A comparison of Gamma and Gaussian dynamic convolution models of the fMRI BOLD response

Blood oxygenation level-dependent (BOLD) contrast-based functional magnetic resonance imaging (fMRI) has been widely utilized to detect brain neural activities and great efforts are now stressed on the hemodynamic processes of different brain regions activated by a stimulus. The focus of this paper...

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Veröffentlicht in:Magnetic resonance imaging 2005, Vol.23 (1), p.83-88
Hauptverfasser: Chen, Huafu, Yao, Dezhong, Liu, Zuxiang
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Yao, Dezhong
Liu, Zuxiang
description Blood oxygenation level-dependent (BOLD) contrast-based functional magnetic resonance imaging (fMRI) has been widely utilized to detect brain neural activities and great efforts are now stressed on the hemodynamic processes of different brain regions activated by a stimulus. The focus of this paper is the comparison of Gamma and Gaussian dynamic convolution models of the fMRI BOLD response. The convolutions are between the perfusion function of the neural response to a stimulus and a Gaussian or Gamma function. The parameters of the two models are estimated by a nonlinear least-squares optimal algorithm for the fMRI data of eight subjects collected in a visual stimulus experiment. The results show that the Gaussian model is better than the Gamma model in fitting the data. The model parameters are different in the left and right occipital regions, which indicate that the dynamic processes seem different in various cerebral functional regions.
doi_str_mv 10.1016/j.mri.2004.11.002
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subjects Algorithms
Analysis of Variance
BOLD
Brain Mapping - methods
Cerebrovascular Circulation - physiology
Functional MRI
Gamma function
Gaussian function
Hemodynamic model
Humans
Least-Squares Analysis
Magnetic Resonance Imaging - methods
Models, Neurological
Photic Stimulation
Visual Cortex - blood supply
Visual Cortex - physiology
title A comparison of Gamma and Gaussian dynamic convolution models of the fMRI BOLD response
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