Karthik Ramakrishnan Sreenivasan1, Martin Havlicek2, Gopikrishna Deshpande, 3
1 AU MRI Research Center, Department of Electrical and Computer Engineering, Auburn University, Auburn, AL, United States; 2Department of Cognitive Neuroscience, Maastricht University, Maastricht, Limburg , Netherlands; 3Department of Psychology, Auburn University, Auburn, AL, United States
In this study we present a method which uses non-parametric blind deconvolution based on homomorphic filtering to investigate the over fitting problem of existing parametric methods. We compare our method to the performance of cubature Kalman filter (CKF)-based parametric approach. Simulations were performed with both methods and estimated neuronal responses were obtained. Correlation between the simulated and estimated neuronal responses indicated that in both cases (CKF-based and homomorphic deconvolution) the temporal neuronal events were correctly estimated, indicating that parametric methods such as CKF-based approaches are not susceptible to over fitting.