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
基本信息
- 批准号:10023213
- 负责人:
- 金额:$ 19.23万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 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:
- 关键词:AffectAreaAxonBrainBrain MappingBrain regionCharacteristicsClinicalComputer ModelsComputer softwareComputersDataDiffuseDiffusion Magnetic Resonance ImagingDistantDoctor of PhilosophyElectric StimulationElectrical Stimulation of the BrainElectrocorticogramElectrodesElementsEpilepsyEvoked PotentialsFDA approvedFreedomFrequenciesGoldHumanImageImplantImplanted ElectrodesIndividualIndustryIntractable PainKnowledgeLanguageLeadLinkLocationMapsMental DepressionMental disordersMentorsModelingMonitorMorbidity - disease rateMotorNetwork-basedNeurologic DeficitNeurosurgeonOperative Surgical ProceduresOutcomePathway interactionsPatient-Focused OutcomesPatientsPhysiologic pulsePhysiologyPostdoctoral FellowResearchResearch PersonnelResidenciesResolutionRestSafetyScientistSeedsSeizuresSiteSoftware EngineeringStimulusStructureSystemTechnologyTestingTissuesTrainingUniversitiesUtahWorkbasecareerdensitydesignexperimental studyimprovedinsightmulti-electrode arraysmultimodalityneuroimagingneuroregulationneurosurgerynovelpatient populationpost-doctoral trainingpredicting responseprogramsprospectiveresponsesensory cortexskillstooltractographywhite matter
项目摘要
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.
项目摘要/摘要
在手术中,大脑的直接皮质刺激被用来治疗癫痫和绘制大脑功能图。
然而,很少有患者在这种治疗下没有癫痫发作,尽管表面上足够治疗,但发病率还是会出现。
映射。当使用皮质刺激时,假设电极附近的区域,在几个
厘米,是受影响最大的。但我们之前的工作表明,刺激在遥远的地方引起广泛的影响
大脑的不同区域。了解这些网络效应将是改善我们对大脑刺激的使用的关键。
利用脑部植入电极治疗癫痫的患者,我会研究大脑皮质
通过1)使用静息状态功能连接来预测诱发电位特征的刺激,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反应性神经刺激器后刺激激活的网络与患者预后的关系
放置。
我是一名执业神经外科医生和神经学家,致力于了解电学
对大脑的刺激。我是作为一名计算机科学家接受培训的,在我的职业生涯中,我一直严重依赖这一技能
博士和博士后培训。在我的博士学位上,我设计了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研究。在我的博士后和实习期间
在神经外科,我研究了使用高密度皮质脑电图电刺激标测的基础。
在工业界时,我在一家设计闭环的公司担任首席软件工程师
多电极阵列的刺激/记录技术。现在,作为一名功能性神经外科医生,我使用
我的病人每天都要进行多电极刺激和记录。
网络成像和刺激的计算机建模将提供新的方式来理解和
恢复大脑功能。这样的建模超越了大多数研究人员收集的经验数据,而且
我之前的大部分研究都集中在。为了开发这些模型,我将与一位专家合作
犹他大学的克里斯托弗·巴特森博士说,神经调节建模。我将通过以下途径获得这些技能
实践培训、授课课程和密集的指导。在我的训练结束后,我希望
创建一个独立的研究计划,进一步将脑刺激与对大脑的了解联系起来
网络,并使用这些洞察力来提高我在我的
病人。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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JOHN D ROLSTON其他文献
JOHN D ROLSTON的其他文献
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{{ truncateString('JOHN D ROLSTON', 18)}}的其他基金
Propagation patterns of microelectrode-recorded human interictal discharges
微电极记录的人体发作间期放电的传播模式
- 批准号:
9807847 - 财政年份:2019
- 资助金额:
$ 19.23万 - 项目类别:
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癫痫直接皮质刺激的可预测性
- 批准号:
10887865 - 财政年份:2019
- 资助金额:
$ 19.23万 - 项目类别:
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癫痫直接皮质刺激的可预测性
- 批准号:
10686306 - 财政年份:2019
- 资助金额:
$ 19.23万 - 项目类别:
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 - 财政年份:2019
- 资助金额:
$ 19.23万 - 项目类别:
High-density electrocorticography to understand cortical speech arrest sites
高密度皮层电描记术了解皮层言语停滞部位
- 批准号:
8718517 - 财政年份:2015
- 资助金额:
$ 19.23万 - 项目类别:
Closed-loop distributed microstimulation for epilepsy
闭环分布式微刺激治疗癫痫
- 批准号:
7544390 - 财政年份:2008
- 资助金额:
$ 19.23万 - 项目类别:
Closed-loop distributed microstimulation for epilepsy
闭环分布式微刺激治疗癫痫
- 批准号:
7689173 - 财政年份:2008
- 资助金额:
$ 19.23万 - 项目类别:
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