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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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