Separate Neural Networks for Gains and Losses in Intertemporal Choice
1School of Psychology, Shaanxi Normal University, Xi’an 710062, China
2Brainnetome Center, Institute of Automation, University of Chinese Academy of Sciences, Beijing 100190, China
3National Laboratory of Pattern Recognition, Institute of Automation, University of Chinese Academy of Sciences, Beijing 100190, China
4CAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing 100101, China
5Department of Psychology, University of Chinese Academy of Sciences, Beijing 100049, China
6Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou 310028, China
7CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Beijing 100190, China
8The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu 610054, China
Abstract
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.
Keywords
Intertemporal choice, Discounting losses, Effective connectivity, Dynamic causal model, Dorsolateral prefrontal cortex, Insula