Dataset Information

Separate Neural Networks for Gains and Losses in Intertemporal Choice.

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.

SUBMITTER: Zhang YY

PROVIDER: S-EPMC6129240 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Publications

Separate Neural Networks for Gains and Losses in Intertemporal Choice.

Zhang Yang-Yang YY Xu Lijuan L Liang Zhu-Yuan ZY Wang Kun K Hou Bing B Zhou Yuan Y Li Shu S Jiang Tianzi T

Neuroscience bulletin 20180807 5

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 tem ...[more]

PMID: 30088149

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Dataset Information

Separate Neural Networks for Gains and Losses in Intertemporal Choice.

Publications

Separate Neural Networks for Gains and Losses in Intertemporal Choice.

Similar Datasets

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