IEEE transactions on medical imaging
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IEEE Trans Med Imaging · Feb 1999
Comparative StudyActivation detection in functional MRI using subspace modeling and maximum likelihood estimation.
A statistical method for detecting activated pixels in functional MRI (fMIRI) data is presented. In this method, the fMRI time series measured at each pixel is modeled as the sum of a response signal which arises due to the experimentally controlled activation-baseline pattern, a nuisance component representing effects of no interest, and Gaussian white noise. For periodic activation-baseline patterns, the response signal is modeled by a truncated Fourier series with a known fundamental frequency but unknown Fourier coefficients. ⋯ The maximal invariant statistic used in this test has an F distribution. The theoretical F distribution under the null hypothesis strongly concurred with the experimental frequency distribution obtained by performing null experiments in which the subjects did not perform any activation task. Application of the theory to motor activation and visual stimulation fMRI studies is presented.