Electro/Magnetoencephalography Signal Processing Methods and Performance

脑电图/脑磁图信号处理方法和性能

• 批准号: 0105334
• 负责人: Arye Nehorai
• 金额: $ 39.43万
• 依托单位: University of Illinois at Chicago
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2001
• 资助国家: 美国
• 起止时间: 2001-05-01 至 2005-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0105334&HistoricalAwards=false
• 关键词: Electro; Magnetoencephalography; Signal; Processing; Methods

Electro/MagnetoencephalographySignal Processing Methods and PerformanceArye NehoraiEECS DepartmentUniversity of Illinois at ChicagoDetecting electric sources in the brain is important for both understanding its function and for clinical applications. Examples include mapping the brain activities and finding foci of epilepsy activities before surgical treatment. We are developing detection methods that find the sources through computer processing of measurements from arrays of sensors around the head. More specifically, we employ Electro/Magnetoencephalography (E/MEG) sensors that measure electric potentials on the scalp and induced magnetic field outside the head. We are developing several new methods of processing the E/MEG signals, analyzing their performance and validating with real data their applicability, thus contributing to improvements in the use and performance of E/MEG equipment and to increase the capabilities of neurological data processing tools.We hope to solve some of the most currently relevant E/MEG problems: (i) estimating and tracking paths of functional and neuronal connectivity, following the trajectories of cerebral sources, (ii) estimating concentrated and extended sources, in the presence of noise with unknown spatio-temporal covariance, (iii) simultaneously estimating source parameters and tissue conductivities, (iv) developing computationally efficient methods for realistically-shaped head models, which reduce the demands on segmentation algorithms, (v) estimating source parameters for evoked responses with inhomogeneous epochs. We are also deriving performance measures for evaluating the newly proposed methods allowing comparison with existing systems and techniques; identifying those that are effective and helping in the optimum design of future systems. Finally, we are using empirical data sets evaluate and validate methods. These data sets are being derived by the Dr. Jeffrey Lewine's group from Clinical and Cognitive Neurosciences studies where whole-head MEG and high-density EEG are recorded simultaneously. The Nehorai group is developing the processing methods and the two groups will collaborate on their evaluation and validation.

脑电/脑磁仪信号处理方法和性能眼NehoraiEECS系伊利诺伊大学芝加哥分校检测大脑中的电源对于了解其功能和临床应用都很重要。例如，在手术治疗前绘制大脑活动图和发现癫痫活动的病灶。我们正在开发检测方法，通过计算机处理来自头部周围传感器阵列的测量值来找到源。更具体地说，我们使用电/脑磁图（E/MEG）传感器来测量头皮上的电位和头部外的感应磁场。我们正在开发几种处理E/MEG信号的新方法，分析其性能并用实际数据验证其适用性，从而有助于改进E/MEG设备的使用和性能，并提高神经学数据处理工具的能力。我们希望解决一些当前最相关的E/MEG问题：(i)根据脑源的轨迹估计和跟踪功能和神经元连接的路径；（ii）在存在未知时空协方差的噪声的情况下估计集中和扩展的源；（iii）同时估计源参数和组织电导率；（iv）为逼真形状的头部模型开发计算效率高的方法，从而减少对分割算法的要求。(v)估计非均匀时期诱发反应的源参数。我们还制定了绩效衡量标准，以评估新提出的方法，以便与现有系统和技术进行比较；识别那些是有效的，并有助于未来系统的优化设计。最后，我们使用经验数据集评估和验证方法。这些数据集是由Jeffrey Lewine博士的团队从临床和认知神经科学研究中获得的，他们同时记录了全头部脑磁图和高密度脑电图。Nehorai小组正在开发加工方法，两个小组将在评估和验证方面进行合作。