Detecting Sparse Signals in Random Fields, With an Application to Brain Mapping
随机场中的稀疏信号检测及其脑图谱应用
Brain mapping data have been modeled as Gaussian random fields, and local increases in mean are detected by local maxima of a random field of test statistics derived from these data. Accurate p values for local maxima are readily available for isotropic data based on the expected Euler characteristic of the excursion set of the test statistic random field. In this article we give a simple method for dealing with nonisotropic data. Our approach has connections to the model of…