Department of Psychology, University of Calgary, Calgary, AB, Canada.
Hotchkiss Brain Institute, University of Calgary, Calgary, AB, Canada.
Mol Psychiatry. 2023 Sep;28(9):3888-3899. doi: 10.1038/s41380-023-02181-1. Epub 2023 Jul 20.
Deep brain stimulation (DBS) has shown therapeutic benefits for treatment resistant depression (TRD). Stimulation of the subcallosal cingulate gyrus (SCG) aims to alter dysregulation between subcortical and cortex. However, the 50% response rates for SCG-DBS indicates that selection of appropriate patients is challenging. Since stimulation influences large-scale network function, we hypothesized that network features can be used as biomarkers to inform outcome. In this pilot project, we used resting-state EEG recorded longitudinally from 10 TRD patients with SCG-DBS (11 at baseline). EEGs were recorded before DBS-surgery, 1-3 months, and 6 months post surgery. We used graph theoretical analysis to calculate clustering coefficient, global efficiency, eigenvector centrality, energy, and entropy of source-localized EEG networks to determine their topological/dynamical features. Patients were classified as responders based on achieving a 50% or greater reduction in Hamilton Depression (HAM-D) scores from baseline to 12 months post surgery. In the delta band, false discovery rate analysis revealed that global brain network features (segregation, integration, synchronization, and complexity) were significantly lower and centrality of subgenual anterior cingulate cortex (ACC) was higher in responders than in non-responders. Accordingly, longitudinal analysis showed SCG-DBS increased global network features and decreased centrality of subgenual ACC. Similarly, a clustering method separated two groups by network features and significant correlations were identified longitudinally between network changes and depression symptoms. Despite recent speculation that certain subtypes of TRD are more likely to respond to DBS, in the SCG it seems that underlying brain network features are associated with ability to respond to DBS. SCG-DBS increased segregation, integration, and synchronizability of brain networks, suggesting that information processing became faster and more efficient, in those patients in whom it was lower at baseline. Centrality results suggest these changes may occur via altered connectivity in specific brain regions especially ACC. We highlight potential mechanisms of therapeutic effect for SCG-DBS.
脑深部刺激（DBS）已显示出对治疗抵抗性抑郁症（TRD）的治疗益处。刺激扣带下回（SCG）旨在改变皮质下和皮质之间的失调。然而，SCG-DBS 的 50%反应率表明选择合适的患者具有挑战性。由于刺激会影响大规模的网络功能，我们假设网络特征可以用作生物标志物来预测结果。在这个试点项目中，我们使用来自 10 名接受 SCG-DBS 的 TRD 患者（基线时为 11 名）的纵向静息状态 EEG。EEG 在 DBS 手术前、术后 1-3 个月和 6 个月进行记录。我们使用图论分析计算聚类系数、全局效率、特征向量中心性、能量和源定位 EEG 网络的熵，以确定它们的拓扑/动力学特征。根据从基线到手术后 12 个月 Hamilton 抑郁（HAM-D）评分降低 50%或更多，患者被分类为反应者。在 delta 波段，假发现率分析表明，反应者的全局脑网络特征（隔离、整合、同步和复杂性）明显低于非反应者，而亚皮质前扣带皮层（ACC）的中心性更高。相应地，纵向分析表明，SCG-DBS 增加了全局网络特征，降低了亚皮质 ACC 的中心性。同样，聚类方法通过网络特征将两组分开，并在网络变化和抑郁症状之间识别出纵向相关性。尽管最近有推测认为某些类型的 TRD 更有可能对 DBS 产生反应，但在 SCG 中，似乎大脑网络特征与对 DBS 的反应能力有关。SCG-DBS 增加了大脑网络的隔离、整合和同步能力，表明在那些基线时较低的患者中，信息处理变得更快、更有效。中心性结果表明，这些变化可能是通过特定脑区（特别是 ACC）的连接改变发生的。我们强调了 SCG-DBS 的治疗效果的潜在机制。
