Bayesian Modelling of fMRI lime Series

Part of Advances in Neural Information Processing Systems 12 (NIPS 1999)

Bibtex Metadata Paper


Pedro Højen-Sørensen, Lars Hansen, Carl Rasmussen


We present a Hidden Markov Model (HMM) for inferring the hidden psychological state (or neural activity) during single trial tMRI activa(cid:173) tion experiments with blocked task paradigms. Inference is based on Bayesian methodology, using a combination of analytical and a variety of Markov Chain Monte Carlo (MCMC) sampling techniques. The ad(cid:173) vantage of this method is that detection of short time learning effects be(cid:173) tween repeated trials is possible since inference is based only on single trial experiments.