Citation

Fonseca A, Kerick S, King JT, Lin CT, Jung TP. Front. Hum. Neurosci. 2018; 12: e418.

Affiliation

Swartz Center for Computational Neuroscience, University of California, San Diego, La Jolla, CA, United States.

Copyright

(Copyright © 2018, Frontiers Research Foundation)

DOI

10.3389/fnhum.2018.00418

PMID

30483080

PMCID

PMC6240698

Abstract

The analysis of neurophysiological changes during driving can clarify the mechanisms of fatigue, considered an important cause of vehicle accidents. The fluctuations in alertness can be investigated as changes in the brain network connections, reflected in the direction and magnitude of the information transferred. Those changes are induced not only by the time on task but also by the quality of sleep. In an unprecedented 5-month longitudinal study, daily sampling actigraphy and EEG data were collected during a sustained-attention driving task within a near-real-world environment. Using a performance index associated with the subjects' reaction times and a predictive score related to the sleep quality, we identify fatigue levels in drivers and investigate the shifts in their effective connectivity in different frequency bands, through the analysis of the dynamical coupling between brain areas. Study results support the hypothesis that combining EEG, behavioral and actigraphy data can reveal new features of the decline in alertness. In addition, the use of directed measures such as the Convergent Cross Mapping can contribute to the development of fatigue countermeasure devices.

Language: en

Keywords

Convergent Cross Mapping; EEG; actigraphy; drivers; effective connectivity; fatigue; sleep