睡眠剥夺影响风险决策的大尺度脑网络模型&#x0002A;

陈星; 郭博文; 闫凯凯; 毛天欣; 饶恒毅

doi:10.16719/j.cnki.1671-6981.20260108

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心理科学 ›› 2026, Vol. 49 ›› Issue (1) : 68-81. DOI: 10.16719/j.cnki.1671-6981.20260108

基础、实验与工效

睡眠剥夺影响风险决策的大尺度脑网络模型^*

陈星, 郭博文, 闫凯凯, 毛天欣^**, 饶恒毅

作者信息 +

The Large-Scale Brain Network Model of Sleep Deprivation on Risky Decision Making

Chen Xing, Guo Bowen, Yan Kaikai, Mao Tianxin, Rao Hengyi

Author information +

文章历史 +

摘要

随着科技发展,睡眠不足问题日益普遍,这会显著损害个体的认知和情绪功能。风险决策在生活中无处不在,并受到睡眠不足的影响。近年来,越来越多研究开始探讨睡眠剥夺对风险决策的影响,但大多关注不同程度睡眠剥夺对特定脑区和单一脑网络激活水平的影响,忽略了大尺度脑网络的整体作用。研究比较了完全睡眠剥夺和部分睡眠剥夺对风险决策的影响,并分别从大尺度脑网络视角分析其作用机制。研究强调了中央执行网络、奖赏网络和凸显网络在这一过程中的执行控制、奖惩预期和风险评估作用,共同决定个体的决策表现。最后,本文讨论了未来研究可以从建立神经计算模型、探究动态影响等方面继续探究。

Abstract

Sleep is a fundamental physiological phenomenon that is essential for physical health, cognitive ability and emotional regulation. However, with technological advances and the accelerated pace of life, sleep deprivation has become increasingly prevalent, significantly impairing the cognitive and emotional functioning of individuals. Risky decision making, as a type of uncertain decision making, refers to the process by which people weigh options that have multiple outcomes and the probability of each outcome occurring is known. People make risky decisions all the time in their daily lives and at work. Most studies have confirmed that sleep deprivation significantly affects an individual's risky decision making preferences.
The neural processes by which sleep deprivation affects risky decision-making involve three main large-scale brain networks: the central executive network, the reward network, and the salience network. Specifically, when individuals experience total sleep deprivation, the activation level of the central executive network is significantly reduced, i.e., the dorsolateral prefrontal activation level decreases and the individual's inhibitory control is severely impaired. The activation levels of the orbitofrontal cortex and the ventral medial prefrontal within the reward network decreased, but the activation level of the striatum was enhanced, and the brain regions interacted with each other to greatly weaken the individual's ability to resist immediate rewards and avoid impulsive behaviors. At the same time, decreased activation levels in the amygdala and the anterior insula within the salience network, but enhanced activation levels in the anterior cingulate cortex, lead individuals to make more irrational decisions. The same three large-scale brain networks are included when individuals with partial sleep deprivation make risky decisions. The difference is that partial sleep deprivation only significantly decreases activation levels in the dorsolateral prefrontal and enhances activation levels in the anterior insula. However, partial sleep deprivation reduces the functional connectivity of the dorsolateral prefrontal and striatum, the anterior insula, and the orbitofrontal cortex and amygdala, resulting in the inability of individuals to effectively inhibit high-risk behaviors and reduce decision-making performance.
Previous studies have mostly focused on the effects of different levels of sleep deprivation on the level of activation in specific brain regions and single brain networks, but ignored the overall role of large-scale brain networks. It has been found that the brain integrates and processes information in the form of brain networks, and multiple brain networks work together to ultimately change an individual's behavioral performance. Complete sleep deprivation affects an individual's risky decision-making performance by directly altering the activation levels of the central executive, reward, and salience networks. When an individual receives a reward or suffers a loss, the activation of the reward network or salience network is further enhanced, which in turn affects the central executive network and ultimately alters the individual's subsequent risky decision-making performance. The feedback mechanism for risky decision-making in partial sleep deprivation is impaired, making it difficult to effectively regulate individual decision-making behavior. As in the case of total sleep deprivation, the results of risky decision making in individuals with partial sleep deprivation were fed back to the reward and salience networks, which influenced the individual's future decision making.
Future research is suggested to further explore the following issues. Considering the development prospects of machine learning and deep learning technologies, future research should use these technologies to computationally model the rich brain network data to further deepen the understanding of brain function and structure. In addition, the dynamic effects of different degrees of sleep deprivation on risky decision making are further refined by carefully dividing sleep deprivation time. At the same time, the generalizability of the effects of sleep deprivation on decision making is explored.

导出引用

陈星, 郭博文, 闫凯凯, 毛天欣, 饶恒毅. 睡眠剥夺影响风险决策的大尺度脑网络模型^*[J]. 心理科学. 2026, 49(1): 68-81 https://doi.org/10.16719/j.cnki.1671-6981.20260108

Chen Xing, Guo Bowen, Yan Kaikai, Mao Tianxin, Rao Hengyi. The Large-Scale Brain Network Model of Sleep Deprivation on Risky Decision Making[J]. Journal of Psychological Science. 2026, 49(1): 68-81 https://doi.org/10.16719/j.cnki.1671-6981.20260108

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