The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China. School of Life Science and Technology, a Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu 611731, People's Republic of China.
J Neural Eng. 2019 Oct 30;16(6):066025. doi: 10.1088/1741-2552/ab39ce.
Despite increasing evidence revealing the relationship between task-related brain activity and decision-making, the association between resting-state functional connectivity and decision-making remains unknown.
In this study, we investigated the potential relationship between the network revealed in the resting-state electroencephalogram (EEG) and decision responses and further predicted individuals' acceptance rates during the ultimatum game (UG) based on the functional connectivity revealed in the resting-state EEG.
The results of this study demonstrated a significant relationship between the resting-state frontal-occipital connectivity and the UG acceptance rate in the alpha band. Increased acceptance rates were accompanied by a larger clustering coefficient and global and local efficiency as well as a shorter characteristic path length. Compared to the low-acceptance group, the high-acceptance group exhibited stronger frontal-occipital linkages. Finally, a multiple linear regression model based on the resting-state EEG network properties was adopted to predict the acceptance rates when subjects made their decision in the UG task.
Together, the findings of this study may deepen our knowledge of decision-making and provide a potential physiological biomarker to predict the decision-making responses of subjects.
尽管越来越多的证据揭示了任务相关脑活动与决策之间的关系，但静息态功能连接与决策之间的关联仍不清楚。
本研究通过静息态脑电图（EEG），探讨了静息态 EEG 网络与决策反应之间的潜在关系，并进一步预测了个体在最后通牒博弈（UG）中的接受率。
本研究结果表明，静息态额枕部连接与 UG 中的 alpha 波段接受率之间存在显著关系。较高的接受率伴随着聚类系数以及全局和局部效率的增加，同时特征路径长度变短。与低接受率组相比，高接受率组表现出更强的额枕部连接。最后，采用基于静息态 EEG 网络特性的多元线性回归模型，预测了被试在 UG 任务中做出决策时的接受率。
综上所述，本研究结果可能加深我们对决策的理解，并为预测被试的决策反应提供潜在的生理生物标志物。
