ISSN 1671-3710
CN 11-4766/R

心理科学进展 ›› 2022, Vol. 30 ›› Issue (6): 1262-1269.doi: 10.3724/SP.J.1042.2022.01262

• 研究前沿 • 上一篇    下一篇


林雯仪1, 何昊1,3, 关青1,2,3()   

  1. 1深圳大学心理学院, 深圳 518060
    2深圳市神经科学研究院, 深圳 518107
    3深港脑科学创新研究院, 深圳 518055
  • 收稿日期:2021-05-13 出版日期:2022-06-15 发布日期:2022-04-26
  • 通讯作者: 关青
  • 基金资助:

Functional brain networks underlying rumination

LIN Wenyi1, HE Hao1,3, GUAN Qing1,2,3()   

  1. 1School of Psychology Shenzhen University, Shenzhen 518060, China
    2Shenzhen Institute of Neuroscience, Shenzhen 518107, China
    3Shenzhen & Hongkong Institute of Brain Science, Shenzhen 518055, China
  • Received:2021-05-13 Online:2022-06-15 Published:2022-04-26
  • Contact: GUAN Qing


反刍思维是指个体在经历了消极生活事件后不由自主地反复思考该事件的产生原因、经过和结果, 表现出负性自我参照加工、消极情绪性以及持续性的特点。采用脑功能网络分析方法, 研究者发现反刍思维的上述三个特点分别与默认网络内部的异常活动模式、突显网络功能连接的改变以及注意相关网络之间的异常耦合有关。未来研究应进一步明确反刍思维与相关脑网络活动之间的因果关系, 探究反刍思维脑功能网络的结构基础, 同时也应关注反刍思维及其脑网络的老龄化特征, 并致力于探索有效干预反刍思维的神经调控技术。

关键词: 反刍思维, 脑网络, 默认网络, 功能连接


Rumination refers to the involuntary reflection of the cause, course and consequence of a negative event that an individual suffered. It is characterized by negative self-referential processing, negative emotion, and persistence. In recent years, a growing body of studies, using functional magnetic resonance imaging, have demonstrated the three characteristics of the large-scale brain networks underlying rumination.
First, the negative self-referential processing involved in rumination is associated with alterations in the default mode network. Recent evidence indicates that during rumination, the three subsystems of the default network (i.e., the core subsystem, the dorsal medial prefrontal cortex subsystem, and the medial temporal lobe subsystem) show different levels of activity, and the functional connectivity between the three subsystems also changes. Specifically, the connection between the core subsystem responsible for self-referential processing and the dorsal medial prefrontal subsystem that is involved in the theory of mind and metacognition is weakened, while the connectivity between the core subsystem and the medial temporal subsystem that is involved in expectations regarding one’s self in the future is strengthened. In addition, previous studies using the graph theory analysis have demonstrated that the increase in the level of rumination is related to enhancing internal entropy (reflecting the chaos of a system) of the default mode network.
Second, rumination involves negative emotions. After negative events, negative self-referential processing will make individuals focus on negative information, which would induce negative emotions. Changes in the salience network that monitors external stimuli and recruit relevant functional networks may underlie the occurrence of negative emotions during rumination. In the state of rumination, functional connectivity between amygdala and dorsolateral prefrontal cortex is reduced, which suggests the deficit in emotional regulation. In contrast, the fronto-insular cortex is overactive, reflecting the conflict between individuals’ expectation and real situations, which may lead to stronger negative emotional experience compared to control conditions.
Finally, rumination is characterized by individuals' repetitive and persistent thinking about negative events, which is associated with the abnormal interactions between attention-related networks. These networks, in particular, include the frontoparietal network that is involved in attentional control, response selection, and response inhibition, and the dorsal attentional network which is engaged in attending external information. Compared to healthy controls, individuals who are experiencing depression and with high levels of rumination show weakened functional connectivity between the frontoparietal network and the dorsal attentional network. In comparison, the functional connectivity between the frontoparietal network and the default mode network would be increased. In addition, previous studies using dynamic network analysis have demonstrated that the increased stability of functional connectivity in the frontoparietal network (reflecting the decline of individual cognitive flexibility) and the decreased stability in the default mode network would be observed during the state of rumination (reflecting excessive self-referential processing). In short, the self-referential processing involved in rumination is associated with alterations in the default mode network, while negative emotion produced by rumination is related to changes in the salience network. The “persistence” property of rumination is associated with altered connections between attention-related networks.
Four questions need to be addressed in the future. First, current evidence on the correlation between rumination and its related brain networks is not enough to clarify the causal relationship between the two. In this regard, future studies should apply neuromodulation technologies to further examine the causal relationship between rumination and its related brain networks.
Second, although previous studies have demonstrated the association between rumination and alterations in brain functional networks, its structural basis remains elusive, as few studies have explored the relationship between brain function and structural network of ruminant thinking. Future studies need to examine whether there is a structural basis of a change in brain functional networks underlying rumination.
Third, characteristics of aging effects on rumination should be profiled. It is not appropriate to simply extend results from the young and middle-aged populations to the elderly. Considering that lines of evidence showing that there is a positive effect in the elderly population (i.e., older adults pay more attention to positive stimuli than negative stimuli compared to young adults), it is plausible to investigate whether the positive emotional effect would compensate for the alterations in functional connectivity under rumination in the future.
Finally, future studies should peruse the clinical value of large-scale brain network basis of rumination. Little is known about the applications of the existing brain network mechanism to clinical intervention and treatment of rumination. Future research should focus on developing neural regulation technology based on brain network to effectively treat rumination.

Key words: rumination, brain network, default mode network, functional connectivity