Application and validation of spatial mixture modelling for the joint detection-estimation of brain activity in fMRI

• Published in: 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Vol. 2007; pp. 5218 - 5222
• Main Authors: Vincent, T., Ciuciu, P., Idier, J.
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 01.01.2007; Institute of Electrical and Electronics Engineers (IEEE)
• Subjects: Algorithms; Bayesian methods; Bioengineering; Brain; Brain - physiology; Brain Mapping; Brain Mapping - methods; Brain modeling; Computer Science; Computer Simulation; Engineering Sciences; Evoked Potentials; Evoked Potentials - physiology; Hemodynamics; Humans; Image analysis; Image Interpretation, Computer-Assisted; Image Interpretation, Computer-Assisted - methods; Imaging; Life Sciences; Magnetic analysis; Magnetic Resonance Imaging; Magnetic Resonance Imaging - methods; Markov random fields; Models, Neurological; Models, Statistical; Reproducibility of Results; Robustness; Scanning probe microscopy; Sensitivity and Specificity; Signal and Image Processing
• ISBN: 9781424407873; 1424407877
• ISSN: 1094-687X; 1557-170X
• DOI: 10.1109/IEMBS.2007.4353518

Within-subject analysis in event-related functional Magnetic Resonance Imaging (fMRI) first relies on (i) a detection step to localize which parts of the brain are activated by a given stimulus type, and second on (ii) an estimation step to recover the temporal dynamics of the brain response. Recently, a Bayesian detection-estimation approach that jointly addresses (i)-(ii) has been proposed in [1]. This work is based on an independent mixture model (IMM) and provides both a spatial activity map and an estimate of brain dynamics. In [2], we accounted for spatial correlation using a spatial mixture model (SMM) based on a binary Markov random field. Here, we assess the SMM robustness and flexibility on simulations which diverge from the priors and the generative BOLD model and further extend comparison between SMM and IMM on real fMRI data, focusing on a region of interest in the auditory cortex.