Predicting individual decision-making responses based on the functional connectivity of resting-state EEG. (30th October 2019)

• Record Type: Journal Article
• Authors: Si, Yajing; Jiang, Lin; Tao, Qin; Chen, Chunli; Li, Fali; Jiang, Yuanling; Zhang, Tao; Cao, Xianyu; Wan, Feng; Yao, Dezhong; Xu, Peng
• Is Part Of: Journal of neural engineering. Volume 16:Number 6(2019:Dec.)
• Publication Date: 2019-10-30
• Subjects: decision-making -- resting-state -- brain network -- response prediction; Neurosciences -- Periodicals; Biomedical engineering -- Periodicals; 612.8
• DOI: 10.1088/1741-2552/ab39ce
• Languages: English
• ISSNs: 1741-2560

Abstract

Abstract: Objective . 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. Approach . 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. Main results . 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. Significance . 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.