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Separate Neural Networks for Gains and Losses in Intertemporal Choice
Zhang, Yang-Yang1; Xu, Lijuan2,3; Liang, Zhu-Yuan4,5; Wang, Kun2; Hou, Bing2,3; Zhou, Yuan4,5; Li, Shu4,5,6; Jiang, Tianzi2,3,7,8
第一作者Yang-Yang Zhang
2018-10-01
发表期刊NEUROSCIENCE BULLETIN
通讯作者邮箱lishu@psych.ac.cn ; jiangtz@nlpr.ia.ac.cn
ISSN1673-7067
卷号34期号:5页码:725-735
摘要

An important and unresolved question is how human brain regions process information and interact with each other in intertemporal choice related to gains and losses. Using psychophysiological interaction and dynamic causal modeling analyses, we investigated the functional interactions between regions involved in the decision-making process while participants performed temporal discounting tasks in both the gains and losses domains. We found two distinct intrinsic valuation systems underlying temporal discounting in the gains and losses domains: gains were specifically evaluated in the medial regions, including the medial prefrontal and orbitofrontal cortices, and losses were evaluated in the lateral dorsolateral prefrontal cortex. In addition, immediate reward or punishment was found to modulate the functional interactions between the dorsolateral prefrontal cortex and distinct regions in both the gains and losses domains: in the gains domain, the mesolimbic regions; in the losses domain, the medial prefrontal cortex, anterior cingulate cortex, and insula. These findings suggest that intertemporal choice of gains and losses might involve distinct valuation systems, and more importantly, separate neural interactions may implement the intertemporal choices of gains and losses. These findings may provide a new biological perspective for understanding the neural mechanisms underlying intertemporal choice of gains and losses.

关键词Intertemporal Choice Discounting Losses Effective Connectivity Dynamic Causal Model Dorsolateral Prefrontal Cortex Insula
DOI10.1007/s12264-018-0267-x
语种英语
项目资助者National Natural Science Foundation of China ; Science Frontier Program of the Chinese Academy of Sciences ; Shenzhen Peacock Plan ; Guangdong Pearl River Talents Plan Innovative and Entrepreneurial Team ; CAS Key Laboratory of Behavioral Science, Institute of Psychology
资助项目National Natural Science Foundation of China[71471171] ; National Natural Science Foundation of China[71071150] ; National Natural Science Foundation of China[91432302] ; National Natural Science Foundation of China[31620103905] ; National Natural Science Foundation of China[31471005] ; National Natural Science Foundation of China[71761167001] ; Science Frontier Program of the Chinese Academy of Sciences[QYZDJ-SSW-SMC019] ; Shenzhen Peacock Plan[KQTD2015033016104926] ; Guangdong Pearl River Talents Plan Innovative and Entrepreneurial Team[2016ZT06S220] ; CAS Key Laboratory of Behavioral Science, Institute of Psychology[Y5CX052003]
WOS研究方向Neurosciences & Neurology
WOS类目Neurosciences
WOS记录号WOS:000444005200002
出版者SPRINGER
关键词[WOS]Economic Decision-making ; Orbitofrontal Cortex ; Prefrontal Cortex ; Impulsive Choice ; Functional Connectivity ; Anterior Cingulate ; Monetary Gains ; Basal Ganglia ; Self-control ; Human Brain
引用统计
文献类型期刊论文
条目标识符http://ir.psych.ac.cn/handle/311026/26957
专题中国科学院行为科学重点实验室
通讯作者Li, Shu; Jiang, Tianzi
作者单位1.Shaanxi Normal Univ, Sch Psychol, Xian 710062, Shaanxi, Peoples R China
2.Univ Chinese Acad Sci, Brainnetome Ctr, Inst Automat, Beijing 100190, Peoples R China
3.Univ Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China
4.Inst Psychol, CAS Key Lab Behav Sci, Beijing 100101, Peoples R China
5.Univ Chinese Acad Sci, Dept Psychol, Beijing 100049, Peoples R China
6.Zhejiang Univ, Dept Psychol & Behav Sci, Hangzhou 310028, Zhejiang, Peoples R China
7.Chinese Acad Sci, CAS Ctr Excellence Brain Sci & Intelligence Techn, Beijing 100190, Peoples R China
8.Univ Elect Sci & Technol China, MOE Key Lab Neuroinformat, Chengdu Brain Sci Inst, Clin Hosp, Chengdu 610054, Sichuan, Peoples R China
推荐引用方式
GB/T 7714
Zhang, Yang-Yang,Xu, Lijuan,Liang, Zhu-Yuan,et al. Separate Neural Networks for Gains and Losses in Intertemporal Choice[J]. NEUROSCIENCE BULLETIN,2018,34(5):725-735.
APA Zhang, Yang-Yang.,Xu, Lijuan.,Liang, Zhu-Yuan.,Wang, Kun.,Hou, Bing.,...&Jiang, Tianzi.(2018).Separate Neural Networks for Gains and Losses in Intertemporal Choice.NEUROSCIENCE BULLETIN,34(5),725-735.
MLA Zhang, Yang-Yang,et al."Separate Neural Networks for Gains and Losses in Intertemporal Choice".NEUROSCIENCE BULLETIN 34.5(2018):725-735.
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