Conductivity Analysis for Improved High-Resolution EEG
电导率分析可改善高分辨率脑电图
基本信息
- 批准号:7538300
- 负责人:
- 金额:$ 54.07万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2006
- 资助国家:美国
- 起止时间:2006-09-21 至 2010-06-30
- 项目状态:已结题
- 来源:
- 关键词:AdoptedAdultAgarAlgorithmsAtlasesBindingBrainCalibrationCerebrospinal FluidCerebrumChildClinicalClinical ResearchCommercial SourcesComprehensionComputer softwareDataDatabasesElectrodesElectroencephalogramElectroencephalographyEpilepsyFoundationsGenerationsGoalsHeadHumanIndividualInfantInfluentialsInvestmentsLaboratoriesLanguageLeadLiteratureLocalizedMRI ScansMagnetic Resonance ImagingMagnetoencephalographyMarketingMeasuresMedical ResearchMethodsModelingNumbersPattern RecognitionPerformancePhasePhase II Clinical TrialsPhotogrammetryPositioning AttributePriceProceduresPropertyPublic HealthRangeRecoveryResearchResearch PersonnelResearch Project GrantsResolutionSalineScalp structureScanningSeizuresShapesSideSimulateSolutionsSourceSpecific qualifier valueSurveysSystemTestingThinkingTimeTissuesValidationVisualization softwareWorkadvanced systembrain electrical activitycommercializationcostcraniumdata acquisitiondesignelectric impedancehuman subjectimprovedinfancyinsightnext generationreconstructionrelating to nervous systemretinal rodssensorsimulationsuccesssystems researchtomographytool
项目摘要
DESCRIPTION (provided by applicant): Electroencephalography (EEG) is a powerful, inexpensive, and underutilized neurodiagnostic tool. Recent technical advances have led to dense-array EEG, with 256-channel sensor nets that can be applied comfortably in 5 minutes, inexpensive, high-performance amplification and digitization systems, methods for exact sensor registration with MR images, and flexible pattern recognition and visualization software. If it were possible to accurately localize the neural sources of EEG activity to specific cortical networks, dense-array EEG could provide new insights in both clinical and research applications. These applications range from localizing seizure onset in neurosurgical planning for epilepsy to identifying the neural foundations of language comprehension in infancy. In Phase I, we showed it is feasible to use 5A impressed currents to measure the conductivity of head tissues, using a "bounded" electrical impedance tomography (bEIT) method in which the geometry of head tissues is specified with segmented MR images. Because the same EEG spectral range and electrodes are used for bEIT that measure the EEG, the bEIT procedure provides an efficient, low-cost specification of the electrical volume conduction through head tissues. This may lead to a major advance in EEG source localization. As evidence of this advance, the Phase I results showed that, in each of the human subjects examined with bEIT, the skull was five times more conductive than was assumed in classical source localization models. If confirmed in the Phase II studies, these results would provide a definitive resolution of the controversy over human skull conductivity in the current literature. The Phase II commercialization would lead to a fast, accurate, and inexpensive bEIT method integrated with each dense-array EEG recording, providing robust and reliable EEG source localization for infants, children, and adults. With dense-array bEIT measured as routinely as testing scalp electrode impedance, we can realize the promise of recent biophysical simulations suggesting that, with accurate correction for head-tissue conductivity, EEG provides spatial resolution of brain activity that is equal to or better than magnetoencephalography (MEG). PUBLIC HEALTH RELEVANCE: The conductivity scanning system created by this research project would provide accurate estimates of the conductivity of human head tissues that aids in the analysis of the brain's electrical activity with the electroencephalogram (EEG). Because data acquisition is fast, safe, and taken from the same scalp sensors that are used for the EEG, conductivity scanning would result in greatly improved information about the brain for both research and medical applications.
描述(由申请人提供): 脑电图(EEG)是一种功能强大,价格低廉,但未得到充分利用的神经诊断工具。最近的技术进步导致了密集阵列EEG,具有256通道传感器网络,可以在5分钟内舒适地应用,廉价,高性能的放大和数字化系统,用于精确传感器与MR图像配准的方法,以及灵活的模式识别和可视化软件。如果能够准确地将EEG活动的神经源定位到特定的皮层网络,密集阵列EEG可以在临床和研究应用中提供新的见解。这些应用范围从癫痫神经外科计划中的癫痫发作定位到婴儿期语言理解的神经基础。在第一阶段,我们表明,它是可行的,使用5A的外加电流来测量头部组织的电导率,使用“有界”电阻抗断层扫描(bEIT)的方法,其中头部组织的几何形状指定与分割的MR图像。因为相同的EEG频谱范围和电极用于测量EEG的bEIT,所以bEIT过程提供了通过头部组织的电体积传导的有效、低成本的规范。这可能导致EEG源定位的重大进展。作为这一进展的证据,第一阶段的结果表明,在每一个用bEIT检查的人类受试者中,头骨的导电性是经典源定位模型中假设的5倍。如果在II期研究中得到证实,这些结果将为当前文献中关于人类头骨电导率的争议提供明确的解决方案。第二阶段的商业化将导致一个快速,准确,廉价的bEIT方法与每个密集阵列EEG记录集成,为婴儿,儿童和成人提供强大和可靠的EEG源定位。通过像测试头皮电极阻抗一样常规测量密集阵列bEIT,我们可以实现最近生物物理模拟的承诺,即通过准确校正头部组织电导率,EEG提供的大脑活动空间分辨率等于或优于脑磁图(MEG)。公共卫生相关性:该研究项目创建的电导率扫描系统将提供对人类头部组织电导率的准确估计,有助于用脑电图(EEG)分析大脑的电活动。由于数据采集快速,安全,并且来自用于EEG的相同头皮传感器,因此电导率扫描将大大改善研究和医疗应用的大脑信息。
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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Sergei Turovets其他文献
Sergei Turovets的其他文献
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{{ truncateString('Sergei Turovets', 18)}}的其他基金
Pediatric Head Models for Improved Imaging of Neurological Development
用于改善神经发育成像的儿科头部模型
- 批准号:
8715176 - 财政年份:2010
- 资助金额:
$ 54.07万 - 项目类别:
Pediatric Head Models for Improved Imaging of Neurological Development
用于改善神经发育成像的儿科头部模型
- 批准号:
7801229 - 财政年份:2010
- 资助金额:
$ 54.07万 - 项目类别:
Pediatric Head Models for Improved Imaging of Neurological Development
用于改善神经发育成像的儿科头部模型
- 批准号:
8034215 - 财政年份:2010
- 资助金额:
$ 54.07万 - 项目类别:
Pediatric Head Models for Improved Imaging of Neurological Development
用于改善神经发育成像的儿科头部模型
- 批准号:
9118332 - 财政年份:2010
- 资助金额:
$ 54.07万 - 项目类别:
Conductivity Analysis for Improved High-Resolution EEG
电导率分析可改善高分辨率脑电图
- 批准号:
7345246 - 财政年份:2006
- 资助金额:
$ 54.07万 - 项目类别:
Conductivity Analysis for Improved High-Resolution EEG
电导率分析可改善高分辨率脑电图
- 批准号:
7158653 - 财政年份:2006
- 资助金额:
$ 54.07万 - 项目类别:
Conductivity Analysis for Improved High-Resolution EEG
电导率分析可改善高分辨率脑电图
- 批准号:
7667877 - 财政年份:2006
- 资助金额:
$ 54.07万 - 项目类别:
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