Brain mechanisms underlying the influence of emotions on spatial decision-making: An EEG study

被引:5
|
作者
Zhao, Yanyan [1 ,2 ]
Wang, Danli [1 ,2 ]
Wang, Xinyuan [1 ,2 ]
Chiu, Steve C. C. [3 ]
机构
[1] Chinese Acad Sci, Inst Automation, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China
[2] Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
[3] Idaho State Univ, ECE Dept, Pocatello, ID USA
基金
中国国家自然科学基金;
关键词
emotion; decision-making; spatial task; electroencephalography (EEG); microstate analysis; effective connectivity analysis; graph theoretical analysis; event-related potentials (ERP); FEEDBACK-RELATED NEGATIVITY; RETROSPLENIAL CORTEX; WORKING-MEMORY; THETA ACTIVITY; REWARD; RISKY; CONNECTIVITY; PARIETAL; LESIONS; FEAR;
D O I
10.3389/fnins.2022.989988
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
It is common for people to make bad decisions because of their emotions in life. When these decisions are important, such as aeronautical decisions and driving decisions, the mistakes of decisions can cause irreversible damage. Therefore, it is important to explore how emotions influence decision-making, so as to avoid the negative influence of emotions on decision-making as much as possible. Although existing researchers have found some mechanisms of emotion's influence on decision-making, only a few studies focused on the influence of emotions on decision-making based on electroencephalography (EEG). In addition, most of them were focused on risky and uncertain decision-making. We designed a novel experimental task to explore the influence of emotion on spatial decision-making and recorded subjective data, decision-making behavioral data, and EEG data. By analyzing these data, we came to three conclusions. Firstly, we observed three similar event-related potentials (ERP) microstates in the decision-making process under different emotions by microstate analysis. Additionally, the prefrontal, parietal and occipital lobes played key roles in decision-making. Secondly, we found that the P2 component of the prefrontal lobe presented the influence of different emotions on decision-making by ERP analysis. Among them, positive emotion evoked the largest P2 amplitude compared to negative emotions and no stimuli. Thirdly, we found some graph metrics that were significantly associated with decision accuracy by effective connectivity analysis combined with graph theoretic analysis. In consequence, the finding of our study may shed more light on the brain mechanisms underlying the influence of emotions on spatial decision-making, thereby providing a basis for avoiding decision-making accidents caused by emotions and realizing better decision-making.
引用
收藏
页数:16
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