Graph theory-based analysis of functional connectivity changes in brain networks underlying cognitive fatigue: An EEG study

作者：Yabing Lou, Ruibin Pi, Ruifeng Sun, Jilin Wu, Wei Wang, Ziman Zhu, Tengteng Dai, Weijun Gong · 发表于：PLoS ONE · 年份：2025 · DOI：10.1371/journal.pone.0329212 · 被引用次数：11 · 研究领域：Functional Brain Connectivity Studies、Sleep and Work-Related Fatigue、EEG and Brain-Computer Interfaces

OBJECTIVE: This investigation was designed to analyze alterations in functional connectivity across brain networks associated with cognitive fatigue through electroencephalogram (EEG) data analysis. Through the application of both global and local graph-theoretical metrics to characterize the topology of brain networks, this study establishes a conceptual framework supporting enhanced detection of cognitive fatigue manifestations while facilitating examination of its neurophysiological substrates. METHODS: The study cohort comprised neurologically intact individuals aged 20-35 years, recruited from Beijing Rehabilitation Hospital, Capital Medical University between February 6 and September 30, 2024 for participation in a cognitive fatigue induction task. Following acquisition of written informed consent, data before and after the task were obtained, including both subjective fatigue assessments using the Visual analog scale for fatigue (VAS-F) scores and EEG data. The preprocessed EEG signals were segmented into three frequency bands: θ (4-8 Hz),α (8-13 Hz), and β (13-30 Hz). To determine the frequency band exhibiting maximal sensitivity to cognitive fatigue, cross-band comparative power spectral density (PSD) was implemented. The selected frequency band subsequently served as the basis for weighted Phase Lag Index (wPLI) computation, yielding a functional connectivity matrix derived from wPLI measurements. Network topology was evaluated through application of five global gra...