Objective: We aimed to explore whether electroencephalography (EEG) could measure fatigue objectively and the pathophysiology of fatigue in PD.

Background: Fatigue is a common, frustrating non-motor symptom of Parkinson’s disease (PD), but its mechanism is unknown.

Method: We investigated 32 de novo PD patients who underwent electroencephalography (EEG). We compared brain activity between 19 PD patients without fatigue and 13 PD patients with fatigue via EEG power spectrum and graph theoretical network analysis including global efficiency (GE), characteristic path length (CPL), clustering coefficient (CCO), small worldness (SW), local efficiency (LE), degree centrality (DC), closeness centrality (CCE), and betweenness centrality (BC).

Results: Higher absolute powers for delta and alpha1 bands in the parieto-occipital area were observed in PD with fatigue (ps < 0.05), but these differences did not survive after multiple comparison corrections (all ps > 0.02, Bonferroni-corrected). In network analysis, the 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 without fatigue (ps > 0.002, p = 0.0039, ps >0.002, respectively, Bonferroni-corrected).

Conclusion: Our study suggests that PD patients with fatigue have less efficient networks in the frontal area compared with networks of those with PD without fatigue. These findings may explain why fatigue is common in PD, a frontostriatal disorder. Brain network analysis using graph theory is more valuable than power spectrum analysis in revealing the brain mechanism related to fatigue.

Acknowledgments

This abstract was presented at the Spring Congress of Korean Society of Clinical Neurophysiology in 2024.

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MDS Abstracts - https://www.mdsabstracts.org/abstract/fatigue-in-pd-is-related-to-decreased-efficiency-of-the-frontal-network/