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Graph theory network function in Parkinson's disease assessed with electroencephalography.

Rene L Utianski1, John N Caviness2, Elisabeth C W van Straaten3

  • 1Department of Neurology, Mayo Clinic, Rochester, MN, USA.

Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology
|April 14, 2016
PubMed
Summary

Graph theory analysis of electroencephalography (EEG) reveals distinct network alterations in Parkinson's disease (PD). These changes in brain network measures correlate with cognitive decline in PD patients.

Keywords:
BiomarkerDementiaEEGNetworkParkinson’s diseasePathologySynucleinopathy

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Area of Science:

  • Neuroscience
  • Network Science
  • Medical Imaging

Background:

  • Parkinson's disease (PD) is a neurodegenerative disorder affecting motor function and cognition.
  • Cognitive impairment is common in PD, ranging from mild cognitive impairment (PD-MCI) to dementia (PD-D).
  • Understanding the neural underpinnings of cognitive changes in PD is crucial for diagnosis and treatment.

Purpose of the Study:

  • To investigate differences in graph theory network measures derived from electroencephalography (EEG) between cognitively normal Parkinson's disease (PD-CN) patients and healthy controls.
  • To compare network measures between PD-CN and Parkinson's disease dementia (PD-D) patients.
  • To explore the relationship between network measures and cognitive performance in PD.

Main Methods:

  • Electroencephalography (EEG) recordings were analyzed using graph theory network analysis.
  • Key metrics quantified included global efficiency and local integration.
  • Minimal spanning tree analysis was employed, with statistical comparisons using t-tests and correlations.

Main Results:

  • Increased local integration was observed across all frequency bands in PD-CN compared to controls.
  • A decrease in local integration within the alpha1 frequency band was found in PD-D compared to PD-CN.
  • Similar network alterations were noted in PD-MCI as in PD-D, with correlations between network measures and global cognitive performance in PD.

Conclusions:

  • Distinct patterns of network measure alteration and breakdown characterize Parkinson's disease and cognitive decline within PD.
  • These findings suggest specific abnormalities in cortical area interactions contributing to PD symptoms across disease stages.
  • Graph theory analysis of EEG data highlights network alterations as key features of PD cortical dysfunction pathophysiology.