ArticleJournal of movement disorders2024
Fatigue in Parkinson's Disease Is Due to Decreased Efficiency of the Frontal Network: Quantitative EEG Analysis.
Article in Journal of movement disorders, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- A Dual-Modal Biosensing Approach to Evaluate Cortico-Muscular Coupling in Adolescent Idiopathic Scoliosis.Biosensors · 2026Article
- Modeling Working Memory in Neurodegeneration: A Focus on EEG Methods.Diagnostics (Basel, Switzerland) · 2025Review
- Neural Correlates of Burnout Syndrome Based on Electroencephalography (EEG)-A Mechanistic Review and Discussion of Burnout Syndrome Cognitive Bias Theory.Journal of clinical medicine · 2025Review
- Functional connectivity in burnout syndrome: a resting-state EEG study.Frontiers in human neuroscience · 2025Article
- Fatigue and neuropsychiatric symptoms in Parkinson's disease: a narrative review.Frontiers in neurology · 2025Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
objectiveFatigue is a common, debilitating nonmotor symptom of Parkinson's disease (PD), but its mechanism is poorly understood. We aimed to determine whether electroencephalography (EEG) could objectively measure fatigue and to explore the pathophysiology of fatigue in PD.
methodsWe studied 32 de novo PD patients who underwent EEG. We compared brain activity between 19 PD patients without fatigue and 13 PD patients with fatigue via EEG power spectra and graphs, including the global efficiency, characteristic path length, clustering coefficient, small-worldness, local efficiency, degree centrality, closeness centrality, and betweenness centrality.
resultsNo significant differences in absolute or relative power were detected between PD patients without or with fatigue (all p > 0.02, Bonferroni-corrected). According to our network analysis, brain network efficiency differed by frequency band. Generally, the brain network in the frontal area for theta and delta bands showed greater efficiency, and in the temporal area, the alpha1 band was less efficient in PD patients without fatigue (p < 0.0001, p = 0.0011, and p = 0.0007, respectively, Bonferroni-corrected).
conclusionOur study suggests that PD patients with fatigue have less efficient networks in the frontal area than PD patients without fatigue. These findings may explain why fatigue is common in PD, a frontostriatal disorder. Increased efficiency in the temporal area in PD patients with fatigue is assumed to be compensatory. Brain network analysis using graph theory is more valuable than power spectrum analysis in revealing the brain mechanism related to fatigue.
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