Functional Connectivity in Multiple Sclerosis: Recent Findings and Future Directions.

摘要: Multiple sclerosis is a debilitating disorder resulting from scattered lesions in the central nervous system. Because of high variability lesion patterns between patients, it difficult to relate existing biomarkers symptoms and their progression. The nature multiple offers itself be studied through lens network analyses. Recent research into has taken such approach by making use functional connectivity. In this review, we briefly introduce measures connectivity how compute them. We then identify several common observations approach: (a) likelihood altered deep-gray matter regions, (b) decrease brain modularity, (c) hemispheric asymmetries alterations, (d) correspondence behavioral with task-related task-unrelated networks. propose incorporating analyses longitudinal studies order improve our understanding underlying mechanisms affected sclerosis, which can consequently offer promising route individualizing imaging-related for sclerosis.