Conference Proceeding

FMRI analysis through Bayesian variable selection with a spatial prior

Dept. of Stat., Univ. of Illinois at Urbana-Champaign, Urbana, IL, USA
Proceedings / IEEE International Symposium on Biomedical Imaging: from nano to macro. IEEE International Symposium on Biomedical Imaging 08/2009; DOI:10.1109/ISBI.2009.5193147 In proceeding of: Biomedical Imaging: From Nano to Macro, 2009. ISBI '09. IEEE International Symposium on
Source: IEEE Xplore

ABSTRACT This paper presents a novel spatial Bayesian method for simultaneous activation detection and hemodynamic response function (HRF) estimation of functional magnetic resonance imaging (fMRI) data. A Bayesian variable selection approach is used to induce shrinkage and sparsity, with a spatial prior on latent variables representing activated hemodynamic response components. Then, the activation map is generated from the full spectrum of posterior inference constructed through a Markov chain Monte Carlo scheme, and HRFs at different voxels are estimated non-parametrically with information pooling from neighboring voxels. By integrating functional activation detection and HRFs estimation in a unified framework, our method is more robust to noise and less sensitive to model mis-specification.

0 0
  • Source
    [show abstract] [hide abstract]
    ABSTRACT: We describe a Bayesian estimation and inference procedure for fMRI time series based on the use of General Linear Models (GLMs). Importantly, we use a spatial prior on regression coefficients which embodies our prior knowledge that evoked responses are spatially contiguous and locally homogeneous. Further, using a computationally efficient Variational Bayes framework, we are able to let the data determine the optimal amount of smoothing. We assume an arbitrary order Auto-Regressive (AR) model for the errors. Our model generalizes earlier work on voxel-wise estimation of GLM-AR models and inference in GLMs using Posterior Probability Maps (PPMs). Results are shown on simulated data and on data from an event-related fMRI experiment.
    NeuroImage 02/2005; 24(2):350-62. · 6.25 Impact Factor
  • Source
    [show abstract] [hide abstract]
    ABSTRACT: The functional Magnetic Resonance Imaging (fMRI) is a technique with increasing applications in studying the brain function. The blood-oxygenation-level-dependent (BOLD) is a fMRI method that allows the detection of brain activated regions after the application of an external stimulus, e.g., visual or auditive. This technique is based on the assumption that the metabolism increases in activated areas as well as the oxygen uptake. Analising this information is a challenging problem because the BOLD signal is very noisy and its changes due to the application of a stimulus are very weak. Therefore, the detection of temporal correlations with the applied stimulus requires sophisticated statistical algorithms to understand if the changes on the BOLD signal are pure noise or are related with the applied stimulus, called paradigm in the fMRI scope.
    Conference proceedings: ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference 02/2008; 2008:4411-4.
  • Source
    [show abstract] [hide abstract]
    ABSTRACT: [eng] Transportation costs and monopoly location in presence of regional disparities. . This article aims at analysing the impact of the level of transportation costs on the location choice of a monopolist. We consider two asymmetric regions. The heterogeneity of space lies in both regional incomes and population sizes: the first region is endowed with wide income spreads allocated among few consumers whereas the second one is highly populated however not as wealthy. Among the results, we show that a low transportation costs induces the firm to exploit size effects through locating in the most populated region. Moreover, a small transport cost decrease may induce a net welfare loss, thus allowing for regional development policies which do not rely on inter-regional transportation infrastructures. cost decrease may induce a net welfare loss, thus allowing for regional development policies which do not rely on inter-regional transportation infrastructures. [fre] Cet article d�veloppe une statique comparative de l'impact de diff�rents sc�narios d'investissement (projet d'infrastructure conduisant � une baisse mod�r�e ou � une forte baisse du co�t de transport inter-r�gional) sur le choix de localisation d'une entreprise en situation de monopole, au sein d'un espace int�gr� compos� de deux r�gions aux populations et revenus h�t�rog�nes. La premi�re r�gion, faiblement peupl�e, pr�sente de fortes disparit�s de revenus, tandis que la seconde, plus homog�ne en termes de revenu, repr�sente un march� potentiel plus �tendu. On montre que l'h�t�rog�n�it� des revenus constitue la force dominante du mod�le lorsque le sc�nario d'investissement privil�gi� par les politiques publiques conduit � des gains substantiels du point de vue du co�t de transport entre les deux r�gions. L'effet de richesse, lorsqu'il est associ� � une forte disparit� des revenus, n'incite pas l'entreprise � exploiter son pouvoir de march� au d�triment de la r�gion l
    Journal of the American Statistical Association 01/2008; 103(March):410-423. · 1.83 Impact Factor


Available from

Jing Xia