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. We study graph spectral energy metrics associated to fMRI data of 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 experimental conditions within each task.
@article{arxiv.1910.09507,
title = {Spectral Characterization of functional MRI data on voxel-resolution cortical graphs},
author = {Hamid Behjat and Martin Larsson},
journal= {arXiv preprint arXiv:1910.09507},
year = {2020}
}
Comments
Fixed two typos in the equations; (1) definition of L in section 2.1, paragraph 1. (2) signal de-meaning and normalization in section 2.4, paragraph 1