静息状态功能磁共振成像
功能连接
功能磁共振成像
默认模式网络
心理学
认知心理学
倾向得分匹配
大脑定位
神经科学
计算机科学
医学
内科学
作者
Lin Jiang,Qingqing Yang,Runyang He,Guangying Wang,Chanlin Yi,Yajing Si,Dezhong Yao,Peng Xu,Liang Yu,Fali Li
出处
期刊:Cerebral Cortex
[Oxford University Press]
日期:2023-05-15
卷期号:33 (14): 8904-8912
被引量:3
标识
DOI:10.1093/cercor/bhad169
摘要
Abstract Despite node-centric studies revealing an association between resting-state functional connectivity and individual risk propensity, the prediction of future risk decisions remains undetermined. Herein, we applied a recently emerging edge-centric method, the edge community similarity network (ECSN), to alternatively describe the community structure of resting-state brain activity and to probe its contribution to predicting risk propensity during gambling. Results demonstrated that inter-individual variability of risk decisions correlates with the inter-subnetwork couplings spanning the visual network (VN) and default mode network (DMN), cingulo-opercular task control network, and sensory/somatomotor hand network (SSHN). Particularly, participants who have higher community similarity of these subnetworks during the resting state tend to choose riskier and higher yielding bets. And in contrast to low-risk propensity participants, those who behave high-risky show stronger couplings spanning the VN and SSHN/DMN. Eventually, based on the resting-state ECSN properties, the risk rate during the gambling task is effectively predicted by the multivariable linear regression model at the individual level. These findings provide new insights into the neural substrates of the inter-individual variability in risk propensity and new neuroimaging metrics to predict individual risk decisions in advance.
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