The connectome as a marker for cognitive dysfunction including fatigue in relapsing remitting multiple sclerosis patients

BACKGROUND: Fatigue is a common symptom experienced in multiple sclerosis (MS). The objectives of our study were first to isolate the brain regions in RRMS patients and networks disrupted in non-fatigued and fatigue subgroups and correlate rsfMRI with neuropsychology scores using seed based and graph theory. METHODS: Resting fMRI analysis was done on a total of 10 RRMS patients and 10 healthy subjects and based on MFIS were subdivided as fatigued and non-fatigued. We then correlated the SDMT and MFIS scores using seed based and graph measures of rsfMRI data. RESULTS: Seed-based techniques showed abnormalities in the DMN, other cognitive networks, increased networks in left brain in non-fatigued and migration to right brain in fatigued as part of neuro plasticity. Areas of hypoconnectivity were extensive and indicated more severity of disease. Compensatory areas of hyperconnectivity in the association areas, cerebellum and striatal hubs were noted. Graph analysis showed tendency of brain networks towards lack of integration and over segregation of networks. Clustering coefficient was reduced and, randomness, path length, inter hemispheric connections was increased in RRMS. Frontal lobe and thalamus showed a significant decrease in rich club network with a weak but increased interhemispheric connectivity in non-fatigued and intrahemispheric connectivity in fatigued groups respectively. CONCLUSIONS: In neuroeconomic terms, the alteration of these connectivity and graph metrics indicate increased metabolic demand between nodes to carry out the normal functions.