Spectral Characterization of Functional MRI Data on Voxel-Resolution Cortical Graphs

The human cortical layer exhibits a convoluted morphology that is unique to each individual. Conventional volumetric fMRI processing schemes take for granted the rich information provided by the underlying anatomy. We present a method to study fMRI data on subject-specific cerebral hemisphere cortex...

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Bibliographic Details
Published inProceedings (International Symposium on Biomedical Imaging) Vol. 2020-April; pp. 558 - 562
Main Authors Behjat, Hamid, Larsson, Martin
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2020
Subjects
cortical morphology
Engineering and Technology
functional MRI
graph signal processing
Medical Engineering
Medical Image Processing
Medicinsk bildbehandling
Medicinteknik
Teknik
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Summary:The human cortical layer exhibits a convoluted morphology that is unique to each individual. Conventional volumetric fMRI processing schemes take for granted the rich information provided by the underlying anatomy. We present a method to study fMRI data on subject-specific cerebral hemisphere cortex (CHC) graphs, which encode the cortical morphology at the resolution of voxels in 3-D. Using graph signal processing principles, we study spectral energy metrics associated to fMRI data, on 100 subjects from the Human Connectome Project database, across seven tasks. Experimental results signify the strength of CHC graphs' Laplacian eigenvector bases in capturing subtle spatial patterns specific to different functional loads as well as to sets of experimental conditions within each task.
ISBN:1538693305
9781538693308
ISSN:1945-8452
1945-7928
1945-8452
DOI:10.1109/ISBI45749.2020.9098667