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


Journal

PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081

Informations de publication

Date de publication:
2024
Historique:
received: 20 12 2023
accepted: 22 06 2024
medline: 15 8 2024
pubmed: 15 8 2024
entrez: 15 8 2024
Statut: epublish

Résumé

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.

Identifiants

pubmed: 39146301
doi: 10.1371/journal.pone.0306729
pii: PONE-D-23-40420
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0306729

Informations de copyright

Copyright: © 2024 Zhao et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

Auteurs

Yashuai Zhao (Y)

School of Urban Rail Transportation, Shanghai University of Engineering Science, Shanghai, P.R. China.

Yuanchun Huang (Y)

School of Urban Rail Transportation, Shanghai University of Engineering Science, Shanghai, P.R. China.

Zhigang Liu (Z)

School of Urban Rail Transportation, Shanghai University of Engineering Science, Shanghai, P.R. China.

Yifan Zhou (Y)

School of Urban Rail Transportation, Shanghai University of Engineering Science, Shanghai, P.R. China.

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