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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 PublicationJournal of Neural Engineering
ISSN1741-2560
Volume16Issue: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.

KeywordDecision-making Resting-state Brain Network Response Prediction
DOI10.1088/1741-2552/ab39ce
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaEngineering ; Neurosciences & Neurology
WOS SubjectEngineering, Biomedical ; Neurosciences
WOS IDWOS:000503794000001
PublisherIOP Publishing LtdTEMPLE CIRCUS, TEMPLE WAY, BRISTOL BS1 6BE, ENGLAND
Scopus ID2-s2.0-85074305244
Fulltext Access
Citation statistics
Document TypeJournal article
CollectionDEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING
Corresponding AuthorXu,Peng
Affiliation1.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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