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Poster communications

Deconvolution of fMRI BOLD signal in time-domain using an exponential operator and Lasso optimization

Abstract : Many techniques have been explored so far in the study of neural activations using the blood oxygenated level dependent (BOLD) signal. Among them, deconvolution methods have been developed in order to explore spontaneous brain activity when the brain is in resting-state. These techniques are powerful since they do not require a priori knowledge about timing and duration of activations [2]. In this work, we propose a regularized deconvolution technique which uses an exponential operator, whose shape and performance can be adjusted by tuning a parameter α, and the Least-Angle Regression (LARS) algorithm, by using the least absolute shrinkage and selection operator (LASSO) model.
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Poster communications
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https://hal.inria.fr/hal-01713304
Contributor : Isa Costantini <>
Submitted on : Tuesday, February 20, 2018 - 2:10:44 PM
Last modification on : Monday, October 12, 2020 - 10:28:54 AM

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Isa Costantini, Patryk Filipiak, Kostiantyn Maksymenko, Rachid Deriche, Samuel Deslauriers-Gauthier. Deconvolution of fMRI BOLD signal in time-domain using an exponential operator and Lasso optimization. CoBCoM 2017 - Computational Brain Connectivity Mapping Winter School Workshop, Nov 2017, Juan Les Pins, France. ⟨hal-01713304⟩

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