A general statistical analysis for fMRI data

Neuroimage. 2002 Jan;15(1):1-15. doi: 10.1006/nimg.2001.0933.


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.

MeSH terms

  • Algorithms
  • Artifacts
  • Bias
  • Brain / blood supply*
  • Hemodynamics / physiology*
  • Humans
  • Image Processing, Computer-Assisted / statistics & numerical data*
  • Imaging, Three-Dimensional / statistics & numerical data*
  • Linear Models
  • Magnetic Resonance Imaging / statistics & numerical data*
  • Mathematical Computing
  • Regression Analysis
  • Reproducibility of Results