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Original Article
- Fatigue in Parkinson’s Disease Is Due to Decreased Efficiency of the Frontal Network: Quantitative EEG Analysis
- Min Seung Kim, Sanguk Park, Ukeob Park, Seung Wan Kang, Suk Yun Kang
- J Mov Disord. 2024;17(3):304-312. Published online June 10, 2024
- DOI: https://doi.org/10.14802/jmd.24038
- 5,427 View
- 135 Download
- 7 Web of Science
- 7 Crossref
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Abstract
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Supplementary Material - Objective
Fatigue 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.
Methods
We 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.
Results
No 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).
Conclusion
Our 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. -
Citations
Citations to this article as recorded by
- The role of exercise and lifestyle factors in fatigue among Parkinson’s disease patients: a cross-sectional study
Sohaila Alshimemeri, Abdullah M. Shadid, Ibrahim A. Alsannat, Nada K. Alamri, Raghad A. Almuslih
Neurological Sciences.2026;[Epub] CrossRef - Behavioral disorders in Parkinson disease: current view
Kurt A. Jellinger
Journal of Neural Transmission.2025; 132(2): 169. CrossRef - Functional connectivity in burnout syndrome: a resting-state EEG study
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Frontiers in Human Neuroscience.2025;[Epub] CrossRef - Pain and fatigue in Parkinson’s disease: advances in diagnosis and management
Michele Tinazzi, Christian Geroin, Mattia Siciliano, Marialuisa Gandolfi, Ilaria Di Vico, Rosa De Micco, Alessandro Tessitore
Neurological Sciences.2025; 46(6): 2437. CrossRef - Neural Correlates of Burnout Syndrome Based on Electroencephalography (EEG)—A Mechanistic Review and Discussion of Burnout Syndrome Cognitive Bias Theory
James Chmiel, Agnieszka Malinowska
Journal of Clinical Medicine.2025; 14(15): 5357. CrossRef - Fatigue and neuropsychiatric symptoms in Parkinson’s disease: a narrative review
Lidia Bojtos, Jon Rodríguez-Antigüedad, Javier Pagonabarraga, Saül Martínez-Horta, Jaime Kulisevsky
Frontiers in Neurology.2025;[Epub] CrossRef - Modeling Working Memory in Neurodegeneration: A Focus on EEG Methods
Yuliya Komarova, Alexander Zakharov, Mariya Sergeeva, Natalia Romanchuk, Tatyana Vladimirova, Igor Shirolapov
Diagnostics.2025; 15(23): 2992. CrossRef
- The role of exercise and lifestyle factors in fatigue among Parkinson’s disease patients: a cross-sectional study
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