Functional connectivity analysis of mental fatigue reveals different network topological alterations between driving and vigilance tasks

Georgios N. Dimitrakopoulos, Ioannis Kakkos, Zhongxiang Dai, Hongtao Wang, Kyriakos Sgarbas, Nitish V Thakor, Anastasios Bezerianos, Yu SUN

Research output: Contribution to journalArticle

Abstract

Despite the apparent importance of mental fatigue detection, a reliable application is hindered due to the incomprehensive understanding of the neural mechanisms of mental fatigue. In this paper, we investigated the topological alterations of functional brain networks in the theta band (4 — 7 Hz) of electroencephalography (EEG) data from 40 male subjects undergoing two distinct fatigue-inducing tasks: a low-intensity one-hour simulated driving and a high-demanding half-hour sustained attention task (psychomotor vigilance task, PVT). Behaviorally, subjects demonstrated a robust mental fatigue effect, as reflected by significantly declined performances in cognitive tasks prior and post these two tasks. Furthermore, characteristic path length presented a positive correlation with task duration, which led to a significant increase between the first and last 5 min of both tasks, indicating a fatigue-related disruption in information processing efficiency. However, significantly increased clustering coefficient was revealed only in the driving task, suggesting distinct network reorganizations between the two fatigue-inducing tasks. Moreover, high accuracy (92% for driving; 97% for PVT) was achieved for fatigue classification with apparently different discriminative functional connectivity features. These findings augment our understanding of the complex nature of fatigue-related neural mechanisms and demonstrate the feasibility of using functional connectivity as neural biomarkers for applicable fatigue monitoring.

Original languageEnglish (US)
JournalIEEE Transactions on Neural Systems and Rehabilitation Engineering
DOIs
StateAccepted/In press - Jan 11 2018
Externally publishedYes

Fingerprint

Mental Fatigue
Functional analysis
Fatigue
Fatigue of materials
Automatic Data Processing
Cluster Analysis
Electroencephalography
Biomarkers
Brain

Keywords

  • classification
  • Electroencephalography
  • Electronic mail
  • Fatigue
  • functional connectivity
  • graph theoretical analysis
  • Life sciences
  • mental fatigue
  • Niobium
  • theta band

ASJC Scopus subject areas

  • Neuroscience(all)
  • Biomedical Engineering
  • Computer Science Applications

Cite this

Functional connectivity analysis of mental fatigue reveals different network topological alterations between driving and vigilance tasks. / Dimitrakopoulos, Georgios N.; Kakkos, Ioannis; Dai, Zhongxiang; Wang, Hongtao; Sgarbas, Kyriakos; Thakor, Nitish V; Bezerianos, Anastasios; SUN, Yu.

In: IEEE Transactions on Neural Systems and Rehabilitation Engineering, 11.01.2018.

Research output: Contribution to journalArticle

Dimitrakopoulos, Georgios N. ; Kakkos, Ioannis ; Dai, Zhongxiang ; Wang, Hongtao ; Sgarbas, Kyriakos ; Thakor, Nitish V ; Bezerianos, Anastasios ; SUN, Yu. / Functional connectivity analysis of mental fatigue reveals different network topological alterations between driving and vigilance tasks. In: IEEE Transactions on Neural Systems and Rehabilitation Engineering. 2018.
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