Characterization of spatial dynamics of Fmri data in white matter using diffusion-informed white matter harmonics
(2021) 18th IEEE International Symposium on Biomedical Imaging, ISBI 2021 In Proceedings - International Symposium on Biomedical Imaging 2021-April. p.1586-1590- Abstract
In this work, we leverage the Laplacian eigenbasis of voxelwise white matter (WM) graphs derived from diffusionweighted MRI data, dubbed WM harmonics, to characterize the spatial structure of WM fMRI data. Our motivation for such a characterization is based on studies that show WM fMRI data exhibit a spatial correlational anisotropy that coincides with underlying fiber patterns. By quantifying the energy content of WM fMRI data associated with subsets of WM harmonics across multiple spectral bands, we show that the data exhibits notable subtle spatial modulations under functional load that are not manifested during rest. WM harmonics provide a novel means to study the spatial dynamics of WM fMRI data, in such way that the analysis is... (More)
In this work, we leverage the Laplacian eigenbasis of voxelwise white matter (WM) graphs derived from diffusionweighted MRI data, dubbed WM harmonics, to characterize the spatial structure of WM fMRI data. Our motivation for such a characterization is based on studies that show WM fMRI data exhibit a spatial correlational anisotropy that coincides with underlying fiber patterns. By quantifying the energy content of WM fMRI data associated with subsets of WM harmonics across multiple spectral bands, we show that the data exhibits notable subtle spatial modulations under functional load that are not manifested during rest. WM harmonics provide a novel means to study the spatial dynamics of WM fMRI data, in such way that the analysis is informed by the underlying anatomical structure.
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- author
- Behjat, Hamid LU ; Aganj, Iman ; Abramian, David ; Eklund, Anders and Westin, Carl Fredrik
- organization
- publishing date
- 2021-04-13
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Diffusion MRI, Functional MRI, Graph signal processin, White matter
- host publication
- 2021 IEEE 18th International Symposium on Biomedical Imaging, ISBI 2021
- series title
- Proceedings - International Symposium on Biomedical Imaging
- volume
- 2021-April
- article number
- 9433958
- pages
- 5 pages
- publisher
- IEEE Computer Society
- conference name
- 18th IEEE International Symposium on Biomedical Imaging, ISBI 2021
- conference location
- Nice, France
- conference dates
- 2021-04-13 - 2021-04-16
- external identifiers
-
- scopus:85107219786
- ISSN
- 1945-7928
- 1945-8452
- ISBN
- 9781665412469
- DOI
- 10.1109/ISBI48211.2021.9433958
- language
- English
- LU publication?
- yes
- id
- d0a79a90-6225-47d8-8800-9d94f560e624
- date added to LUP
- 2021-06-24 12:25:06
- date last changed
- 2024-09-07 20:57:11
@inproceedings{d0a79a90-6225-47d8-8800-9d94f560e624, abstract = {{<p>In this work, we leverage the Laplacian eigenbasis of voxelwise white matter (WM) graphs derived from diffusionweighted MRI data, dubbed WM harmonics, to characterize the spatial structure of WM fMRI data. Our motivation for such a characterization is based on studies that show WM fMRI data exhibit a spatial correlational anisotropy that coincides with underlying fiber patterns. By quantifying the energy content of WM fMRI data associated with subsets of WM harmonics across multiple spectral bands, we show that the data exhibits notable subtle spatial modulations under functional load that are not manifested during rest. WM harmonics provide a novel means to study the spatial dynamics of WM fMRI data, in such way that the analysis is informed by the underlying anatomical structure. </p>}}, author = {{Behjat, Hamid and Aganj, Iman and Abramian, David and Eklund, Anders and Westin, Carl Fredrik}}, booktitle = {{2021 IEEE 18th International Symposium on Biomedical Imaging, ISBI 2021}}, isbn = {{9781665412469}}, issn = {{1945-7928}}, keywords = {{Diffusion MRI; Functional MRI; Graph signal processin; White matter}}, language = {{eng}}, month = {{04}}, pages = {{1586--1590}}, publisher = {{IEEE Computer Society}}, series = {{Proceedings - International Symposium on Biomedical Imaging}}, title = {{Characterization of spatial dynamics of Fmri data in white matter using diffusion-informed white matter harmonics}}, url = {{http://dx.doi.org/10.1109/ISBI48211.2021.9433958}}, doi = {{10.1109/ISBI48211.2021.9433958}}, volume = {{2021-April}}, year = {{2021}}, }