Robust Space-Time Signal Processing for MEG/EEG

描述（由申请人提供）：该计划的目标是发展信号处理方法，以扩大MEG/EEG功能脑成像作为脑功能障碍诊断的临床工具的作用，并作为脑发育和功能研究的科学工具。该研究项目引入了一种新的方法，即使用多分辨率基函数展开来表示测量数据和下皮层表面。通过开发利用基函数展开的信号处理、源定位和成像算法，提高了性能。提出的研究的具体目的是：1)建立共同代表大脑活动在传感器和皮层表面的时空分布的基函数展开。我们提出的多分辨率方法采用了不同时空尺度下大脑活动的简洁表示，这是有效解决反问题各个方面的关键特性。2)开发鲁棒的信号处理算法，利用基函数表示对多源进行检测、定位和监测，并对皮质表面的活动进行成像。与现有方法相比，所提出的算法将降低复杂性并提高性能。3)利用非参数统计分析和计算机模拟来表征目标1和目标2下开发的算法的性能。4)获得人体受试者试点数据，证明目标1和目标2下开发的算法的有效性。

DESCRIPTION (provided by applicant): The goal of this program is development of signal processing methods that will expand the role MEG/EEG functional brain imaging as a clinical tool for diagnosis of brain dysfunction and as a scientific tool for the study of brain development and function. The research program introduces a new approach in which both the measured data and underlying cortical surface are represented using multiresolution basis function expansions. Improved performance is obtained by developing signal processing, source localization, and imaging algorithms that exploit the basis function expansion. The specific aims of the proposed studies are: 1) To develop basis function expansions that jointly represent the spatio-temporal distribution of brain activity at the sensors and on the cortical surface. Our proposed multiresolution approach employs a parsimonious representation for brain activity at different temporal and spatial scales, a critical property for effective solution of various aspects of the inverse problem. 2) To develop robust signal processing algorithms that exploit the basis function representation to perform detection, localization and monitoring of multiple sources, and imaging of the activity on the cortical surface. The proposed algorithms will have reduced complexity and improved performance relative to existing methods. 3) To characterize the performance of the algorithms developed under Aims 1 and 2 using nonparametric statistical analysis and computer simulation. 4) To obtain human subject pilot data demonstrating the effectiveness of the algorithms developed under Aims 1 and 2.