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Probabilistic modeling of single-trial fMRI data

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3 Author(s)
Svensen, M. ; Max-Planck Inst. of Cognitive Neurosci., Leipzig, Germany ; Kruggel, F. ; von Cramon, D.Y.

Describes a probabilistic framework for modeling single-trial functional magnetic resonance (fMR) images based on a parametric model for the hemodynamic response and Markov random field (MRF) image models. The model is fitted to image data by maximizing a lower bound on the log likelihood. The result is an approximate maximum a posteriori estimate of the joint distribution over the model parameters and pixel labels. Examples show how this technique can used to segment two-dimensional (2-D) fMR images, or parts thereof, into regions with different characteristics of their hemodynamic response.

Published in:

Medical Imaging, IEEE Transactions on  (Volume:19 ,  Issue: 1 )