Graph Theoretical Framework of Brain Networks in Multiple Sclerosis: A Review of Concepts
[Display omitted] •Network science in combination with graph theory is becoming an important approach to model tissue organization in MS.•Connectivity disruption and loss of network efficiency have led to the notion of MS as a so-called disconnection syndrome.•Early adaptive network response might r...
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Veröffentlicht in: | Neuroscience 2019-04, Vol.403, p.35-53 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | [Display omitted]
•Network science in combination with graph theory is becoming an important approach to model tissue organization in MS.•Connectivity disruption and loss of network efficiency have led to the notion of MS as a so-called disconnection syndrome.•Early adaptive network response might represent an important hallmark of the disease to counteract chronic damage.•Functional and structural network properties could become biomarkers for monitoring the disease course.
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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ISSN: | 0306-4522 1873-7544 |
DOI: | 10.1016/j.neuroscience.2017.10.033 |