探究DBS对大脑的调控与治疗机制，尤其是实现脑网络水平的DBS机制研究，对DBS的进一步发展与应用具有重大意义。我们以STN-DBS与帕金森病这两个最常见的DBS应用场景作为切入点。fMRI是在全脑范围进行脑功能研究的最佳工具。基于近期在磁共振兼容DBS技术上的突破，我们得以在接受了STN-DBS治疗的帕金森病患者身上完成了以fMRI为核心技术的临床研究。当前基于传统fMRI分析技术的数据分析不够可靠、不够准确。本文通过将fMRI信号成分归类为大脑响应、固定成分及随机成分，从三个角度探讨了传统fMRI分析技术的主要缺陷。我们针对性的从三个部分改进了fMRI分析技术，最终构建了一个相比传统方法更加精准的fMRI信号处理方法。接下来，本文基于任务态fMRI技术观察了STN-DBS对帕金森病患者的脑网络产生的刺激效果。通过周期性的DBS刺激与同步的fMRI扫描，我们说明了STN-DBS对两个脑网络产生的不同的刺激效果，并在其中的GPi网络中发现了刺激效果从GPi单向传导至丘脑的现象。同时，我们在这两个脑网络中首次观察到了STN-DBS对两个关键小脑区域的调控作用。接下来，本文基于静息态fMRI技术观察了STN-DBS对帕金森病患者的脑网络产生的刺激效果。首先，我们采用混合效应模型建模了静息态功能连接，实现了更加有效的静息态fMRI数据分析。结合帕金森病患者中采集到的静息态fMRI数据，我们观察到了STN-DBS对运动—视觉、背侧注意—额顶网络产生的调控作用，且发现了丘脑在运动—视觉连接的调控中起到的关键作用。最后，本文基于多模态数据进一步研究了STN-DBS治疗帕金森病的机制，并阐述了fMRI技术的临床价值。本文用能够同步记录电生理信号的DBS技术解释了STN与GPi之间的直接连接。用结构MRI成像技术解释了STN-DBS对M1网络的调控中的时间效应。最后，结合CT成像技术与对患者运动功能的量化，围绕着fMRI技术构建了具有临床价值的预测模型。本文中关于fMRI信号处理与统计建模的研究提高了fMRI分析技术的可靠性、准确性，在神经科学与临床实践中具有关键意义。本文中关于STN-DBS治疗机制的探索基于fMRI技术实现了一项系统性的临床研究，在帕金森病的治疗及DBS技术的推广中具有关键意义。
The purpose of the presented thesis is to explore the mechanism of action of DBS, especially at the brain network level. We investigated the brain modulatory effect of STN-DBS in patients with Parkinson’s disease. fMRI may provide a comprehensive picture of DBS-induced changes in brain networks. Recent advances in MRI-compatible DBS technology, which can now be safely applied to human subjects, have provided an unprecedented opportunity for exploring specific, but subtle changes in brain circuits. We have accomplished a systematic study based on fMRI in patients with Parkinson’s disease, who underwent DBS implantation into the STN.The low reliability and accuracy of fMRI restricts its use in clinical practice and impedes the investigations of the neural basis of human cognition. By decomposing fMRI signal time-series into stimuli-related responses, fixed-effect components, and random-effect components, we illustrated three major limitations in conventional fMRI analysis. We have achieved accurate fMRI analysis by improving fMRI signal modeling.Then, we aimed to reveal the neuromodulatory effect of STN-DBS on the brain networks by using the task fMRI technique. By employing block-desinged DBS stimulation and simultaneous fMRI scanning, we have first reported that STN-DBS modulates two cerebellar regions situated in two different brain networks. We showed that STN-DBS (de)activates two distinct brain networks and that the GPi is asymmetrically connected to the thalamus under STN-DBS.Then, we aimed to reveal the neuromodulatory effect of STN-DBS on the brain networks by using the resting-state fMRI technique. We have achieved efficient connectomics analysis based on linear mixed effect modeling of functional connectivity. We showed that STN-DBS modulates four of seven cortical functional networks, in which the motor-visual networks were significantly normalized and the dorsal attention-frontoparietal networks were significantly denormalized. We have further illustrated that the functional normalization was related to the neuromodulatory effect inside the thalamus.Then, we aimed to achieve a multimodal analysis of the STN-DBS modulation effect and to specify the clinical significance of employing fMRI in the STN-DBS study. We showed a close relationship between the functional activity of the STN and the GPi, by combining fMRI and electrophysiology; the time-related structural volume change related to the deactivation of M1-network, by using T1- and QSM- weighted MR imaging. Finally, we created a multi-information prediction model which can predict the clinical outcome of STN-DBS.The investigation of signal modeling and statistical modeling improves the reliability and accuracy of fMRI, broadening the application of fMRI in both neuroscience and clinical application. The investigation of the mechanism of action of STN-DBS was achieved based on a systematic study combining MRI compatible DBS and functional MRI techniques, providing novel insights into the neural mechanisms underlying DBS.
