Abstract #3923
Fuzzy General Linear Model for functional Magnetic Resonance Imaging
Alejandro Veloz 1,2 , Luis Hernandez-Garcia 3 , Hector Allende 2 , Claudio Moraga 4 , Rodrigo Salas 1 , and Steren Chabert 1
1
Biomedical Engineering School, Universidad
de Valparaiso, Valparaiso, Chile,
2
Department
of Informatics, Universidad Tecnica Federico Santa
Maria, Valparaiso, Chile,
3
Functional
Magnetic Resonance Imaging Laboratory, University of
Michigan, Ann Arbor, Michigan, United States,
4
European
Centre for Soft-Computing, Mieres, Spain
Since the introduction of fMRI, accurate delineation of
brain activity is a relevant topic. This is a difficult
task, among other reasons, due to the fact that the
Haemodynamic Response varies over time, and across
individuals or brain regions. This work focuses on
developing a tool more adequate to represent a broader
range of possible shapes of the HRF, based on the
framework of fuzzy variables. Promising results are
obtained in both simulation and healthy volunteer data,
where the activated region obtained with the fuzzy GLM
completely intersects the canonical GLM, in addition to
obtaining a broader activated region.
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