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Assessing Brain Activity Using Spatial Bayesian Variable Selection, Michael Smith, B Putz, D Auer, Ludwig Fahrmeir
Assessing Brain Activity Using Spatial Bayesian Variable Selection, Michael Smith, B Putz, D Auer, Ludwig Fahrmeir
Michael Stanley Smith
Statistical parametric mapping (SPM), relying on the general linear model and classical hypothesis testing, is a benchmark tool for assessing human brain activity using data from fMRI experiments. Friston et al. (Neuroimage 16 (2002a), 484) discuss some limitations of this frequentist approach and point out promising Bayesian perspectives. In particular, a Bayesian formulation allows explicit modeling and estimation of activation probabilities. In this study, we directly address this issue and develop a new regression based approach using spatial Bayesian variable selection. Our method has several advantages. First, spatial correlation is directly modeled for activation probabilities and indirectly for activation amplitudes. …