Use of resting-state networks to predict the ideal site for brain stimulation

描述(申请人提供)：局部脑刺激，包括脑深部刺激(DBS)和重复经颅磁刺激(RTMS)，可以对越来越多的大脑疾病患者产生治疗效果，包括帕金森氏症、中风后缺陷，甚至潜在的最低意识状态。然而，人们往往不清楚哪个刺激部位对特定的患者或疾病最有效，从而限制了疗效和对新疾病的推广。选择一个理想的刺激地点很困难，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网络，而这些网络效应可以决定临床反应。因此，决定在哪里刺激在一定程度上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磁共振成像(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。这个项目测试了这样一种假设，即rs-fcmri看到的网络可以预测局灶性脑刺激如何传播，从而有助于选择理想的刺激地点，最终针对特定患者的特定网络。我建议在运动网络中验证这一假设，在运动网络中，可以通过经颅磁刺激(TMS)测量局部脑刺激的传播。对初级运动皮质(M1)的TMS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。如果一个人将TMS应用于一个相连的区域，然后该区域传播到并改变M1，它将影响TMS诱导的肌肉收缩的强度。因此，目前的研究将审查RS-fcMRI是否可以用来确定TMS的影响将以可预测的方式传播到并影响M1的地点。它将进一步阐明rS-fcMRI的哪些特性最有用，以及基于个性化的rS-fcMRI模式选择的刺激部位是否优于基于组数据选择的刺激部位。如果该项目成功，未来的努力将扩大识别TMS和DBS站点的方法，这些站点最有可能具体影响与不同疾病有关的网络。潜在的应用包括识别最有可能传播到注意网络并改善空间忽视的顶叶TMS站点，最可能影响帕金森患者的运动网络而不影响认知或情绪网络的DBS站点，或者处于最低意识状态的候选刺激站点最可能影响涉及觉醒和意识的网络。

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.