Efficient solution methodology for calibrating the hemodynamic model using functional Magnetic Resonance Imaging (fMRI) measurements
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Our aim is to propose a numerical strategy for retrieving accurately and efficiently the biophysiological parameters as well as the external stimulus characteristics corresponding to the hemodynamic mathematical model that describes changes in blood flow and blood oxygenation during brain activation. The proposed method employs the TNM-CKF method developed in [1], but in a prediction/correction framework. We present numerical results using both real and synthetic functional Magnetic Resonance Imaging (fMRI) measurements to highlight the performance characteristics of this computational methodology.
[1] Nafiseh Khoram,et al. On the characterization of single-event related brain activity from functional Magnetic Resonance Imaging (fMRI) measurements , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[2] R. Buxton,et al. Dynamics of blood flow and oxygenation changes during brain activation: The balloon model , 1998, Magnetic resonance in medicine.
[3] Vince D. Calhoun,et al. Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering , 2011, NeuroImage.