心理疲劳的神经机制——脑连接组的新见解

工程(英文) ›› 2019, Vol. 5 ›› Issue (2) : 276-286.

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PDF(1946 KB)
工程(英文) ›› 2019, Vol. 5 ›› Issue (2) : 276-286. DOI: 10.1016/j.eng.2018.11.025
研究论文
Research AI for Precision Medicine—Review

心理疲劳的神经机制——脑连接组的新见解

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Neural Mechanisms of Mental Fatigue Revisited: New Insights from the Brain Connectome

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Abstract

Maintaining sustained attention during a prolonged cognitive task often comes at a cost: high levels of mental fatigue. Heuristically, mental fatigue refers to a feeling of tiredness or exhaustion, and a disengagement from the task at hand; it manifests as impaired cognitive and behavioral performance. In order to effectively reduce the undesirable yet preventable consequences of mental fatigue in many real-world workspaces, a better understanding of the underlying neural mechanisms is needed, and continuous efforts have been devoted to this topic. In comparison with conventional univariate approaches, which are widely utilized in fatigue studies, convergent evidence has shown that multivariate functional connectivity analysis may lead to richer information about mental fatigue. In fact, mental fatigue is increasingly thought to be related to the deviated reorganization of functional connectivity among brain regions in recent studies. In addition, graph theoretical analysis has shed new light on quantitatively assessing the reorganization of the brain functional networks that are modulated by mental fatigue. This review article begins with a brief introduction to neuroimaging studies on mental fatigue and the brain connectome, followed by a thorough overview of connectome studies on mental fatigue. Although only a limited number of studies have been published thus far, it is believed that the brain connectome can be a useful approach not only for the elucidation of underlying neural mechanisms in the nascent field of neuroergonomics, but also for the automatic detection and classification of mental fatigue in order to address the prevention of fatigue-related human error in the near future.

Keywords

Mental fatigue / Functional connectivity / Graph theoretical analysis / Brain network

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. . Engineering. 2019, 5(2): 276-286 https://doi.org/10.1016/j.eng.2018.11.025

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Acknowledgements

This work was supported by the “Hundred Talents Program” of Zhejiang University (awarded to Yu Sun), by the Fundamental Research Funds for the Central Universities (2018QNA5017, awarded to Yu Sun), and by the National Natural Science Foundation of China (81801785, awarded to Yu Sun). The authors would also like to thank the National University of Singapore for supporting the Cognitive Engineering Group at the Singapore Institute for Neurotechnology (R-719-001-102-232, awarded to Nitish Thakor). This work was supported in part by the Ministry of Education of Singapore (MOE2014-T2-1-115, awarded to Anastasios Bezerianos) and the Shanghai Sailing Program (17YF1420400, awarded to Peng Qi).
Compliance with ethics guidelines

Peng Qi, Hua Ru, Lingyun Gao, Xiaobing Zhang, Tianshu Zhou, Yu Tian, Nitish Thakor, Anastasios Bezerianos, Jinsong Li, and Yu Sun declare that they have no conflict of interest or financial conflicts to disclose.

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