Estimation of the neuronal activation using fMRI data: An observer-based approach
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Chadia Zayane-Aissa | Taous-Meriem Laleg-Kirati | M. Tadjine | H. Arabi | M. Tadjine | Chadia Zayane-Aissa | T. Laleg‐Kirati | H. Arabi
[1] Rajesh Rajamani,et al. Nonlinear Observer for Bounded Jacobian Systems, With Applications to Automotive Slip Angle Estimation , 2011, IEEE Transactions on Automatic Control.
[2] D. Heeger,et al. Linear Systems Analysis of Functional Magnetic Resonance Imaging in Human V1 , 1996, The Journal of Neuroscience.
[3] R. Rajamani,et al. Observer design for Lipschitz nonlinear systems using Riccati equations , 2010, Proceedings of the 2010 American Control Conference.
[4] Karl J. Friston,et al. Statistical parametric maps in functional imaging: A general linear approach , 1994 .
[5] Naoki Miura,et al. A state-space model of the hemodynamic approach: nonlinear filtering of BOLD signals , 2004, NeuroImage.
[6] Olivier Faugeras,et al. Using nonlinear models in fMRI data analysis: Model selection and activation detection , 2006, NeuroImage.
[7] Vince D. Calhoun,et al. Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering , 2011, NeuroImage.
[8] Karl J. Friston,et al. Nonlinear Responses in fMRI: The Balloon Model, Volterra Kernels, and Other Hemodynamics , 2000, NeuroImage.
[9] G. Glover. Deconvolution of Impulse Response in Event-Related BOLD fMRI1 , 1999, NeuroImage.
[10] R. Buxton,et al. Dynamics of blood flow and oxygenation changes during brain activation: The balloon model , 1998, Magnetic resonance in medicine.
[11] D. Noll,et al. Nonlinear Aspects of the BOLD Response in Functional MRI , 1998, NeuroImage.
[12] Arun T. Vemuri,et al. Nonlinear Fault Diagnosis in Diierential Algebraic Systems , 1997 .
[13] Qinghua Zhang,et al. Nonlinear system fault diagnosis based on adaptive estimation , 2004, Autom..
[14] Riccardo Marino,et al. Nonlinear control design: geometric, adaptive and robust , 1995 .
[15] Qinghua Zhang,et al. Revisiting different adaptive observers through a unified formulation , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.
[16] A. Dale,et al. Selective averaging of rapidly presented individual trials using fMRI , 1997, Human brain mapping.
[17] R. Buxton,et al. Modeling the hemodynamic response to brain activation , 2004, NeuroImage.
[18] Qinghua Zhang,et al. Adaptive observer for multiple-input-multiple-output (MIMO) linear time-varying systems , 2002, IEEE Trans. Autom. Control..
[19] P. Bandettini,et al. Spatial Heterogeneity of the Nonlinear Dynamics in the FMRI BOLD Response , 2001, NeuroImage.
[20] Karl J. Friston,et al. DEM: A variational treatment of dynamic systems , 2008, NeuroImage.
[21] S. Ogawa,et al. Oxygenation‐sensitive contrast in magnetic resonance image of rodent brain at high magnetic fields , 1990, Magnetic resonance in medicine.
[22] Antígona Martínez,et al. Nonlinear temporal dynamics of the cerebral blood flow response , 2001, Human brain mapping.