Use of Resting-State Networks to Predict the Ideal Site for Brain Stimulation

描述（由申请人提供）：局灶性脑刺激，包括深部脑刺激（DBS）和重复性经颅磁刺激（rTMS），可以对越来越多的脑部疾病（包括帕金森病，卒中后缺陷，甚至潜在的最低意识状态）患者具有治疗益处。然而，对于特定的病人或疾病，什么刺激部位最有效往往是不清楚的，这限制了疗效和对新疾病的扩展。选择一个理想的刺激点是困难的，部分原因是局部脑刺激通过连接传播，影响大脑区域的分布式网络，而这些网络效应可以决定临床反应。因此，决定刺激的位置部分取决于我们预测刺激将在哪里传播的能力。神经成像技术的进步，如静息状态功能连接MRI (rs-fcMRI)，使我们能够以前所未有的清晰度可视化人类的大脑网络。该项目验证了一个假设，即用rs-fcMRI观察到的神经网络可以预测局灶性脑刺激将如何传播，从而有助于选择理想的刺激位点，最终针对特定患者的特定神经网络。我建议在运动网络中测试这一假设，在运动网络中，局部脑刺激的传播可以用经颅磁刺激（TMS）来测量。对初级运动皮层（M1）的经颅磁刺激导致可测量的肌肉收缩，其强度取决于M1中潜在的神经元活动。如果将经颅磁刺激应用于连接的区域，然后传播并改变M1，它将影响经颅磁刺激引起的肌肉收缩的强度。因此，目前的研究将检查rs-fcMRI是否可以用于确定经颅磁刺激的影响将以可预测的方式传播到M1的位置。它将进一步阐明rs-fcMRI的哪些特性是最有用的，以及基于个性化rs-fcMRI模式选择的刺激位点是否优于基于群体数据选择的刺激位点。如果这个项目成功，未来的努力将扩展该方法，以确定最有可能具体影响与不同疾病相关的网络的TMS和DBS位点。潜在的应用包括识别顶叶TMS最有可能传播到注意网络并改善空间忽视的位点，DBS最有可能影响运动网络而不影响帕金森患者的认知或情绪网络，或者在最低意识状态下最有可能影响涉及觉醒和意识的网络的候选刺激位点。

DESCRIPTION (provided by applicant): Focal brain stimulation, including deep brain stimulation (DBS) and repetitive trans cranial magnetic stimulation (rTMS), can have therapeutic benefit in patients with an increasing number of brain disorders including Parkinson's, post-stroke deficits, and potentially even minimally conscious states. However it is often unclear what stimulation site will work best for a given patient or disease, limiting efficacy and extension to new disorders. Choosing an ideal stimulation site is difficult in part because focal brain stimulation propagates through connections to impact a distributed network of brain regions, and these network effects can determine the clinical response. Thus deciding where to stimulate depends in part on our ability to predict where stimulation will propagate. Advances in neuroimaging technology, such as resting-state functional connectivity MRI (rs-fcMRI) allow us to visualize brain networks in humans with unprecedented clarity. This project tests the hypothesis that networks seen with rs-fcMRI can predict how focal brain stimulation will propagate, thus facilitating selection of an ideal stimulation site to eventually target specific networks in specific patients. I propose to test this hypothesis in the motor network, where propagation of focal brain stimulation can be measured with transcranial magnetic stimulation (TMS). TMS to primary motor cortex (M1) results in a measurable muscle contraction, the strength of which depends on the underlying neuronal activity in M1. If one applies TMS to a connected region that then propagates to and alters M1, it will impact the strength of the TMS-induced muscle contraction. The current study will therefore examine whether rs-fcMRI can be used to identify sites from which the effects of TMS will propagate to and affect M1 in a predictable manner. It will further clarify what properties of rs-fcMRI are most useful and whether stimulation sites selected based on individualized rs-fcMRI patterns are superior to those selected based on group data. If this project is successful, future efforts will extend the approach to identify TMS and DBS sites most likely to specifically affect networks implicated in different diseases. Potential applications include identifying parietal TMS sites most likely to propagate to attention networks and improve spatial neglect, DBS sites most likely to impact motor networks without affecting cognitive or mood networks in a patient with Parkinson's, or candidate stimulation sites in minimally conscious states most likely to impact networks involved in arousal and consciousness.