Graph Theoretical Framework of Brain Networks in Multiple Sclerosis: A Review of Concepts. (1st April 2019)

• Record Type: Journal Article
• Authors: Fleischer, Vinzenz; Radetz, Angela; Ciolac, Dumitru; Muthuraman, Muthuraman; Gonzalez-Escamilla, Gabriel; Zipp, Frauke; Groppa, Sergiu
• Is Part Of: Neuroscience. Volume 403(2019)
• Page Start: 35
• Page End: 53
• Publication Date: 2019-04-01
• Subjects: CIS clinically isolated syndrome -- DMN default mode network -- DTI diffusion tensor imaging -- EDSS expanded disability status scale -- EEG electroencephalography -- fMRI functional magnetic resonance imaging -- GM gray matter -- MEG magnetoencephalography -- MRI magnetic resonance imaging -- MS multiple sclerosis -- MSFC multiple sclerosis functional composite -- NAWM normal-appearing white matter -- PASAT paced auditory serial addition test -- PPMS primary progressive multiple sclerosis -- RRMS relapsing-remitting multiple sclerosis -- SPMS secondary progressive multiple sclerosis -- TWMLL total white matter lesion load -- WM white matter; multiple sclerosis -- network analysis -- graph theory -- network reorganization -- functional connectivity -- structural connectivity; Neurochemistry -- Periodicals; Neurophysiology -- Periodicals; Neurology -- Periodicals; Neurochimie -- Périodiques; Neurophysiologie -- Périodiques; Neurochemistry; Neurophysiology; Electronic journals; Periodicals; Electronic journals; 612.8
• DOI: 10.1016/j.neuroscience.2017.10.033
• Languages: English
• ISSNs: 0306-4522

Abstract

Graphical abstract: Highlights: 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. 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.