Default mode network mechanisms of transcranial magnetic stimulation in depression

经颅磁刺激治疗抑郁症的默认模式网络机制

阅读:1

Abstract

BACKGROUND: Repetitive transcranial magnetic stimulation (TMS) of the dorsolateral prefrontal cortex (DLPFC) is an established treatment for depression, but its underlying mechanism of action remains unknown. Abnormalities in two large-scale neuronal networks-the frontoparietal central executive network (CEN) and the medial prefrontal-medial parietal default mode network (DMN)-are consistent findings in depression and potential therapeutic targets for TMS. Here, we assessed the impact of TMS on activity in these networks and their relation to treatment response. METHODS: We used resting state functional magnetic resonance imaging to measure functional connectivity within and between the DMN and CEN in 17 depressed patients, before and after a 5-week course of TMS. Motivated by prior reports, we focused on connectivity seeded from the DLPFC and the subgenual cingulate, a key region closely aligned with the DMN in depression. Connectivity was also compared with a cohort of 35 healthy control subjects. RESULTS: Before treatment, functional connectivity in depressed patients was abnormally elevated within the DMN and diminished within the CEN, and connectivity between these two networks was altered. Transcranial magnetic stimulation normalized depression-related subgenual hyperconnectivity in the DMN but did not alter connectivity in the CEN. Transcranial magnetic stimulation also induced anticorrelated connectivity between the DLPFC and medial prefrontal DMN nodes. Baseline subgenual connectivity predicted subsequent clinical improvement. CONCLUSIONS: Transcranial magnetic stimulation selectively modulates functional connectivity both within and between the CEN and DMN, and modulation of subgenual cingulate connectivity may play an important mechanistic role in alleviating depression. The results also highlight potential neuroimaging biomarkers for predicting treatment response.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。