Functional connectivity changes caused by multiple sclerosis

Brain connectivity refers to the time dependence of neural activity between anatomically separated regions. Using the techniques of functional MRI (fMRI) and elements of the graph theory is possible to identify functional connectivity networks. Because functional connectivity between brain regions can characterize the integrity of large-scale systems, there is great interest in understanding the variability of these networks in normal development and clinical settings, for the presence of neurological diseases such as multiple sclerosis (MS) that affects the neuronal communication speed leading to a reduction or loss of function. This paper shows the implementation of a methodology for the analysis of the BOLD signal at rest using graph theory in high resolution (20092 voxels). There is obtained functional connectivity networks for healthy subjects and patients with MS, and calculated measurements of average degree, efficiency, transitivity, degree distribution and entropy for each network. It was found that in MS patients exists variations in all measures, suggesting greater connectivity associated a possible mechanism of brain plasticity in response to damage caused by the disease.