Joint estimation of activity signal and HRF in fMRI using fused LASSO

In this paper, we propose a novel voxel-based method for joint estimation of underlying activity signal and hemodynamic response function (HRF) in functional magnetic resonance imaging (fMRI). In the proposed two stage iterative framework, fused-least absolute shrinkage and selection operator (Fused LASSO) penalty is utilized for activity detection and HRF estimation. Conditions of smoothness and sparsity are imposed on HRF for its estimation. The validity of the proposed method is demonstrated on both synthetic and real fMRI data.

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