A Kullback-Leibler methodology for HRF estimation in fMRI data
Date
2010
Authors
Seghouane, Abd-Krim
Journal Title
Journal ISSN
Volume Title
Publisher
Institute of Electrical and Electronics Engineers (IEEE Inc)
Abstract
Hemodynamic Response Function (HRF) estimation in functional Magnetic Resonance Imaging (fMRI) experiments is an important issue in functional neuroimages analysis. Indeed, when modeling each brain region as a stationary linear system characterized by its impulse response, the HRF describes the temporal dynamic of the brain region response during activations. Using the mixed-effects model, a new algorithm for maximum likelihood HRF estimation is derived. In this model, the random effect is used to better account for the variability of the drift. Contrary to the usual approaches, the proposed algorithm has the benefit of considering an unknown drift matrix. Estimations of the HRF and the hyperparameters are derived by alternating minimization of the Kullback-Leibler divergence between a model family of probability distributions defined using the mixed-effects model and a desired family of probability distributions constrained to be concentrated on the observed data. The relevance of proposed approach is demonstrated both on simulated and real data.
Description
Keywords
Keywords: algorithm; article; brain; brain mapping; computer simulation; hemodynamics; human; image processing; methodology; normal distribution; nuclear magnetic resonance imaging; pathology; probability; regression analysis; reproducibility; statistical model; Al
Citation
Collections
Source
Proceedings of IEEE International Conference of the Engineering in Medicine and Biology Society (EMBS 2010)
Type
Conference paper
Book Title
Entity type
Access Statement
License Rights
Restricted until
2037-12-31