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Engineering >> 2019, Volume 5, Issue 2 doi: 10.1016/j.eng.2018.11.025

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

a Department of Control Science and Engineering, College of Electronics and Information Engineering, Tongji University, Shanghai
200092, China

b Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, Zhejiang University,
Zhejiang, 310000, China

c Department of Neurosurgery, Shaoxing People’s Hospital (Shaoxing Hospital, Zhejiang University School of Medicine), Zhejiang,
312000, China

d Singapore Institute for Neurotechnology (SINAPSE), Centre for Life Science, National University of Singapore, 117456, Singapore

Received: 2018-05-24 Revised: 2018-10-15 Accepted: 2018-11-08 Available online: 2019-02-23

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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.


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