Publications
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A general statistical analysis for fMRI data.
Source: Neuroimage 2002 Jan;15(1):1-15.
Author: Worsley KJ, Liao CH, Aston J, Petre V, Duncan GH, Morales F, Evans AC.
PubMed ID: 11771969
Abstract:
We propose a method for the statistical analysis of fMRI data that seeks a compromise between efficiency, generality, validity, simplicity, and execution speed. The main differences between this analysis and previous ones are: a simple bias reduction and regularization for voxel-wise autoregressive model parameters; the combination of effects and their estimated standard deviations across different runs/sessions/subjects via a hierarchical random effects analysis using the EM algorithm; overcoming the problem of a small number of runs/session/subjects using a regularized variance ratio to increase the degrees of freedom.
Source: Neuroimage 2002 Jan;15(1):1-15.
Author: Worsley KJ, Liao CH, Aston J, Petre V, Duncan GH, Morales F, Evans AC.
PubMed ID: 11771969
Abstract:
We propose a method for the statistical analysis of fMRI data that seeks a compromise between efficiency, generality, validity, simplicity, and execution speed. The main differences between this analysis and previous ones are: a simple bias reduction and regularization for voxel-wise autoregressive model parameters; the combination of effects and their estimated standard deviations across different runs/sessions/subjects via a hierarchical random effects analysis using the EM algorithm; overcoming the problem of a small number of runs/session/subjects using a regularized variance ratio to increase the degrees of freedom.