Anxiety in Parkinson's disease: A resting-state high density EEG study

Nacim Betrouni*, Edouard Alazard, Madli Bayot, Guillaume Carey, Philippe Derambure, Luc Defebvre, Albert Fg Leentjens, Arnaud Delval, Kathy Dujardin

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

34 Downloads (Pure)

Abstract

OBJECTIVE: To identify markers of Parkinson's disease (PD) related anxiety, using high density electroencephalography (hd-EEG).

METHODS: 108 patients participated in the study. They were divided into two groups: with and without clinically relevant anxiety, according to their score on the Parkinson Anxiety Scale. Resting-state hd-EEG was recorded. Spectral and functional connectivity characteristics were compared between the two groups.

RESULTS: Thirty-three patients (31%) had significant anxiety symptoms. In the spectral analysis, relative power in the alpha1 frequency band in the right prefrontal cortex was lower in patients with anxiety than without. Functional connectivity analysis showed a stronger connectivity between the left insula and several regions of the right prefrontal cortex in patients with anxiety than in those without.

CONCLUSION: This study shows the pivotal role of the insula and frontal cortex in the pathophysiology of anxiety in PD and extends the results of previous studies using magnetic resonance imaging or positron emission tomography imaging.

Original languageEnglish
Pages (from-to)202-211
Number of pages10
JournalNeurophysiologie Clinique-Clinical Neurophysiology
Volume52
Issue number3
Early online date15 Jan 2022
DOIs
Publication statusPublished - Jun 2022

Keywords

  • ALPHA-OSCILLATIONS
  • Anxiety disorders
  • CORRELATE
  • CORTEX
  • DISORDER
  • Electroencephalo-graphy
  • FUNCTIONAL CONNECTIVITY
  • Functional connectivity
  • RATING-SCALE
  • SYSTEM
  • Spectral analysis
  • VALIDATION

Fingerprint

Dive into the research topics of 'Anxiety in Parkinson's disease: A resting-state high density EEG study'. Together they form a unique fingerprint.

Cite this