Altered brain functional connectivity in vegetative state and minimally conscious state

Objectives The pathological mechanism for a disorder of consciousness (DoC) is still not fully understood. Based on traditional behavioral scales, there high rate misdiagnosis subtypes DoC. We aimed to explore whether topological characterization may explain the mechanisms DoC and be effective in diagnosing Methods Using resting-state functional magnetic resonance imaging data, weighted brain networks normal control subjects patients with vegetative state (VS) minimally conscious (MCS) were constructed. Global local network characteristics each group analyzed. A support vector machine was employed identify MCS VS patients. Results average connection strength reduced roughly equivalent groups. efficiency, clustering coefficients reduced, characteristic path length increased ( p < 0.05). For both groups, global measures significantly different > Nodal nodal coefficient frontoparietal areas, limbic structures, occipital temporal areas comparison centrality suggested that causes reorganization structure large scale, especially thalamus. Lobal emphasized differences between two groups mainly involved areas. accuracy, sensitivity, specificity classifier identifying 89.83, 78.95, 95%, respectively. Conclusion There an association altered structures clinical symptoms With help metrics, it feasible differentiate