Gain-loss asymmetry in neural correlates of temporal discounting: An approach-avoidance motivation perspective

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作者
Yang-Yang Zhang
Lijuan Xu
Li-Lin Rao
Lei Zhou
Yuan Zhou
Tianzi Jiang
Shu Li
Zhu-Yuan Liang
机构
[1] Key Laboratory of Behavioral Sciences & Magnetic Resonance Imaging Research Center,
[2] Institute of Psychology,undefined
[3] Chinese Academy of Sciences,undefined
[4] University of Chinese Academy of Sciences,undefined
[5] National Laboratory of Pattern Recognition,undefined
[6] Institute of Automation,undefined
[7] Chinese Academy of Sciences,undefined
[8] Brainnetome Center,undefined
[9] Institute of Automation,undefined
[10] Chinese Academy of Sciences,undefined
[11] Key Laboratory for NeuroInformation of the Ministry of Education,undefined
[12] School of Life Science and Technology,undefined
[13] University of Electronic Science and Technology of China,undefined
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摘要
Gain-loss asymmetry in temporal discounting (i.e., when individuals discount gains more than losses) has been implicated in numerous problematic and addictive behaviors, resulting in enormous personal and societal costs. On the basis of findings from a previous study, we speculated that approach-avoidance motivation would modulate gain-loss asymmetry. To test this speculation, we examined the effects of motivation on gain-loss asymmetry by analyzing functional connectivity. We found that approach and avoidance motivation were negatively associated with functional connectivity between the medial orbitofrontal cortex (MOFC) and the dorsolateral prefrontal cortex and functional connectivity between the MOFC and the posterior parietal cortex (PPC) in the gain domain. Only avoidance motivation was found to be positively associated with functional connectivity between the medial prefrontal cortex (MPFC) and the posterior cingulate cortex (PCC) as well as between the MPFC and the insula in the loss domain. Our findings suggest that the relationships of approach-avoidance motivation and neural correlates yielded an asymmetrical pattern between the gain and loss domains in temporal discounting. Thus, we provide new insight into understanding gain-loss asymmetry in temporal discounting.
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