Residential College | false |
Status | 已發表Published |
Predicting individual decision-making responses based on the functional connectivity of resting-state EEG | |
Si,Yajing1,2; Jiang,Lin1,2; Tao,Qin1,2; Chen,Chunli1,2; Li,Fali1,2; Jiang,Yuanling1,2; Zhang,Tao1,2,3; Cao,Xianyu1,2; Wan,Feng4; Yao,Dezhong1,2; Xu,Peng1,2 | |
2019-12 | |
Source Publication | Journal of Neural Engineering |
ISSN | 1741-2560 |
Volume | 16Issue:6Pages:066025 |
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. |
Keyword | Decision-making Resting-state Brain Network Response Prediction |
DOI | 10.1088/1741-2552/ab39ce |
URL | View the original |
Indexed By | SCIE |
Language | 英語English |
WOS Research Area | Engineering ; Neurosciences & Neurology |
WOS Subject | Engineering, Biomedical ; Neurosciences |
WOS ID | WOS:000503794000001 |
Publisher | IOP Publishing LtdTEMPLE CIRCUS, TEMPLE WAY, BRISTOL BS1 6BE, ENGLAND |
Scopus ID | 2-s2.0-85074305244 |
Fulltext Access | |
Citation statistics | |
Document Type | Journal article |
Collection | DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING |
Corresponding Author | Xu,Peng |
Affiliation | 1.Clinical Hospital of Chengdu Brain Science Institute,MOE Key Lab for Neuroinformation,University of Electronic Science and Technology of China,Chengdu,611731,China 2.School of Life Science and Technology,Center for Information in BioMedicine,University of Electronic Science and Technology of China,Chengdu,611731,China 3.Xihua University,Chengdu,610039,China 4.Faculty of Science and Technology,University of Macau,Macau,999078,Macao |
Recommended Citation GB/T 7714 | Si,Yajing,Jiang,Lin,Tao,Qin,et al. Predicting individual decision-making responses based on the functional connectivity of resting-state EEG[J]. Journal of Neural Engineering, 2019, 16(6), 066025. |
APA | Si,Yajing., Jiang,Lin., Tao,Qin., Chen,Chunli., Li,Fali., Jiang,Yuanling., Zhang,Tao., Cao,Xianyu., Wan,Feng., Yao,Dezhong., & Xu,Peng (2019). Predicting individual decision-making responses based on the functional connectivity of resting-state EEG. Journal of Neural Engineering, 16(6), 066025. |
MLA | Si,Yajing,et al."Predicting individual decision-making responses based on the functional connectivity of resting-state EEG".Journal of Neural Engineering 16.6(2019):066025. |
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