Resting-state network predicts the decision-making behaviors of the proposer during the ultimatum game

Objective . The decision-making behavior of the proposer is a key factor in achieving effective and equitable maintenance of social resources, particularly in economic interactions, and thus understanding the neurocognitive basis of the proposer’s decision-making is a crucial issue. Yet the neural s...

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Veröffentlicht in:Journal of neural engineering 2023-10, Vol.20 (5), p.56003
Hauptverfasser: Li, Yuqin, Yang, Qian, Liu, Yuxin, Wang, Rui, Zheng, Yutong, Zhang, Yubo, Si, Yajing, Jiang, Lin, Chen, Baodan, Peng, Yueheng, Wan, Feng, Yu, Jing, Yao, Dezhong, Li, Fali, He, Baoming, Xu, Peng
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container_issue 5
container_start_page 56003
container_title Journal of neural engineering
container_volume 20
creator Li, Yuqin
Yang, Qian
Liu, Yuxin
Wang, Rui
Zheng, Yutong
Zhang, Yubo
Si, Yajing
Jiang, Lin
Chen, Baodan
Peng, Yueheng
Wan, Feng
Yu, Jing
Yao, Dezhong
Li, Fali
He, Baoming
Xu, Peng
description Objective . The decision-making behavior of the proposer is a key factor in achieving effective and equitable maintenance of social resources, particularly in economic interactions, and thus understanding the neurocognitive basis of the proposer’s decision-making is a crucial issue. Yet the neural substrate of the proposer’s decision behavior, especially from the resting-state network perspective, remains unclear. Approach . In this study, we investigated the relationship between the resting-state network and decision proposals and further established a multivariable model to predict the proposers’ unfair offer rates in the ultimatum game. Main results. The results indicated the unfair offer rates of proposers are significantly related to the resting-state frontal-occipital and frontal-parietal connectivity in the delta band, as well as the network properties. And compared to the conservative decision group (low unfair offer rate), the risk decision group (high unfair offer rate) exhibited stronger resting-state long-range linkages. Finally, the established multivariable model did accurately predict the unfair offer rates of the proposers, along with a correlation coefficient of 0.466 between the actual and predicted behaviors. Significance . Together, these findings demonstrated that related resting-state frontal-occipital and frontal-parietal connectivity may serve as a dispositional indicator of the risky behaviors for the proposers and subsequently predict a highly complex decision-making behavior, which contributed to the development of artificial intelligence decision-making system with biological characteristics as well.
doi_str_mv 10.1088/1741-2552/acf61e
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The decision-making behavior of the proposer is a key factor in achieving effective and equitable maintenance of social resources, particularly in economic interactions, and thus understanding the neurocognitive basis of the proposer’s decision-making is a crucial issue. Yet the neural substrate of the proposer’s decision behavior, especially from the resting-state network perspective, remains unclear. Approach . In this study, we investigated the relationship between the resting-state network and decision proposals and further established a multivariable model to predict the proposers’ unfair offer rates in the ultimatum game. Main results. The results indicated the unfair offer rates of proposers are significantly related to the resting-state frontal-occipital and frontal-parietal connectivity in the delta band, as well as the network properties. And compared to the conservative decision group (low unfair offer rate), the risk decision group (high unfair offer rate) exhibited stronger resting-state long-range linkages. Finally, the established multivariable model did accurately predict the unfair offer rates of the proposers, along with a correlation coefficient of 0.466 between the actual and predicted behaviors. Significance . Together, these findings demonstrated that related resting-state frontal-occipital and frontal-parietal connectivity may serve as a dispositional indicator of the risky behaviors for the proposers and subsequently predict a highly complex decision-making behavior, which contributed to the development of artificial intelligence decision-making system with biological characteristics as well.</description><identifier>ISSN: 1741-2560</identifier><identifier>ISSN: 1741-2552</identifier><identifier>EISSN: 1741-2552</identifier><identifier>DOI: 10.1088/1741-2552/acf61e</identifier><identifier>CODEN: JNEOBH</identifier><language>eng</language><publisher>IOP Publishing</publisher><subject>decision-making ; proposer ; resting-state network ; ultimatum game ; unfair offer rate</subject><ispartof>Journal of neural engineering, 2023-10, Vol.20 (5), p.56003</ispartof><rights>2023 IOP Publishing Ltd</rights><rights>2023 IOP Publishing Ltd.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c345t-b8a2ce0b7d76fc9cd01d43af437623d33ccae5b5c6936776cbaa31f06d93f1ad3</citedby><cites>FETCH-LOGICAL-c345t-b8a2ce0b7d76fc9cd01d43af437623d33ccae5b5c6936776cbaa31f06d93f1ad3</cites><orcidid>0000-0001-9753-2617 ; 0000-0002-9359-0737 ; 0000-0002-7932-0386 ; 0000-0002-8042-879X ; 0000-0002-2450-4591 ; 0000-0002-7892-118X ; 0000-0002-4226-9281</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://iopscience.iop.org/article/10.1088/1741-2552/acf61e/pdf$$EPDF$$P50$$Giop$$H</linktopdf><link.rule.ids>314,776,780,27901,27902,53821,53868</link.rule.ids></links><search><creatorcontrib>Li, Yuqin</creatorcontrib><creatorcontrib>Yang, Qian</creatorcontrib><creatorcontrib>Liu, Yuxin</creatorcontrib><creatorcontrib>Wang, Rui</creatorcontrib><creatorcontrib>Zheng, Yutong</creatorcontrib><creatorcontrib>Zhang, Yubo</creatorcontrib><creatorcontrib>Si, Yajing</creatorcontrib><creatorcontrib>Jiang, Lin</creatorcontrib><creatorcontrib>Chen, Baodan</creatorcontrib><creatorcontrib>Peng, Yueheng</creatorcontrib><creatorcontrib>Wan, Feng</creatorcontrib><creatorcontrib>Yu, Jing</creatorcontrib><creatorcontrib>Yao, Dezhong</creatorcontrib><creatorcontrib>Li, Fali</creatorcontrib><creatorcontrib>He, Baoming</creatorcontrib><creatorcontrib>Xu, Peng</creatorcontrib><title>Resting-state network predicts the decision-making behaviors of the proposer during the ultimatum game</title><title>Journal of neural engineering</title><addtitle>JNE</addtitle><addtitle>J. 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And compared to the conservative decision group (low unfair offer rate), the risk decision group (high unfair offer rate) exhibited stronger resting-state long-range linkages. Finally, the established multivariable model did accurately predict the unfair offer rates of the proposers, along with a correlation coefficient of 0.466 between the actual and predicted behaviors. Significance . 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Neural Eng</addtitle><date>2023-10-01</date><risdate>2023</risdate><volume>20</volume><issue>5</issue><spage>56003</spage><pages>56003-</pages><issn>1741-2560</issn><issn>1741-2552</issn><eissn>1741-2552</eissn><coden>JNEOBH</coden><abstract>Objective . The decision-making behavior of the proposer is a key factor in achieving effective and equitable maintenance of social resources, particularly in economic interactions, and thus understanding the neurocognitive basis of the proposer’s decision-making is a crucial issue. Yet the neural substrate of the proposer’s decision behavior, especially from the resting-state network perspective, remains unclear. Approach . In this study, we investigated the relationship between the resting-state network and decision proposals and further established a multivariable model to predict the proposers’ unfair offer rates in the ultimatum game. Main results. The results indicated the unfair offer rates of proposers are significantly related to the resting-state frontal-occipital and frontal-parietal connectivity in the delta band, as well as the network properties. And compared to the conservative decision group (low unfair offer rate), the risk decision group (high unfair offer rate) exhibited stronger resting-state long-range linkages. Finally, the established multivariable model did accurately predict the unfair offer rates of the proposers, along with a correlation coefficient of 0.466 between the actual and predicted behaviors. Significance . Together, these findings demonstrated that related resting-state frontal-occipital and frontal-parietal connectivity may serve as a dispositional indicator of the risky behaviors for the proposers and subsequently predict a highly complex decision-making behavior, which contributed to the development of artificial intelligence decision-making system with biological characteristics as well.</abstract><pub>IOP Publishing</pub><doi>10.1088/1741-2552/acf61e</doi><tpages>14</tpages><orcidid>https://orcid.org/0000-0001-9753-2617</orcidid><orcidid>https://orcid.org/0000-0002-9359-0737</orcidid><orcidid>https://orcid.org/0000-0002-7932-0386</orcidid><orcidid>https://orcid.org/0000-0002-8042-879X</orcidid><orcidid>https://orcid.org/0000-0002-2450-4591</orcidid><orcidid>https://orcid.org/0000-0002-7892-118X</orcidid><orcidid>https://orcid.org/0000-0002-4226-9281</orcidid></addata></record>
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source IOP Publishing Journals; Institute of Physics (IOP) Journals - HEAL-Link
subjects decision-making
proposer
resting-state network
ultimatum game
unfair offer rate
title Resting-state network predicts the decision-making behaviors of the proposer during the ultimatum game
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