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  4. Fuzzy Deconvolution Of Neuronal Events In Functional Magnetic Resonance Imaging
 
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Fuzzy Deconvolution Of Neuronal Events In Functional Magnetic Resonance Imaging

Date Issued
2023-01-01
Author(s)
El-deredy, Wael  
Facultad de Ingeniería  
Veloz, Alejandro  
Facultad de Ingeniería  
Alejandro Weinstein
Juan Zamora
Claudio Moraga
Daniele Marinazzo
DOI
10.1016/j.procs.2023.10.337
Abstract
The variability in the shape of the Blood Oxygenation Level Dependent (BOLD) response, as measured in Functional Magnetic Resonance Imaging (fMRI), can introduce significant uncertainty and inaccuracies in estimating brain connectivity and detecting brain activity. To address this issue, this paper proposes a fuzzy method that offers enhanced robustness in dealing with the inherent uncertainty associated with the brain's response in fMRI data. The results obtained from simulated data demonstrate that the proposed fuzzy method is capable of effectively handling deviations of the Hemodynamic Response Function from its canonical shape, providing promising potential for improving the accuracy and reliability of fMRI analyses.
Subjects

Computer Science

OCDE Subjects

Natural Sciences::Phy...

Quartile (Date Issued)
SQ
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