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背内侧前额皮质在基于努力和风险的决策中代表主观价值。

The dorsomedial prefrontal cortex represents subjective value across effort-based and risky decision-making.

机构信息

Department of Education and Psychology, Freie Universität Berlin, Berlin, Germany; Einstein Center for Neurosciences Berlin, Charité - Universitätsmedizin Berlin, Germany; Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany; Max Planck Research Group NeuroCode, Max Planck Institute for Human Development, Berlin, Germany.

State Key Laboratory of Cognitive Neuroscience and Learning and IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.

出版信息

Neuroimage. 2023 Oct 1;279:120326. doi: 10.1016/j.neuroimage.2023.120326. Epub 2023 Aug 12.

Abstract

Decisions that require taking effort costs into account are ubiquitous in real life. The neural common currency theory hypothesizes that a particular neural network integrates different costs (e.g., risk) and rewards into a common scale to facilitate value comparison. Although there has been a surge of interest in the computational and neural basis of effort-related value integration, it is still under debate if effort-based decision-making relies on a domain-general valuation network as implicated in the neural common currency theory. Therefore, we comprehensively compared effort-based and risky decision-making using a combination of computational modeling, univariate and multivariate fMRI analyses, and data from two independent studies. We found that effort-based decision-making can be best described by a power discounting model that accounts for both the discounting rate and effort sensitivity. At the neural level, multivariate decoding analyses indicated that the neural patterns of the dorsomedial prefrontal cortex (dmPFC) represented subjective value across different decision-making tasks including either effort or risk costs, although univariate signals were more diverse. These findings suggest that multivariate dmPFC patterns play a critical role in computing subjective value in a task-independent manner and thus extend the scope of the neural common currency theory.

摘要

在现实生活中,需要考虑成本的决策无处不在。神经通用货币理论假设,一个特定的神经网络将不同的成本(例如风险)和回报整合到一个通用的尺度中,以方便价值比较。尽管人们对与努力相关的价值整合的计算和神经基础产生了浓厚的兴趣,但努力决策是否依赖于神经通用货币理论所暗示的通用估值网络仍存在争议。因此,我们使用计算建模、单变量和多变量 fMRI 分析以及来自两个独立研究的数据,全面比较了基于努力的决策和风险决策。我们发现,基于努力的决策可以通过一个幂折扣模型来最好地描述,该模型既考虑了折扣率,也考虑了努力敏感性。在神经水平上,多元解码分析表明,背内侧前额叶皮层(dmPFC)的神经模式代表了不同决策任务(包括努力或风险成本)的主观价值,尽管单变量信号更加多样化。这些发现表明,多元 dmPFC 模式以任务独立的方式在计算主观价值方面起着关键作用,从而扩展了神经通用货币理论的范围。

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