Modeling and inference of multisubject fMRI data

@article{Mumford2006ModelingAI,
  title={Modeling and inference of multisubject fMRI data},
  author={J. Mumford and Tommy Nichols},
  journal={IEEE Engineering in Medicine and Biology Magazine},
  year={2006},
  volume={25},
  pages={42-51}
}
This article reviews four commonly used approaches to group modeling in fMRI. The methods differ in their computational intensity (FSL with its two-level estimation including MCM being the most intense) and assumptions (SPM2 with its assumption of spatially homogeneous covariance V/sub g/ being most restrictive). This study also distinguishes fixed-effects models from mixed-effects models and motivates the importance of a mixed-effects model for group fMRI analysis. The sections following that… CONTINUE READING
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