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dc.contributor.authorFonseca, Andreen_US
dc.contributor.authorKerick, Scotten_US
dc.contributor.authorKing, Jung-Taien_US
dc.contributor.authorLin, Chin-Tengen_US
dc.contributor.authorJung, Tzyy-Pingen_US
dc.date.accessioned2019-04-02T05:58:41Z-
dc.date.available2019-04-02T05:58:41Z-
dc.date.issued2018-11-12en_US
dc.identifier.issn1662-5161en_US
dc.identifier.urihttp://dx.doi.org/10.3389/fnhum.2018.00418en_US
dc.identifier.urihttp://hdl.handle.net/11536/148450-
dc.description.abstractThe 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.en_US
dc.language.isoen_USen_US
dc.subjectdriversen_US
dc.subjectfatigueen_US
dc.subjectsleepen_US
dc.subjectactigraphyen_US
dc.subjectEEGen_US
dc.subjecteffective connectivityen_US
dc.subjectConvergent Cross Mappingen_US
dc.titleBrain Network Changes in Fatigued Drivers: A Longitudinal Study in a Real-World Environment Based on the Effective Connectivity Analysis and Actigraphy Dataen_US
dc.typeArticleen_US
dc.identifier.doi10.3389/fnhum.2018.00418en_US
dc.identifier.journalFRONTIERS IN HUMAN NEUROSCIENCEen_US
dc.citation.volume12en_US
dc.contributor.department腦科學研究中心zh_TW
dc.contributor.departmentBrain Research Centeren_US
dc.identifier.wosnumberWOS:000449908200001en_US
dc.citation.woscount0en_US
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