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Independent component analysis (ICA) and statistical parametric mapping (SPM) are two commonly used methods of analyzing fMRI measurements. Typically, these methods are applied separately to the measurements to produce brain maps indicating active brain regions in response to a stimulus or a performed task. However, ICA can also be used to develop a hemodynamic response model that can be used as a...
Brain or any other tissue signatures are considered to be linear combinations of tissue components. Mixtures of such tissue components are "blindly" separated by means of geometrical sparse component analysis. The original set of at least two MR images, acquired by using the spin-echo or spoiled FLASH techniques with specific set of Tr and Te, are sparsified by using multiple wavelets and...
In this study we investigate the correlation between single-trial evoked brain responses and galvanic skin responses (GSR). The correlation between the two signals is examined by using a modified principal component regression based approach. A potential application of the study is to utilize the GSR measurements in a form of a prior information in the estimation of the brain potentials when only...
Independent component analysis (ICA) and statistical parametric mapping (SPM) are two commonly used methods of analyzing fMRI measurements. Typically, these methods are applied separately to the measurements to produce brain maps indicating active brain regions in response to a stimulus or a performed task. However, ICA can also be used to develop a hemodynamic response model that can be used as a...
In this study we investigate the correlation between single-trial evoked brain responses and galvanic skin responses (GSR). The correlation between the two signals is examined by using a modified principal component regression based approach. A potential application of the study is to utilize the GSR measurements in a form of a prior information in the estimation of the brain potentials when only...
Brain or any other tissue signatures are considered to be linear combinations of tissue components. Mixtures of such tissue components are "blindly" separated by means of geometrical sparse component analysis. The original set of at least two MR images, acquired by using the spin-echo or spoiled FLASH techniques with specific set of Tr and Te, are sparsified by using multiple wavelets and...
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