Bayesian Analysis of Single Subject fMRI Data
In this work, we are investigating the use of completely specified Bayesian models for the analysis of single subject functional magnetic resonance imaging data. Particular emphasis is given to the appropriate use of Markov Chain Monte Carlo for fitting. The developed methods will be applied to data involving a color-word Stroop exam.
This investigation is a joint collaboration between Galin Jones at the University of Minnesota-Twin Cities and Michael Smith at the University of Sydney in Australia.