Epileptiform oscillations, EEG & seizure prediction
癫痫样振荡,脑电图
基本信息
- 批准号:6832791
- 负责人:
- 金额:$ 16.54万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2004
- 资助国家:美国
- 起止时间:2004-01-01 至 2008-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
DESCRIPTION (provided by applicant): Worldwide, 50 million people suffer from epilepsy, and for 25% of these patients the seizures are not controlled by any available medical or surgical treatments. Development of new treatment options and improving the efficacy of epilepsy surgery are presently limited by our poor understanding of how epileptic brain generates spontaneous seizures (ictogenesis). There is accumulating evidence that high-frequency epileptiform oscillations (60 - 500 Hz) are a unique signature of epileptic brain, and play an important role in neocortical seizure ictogenesis [1-3]. As part of a program to develop the principal investigator's (PI) career as a clinician-investigator, we propose a multidisciplinary collaboration between the Mayo Clinic and University of Pennsylvania directed at understanding neocortical ictogenesis and improving the ability to localize regions of epileptogenic brain. This project is an initial step toward a more complete understanding of a common, and difficult to treat, neurological disease. We will develop bioengineering methods to detect and quantify high-frequency epileptiform oscillations (HFEO) from human intracranial EEG recordings. We will investigate the clinical usefulness of HFEO as a signature of epileptogenic brain for epilepsy surgery and seizure prediction. We believe understanding the cellular and network mechanisms underlying HFEO will improve our ability to localize regions of focal epileptogenic brain, an area presently limiting the success of epilepsy surgery, while laying the foundation for the rational development of new therapies such as implantable devices for seizure prediction and prevention. The proposed project will continue a collaboration that combines the neuroscience and neuroengineering strengths of the University of Pennsylvania with the clinical strength of the Mayo Clinic's large surgical epilepsy practice, thus providing a fertile environment for a developing clinician-investigator. The principal investigator has demonstrated potential for independent patient-based research, and with the training provided by this project will develop an independent research program translating advances in neuroengineering and clinical research into clinical practice.
描述(申请人提供):全世界有5000万人患有癫痫,其中25%的患者的癫痫发作不能通过任何可用的内科或外科治疗来控制。目前,由于我们对癫痫大脑如何产生自发性癫痫发作(癫痫的发生)缺乏了解,新的治疗方案的开发和癫痫手术疗效的提高受到了限制。越来越多的证据表明,高频癫痫样振荡(60-500赫兹)是癫痫脑的独特特征,在新皮质癫痫的发生中发挥着重要作用[1-3]。作为发展首席研究员(PI)作为临床医生-研究员职业生涯的计划的一部分,我们建议梅奥诊所和宾夕法尼亚大学之间进行多学科合作,旨在了解新皮质发育和提高定位致痫脑区域的能力。这个项目是朝着更全面地了解一种常见的、难以治疗的神经疾病迈出的第一步。我们将开发生物工程方法来检测和量化人类脑电记录中的高频癫痫样振荡(HFEO)。我们将探讨HFEO作为致痫脑信号在癫痫手术和癫痫预测中的临床应用价值。我们相信,了解HFEO背后的细胞和网络机制将提高我们定位局灶性致痫脑区域的能力,这一区域目前限制了癫痫手术的成功,同时为合理开发新的治疗方法,如用于癫痫预测和预防的植入性装置奠定了基础。拟议中的项目将继续合作,将宾夕法尼亚大学的神经科学和神经工程优势与梅奥诊所大型外科癫痫实践的临床优势结合起来,从而为发展中的临床医生兼研究人员提供一个肥沃的环境。首席研究员已经展示了独立的以患者为基础的研究的潜力,通过该项目提供的培训,将开发一个独立的研究计划,将神经工程和临床研究的进展转化为临床实践。
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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Gregory A Worrell其他文献
Spatiotemporal Rhythmic Seizure Sources Can be Imaged by means of Biophysically Constrained Deep Neural Networks
时空节律性癫痫发作源可以通过生物物理约束的深度神经网络进行成像
- DOI:
10.1101/2023.11.30.23299218 - 发表时间:
2023 - 期刊:
- 影响因子:0
- 作者:
Rui Sun;Abbas Sohrabpour;Boney Joseph;Gregory A Worrell;Bin He - 通讯作者:
Bin He
Gregory A Worrell的其他文献
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{{ truncateString('Gregory A Worrell', 18)}}的其他基金
Reliable Seizure Prediction Using Physiological Signals and Machine Learning
使用生理信号和机器学习进行可靠的癫痫发作预测
- 批准号:
10518240 - 财政年份:2022
- 资助金额:
$ 16.54万 - 项目类别:
Reliable Seizure Prediction Using Physiological Signals and Machine Learning
使用生理信号和机器学习进行可靠的癫痫发作预测
- 批准号:
10629373 - 财政年份:2022
- 资助金额:
$ 16.54万 - 项目类别:
Reliable Seizure Prediction Using Physiological Signals and Machine Learning
使用生理信号和机器学习进行可靠的癫痫发作预测
- 批准号:
9445497 - 财政年份:2015
- 资助金额:
$ 16.54万 - 项目类别:
Neurophysiologically Based Brain State Tracking & Modulation in Focal Epilepsy
基于神经生理学的大脑状态跟踪
- 批准号:
9921573 - 财政年份:2015
- 资助金额:
$ 16.54万 - 项目类别:
Reliable Seizure Prediction Using Physiological Signals and Machine Learning
使用生理信号和机器学习进行可靠的癫痫发作预测
- 批准号:
9238808 - 财政年份:2015
- 资助金额:
$ 16.54万 - 项目类别:
Neurophysiologically Based Brain State Tracking & Modulation in Focal Epilepsy
基于神经生理学的大脑状态跟踪
- 批准号:
9972970 - 财政年份:2015
- 资助金额:
$ 16.54万 - 项目类别:
Microseizures, Ultra-slow & High Frequency Oscillations: Biomarkers of epilepsy
微惊厥,超慢
- 批准号:
8448247 - 财政年份:2009
- 资助金额:
$ 16.54万 - 项目类别:
Microseizures, Ultra-slow & High Frequency Oscillations: Biomarkers of epilepsy
微惊厥,超慢
- 批准号:
7653568 - 财政年份:2009
- 资助金额:
$ 16.54万 - 项目类别:
Microseizures, Ultra-slow & High Frequency Oscillations: Biomarkers of epilepsy
微惊厥,超慢
- 批准号:
8234974 - 财政年份:2009
- 资助金额:
$ 16.54万 - 项目类别:
Microseizures, Ultra-slow & High Frequency Oscillations: Biomarkers of epilepsy
微惊厥,超慢
- 批准号:
8053265 - 财政年份:2009
- 资助金额:
$ 16.54万 - 项目类别:
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