May 15:400:129-134. doi: 10.1016/j.jns.2019.03.022. Epub 2019 Mar 25.

Abstract

Background and purpose: Parkinson's disease (PD) does not present with motor symptoms until dopaminergic neuronal loss exceeds 50%. This might indicate that a network-level compensatory mechanism involving surviving regions in PD acts to reduce brain abnormalities. In contrast, there is no evidence of a compensatory mechanism in multiple system atrophy (MSA). We hypothesized that a comparison of these two diseases would help to identify compensatory effects in PD.

Methods: We recruited 23 patients with PD, 11 patients with MSA, and 11 controls that showed an aging brain but no neurological deficits. All subjects underwent resting state functional magnetic resonance imaging (fMRI). Regions of interest were defined according to the motor network related to the basal ganglia and cerebellum. Network-level analyses were performed.

Results: Network-based statistical analyses revealed that functional connectivity in PD brains was reduced between cerebellar lobules IX on both sides and vermis X, as compared with MSA brains. Transitivity was reduced in MSA as compared with controls.

Conclusion: We demonstrated that a part of the intra-cerebellar connectivity was reduced in PD, and that network segregation was reduced in MSA. However, there was no evidence of compensatory effects in PD.

Keywords: Cerebellum; Functional magnetic resonance imaging; Graph theory; Multiple system atrophy; Parkinson's disease.

MeSH terms

  • Aged
  • Aged, 80 and over
  • Cerebellum / diagnostic imaging*
  • Cerebellum / physiopathology
  • Female
  • Humans
  • Magnetic Resonance Imaging / methods*
  • Male
  • Middle Aged
  • Multiple System Atrophy / diagnostic imaging*
  • Multiple System Atrophy / physiopathology
  • Nerve Net / diagnostic imaging*
  • Nerve Net / physiopathology
  • Parkinson Disease / diagnostic imaging*
  • Parkinson Disease / physiopathology