Department of Psychiatry, Harvard Medical School, and Center for Depression, Anxiety, and Stress Research, McLean Hospital, Belmont, Massachusetts.
Department of Psychology and Neuroscience, University of Colorado, Boulder.
JAMA Psychiatry. 2015 Jun;72(6):603-11. doi: 10.1001/jamapsychiatry.2015.0071.
IMPORTANCE: Major depressive disorder (MDD) has been linked to imbalanced communication among large-scale brain networks, as reflected by abnormal resting-state functional connectivity (rsFC). However, given variable methods and results across studies, identifying consistent patterns of network dysfunction in MDD has been elusive. OBJECTIVE: To investigate network dysfunction in MDD through a meta-analysis of rsFC studies. DATA SOURCES: Seed-based voxelwise rsFC studies comparing individuals with MDD with healthy controls (published before June 30, 2014) were retrieved from electronic databases (PubMed, Web of Science, and EMBASE) and authors contacted for additional data. STUDY SELECTION: Twenty-seven seed-based voxel-wise rsFC data sets from 25 publications (556 individuals with MDD and 518 healthy controls) were included in the meta-analysis. DATA EXTRACTION AND SYNTHESIS: Coordinates of seed regions of interest and between-group effects were extracted. Seeds were categorized into seed-networks by their location within a priori functional networks. Multilevel kernel density analysis of between-group effects identified brain systems in which MDD was associated with hyperconnectivity (increased positive or reduced negative connectivity) or hypoconnectivity (increased negative or reduced positive connectivity) with each seed-network. RESULTS: Major depressive disorder was characterized by hypoconnectivity within the frontoparietal network, a set of regions involved in cognitive control of attention and emotion regulation, and hypoconnectivity between frontoparietal systems and parietal regions of the dorsal attention network involved in attending to the external environment. Major depressive disorder was also associated with hyperconnectivity within the default network, a network believed to support internally oriented and self-referential thought, and hyperconnectivity between frontoparietal control systems and regions of the default network. Finally, the MDD groups exhibited hypoconnectivity between neural systems involved in processing emotion or salience and midline cortical regions that may mediate top-down regulation of such functions. CONCLUSIONS AND RELEVANCE: Reduced connectivity within frontoparietal control systems and imbalanced connectivity between control systems and networks involved in internal or external attention may reflect depressive biases toward internal thoughts at the cost of engaging with the external world. Meanwhile, altered connectivity between neural systems involved in cognitive control and those that support salience or emotion processing may relate to deficits regulating mood. These findings provide an empirical foundation for a neurocognitive model in which network dysfunction underlies core cognitive and affective abnormalities in depression.
重要性:重度抑郁症(MDD)与大尺度脑网络之间的通讯失衡有关,这反映在静息状态功能连接(rsFC)的异常上。然而,由于研究之间的方法和结果各不相同,因此确定 MDD 中网络功能障碍的一致模式一直难以捉摸。 目的:通过对 rsFC 研究的荟萃分析来研究 MDD 中的网络功能障碍。 数据来源:从电子数据库(PubMed、Web of Science 和 EMBASE)中检索到比较 MDD 个体与健康对照者的基于种子的体素 rsFC 研究(发表于 2014 年 6 月 30 日之前),并联系作者获取额外数据。 研究选择:荟萃分析包括 25 项研究中的 27 个基于种子的体素 rsFC 数据集(556 名 MDD 患者和 518 名健康对照者)。 数据提取和综合:提取了感兴趣种子区域的坐标和组间效应。根据种子在预先确定的功能网络中的位置,将种子分类为种子网络。对组间效应的多级核密度分析确定了与每个种子网络相关的与过度连接(增加正或减少负连接)或连接不足(增加负或减少正连接)的脑系统。 结果:MDD 的特征是额顶网络内的连接不足,额顶网络是一组参与注意力和情绪调节的认知控制的区域,以及额顶系统与参与外部环境注意的背侧注意网络的顶叶区域之间的连接不足。MDD 还与默认网络内的过度连接有关,默认网络被认为支持内向和自我参照的思维,以及额顶控制系统与默认网络区域之间的过度连接。最后,MDD 组表现出参与处理情绪或突显的神经系统之间的连接不足,以及中线皮质区域的连接不足,这可能介导了对这些功能的自上而下的调节。 结论和相关性:额顶控制系统内的连接减少,以及控制系统与参与内部或外部注意力的网络之间的连接不平衡,可能反映了抑郁者对内部思维的偏见,而不是与外部世界接触。同时,参与认知控制的神经系统与支持突显或情绪处理的系统之间的连接改变可能与调节情绪的能力缺陷有关。这些发现为神经认知模型提供了一个实证基础,该模型认为网络功能障碍是抑郁症核心认知和情感异常的基础。
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