ABSTRACT
In this work, we leverage the Laplacian eigenbasis of voxelwise white matter (WM) graphs derived from diffusion-weighted 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.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
A sentence added to Abstract; a sentence and reference added to Introduction; updated Acknowledgements; a few other miscellaneous minor edits throughout the paper.