| Literature DB >> 29101079 |
Vinzenz Fleischer1, Angela Radetz1, Dumitru Ciolac2, Muthuraman Muthuraman1, Gabriel Gonzalez-Escamilla1, Frauke Zipp1, Sergiu Groppa3.
Abstract
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.Entities:
Keywords: functional connectivity; graph theory; multiple sclerosis; network analysis; network reorganization; structural connectivity
Mesh:
Year: 2017 PMID: 29101079 DOI: 10.1016/j.neuroscience.2017.10.033
Source DB: PubMed Journal: Neuroscience ISSN: 0306-4522 Impact factor: 3.590