Patient-specific modeling and network perturbation to enhance the predictability of direct cortical stimulation for epilepsy

患者特异性建模和网络扰动可增强直接皮质刺激治疗癫痫的可预测性

• 批准号: 10247063
• 负责人: JOHN D ROLSTON
• 金额: $ 19.23万
• 依托单位: UNIVERSITY OF UTAH
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-30 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10247063
• 关键词: Affect; Area; Axon; Brain; Brain Mapping; Brain region; Characteristics; Clinical; Computer Models; Computer software; Computers; Data; Diffuse; Diffusion Magnetic Resonance Imaging; Distant; Doctor of Philosophy; Electric Stimulation; Electrical Stimulation of the Brain; Electrocorticogram; Electrodes; Elements; Epilepsy; Evoked Potentials; FDA approved; Freedom; Frequencies; Gold; Human; Image; Implant; Implanted Electrodes; Individual; Industry; Intractable Pain; Knowledge; Language; Lead; Link; Location; Maps; Mental Depression; Mental disorders; Mentors; Modeling; Monitor; Morbidity - disease rate; Motor; Network-based; Neurologic Deficit; Neurosurgeon; Operative Surgical Procedures; Outcome; Pathway interactions; Patient-Focused Outcomes; Patients; Physiologic pulse; Physiology; Postdoctoral Fellow; Research; Research Personnel; Residencies; Resolution; Rest; Safety; Scientist; Seeds; Seizures; Site; Software Engineering; Stimulus; Structure; System; Technology; Testing; Tissues; Training; Universities; Utah; Work; base; career; density; design; experimental study; improved; insight; multi-electrode arrays; multimodality; neuroimaging; neuroregulation; neurosurgery; novel; patient population; post-doctoral training; predicting response; programs; prospective; response; sensory cortex; skills; tool; tractography; white matter

PROJECT SUMMARY/ABSTRACT Direct cortical stimulation of the brain is used to treat epilepsy and map brain function during surgery. Yet few patients are free of seizures with this treatment, and morbidity occurs despite ostensibly adequate mapping. When cortical stimulation is used, it is assumed that the area nearby the electrode, within a few centimeters, is most affected. But our prior work shows that stimulation evokes widespread effects in distant regions of the brain. Understanding these network effects will be key in improving our use of brain stimulation. Using patients with electrodes implanted in the brain for epilepsy treatment, I will investigate cortical stimulation by 1) using resting-state functional connectivity to predict evoked potential characteristics, 2) using detailed computer models of patient brains to predict the responses of stimulation, and 3) correlating the networks activated by stimulation with patient outcomes following NeuroPace Responsive Neurostimulator placement. I am a practicing neurosurgeon and neuroscientist with a career devoted to understanding electrical stimulation of the brain. I was trained as a computer scientist and have relied heavily on this skillset during my PhD and post-doctoral training. For my PhD, I designed the hardware and software for a closed-loop neurostimulator, and applied this system to epilepsy research. During my post-doc and residency in neurosurgery, I studied the basis of electrical stimulation mapping using high-density electrocorticography. While in industry, I worked as lead software engineer for a company designing closed-loop stimulation/recording technology for multielectrode arrays. Now, as a functional neurosurgeon, I use multielectrode stimulation and recording daily in my patients. Network imaging and computer modeling of stimulation will provide new ways to understand and restore brain function. Such modeling goes beyond the empirical data that most researchers collect, and that most of my prior research has focused on. To develop these models, I will work with an expert in neuromodulation modeling, Dr. Christopher Butson, at the University of Utah. I will acquire these skills through hands-on training, didactic coursework, and intensive mentoring. At the end of my training, my hope is to create an independent research program to further link brain stimulation with an understanding of brain networks, and use these insights to improve the safety and efficacy of the direct cortical stimulation I use in my patients.

项目总结/摘要 大脑的直接皮层刺激用于治疗癫痫和在手术期间映射大脑功能。 然而，很少有病人是免费的癫痫与这种治疗，发病率发生，尽管表面上足够的 映射.当使用皮层刺激时，假设电极附近的区域，在几分钟内， 厘米，受影响最大。但我们先前的工作表明，刺激引起了广泛的影响，在遥远的 大脑的各个区域。了解这些网络效应将是改善我们使用大脑刺激的关键。 使用在大脑中植入电极的癫痫治疗患者，我将研究皮层 通过1）使用静息状态功能连接来预测诱发电位特征，2）使用 患者大脑的详细计算机模型，以预测刺激的反应，以及3）将 NeuroPace响应神经刺激器后，通过刺激激活的网络与患者结局 安置 我是一名执业神经外科医生和神经科学家，我的职业生涯致力于了解电 刺激大脑。我是一名计算机科学家，在我的职业生涯中， 博士和博士后培训。在我的博士学位上，我设计了一个闭环系统的硬件和软件， 神经刺激器，并将该系统应用于癫痫的研究。在我的博士后和实习期间， 神经外科，我研究了电刺激映射的基础上使用高密度皮质电图。 在工业界，我担任一家公司的首席软件工程师，设计闭环 多电极阵列的刺激/记录技术。作为一名功能性神经外科医生， 多电极刺激和记录每天在我的病人。 刺激的网络成像和计算机建模将提供新的方法来理解和 恢复大脑功能这种建模超越了大多数研究人员收集的经验数据， 为了开发这些模型，我将与一位专家合作， 神经调节模型，克里斯托弗·巴特森博士，犹他州大学。我将通过以下方式获得这些技能 实践培训、教学课程和强化辅导。训练结束后，我希望 创建一个独立的研究项目，进一步将大脑刺激与对大脑的理解联系起来。 网络，并使用这些见解来提高我在我的大脑中使用的直接皮层刺激的安全性和有效性。 患者