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Brain Network Analysis Reveals Age-related Differences in Topological Reorganization During Vigilance Decline
Author(s) -
Lingyun Gao,
Zhang Rui,
Mengru Xu,
Yi Sun,
Gang Li,
Yu Sun
Publication year - 2025
Publication title -
ieee transactions on neural systems and rehabilitation engineering
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 1.093
H-Index - 140
eISSN - 1558-0210
pISSN - 1534-4320
DOI - 10.1109/tnsre.2025.3598197
Subject(s) - bioengineering , computing and processing , robotics and control systems , signal processing and analysis , communication, networking and broadcast technologies
To mitigate the economic losses and safety risks caused by reduced alertness of individuals in the context of an aging workforce, mental fatigue among the elderly is an issue worthy of in-depth exploration. Despite convergent studies on cognitive aging, the differential alterations in brain network topology between the elderly and young individuals during vigilance decline remain unclear. Here, a prolonged 30-min psychomotor vigilance task (PVT) was employed to induce mental fatigue, where both behavioral performance and electroencephalography (EEG) data were collected from healthy elderly (n = 30) and young participants (n = 40). Subsequently, EEG functional connectivity was constructed and the differences in network topological properties between the two groups were quantitatively evaluated based on global and nodal metrics. Both groups exhibited age-independent significant decline in behavioral performance with time on task. Moreover, age-related dysconnectivity pattern was revealed over a wide frequency range (1−45 Hz) in the elderly group, which further developed toward less optimal network architecture. Specifically, significant deficit of nodal efficiency was revealed in most of the brain regions with frontal area exhibited significant age-by-time interaction effect, attributing to a significant decline in the elderly group. Statistically significant correlation between behavioral and network metrics was also found. Overall, our results provide some of the first quantitative insights for revealing the neural mechanisms of age differences during mental fatigue, which may contribute to the rational arrangement of personnel in real-world scenarios with high alertness demands.

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