Michiel Cottaar
Modelling white matter in gyral blades as a continuous vector field
Cottaar, Michiel; Bastiani, Matteo; Boddu, Nikhil; Glasser, Matthew F.; Haber, Suzanne; van Essen, David C.; Sotiropoulos, Stamatios N.; Jbabdi, Saad
Authors
Matteo Bastiani
Nikhil Boddu
Matthew F. Glasser
Suzanne Haber
David C. van Essen
STAMATIOS SOTIROPOULOS STAMATIOS.SOTIROPOULOS@NOTTINGHAM.AC.UK
Professor of Computational Neuroimaging
Saad Jbabdi
Abstract
© 2020 Many brain imaging studies aim to measure structural connectivity with diffusion tractography. However, biases in tractography data, particularly near the boundary between white matter and cortical grey matter can limit the accuracy of such studies. When seeding from the white matter, streamlines tend to travel parallel to the convoluted cortical surface, largely avoiding sulcal fundi and terminating preferentially on gyral crowns. When seeding from the cortical grey matter, streamlines generally run near the cortical surface until reaching deep white matter. These so-called “gyral biases” limit the accuracy and effective resolution of cortical structural connectivity profiles estimated by tractography algorithms, and they do not reflect the expected distributions of axonal densities seen in invasive tracer studies or stains of myelinated fibres. We propose an algorithm that concurrently models fibre density and orientation using a divergence-free vector field within gyral blades to encourage an anatomically-justified streamline density distribution along the cortical white/grey-matter boundary while maintaining alignment with the diffusion MRI estimated fibre orientations. Using in vivo data from the Human Connectome Project, we show that this algorithm reduces tractography biases. We compare the structural connectomes to functional connectomes from resting-state fMRI, showing that our model improves cross-modal agreement. Finally, we find that after parcellation the changes in the structural connectome are very minor with slightly improved interhemispheric connections (i.e, more homotopic connectivity) and slightly worse intrahemispheric connections when compared to tracers.
Citation
Cottaar, M., Bastiani, M., Boddu, N., Glasser, M. F., Haber, S., van Essen, D. C., …Jbabdi, S. (2021). Modelling white matter in gyral blades as a continuous vector field. NeuroImage, 227, Article 117693. https://doi.org/10.1016/j.neuroimage.2020.117693
Journal Article Type | Article |
---|---|
Acceptance Date | Dec 21, 2020 |
Online Publication Date | Dec 30, 2020 |
Publication Date | Feb 15, 2021 |
Deposit Date | Jan 5, 2021 |
Publicly Available Date | Jan 14, 2021 |
Journal | NeuroImage |
Print ISSN | 1053-8119 |
Electronic ISSN | 1095-9572 |
Publisher | Elsevier |
Peer Reviewed | Peer Reviewed |
Volume | 227 |
Article Number | 117693 |
DOI | https://doi.org/10.1016/j.neuroimage.2020.117693 |
Keywords | Cognitive Neuroscience; Neurology |
Public URL | https://nottingham-repository.worktribe.com/output/5184165 |
Publisher URL | https://www.sciencedirect.com/science/article/pii/S1053811920311782?via%3Dihub |
Files
Modelling white matter in gyral blades as a continuous vector field
(5.6 Mb)
PDF
Publisher Licence URL
https://creativecommons.org/licenses/by/4.0/
You might also like
QuNex – An Integrative Platform for Reproducible Neuroimaging Analytics
(2023)
Journal Article
Mapping brain endophenotypes associated with idiopathic pulmonary fibrosis genetic risk
(2022)
Journal Article
Predicting time-resolved electrophysiological brain networks from structural eigenmodes
(2022)
Journal Article
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: digital-library-support@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search