Published June 14, 2018 | Version v1
Publication Metadata-only

L1-Norm Regularized Deconvolution of Functional MRI BOLD Signal

Costantini, Isa
Filipiak, Patryk
Maksymenko, Kostiantyn
Deslauriers-Gauthier, Samuel
Deriche, Rachid
Others:
Computational Imaging of the Central Nervous System (ATHENA) ; Inria Sophia Antipolis - Méditerranée (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)

Description

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

Abstract

International audience

Additional details

Identifiers Origin repository
Created:
December 4, 2022
Modified:
November 28, 2023