@inproceedings{a8c5b30519af48b59d1a9f786d514e9a,
title = "Spectral Characterization of Functional MRI Data on Voxel-Resolution Cortical Graphs",
abstract = "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.",
keywords = "cortical morphology, functional MRI, graph signal processing",
author = "Hamid Behjat and Martin Larsson",
year = "2020",
month = apr,
doi = "10.1109/ISBI45749.2020.9098667",
language = "English",
series = "Proceedings - International Symposium on Biomedical Imaging",
publisher = "IEEE Computer Society",
pages = "558--562",
booktitle = "ISBI 2020 - 2020 IEEE International Symposium on Biomedical Imaging",
address = "United States",
note = "17th IEEE International Symposium on Biomedical Imaging, ISBI 2020 ; Conference date: 03-04-2020 Through 07-04-2020",
}