Investigating the Influence of Driving on Brain Connectivity Networks and Emotion Processing Mechanism Based on EEG Signals
Humans are frequently driving with different emotions, but how driving affects the human brain information processing mechanism in different emotional states is still unknown. In this study, we investigate the effects of driving on brain functional connectivity networks across different emotions based on electroencephalogram (EEG) signals. We utilize the phase lag index (PLI) to measure the degree of phase synchronization among electrode channels and visualize the functional connectivity networks. We also employ graph theory to analyze the functional connectivity networks. Our findings indicate that the strength of functional connectivity among brain regions under different emotions significantly increased after involving in driving, with more efficient and rapid information transmission in the functional connectivity networks. This enhancement is particularly evident in the frontal and parietal lobes, with 507 enhanced connections related to the frontal lobe and 300 related to the parietal lobe, accounting for 41.94% and 24.81% of the total enhanced connections, respectively. These results offer valuable insights into the understanding of how human drives, holding potential for the development of interventions and technologies to improve emotional regulation and driving safety technologies.
Authors
- Ling Zheng (ORCID: https://orcid.org/0000-0001-8292-1476)
- Guofa Li (ORCID: https://orcid.org/0000-0002-7889-4695)
- Chuzhao Li
- Feng Gao (ORCID: https://orcid.org/0000-0002-3136-1410)
- Long Zhang (ORCID: https://orcid.org/0009-0001-2746-533X)
- Paul Green (ORCID: https://orcid.org/0000-0002-1864-3931)
- Zhenning Li (ORCID: https://orcid.org/0000-0002-0877-6829)
Institutions
- Chongqing University (CN)
- Shenzhen University (CN)
- University of Macau (MO)
- University of Michigan (US)
- City University of Macau (MO)
Publication Details
- Journal
- IEEE Sensors Journal
- Published
- 2024-09-27
- DOI
- https://doi.org/10.1109/jsen.2024.3466124
- Citations
- 3
- Primary Topic
- EEG and Brain-Computer Interfaces
- Type
- article
- Field-Weighted Citation Impact
- 1.03
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Chongqing