Evidence map›Paper›PMID 30088149›Full record

ArticleNeuroscience bulletin2018

Separate Neural Networks for Gains and Losses in Intertemporal Choice.

Yang-Yang Zhang, Lijuan Xu, Zhu-Yuan Liang, Kun Wang, Bing Hou, Yuan Zhou, Shu Li, Tianzi Jiang

Abstract read
In one paragraph

Article in Neuroscience bulletin, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed.

  1. Article
  2. Sense of agency and decision making.Frontiers in psychology · 2026
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  3. Article
  4. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Yang-Yang ZhangSchool of Psychology, Shaanxi Normal University, Xi'an, 710062, China.
Lijuan XuBrainnetome Center, Institute of Automation, University of Chinese Academy of Sciences, Beijing, 100190, China.
Zhu-Yuan LiangCAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, 100101, China.
Kun WangBrainnetome Center, Institute of Automation, University of Chinese Academy of Sciences, Beijing, 100190, China.
Bing HouBrainnetome Center, Institute of Automation, University of Chinese Academy of Sciences, Beijing, 100190, China.
Yuan ZhouCAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, 100101, China.
Shu LiCAS Key Laboratory of Behavioral Science, Institute of Psychology, Beijing, 100101, China. lishu@psych.ac.cn.
Tianzi JiangBrainnetome Center, Institute of Automation, University of Chinese Academy of Sciences, Beijing, 100190, China. jiangtz@nlpr.ia.ac.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

RewardAdultBrainBrain MappingDelay DiscountingFemaleHumansMagnetic Resonance ImagingMaleNeural PathwaysNeuropsychological TestsPsychophysicsYoung AdultDiscounting lossesDorsolateral prefrontal cortexDynamic causal modelEffective connectivityInsulaIntertemporal choice

Identifiers

PMID30088149
PMCPMC6129240

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.