Bayesian comparison of spatially regularised general linear models.

@article{Penny2007BayesianCO,
  title={Bayesian comparison of spatially regularised general linear models.},
  author={William D. Penny and Guillaume Flandin and Nelson J. Trujillo-Barreto},
  journal={Human brain mapping},
  year={2007},
  volume={28 4},
  pages={275-93}
}
In previous work (Penny et al., [2005]: Neuroimage 24:350-362) we have developed a spatially regularised General Linear Model for the analysis of functional magnetic resonance imaging data that allows for the characterisation of regionally specific effects using Posterior Probability Maps (PPMs). In this paper we show how it also provides an approximation to the model evidence. This is important as it is the basis of Bayesian model comparison and provides a unified framework for Bayesian… CONTINUE READING
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