Mental fatigue decreases complexity: Evidence from multiscale entropy analysis of instantaneous frequency variation in alpha rhythm

• Published in: Frontiers in human neuroscience Vol. 16; p. 906735
• Main Authors: Zhai, Yawen, Li, Yan, Zhou, Shengyi, Zhang, Chenxu, Luo, Erping, Tang, Chi, Xie, Kangning
• Format: Journal Article
• Language: English
• Published: Lausanne Frontiers Research Foundation 26.10.2022; Frontiers Media S.A
• Subjects: Alzheimer's disease; auditory steady-state response; Cognitive ability; complexity; Diabetes; EEG; Electroencephalography; Entropy; Fatigue; Human Neuroscience; mental fatigue; multiscale entropy; nonlinear analysis; Sleep; Sound; Time series
• ISSN: 1662-5161; 1662-5161
• DOI: 10.3389/fnhum.2022.906735

Mental fatigue (MF) jeopardizes performance and safety through a variety of cognitive impairments and according to the complexity loss theory, should represent “complexity loss” in electroencephalogram (EEG). However, the studies are few and inconsistent concerning the relationship between MF and loss of complexity, probably because of the susceptibility of brain waves to noise. In this study, MF was induced in thirteen male college students by a simulated flight task. Before and at the end of the task, spontaneous EEG and auditory steady-state response (ASSR) were recorded and instantaneous frequency variation (IFV) in alpha rhythm was extracted and analyzed by multiscale entropy (MSE) analysis. The results show that there were significant differences in IFV in alpha rhythm either from spontaneous EEG or from ASSR for all subjects. Therefore, the proposed method can be effective in revealing the complexity loss caused by MF in spontaneous EEG and ASSR, which may serve as a promising analyzing method to mark mild mental impairments.