Brain architecture or connectivity is complex and defines the basis of cognitive processing. Recent studies have revealed new insights about its organization by the combination of structural Magnetic Resonance Imaging (MRI) such as tractography (using Diffusion Spectrum Imaging, DSI) and functional MRI (fMRI) using resting-state. However, the complexity of brain connectivity and technical limitations prevent a comprehensive understanding of its organization. For this reason, the use of disease models producing disconnection syndromes, such as Multiple Sclerosis (MS) are important approaches for improving our understanding about brain organization. Moreover, MRI analysis of MS by DSI and fMRI can provide new insights on MS pathogenesis and development of new biomarkers of the disease, helping to solve the “clinical-MRI paradox”, namely the low correlation between MRI findings and clinical course.In this proposal we present new models for studying brain connectivity by analyzing MS. We intend to use state-of-the-art approaches in brain connectomics and apply inter-disciplinary techniques ranging form different MRI modalities to network analysis and image processing techniques. The candidate has a strong technical background and a PhD in a very related area - the technical aspects of the imaging techniques. The host group is strong in applied clinical research, with focus on MS, imaging, cognitive sciences and systems neurosciences. The host group has several ongoing collaborations with top researchers in cognitive neuroscience and connectomics. Finally, the findings and techniques that will be developed in this project can be transferable to clinical practice but also with minor modifications applied to similar neurological diseases and the research involving general questions on how the brain functions.