Graph theoretical framework of brain networks in multiple sclerosis: a review of concepts
Open accessAbstract
Network science provides powerful access to essential organizational principles of the human brain. It has been applied in combination with graph theory to characterize brain connectivity patterns. In multiple sclerosis (MS), analysis of the brain networks derived from either structural or functional imaging provides new insights into pathological processes within the gray and white matter. Beyond focal lesions and diffuse tissue damage, network connectivity patterns could be important for closely tracking and predicting the disease course. In this review, we describe concepts of graph theory, highlight novel issues of tissue reorganization in acute and chronic neuroinflammation and address pitfalls with regard to network analysis in MS patients. We further provide an outline of functional and structural connectivity patterns observed in MS, spanning from disconnection and disruption on one hand to adaptation and compensation on the other. Moreover, we link network changes and their relation to clinical disability based on the current literature. Finally, we discuss the perspective of network science in MS for future research and postulate its role in the clinical framework.
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Multiple sclerosis is a demyelinating disease with multiple focal white matter lesions.
“Multiple sclerosis is a demyelinating disease with multiple focal white matter lesions (Fleischer et al., 2019).”
From Quantitative mapping of the brain’s structural connectivity using diffusion MRI tractography: A review (2022) · cites this paper as Fleischer et al., 2019
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BackgroundInfluentialTranslational value of choroid plexus imaging for tracking neuroinflammation in mice and humans
Fleischer, V., Gonzalez-Escamilla, G., Ciolac, D., Albrecht, P., Küry, P., Gruchot, J., Dietrich, M., Hecker, C., Müntefering, T., Bock, S., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2025000118 · Cited by 152 · see citing works
Self-citationSun, Y., Xu, Y., Lv, J., & Liu, Y. (2022) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2022.108282 · Cited by 11 · see citing works
- Authors
- Fleischer, V., Radetz, A., Ciolac, D., Muthuraman, M., Gonzalez-Escamilla, G., Zipp, F., & Groppa, S.
- Affiliations
- University Medical Center of the Johannes Gutenberg University Mainz (DE)
- Johannes Gutenberg University Mainz (DE)
- Corresponding author
- Groppa, Sergiu
- ORCID
- Venue
- Neuroscience
- Publisher
- Elsevier BV
- Published
- 2019-04
- Volume
- 403
- Pages
- 35-53
- ISSN
- 0306-4522 (ISSN-L)
- OpenAlex
- W2766022883
- Cited by
- 151
- References
- 9
- Citations by year
- 2026: 7 · 2025: 14 · 2024: 15 · 2023: 21 · 2022: 22 · 2021: 22 · 2020: 18 · 2019: 21 · 2018: 11
- FWCI
- 1.53
- Type
- journal article
- Language
- en
- Open access
- green
- ibn.idsi.md
- Licence
- Locations
- Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- OPUS (Augsburg University) (submittedVersion, cc-by-nc-nd)
- Funders
- German Research Council
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Pathology and Forensic Medicine › Multiple Sclerosis Research Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- multiple sclerosis, brain networks, graph theory, structural connectivity, functional connectivity, neuroinflammation, tissue reorganization, disconnection, clinical disability, white matter lesions, gray matter damage, disease progression
- MeSH terms
- Animals, Brain, Encephalomyelitis, Autoimmune, Experimental, Humans, Models, Neurological, Multiple Sclerosis, Neural Pathways
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