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The architecture of functional brain network modulated by driving under train running noise exposure

Zhao, Yashuai ; Huang, Yuanchun ; Liu, Zhigang ; Zhou, Yifan

PloS one, 2024-08, Vol.19 (8), p.e0306729 [Periódico revisado por pares]

San Francisco: Public Library of Science

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Título:
The architecture of functional brain network modulated by driving under train running noise exposure
Autor: Zhao, Yashuai ; Huang, Yuanchun ; Liu, Zhigang ; Zhou, Yifan
Assuntos: Analysis ; Attention ; Band theory ; Biology and Life Sciences ; Brain ; Brain architecture ; Brain research ; Clustering ; Computer and Information Sciences ; Decision making ; Driving ability ; Efficiency ; Electroencephalography ; Experiments ; Fatigue ; Frequencies ; Frequency ranges ; Graph theory ; Human factors research ; Light rail transit ; Medicine and Health Sciences ; Networks ; Neural networks ; Noise control ; Noise levels ; Noise reduction ; Phase lag ; Physical Sciences ; Physiology ; Research and Analysis Methods ; Running ; Simulation ; Synchronism ; Theta rhythms ; Traffic accidents ; Urban rail ; Vehicle safety
É parte de: PloS one, 2024-08, Vol.19 (8), p.e0306729
Notas: ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Competing Interests: The authors have declared that no competing interests exist.
Descrição: A noisy environment can considerably impact drivers' attention and fatigue, endangering driving safety. Consequently, this study designed a simulated driving experimental scenario to analyse the effects of noise generated during urban rail transit train operation on drivers' functional brain networks. The experiment recruited 16 participants, and the simulated driving scenario was conducted at noise levels of 50, 60, 70, and 80 dB. Functional connectivity between all electrode pairs across various frequency bands was evaluated using the weighted phase lag index (WPLI), and a brain network based on this was constructed. Graph theoretic analysis employed network global efficiency, degree, and clustering coefficient as metrics. Significant increases in the WPLI values of theta and alpha frequency bands were observed in high noise environments (70 dB, 80 dB), as well as enhanced brain synchronisation. Furthermore, concerning the topological metrics of brain networks, it was observed that the global efficiency of brain networks in theta and alpha frequency ranges, as well as the node degree and clustering coefficients, experienced substantial growth in high noise environments (70 dB, 80 dB) as opposed to 50 dB and 60 dB. This finding indicates that high-noise environments impact the reorganisation of functional brain networks, leading to a preference for network structures with improved global efficiency. Such findings may improve our understanding of the neural mechanisms of driving under noise exposure, and thus potentially reduce road accidents to some extent.
Editor: San Francisco: Public Library of Science
Idioma: Inglês

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The architecture of functional brain network modulated by driving under train running noise exposure

Zhao, Yashuai ; Huang, Yuanchun ; Liu, Zhigang ; Zhou, Yifan

San Francisco: Public Library of Science

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