MEG数据分析中平稳背景的广义时空协方差模型
A generalized spatiotemporal covariance model for stationary background in analysis of MEG data
摘要：
在MEG数据的时空分析中使用基于空间和时间协方差的单个Kronecker乘积的噪声协方差模型被证明比常用的对角噪声协方差模型的结果提供改进。在本文中，我们提出了一个模型，是上述所有模型的推广。它描述了基于空间和时间协方差的单个克罗内克积的模型，以及更复杂的多对模型，以及任何中间形式，表示为降秩空间分量矩阵及其相应时间协方差矩阵的克罗内克积之和。该模型提供了一个框架，用于控制所描述的复杂性的背景和计算需求的分析使用该模型之间的权衡。本文还讨论了控制这种折衷的参数的估计值的方法
英文摘要：
Using a noise covariance model based on a single Kronecker product of spatial and temporal covariance in the spatiotemporal analysis of MEG data was demonstrated to provide improvement in the results over that of the commonly used diagonal noise covariance model. In this paper we present a model that is a generalization of all of the above models. It describes models based on a single Kronecker product of spatial and temporal covariance as well as more complicated multi-pair models together with any intermediate form expressed as a sum of Kronecker products of spatial component matrices of reduced rank and their corresponding temporal covariance matrices. The model provides a framework for controlling the tradeoff between the described complexity of the background and computational demand for the analysis using this model. Ways to estimate the value of the parameter controlling this tradeoff are also discussed
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