Multiscale analysis and modeling of spatiotemporal dynamics in human epilepsy
人类癫痫时空动力学的多尺度分析和建模
基本信息
- 批准号:8140975
- 负责人:
- 金额:$ 37.83万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2011
- 资助国家:美国
- 起止时间:2011-05-01 至 2016-04-30
- 项目状态:已结题
- 来源:
- 关键词:Action PotentialsAddressAdverse effectsBiologicalBrainBrain regionCharacteristicsClinicalComplexComputer SimulationCortical ColumnCouplingDataData AnalysesData SetDevelopmentDiseaseDisease ManagementElectrocorticogramEpilepsyEvolutionHumanIndividualInterdisciplinary StudyLinkMeasuresMedicalMedicineMethodsMicroscopicModelingNervous system structureNeuronsPatientsPatternPharmaceutical PreparationsPhasePhysiologicalPhysiologyPopulationProcessResearchResearch PersonnelSeizuresSimulateSystemTechniquesTestingTherapeuticTherapeutic InterventionTimehuman datain vivoinnovationmulti-scale modelingneuromechanismnovelrelating to nervous systemspatiotemporalstatisticstreatment strategyvoltage
项目摘要
DESCRIPTION (provided by applicant): PROJECT SUMMARY / ABSTRACT Across the world, nearly 50 million people suffer from epilepsy. For an estimated 30% of these individuals, seizures remain poorly controlled despite maximal medical management. Moreover, treatment of epilepsy through medication often results in significant - sometimes debilitating - side effects. To advance the therapeutic management of epilepsy, we must understand the physiological mechanisms which support this disease. Unraveling these mechanisms is especially difficult. Like many neural processes, the seizure involves spatial scales spanning many orders of magnitude, from the individual neuron to the entire nervous system. Moreover, typical clinical recordings provide only a limited view of the vast mechanisms underlying the seizure. In this project, an interdisciplinary research group consisting of clinicians, statisticians, and mathematicians will study the dynamical mechanisms that support epilepsy and, in doing so, suggest novel therapies to treat the disease. The research will focus on three fundamental aspects of the seizure - how it begins, how it spreads over the brain, and how it ends - observed in voltage recordings from human patients with epilepsy. These recordings will span multiple spatial scales and include activity generated by individual neurons, small neural populations, and large brain regions. To characterize these data, sophisticated analysis techniques will be applied that link the activity across spatial scales. In addition, computational models of the neural activity will be developed and constrained using the multiscale data. These models will then be applied to suggest the mechanisms that support multiscale interactions during seizure and to propose novel therapies to treat epilepsy. Completion of the proposed research will represent a significant step forward toward a deeper and more complete understanding of epileptic physiology, and toward a system for exploring and testing innovative methods for seizure control.
PUBLIC HEALTH RELEVANCE: PROJECT NARRATIVE Epilepsy is a devastating and poorly understood illness that evolves on multiple spatial scales. During a seizure, multiscale interactions are prominent yet the mechanisms that support these interactions remain unknown. To address (and eventually treat) these mechanisms, an interdisciplinary team of researchers will record, analyze and model multiscale voltage data from human patients with epilepsy.
描述(由申请人提供):项目概述/摘要在世界各地,近5000万人患有癫痫。据估计,这些人中有30%的人,尽管进行了最大限度的医疗管理,癫痫发作仍然控制不佳。此外,通过药物治疗癫痫往往会导致严重的-有时使人衰弱的-副作用。为了推进癫痫的治疗管理,我们必须了解支持这种疾病的生理机制。解开这些机制尤其困难。像许多神经过程一样,癫痫发作涉及跨越许多数量级的空间尺度,从单个神经元到整个神经系统。此外,典型的临床记录仅提供了癫痫发作背后的巨大机制的有限视图。在这个项目中,一个由临床医生、统计学家和数学家组成的跨学科研究小组将研究支持癫痫的动力机制,并提出治疗这种疾病的新疗法。这项研究将集中在癫痫发作的三个基本方面-它如何开始,如何在大脑中传播,以及如何结束-在癫痫患者的电压记录中观察到。这些记录将跨越多个空间尺度,包括单个神经元、小神经群和大大脑区域产生的活动。为了确定这些数据的特点,将采用复杂的分析技术,将不同空间尺度的活动联系起来。此外,神经活动的计算模型将使用多尺度数据开发和约束。然后,这些模型将被应用于建议的机制,支持癫痫发作期间的多尺度相互作用,并提出新的疗法来治疗癫痫。拟议研究的完成将代表着朝着更深入和更完整地了解癫痫生理学,以及探索和测试癫痫控制创新方法的系统迈出的重要一步。
公共卫生相关性:项目叙述癫痫是一种破坏性和知之甚少的疾病,在多个空间尺度上演变。在癫痫发作期间,多尺度相互作用是突出的,但支持这些相互作用的机制仍然未知。为了解决(并最终治疗)这些机制,一个跨学科的研究团队将记录、分析和建模来自癫痫患者的多尺度电压数据。
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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Uri Tzvi Eden其他文献
Uri Tzvi Eden的其他文献
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