Statistical Modelling 2 (2002), 235249
Ludwig Fahrmeir,
Department of Statistics, Ludwig-Maximilians-University Munich,
Ludwigstraße 33,
D-80539 Munich,
Germany
eMail: fahrmeir@stat.uni-muenchen.de
C. Gössl,
Max-Planck-Institute of Psychiatry,
Munich,
Germany
The purpose of this paper is twofold. First, it provides a review of general semiparametric Bayesian models for the analysis of fMRI data. Most approaches focus on important but separate temporal or spatial aspects of the overall problem, or they proceed by stepwise procedures. Therefore, as a second aim, we suggest a complete spatiotemporal model for analysing fMRI data within a unified semiparametric Bayesian framework. An application to data from a visual stimulation experiment illustrates our approach and demonstrates its computational feasibility.