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A general statistical analysis for fMRI data.

K J Worsley·C H Liao·J Aston·V Petre·G H Duncan·F Morales·A C Evans
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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.

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AlgorithmsArtifactsBiasBrainHemodynamicsHumansImage Processing, Computer-AssistedImaging, Three-DimensionalLinear ModelsMagnetic Resonance ImagingMathematical ComputingRegression AnalysisReproducibility of ResultsJournal Article

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K J Worsley, C H Liao, J Aston, V Petre, G H Duncan, F Morales, A C Evans. 2002. A general statistical analysis for fMRI data.. https://doi.org/10.1006/nimg.2001.0933

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