L1-Norm Regularized Deconvolution of Functional MRI BOLD Signal

Abstract : Deconvolution methods are used to denoise the blood oxygen level-dependent (BOLD) response, the signal that forms the basis of functional MRI (fMRI). In this work we propose a novel approach based on a temporal regularized deconvolution of the BOLD fMRI signal with the least absolute shrinkage and selection operator (LASSO) model, solved using the angle regression algorithm (LARS). In this way we were able to recover the underlying neurons activations and their dynamics
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Poster communications
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https://hal.inria.fr/hal-01855505
Contributor : Isa Costantini <>
Submitted on : Wednesday, August 8, 2018 - 11:12:35 AM
Last modification on : Wednesday, September 12, 2018 - 1:15:53 AM
Long-term archiving on: Friday, November 9, 2018 - 12:46:00 PM

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Isa Costantini, Patryk Filipiak, Kostiantyn Maksymenko, Samuel Deslauriers-Gauthier, Rachid Deriche. L1-Norm Regularized Deconvolution of Functional MRI BOLD Signal. C@UCA, Jun 2018, Fréjus, France. ⟨hal-01855505⟩

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