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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：
7667877
负责人：
Sergei Turovets
金额：
$ 48.5万
依托单位：
ELECTRICAL GEODESICS, INC.
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 2011-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/7667877
关键词：
Adopted Adult Agar Algorithms Atlases Binding Brain Calibration Cerebrospinal Fluid Cerebrum Child Clinical Clinical Research Comprehension Computer software Data Databases Electrodes Electroencephalogram Electroencephalography Epilepsy Foundations Generations Goals Head Human Individual Infant Influentials Investments Laboratories Language Lead Literature MRI Scans Magnetic Resonance Imaging Magnetoencephalography Marketing Measures Medical Research Methods Modeling Pattern Recognition Performance Phase Phase II Clinical Trials Photogrammetry Positioning Attribute Price Procedures Property Recovery Research Research Personnel Research Project Grants Resolution Saline Scalp structure Scanning Seizures Shapes Side Simulate Solutions Source Specific qualifier value Surveys System Testing Time Tissues Validation Visualization software Work advanced system brain electrical activity commercialization cost cranium data acquisition design electric impedance flexibility human subject imaging Segmentation improved infancy insight next generation public health relevance reconstruction relating to nervous system retinal rods sensor simulation success systems research tissue reconstruction tomography tool

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、廉价且未得到充分利用的神经诊断工具。最近的技术进步催生了密集阵列脑电图，其中包括可在 5 分钟内轻松应用的 256 通道传感器网络、廉价的高性能放大和数字化系统、传感器与 MR 图像精确配准的方法以及灵活的模式识别和可视化软件。如果能够将脑电图活动的神经源准确定位到特定的皮质网络，那么密集阵列脑电图可以为临床和研究应用提供新的见解。这些应用范围从癫痫神经外科计划中定位癫痫发作到确定婴儿期语言理解的神经基础。在第一阶段，我们证明了使用“有界”电阻抗断层扫描（bEIT）方法，使用 5A 外加电流来测量头部组织的电导率是可行的，其中头部组织的几何形状由分段 MR 图像指定。由于测量 EEG 的 bEIT 使用相同的 EEG 光谱范围和电极，因此 bEIT 程序提供了通过头部组织的电容量传导的高效、低成本规范。这可能会导致脑电图源定位的重大进步。作为这一进展的证据，第一阶段的结果表明，在每个使用 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五倍。如果在第二阶段研究中得到证实，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带来一种快速、准确且廉价的 bEIT 方法，与每个密集阵列脑电图记录相集成，为婴儿、儿童和成人提供强大且可靠的脑电图源定位。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前景，表明通过精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)。公共健康相关性：该研究项目创建的电导率扫描系统将提供对人体头部组织电导率的准确估计，有助于通过脑电图（EEG）分析大脑的电活动。由于数据采集快速、安全，并且取自用于脑电图的同一头皮传感器，因此电导率扫描将大大改善研究和医疗应用中有关大脑的信息。